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[ "_The documentation is not available anymore as the PR was closed or merged._", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007703 / 0.011353 (-0.003650) | 0.004699 / 0.011008 (-0.006309) | 0.090195 / 0.038508 (0.051687) | 0.119165 / 0.023109 (0.096056) | 0.361435 / 0.275898 (0.085537) | 0.404429 / 0.323480 (0.080949) | 0.006172 / 0.007986 (-0.001814) | 0.003932 / 0.004328 (-0.000397) | 0.068384 / 0.004250 (0.064133) | 0.066730 / 0.037052 (0.029678) | 0.360978 / 0.258489 (0.102489) | 0.401301 / 0.293841 (0.107460) | 0.032836 / 0.128546 (-0.095710) | 0.010821 / 0.075646 (-0.064825) | 0.294526 / 0.419271 (-0.124745) | 0.068751 / 0.043533 (0.025218) | 0.368427 / 0.255139 (0.113288) | 0.376969 / 0.283200 (0.093770) | 0.040538 / 0.141683 (-0.101145) | 1.509966 / 1.452155 (0.057811) | 1.564885 / 1.492716 (0.072169) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.292243 / 0.018006 (0.274237) | 0.662067 / 0.000490 (0.661577) | 0.004966 / 0.000200 (0.004766) | 0.000103 / 0.000054 (0.000048) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.029050 / 0.037411 (-0.008361) | 0.099880 / 0.014526 (0.085354) | 0.109277 / 0.176557 (-0.067280) | 0.167877 / 0.737135 (-0.569258) | 0.110770 / 0.296338 (-0.185569) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.395742 / 0.215209 (0.180533) | 3.944152 / 2.077655 (1.866498) | 1.875295 / 1.504120 (0.371175) | 1.705088 / 1.541195 (0.163893) | 1.884443 / 1.468490 (0.415953) | 0.497243 / 4.584777 (-4.087534) | 3.749287 / 3.745712 (0.003575) | 4.418826 / 5.269862 (-0.851035) | 2.481149 / 4.565676 (-2.084528) | 0.058260 / 0.424275 (-0.366015) | 0.007744 / 0.007607 (0.000137) | 0.472531 / 0.226044 (0.246486) | 4.716022 / 2.268929 (2.447094) | 2.480446 / 55.444624 (-52.964179) | 2.163098 / 6.876477 (-4.713379) | 2.217555 / 2.142072 (0.075482) | 0.601965 / 4.805227 (-4.203262) | 0.139364 / 6.500664 (-6.361301) | 0.067097 / 0.075469 (-0.008372) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.330537 / 1.841788 (-0.511251) | 22.176270 / 8.074308 (14.101962) | 16.224981 / 10.191392 (6.033589) | 0.173708 / 0.680424 (-0.506715) | 0.019402 / 0.534201 (-0.514799) | 0.401994 / 0.579283 (-0.177289) | 0.432597 / 0.434364 (-0.001767) | 0.489933 / 0.540337 (-0.050404) | 0.672334 / 1.386936 (-0.714602) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.008622 / 0.011353 (-0.002731) | 0.004609 / 0.011008 (-0.006399) | 0.067791 / 0.038508 (0.029283) | 0.112770 / 0.023109 (0.089661) | 0.380939 / 0.275898 (0.105041) | 0.416940 / 0.323480 (0.093460) | 0.006170 / 0.007986 (-0.001815) | 0.003876 / 0.004328 (-0.000452) | 0.066227 / 0.004250 (0.061976) | 0.073132 / 0.037052 (0.036080) | 0.390120 / 0.258489 (0.131631) | 0.420893 / 0.293841 (0.127052) | 0.033235 / 0.128546 (-0.095311) | 0.009659 / 0.075646 (-0.065987) | 0.072668 / 0.419271 (-0.346604) | 0.051333 / 0.043533 (0.007801) | 0.393828 / 0.255139 (0.138689) | 0.412376 / 0.283200 (0.129176) | 0.027760 / 0.141683 (-0.113923) | 1.494369 / 1.452155 (0.042214) | 1.592862 / 1.492716 (0.100145) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.345376 / 0.018006 (0.327369) | 0.609399 / 0.000490 (0.608909) | 0.000546 / 0.000200 (0.000346) | 0.000061 / 0.000054 (0.000007) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.035601 / 0.037411 (-0.001810) | 0.106527 / 0.014526 (0.092001) | 0.114388 / 0.176557 (-0.062168) | 0.175607 / 0.737135 (-0.561529) | 0.113009 / 0.296338 (-0.183329) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.417237 / 0.215209 (0.202028) | 4.136329 / 2.077655 (2.058675) | 2.147134 / 1.504120 (0.643014) | 2.009501 / 1.541195 (0.468306) | 2.139499 / 1.468490 (0.671009) | 0.491593 / 4.584777 (-4.093184) | 3.766734 / 3.745712 (0.021022) | 5.652446 / 5.269862 (0.382585) | 3.021654 / 4.565676 (-1.544022) | 0.058458 / 0.424275 (-0.365817) | 0.008271 / 0.007607 (0.000664) | 0.488229 / 0.226044 (0.262184) | 4.861343 / 2.268929 (2.592415) | 2.694142 / 55.444624 (-52.750482) | 2.489130 / 6.876477 (-4.387346) | 2.679376 / 2.142072 (0.537304) | 0.589959 / 4.805227 (-4.215268) | 0.137939 / 6.500664 (-6.362725) | 0.066833 / 0.075469 (-0.008636) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.444871 / 1.841788 (-0.396916) | 22.874961 / 8.074308 (14.800653) | 15.842130 / 10.191392 (5.650738) | 0.175529 / 0.680424 (-0.504895) | 0.019024 / 0.534201 (-0.515177) | 0.406551 / 0.579283 (-0.172732) | 0.430335 / 0.434364 (-0.004029) | 0.475750 / 0.540337 (-0.064587) | 0.624836 / 1.386936 (-0.762100) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#dabbb7467f49fd22ae1a43cc577eb43008d63ee8 \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006068 / 0.011353 (-0.005285) | 0.003694 / 0.011008 (-0.007315) | 0.080321 / 0.038508 (0.041813) | 0.061738 / 0.023109 (0.038629) | 0.329675 / 0.275898 (0.053777) | 0.364008 / 0.323480 (0.040528) | 0.004722 / 0.007986 (-0.003263) | 0.002857 / 0.004328 (-0.001471) | 0.062447 / 0.004250 (0.058197) | 0.047006 / 0.037052 (0.009953) | 0.335730 / 0.258489 (0.077241) | 0.373047 / 0.293841 (0.079206) | 0.027273 / 0.128546 (-0.101274) | 0.007979 / 0.075646 (-0.067667) | 0.262693 / 0.419271 (-0.156579) | 0.045416 / 0.043533 (0.001883) | 0.340774 / 0.255139 (0.085635) | 0.359667 / 0.283200 (0.076468) | 0.020848 / 0.141683 (-0.120835) | 1.450110 / 1.452155 (-0.002045) | 1.489511 / 1.492716 (-0.003206) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.185090 / 0.018006 (0.167084) | 0.429823 / 0.000490 (0.429334) | 0.000703 / 0.000200 (0.000503) | 0.000058 / 0.000054 (0.000003) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.024398 / 0.037411 (-0.013013) | 0.072983 / 0.014526 (0.058457) | 0.084012 / 0.176557 (-0.092544) | 0.146160 / 0.737135 (-0.590975) | 0.084068 / 0.296338 (-0.212270) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.432204 / 0.215209 (0.216995) | 4.320593 / 2.077655 (2.242939) | 2.261260 / 1.504120 (0.757140) | 2.087148 / 1.541195 (0.545954) | 2.144520 / 1.468490 (0.676029) | 0.501477 / 4.584777 (-4.083300) | 3.119557 / 3.745712 (-0.626156) | 3.572527 / 5.269862 (-1.697335) | 2.208836 / 4.565676 (-2.356840) | 0.057232 / 0.424275 (-0.367043) | 0.006494 / 0.007607 (-0.001113) | 0.508135 / 0.226044 (0.282091) | 5.090416 / 2.268929 (2.821488) | 2.739800 / 55.444624 (-52.704824) | 2.416105 / 6.876477 (-4.460372) | 2.616037 / 2.142072 (0.473965) | 0.583730 / 4.805227 (-4.221497) | 0.124312 / 6.500664 (-6.376352) | 0.060760 / 0.075469 (-0.014709) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.256097 / 1.841788 (-0.585691) | 18.326073 / 8.074308 (10.251765) | 13.859173 / 10.191392 (3.667781) | 0.143639 / 0.680424 (-0.536785) | 0.016649 / 0.534201 (-0.517552) | 0.331671 / 0.579283 (-0.247612) | 0.365370 / 0.434364 (-0.068994) | 0.392753 / 0.540337 (-0.147584) | 0.549302 / 1.386936 (-0.837634) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006054 / 0.011353 (-0.005299) | 0.003641 / 0.011008 (-0.007367) | 0.063109 / 0.038508 (0.024601) | 0.060482 / 0.023109 (0.037372) | 0.404047 / 0.275898 (0.128149) | 0.425436 / 0.323480 (0.101956) | 0.004603 / 0.007986 (-0.003382) | 0.002905 / 0.004328 (-0.001423) | 0.063207 / 0.004250 (0.058956) | 0.048248 / 0.037052 (0.011196) | 0.404325 / 0.258489 (0.145836) | 0.432652 / 0.293841 (0.138811) | 0.027630 / 0.128546 (-0.100916) | 0.008062 / 0.075646 (-0.067584) | 0.068367 / 0.419271 (-0.350905) | 0.042169 / 0.043533 (-0.001364) | 0.384903 / 0.255139 (0.129764) | 0.418617 / 0.283200 (0.135417) | 0.020767 / 0.141683 (-0.120915) | 1.463606 / 1.452155 (0.011451) | 1.512081 / 1.492716 (0.019365) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.229601 / 0.018006 (0.211594) | 0.417878 / 0.000490 (0.417388) | 0.000373 / 0.000200 (0.000173) | 0.000053 / 0.000054 (-0.000002) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.026354 / 0.037411 (-0.011057) | 0.078100 / 0.014526 (0.063574) | 0.087122 / 0.176557 (-0.089434) | 0.140017 / 0.737135 (-0.597118) | 0.089923 / 0.296338 (-0.206415) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.422405 / 0.215209 (0.207196) | 4.237383 / 2.077655 (2.159728) | 2.161104 / 1.504120 (0.656984) | 1.982337 / 1.541195 (0.441142) | 2.050216 / 1.468490 (0.581726) | 0.499281 / 4.584777 (-4.085496) | 2.996953 / 3.745712 (-0.748759) | 5.027069 / 5.269862 (-0.242792) | 2.804703 / 4.565676 (-1.760974) | 0.057707 / 0.424275 (-0.366568) | 0.006809 / 0.007607 (-0.000798) | 0.495196 / 0.226044 (0.269152) | 4.946593 / 2.268929 (2.677665) | 2.598965 / 55.444624 (-52.845660) | 2.349871 / 6.876477 (-4.526606) | 2.451665 / 2.142072 (0.309593) | 0.592314 / 4.805227 (-4.212913) | 0.125685 / 6.500664 (-6.374979) | 0.063252 / 0.075469 (-0.012217) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.325422 / 1.841788 (-0.516366) | 18.521059 / 8.074308 (10.446751) | 14.046757 / 10.191392 (3.855365) | 0.133009 / 0.680424 (-0.547415) | 0.017097 / 0.534201 (-0.517104) | 0.339804 / 0.579283 (-0.239479) | 0.345464 / 0.434364 (-0.088900) | 0.387623 / 0.540337 (-0.152714) | 0.519880 / 1.386936 (-0.867056) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#88896a7b28610ace95e444b94f9a4bc332cc1ee3 \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.008671 / 0.011353 (-0.002682) | 0.004681 / 0.011008 (-0.006327) | 0.107517 / 0.038508 (0.069008) | 0.078846 / 0.023109 (0.055737) | 0.449745 / 0.275898 (0.173847) | 0.504075 / 0.323480 (0.180596) | 0.005837 / 0.007986 (-0.002148) | 0.004031 / 0.004328 (-0.000297) | 0.092021 / 0.004250 (0.087771) | 0.065954 / 0.037052 (0.028902) | 0.442082 / 0.258489 (0.183593) | 0.529349 / 0.293841 (0.235508) | 0.052527 / 0.128546 (-0.076019) | 0.013854 / 0.075646 (-0.061792) | 0.367315 / 0.419271 (-0.051956) | 0.068731 / 0.043533 (0.025199) | 0.494733 / 0.255139 (0.239594) | 0.472801 / 0.283200 (0.189601) | 0.036791 / 0.141683 (-0.104892) | 1.877648 / 1.452155 (0.425493) | 1.928399 / 1.492716 (0.435683) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.231910 / 0.018006 (0.213904) | 0.553464 / 0.000490 (0.552974) | 0.011915 / 0.000200 (0.011715) | 0.000378 / 0.000054 (0.000324) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.028232 / 0.037411 (-0.009179) | 0.091441 / 0.014526 (0.076916) | 0.110394 / 0.176557 (-0.066162) | 0.187638 / 0.737135 (-0.549497) | 0.111810 / 0.296338 (-0.184529) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.599987 / 0.215209 (0.384778) | 6.008709 / 2.077655 (3.931054) | 2.518769 / 1.504120 (1.014650) | 2.197029 / 1.541195 (0.655834) | 2.217165 / 1.468490 (0.748675) | 0.894939 / 4.584777 (-3.689837) | 5.001217 / 3.745712 (1.255505) | 4.636482 / 5.269862 (-0.633379) | 3.237613 / 4.565676 (-1.328063) | 0.104227 / 0.424275 (-0.320048) | 0.008504 / 0.007607 (0.000897) | 0.750190 / 0.226044 (0.524145) | 7.514571 / 2.268929 (5.245642) | 3.358003 / 55.444624 (-52.086621) | 2.585649 / 6.876477 (-4.290827) | 2.731129 / 2.142072 (0.589056) | 1.088828 / 4.805227 (-3.716400) | 0.217308 / 6.500664 (-6.283356) | 0.076410 / 0.075469 (0.000941) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.620087 / 1.841788 (-0.221701) | 23.145743 / 8.074308 (15.071435) | 20.583403 / 10.191392 (10.392011) | 0.225467 / 0.680424 (-0.454956) | 0.029063 / 0.534201 (-0.505138) | 0.480563 / 0.579283 (-0.098720) | 0.539083 / 0.434364 (0.104719) | 0.563787 / 0.540337 (0.023449) | 0.782902 / 1.386936 (-0.604034) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.010113 / 0.011353 (-0.001239) | 0.004997 / 0.011008 (-0.006011) | 0.082974 / 0.038508 (0.044466) | 0.090375 / 0.023109 (0.067266) | 0.440273 / 0.275898 (0.164375) | 0.476939 / 0.323480 (0.153459) | 0.005955 / 0.007986 (-0.002031) | 0.004375 / 0.004328 (0.000046) | 0.080459 / 0.004250 (0.076209) | 0.061787 / 0.037052 (0.024734) | 0.477211 / 0.258489 (0.218722) | 0.487164 / 0.293841 (0.193323) | 0.054198 / 0.128546 (-0.074348) | 0.013945 / 0.075646 (-0.061701) | 0.093006 / 0.419271 (-0.326266) | 0.062685 / 0.043533 (0.019152) | 0.461373 / 0.255139 (0.206234) | 0.475766 / 0.283200 (0.192567) | 0.032059 / 0.141683 (-0.109623) | 1.857989 / 1.452155 (0.405834) | 1.837993 / 1.492716 (0.345277) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.243048 / 0.018006 (0.225042) | 0.535850 / 0.000490 (0.535360) | 0.007204 / 0.000200 (0.007004) | 0.000104 / 0.000054 (0.000049) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.032584 / 0.037411 (-0.004827) | 0.098151 / 0.014526 (0.083625) | 0.109691 / 0.176557 (-0.066866) | 0.172803 / 0.737135 (-0.564333) | 0.110469 / 0.296338 (-0.185869) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.635086 / 0.215209 (0.419877) | 6.500864 / 2.077655 (4.423210) | 2.996727 / 1.504120 (1.492607) | 2.537218 / 1.541195 (0.996023) | 2.572310 / 1.468490 (1.103820) | 0.870868 / 4.584777 (-3.713909) | 4.989744 / 3.745712 (1.244032) | 4.422174 / 5.269862 (-0.847687) | 2.935874 / 4.565676 (-1.629803) | 0.097118 / 0.424275 (-0.327157) | 0.009360 / 0.007607 (0.001753) | 0.790447 / 0.226044 (0.564403) | 7.859519 / 2.268929 (5.590591) | 3.975616 / 55.444624 (-51.469009) | 3.018271 / 6.876477 (-3.858206) | 3.111173 / 2.142072 (0.969101) | 1.085577 / 4.805227 (-3.719651) | 0.225719 / 6.500664 (-6.274945) | 0.080576 / 0.075469 (0.005107) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.802284 / 1.841788 (-0.039504) | 23.487921 / 8.074308 (15.413613) | 20.595171 / 10.191392 (10.403779) | 0.196610 / 0.680424 (-0.483814) | 0.027483 / 0.534201 (-0.506718) | 0.485840 / 0.579283 (-0.093443) | 0.542661 / 0.434364 (0.108297) | 0.580602 / 0.540337 (0.040265) | 0.768195 / 1.386936 (-0.618741) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#88896a7b28610ace95e444b94f9a4bc332cc1ee3 \"CML watermark\")\n" ]

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[ "_The documentation is not available anymore as the PR was closed or merged._", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.008340 / 0.011353 (-0.003013) | 0.005053 / 0.011008 (-0.005955) | 0.103294 / 0.038508 (0.064786) | 0.069417 / 0.023109 (0.046308) | 0.436922 / 0.275898 (0.161024) | 0.461348 / 0.323480 (0.137868) | 0.006030 / 0.007986 (-0.001955) | 0.003727 / 0.004328 (-0.000601) | 0.076384 / 0.004250 (0.072134) | 0.056742 / 0.037052 (0.019689) | 0.439996 / 0.258489 (0.181507) | 0.469417 / 0.293841 (0.175577) | 0.044343 / 0.128546 (-0.084203) | 0.012634 / 0.075646 (-0.063013) | 0.359746 / 0.419271 (-0.059525) | 0.064842 / 0.043533 (0.021309) | 0.425960 / 0.255139 (0.170821) | 0.458568 / 0.283200 (0.175368) | 0.039802 / 0.141683 (-0.101881) | 1.687320 / 1.452155 (0.235165) | 1.806212 / 1.492716 (0.313496) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.255484 / 0.018006 (0.237478) | 0.563039 / 0.000490 (0.562549) | 0.000445 / 0.000200 (0.000245) | 0.000076 / 0.000054 (0.000022) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.027511 / 0.037411 (-0.009900) | 0.089185 / 0.014526 (0.074659) | 0.098397 / 0.176557 (-0.078160) | 0.163897 / 0.737135 (-0.573238) | 0.099905 / 0.296338 (-0.196434) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.612737 / 0.215209 (0.397528) | 6.209948 / 2.077655 (4.132294) | 2.756060 / 1.504120 (1.251940) | 2.402115 / 1.541195 (0.860920) | 2.422665 / 1.468490 (0.954175) | 0.834799 / 4.584777 (-3.749977) | 5.251699 / 3.745712 (1.505986) | 5.554141 / 5.269862 (0.284280) | 3.254699 / 4.565676 (-1.310977) | 0.095697 / 0.424275 (-0.328578) | 0.009406 / 0.007607 (0.001799) | 0.729025 / 0.226044 (0.502980) | 7.195521 / 2.268929 (4.926593) | 3.360264 / 55.444624 (-52.084361) | 2.696764 / 6.876477 (-4.179713) | 2.702796 / 2.142072 (0.560724) | 0.974420 / 4.805227 (-3.830808) | 0.195215 / 6.500664 (-6.305450) | 0.069754 / 0.075469 (-0.005715) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.553458 / 1.841788 (-0.288330) | 21.972436 / 8.074308 (13.898128) | 20.027392 / 10.191392 (9.836000) | 0.216950 / 0.680424 (-0.463474) | 0.032196 / 0.534201 (-0.502005) | 0.449884 / 0.579283 (-0.129399) | 0.586213 / 0.434364 (0.151849) | 0.537227 / 0.540337 (-0.003111) | 0.751022 / 1.386936 (-0.635914) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007859 / 0.011353 (-0.003493) | 0.004762 / 0.011008 (-0.006246) | 0.086023 / 0.038508 (0.047515) | 0.069218 / 0.023109 (0.046109) | 0.449312 / 0.275898 (0.173414) | 0.481687 / 0.323480 (0.158207) | 0.006318 / 0.007986 (-0.001668) | 0.004063 / 0.004328 (-0.000266) | 0.076917 / 0.004250 (0.072667) | 0.058034 / 0.037052 (0.020981) | 0.474265 / 0.258489 (0.215775) | 0.497736 / 0.293841 (0.203895) | 0.044587 / 0.128546 (-0.083959) | 0.013880 / 0.075646 (-0.061766) | 0.089233 / 0.419271 (-0.330038) | 0.058760 / 0.043533 (0.015227) | 0.439515 / 0.255139 (0.184376) | 0.473246 / 0.283200 (0.190047) | 0.042968 / 0.141683 (-0.098715) | 1.802647 / 1.452155 (0.350493) | 1.778563 / 1.492716 (0.285847) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.343741 / 0.018006 (0.325735) | 0.567409 / 0.000490 (0.566919) | 0.029727 / 0.000200 (0.029527) | 0.000147 / 0.000054 (0.000092) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.031021 / 0.037411 (-0.006390) | 0.096659 / 0.014526 (0.082133) | 0.103341 / 0.176557 (-0.073215) | 0.169893 / 0.737135 (-0.567242) | 0.103280 / 0.296338 (-0.193058) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.584724 / 0.215209 (0.369515) | 5.792596 / 2.077655 (3.714941) | 2.683133 / 1.504120 (1.179013) | 2.367837 / 1.541195 (0.826643) | 2.378567 / 1.468490 (0.910076) | 0.803427 / 4.584777 (-3.781350) | 5.179017 / 3.745712 (1.433305) | 4.446323 / 5.269862 (-0.823538) | 2.771731 / 4.565676 (-1.793945) | 0.100943 / 0.424275 (-0.323332) | 0.009875 / 0.007607 (0.002268) | 0.725260 / 0.226044 (0.499216) | 7.149728 / 2.268929 (4.880800) | 3.646438 / 55.444624 (-51.798187) | 2.793858 / 6.876477 (-4.082618) | 2.971966 / 2.142072 (0.829894) | 0.998147 / 4.805227 (-3.807080) | 0.198004 / 6.500664 (-6.302660) | 0.072581 / 0.075469 (-0.002888) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.696737 / 1.841788 (-0.145051) | 22.615193 / 8.074308 (14.540884) | 20.272421 / 10.191392 (10.081029) | 0.237459 / 0.680424 (-0.442965) | 0.034774 / 0.534201 (-0.499427) | 0.484649 / 0.579283 (-0.094634) | 0.590263 / 0.434364 (0.155899) | 0.547833 / 0.540337 (0.007495) | 0.762109 / 1.386936 (-0.624827) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#4bc3628b5a8f71ad7cfc014d8ba5e798f26becb7 \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.011183 / 0.011353 (-0.000170) | 0.005267 / 0.011008 (-0.005741) | 0.108506 / 0.038508 (0.069997) | 0.083541 / 0.023109 (0.060431) | 0.452189 / 0.275898 (0.176291) | 0.496229 / 0.323480 (0.172749) | 0.004951 / 0.007986 (-0.003035) | 0.004452 / 0.004328 (0.000124) | 0.085133 / 0.004250 (0.080883) | 0.061291 / 0.037052 (0.024239) | 0.450453 / 0.258489 (0.191964) | 0.506456 / 0.293841 (0.212616) | 0.049784 / 0.128546 (-0.078762) | 0.014738 / 0.075646 (-0.060908) | 0.372603 / 0.419271 (-0.046669) | 0.065223 / 0.043533 (0.021690) | 0.467872 / 0.255139 (0.212733) | 0.500062 / 0.283200 (0.216862) | 0.040911 / 0.141683 (-0.100772) | 1.852970 / 1.452155 (0.400816) | 2.016996 / 1.492716 (0.524280) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.262620 / 0.018006 (0.244614) | 0.593925 / 0.000490 (0.593435) | 0.000413 / 0.000200 (0.000213) | 0.000085 / 0.000054 (0.000030) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.035713 / 0.037411 (-0.001698) | 0.111403 / 0.014526 (0.096878) | 0.117259 / 0.176557 (-0.059298) | 0.201545 / 0.737135 (-0.535590) | 0.133111 / 0.296338 (-0.163228) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.597318 / 0.215209 (0.382109) | 5.882691 / 2.077655 (3.805036) | 2.572203 / 1.504120 (1.068083) | 2.248016 / 1.541195 (0.706821) | 2.359103 / 1.468490 (0.890613) | 0.852023 / 4.584777 (-3.732754) | 5.270831 / 3.745712 (1.525119) | 4.712915 / 5.269862 (-0.556947) | 3.124295 / 4.565676 (-1.441381) | 0.092045 / 0.424275 (-0.332230) | 0.007834 / 0.007607 (0.000227) | 0.695711 / 0.226044 (0.469666) | 7.011760 / 2.268929 (4.742831) | 3.333300 / 55.444624 (-52.111325) | 2.745889 / 6.876477 (-4.130587) | 3.153458 / 2.142072 (1.011385) | 1.011089 / 4.805227 (-3.794139) | 0.207467 / 6.500664 (-6.293197) | 0.079802 / 0.075469 (0.004333) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.703784 / 1.841788 (-0.138003) | 24.414340 / 8.074308 (16.340032) | 22.534528 / 10.191392 (12.343136) | 0.276129 / 0.680424 (-0.404295) | 0.027954 / 0.534201 (-0.506247) | 0.484261 / 0.579283 (-0.095022) | 0.605316 / 0.434364 (0.170952) | 0.557219 / 0.540337 (0.016882) | 0.802209 / 1.386936 (-0.584727) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.009109 / 0.011353 (-0.002244) | 0.005376 / 0.011008 (-0.005632) | 0.085141 / 0.038508 (0.046633) | 0.100560 / 0.023109 (0.077450) | 0.482673 / 0.275898 (0.206775) | 0.551582 / 0.323480 (0.228103) | 0.006756 / 0.007986 (-0.001229) | 0.004171 / 0.004328 (-0.000158) | 0.084184 / 0.004250 (0.079933) | 0.069283 / 0.037052 (0.032230) | 0.517722 / 0.258489 (0.259233) | 0.542641 / 0.293841 (0.248801) | 0.047790 / 0.128546 (-0.080756) | 0.014063 / 0.075646 (-0.061583) | 0.110591 / 0.419271 (-0.308680) | 0.064373 / 0.043533 (0.020840) | 0.496636 / 0.255139 (0.241497) | 0.551906 / 0.283200 (0.268707) | 0.046187 / 0.141683 (-0.095496) | 1.864836 / 1.452155 (0.412681) | 1.923765 / 1.492716 (0.431049) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.286558 / 0.018006 (0.268552) | 0.610353 / 0.000490 (0.609863) | 0.012647 / 0.000200 (0.012447) | 0.000162 / 0.000054 (0.000107) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.037099 / 0.037411 (-0.000313) | 0.108608 / 0.014526 (0.094082) | 0.120386 / 0.176557 (-0.056170) | 0.183450 / 0.737135 (-0.553686) | 0.124860 / 0.296338 (-0.171479) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.629006 / 0.215209 (0.413797) | 6.309206 / 2.077655 (4.231551) | 2.878558 / 1.504120 (1.374438) | 2.616093 / 1.541195 (1.074898) | 2.668096 / 1.468490 (1.199606) | 0.865732 / 4.584777 (-3.719045) | 5.312433 / 3.745712 (1.566721) | 4.799352 / 5.269862 (-0.470509) | 3.142207 / 4.565676 (-1.423469) | 0.099591 / 0.424275 (-0.324684) | 0.009159 / 0.007607 (0.001552) | 0.730999 / 0.226044 (0.504954) | 7.486442 / 2.268929 (5.217513) | 3.657699 / 55.444624 (-51.786925) | 3.080094 / 6.876477 (-3.796383) | 3.320976 / 2.142072 (1.178904) | 1.089324 / 4.805227 (-3.715904) | 0.222831 / 6.500664 (-6.277833) | 0.083976 / 0.075469 (0.008507) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.793181 / 1.841788 (-0.048607) | 25.307444 / 8.074308 (17.233136) | 21.321713 / 10.191392 (11.130321) | 0.216326 / 0.680424 (-0.464098) | 0.034298 / 0.534201 (-0.499903) | 0.497173 / 0.579283 (-0.082110) | 0.643550 / 0.434364 (0.209186) | 0.581213 / 0.540337 (0.040876) | 0.830973 / 1.386936 (-0.555963) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#24875bb8494c3a7803182b08c70747b1b1a6bf4d \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006886 / 0.011353 (-0.004467) | 0.004267 / 0.011008 (-0.006741) | 0.086182 / 0.038508 (0.047674) | 0.083405 / 0.023109 (0.060296) | 0.313717 / 0.275898 (0.037819) | 0.351476 / 0.323480 (0.027996) | 0.005702 / 0.007986 (-0.002284) | 0.003802 / 0.004328 (-0.000526) | 0.065759 / 0.004250 (0.061508) | 0.060056 / 0.037052 (0.023003) | 0.315871 / 0.258489 (0.057382) | 0.364520 / 0.293841 (0.070679) | 0.032067 / 0.128546 (-0.096479) | 0.008679 / 0.075646 (-0.066967) | 0.294968 / 0.419271 (-0.124303) | 0.054684 / 0.043533 (0.011152) | 0.314124 / 0.255139 (0.058985) | 0.337312 / 0.283200 (0.054113) | 0.025051 / 0.141683 (-0.116632) | 1.505242 / 1.452155 (0.053087) | 1.608263 / 1.492716 (0.115547) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.266562 / 0.018006 (0.248556) | 0.579887 / 0.000490 (0.579397) | 0.004161 / 0.000200 (0.003961) | 0.000090 / 0.000054 (0.000035) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.031153 / 0.037411 (-0.006258) | 0.087703 / 0.014526 (0.073177) | 0.103864 / 0.176557 (-0.072693) | 0.159032 / 0.737135 (-0.578104) | 0.102482 / 0.296338 (-0.193857) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.405805 / 0.215209 (0.190596) | 4.050669 / 2.077655 (1.973014) | 2.064384 / 1.504120 (0.560264) | 1.892825 / 1.541195 (0.351630) | 2.001083 / 1.468490 (0.532593) | 0.478174 / 4.584777 (-4.106603) | 3.542580 / 3.745712 (-0.203132) | 3.319205 / 5.269862 (-1.950656) | 2.075868 / 4.565676 (-2.489808) | 0.057345 / 0.424275 (-0.366930) | 0.007459 / 0.007607 (-0.000148) | 0.483564 / 0.226044 (0.257520) | 4.827746 / 2.268929 (2.558818) | 2.579541 / 55.444624 (-52.865083) | 2.205125 / 6.876477 (-4.671352) | 2.489206 / 2.142072 (0.347133) | 0.575843 / 4.805227 (-4.229384) | 0.133010 / 6.500664 (-6.367654) | 0.061082 / 0.075469 (-0.014387) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.286059 / 1.841788 (-0.555729) | 20.575173 / 8.074308 (12.500865) | 14.351692 / 10.191392 (4.160300) | 0.150401 / 0.680424 (-0.530022) | 0.018678 / 0.534201 (-0.515523) | 0.397860 / 0.579283 (-0.181423) | 0.419474 / 0.434364 (-0.014890) | 0.474492 / 0.540337 (-0.065846) | 0.659510 / 1.386936 (-0.727426) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006948 / 0.011353 (-0.004405) | 0.004305 / 0.011008 (-0.006703) | 0.064220 / 0.038508 (0.025712) | 0.083251 / 0.023109 (0.060142) | 0.388148 / 0.275898 (0.112250) | 0.417834 / 0.323480 (0.094354) | 0.005762 / 0.007986 (-0.002224) | 0.003803 / 0.004328 (-0.000525) | 0.066365 / 0.004250 (0.062114) | 0.061808 / 0.037052 (0.024756) | 0.390889 / 0.258489 (0.132400) | 0.430619 / 0.293841 (0.136778) | 0.031777 / 0.128546 (-0.096770) | 0.008781 / 0.075646 (-0.066865) | 0.070844 / 0.419271 (-0.348427) | 0.050552 / 0.043533 (0.007019) | 0.378420 / 0.255139 (0.123281) | 0.403273 / 0.283200 (0.120074) | 0.024578 / 0.141683 (-0.117105) | 1.494790 / 1.452155 (0.042636) | 1.549408 / 1.492716 (0.056692) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.302668 / 0.018006 (0.284662) | 0.542235 / 0.000490 (0.541746) | 0.001847 / 0.000200 (0.001647) | 0.000092 / 0.000054 (0.000037) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.031947 / 0.037411 (-0.005465) | 0.092220 / 0.014526 (0.077694) | 0.104525 / 0.176557 (-0.072031) | 0.162000 / 0.737135 (-0.575135) | 0.106795 / 0.296338 (-0.189543) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.412035 / 0.215209 (0.196826) | 4.106527 / 2.077655 (2.028872) | 2.111529 / 1.504120 (0.607409) | 1.953201 / 1.541195 (0.412006) | 2.079258 / 1.468490 (0.610768) | 0.479562 / 4.584777 (-4.105215) | 3.606256 / 3.745712 (-0.139456) | 5.175250 / 5.269862 (-0.094612) | 3.292465 / 4.565676 (-1.273212) | 0.057726 / 0.424275 (-0.366549) | 0.008247 / 0.007607 (0.000640) | 0.486143 / 0.226044 (0.260098) | 4.859051 / 2.268929 (2.590123) | 2.675629 / 55.444624 (-52.768995) | 2.267448 / 6.876477 (-4.609029) | 2.567639 / 2.142072 (0.425567) | 0.580822 / 4.805227 (-4.224406) | 0.134942 / 6.500664 (-6.365722) | 0.063825 / 0.075469 (-0.011644) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.334421 / 1.841788 (-0.507367) | 20.481428 / 8.074308 (12.407120) | 14.227943 / 10.191392 (4.036551) | 0.170711 / 0.680424 (-0.509713) | 0.018212 / 0.534201 (-0.515989) | 0.397212 / 0.579283 (-0.182071) | 0.411934 / 0.434364 (-0.022430) | 0.478019 / 0.540337 (-0.062319) | 0.645434 / 1.386936 (-0.741502) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#ef3d3f10886e23a65cce3bfd939b8ec0d5a5c2c1 \"CML watermark\")\n" ]

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[ "_The documentation is not available anymore as the PR was closed or merged._", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007700 / 0.011353 (-0.003653) | 0.004680 / 0.011008 (-0.006328) | 0.098812 / 0.038508 (0.060304) | 0.085062 / 0.023109 (0.061952) | 0.371472 / 0.275898 (0.095574) | 0.412552 / 0.323480 (0.089072) | 0.004700 / 0.007986 (-0.003285) | 0.003765 / 0.004328 (-0.000564) | 0.074267 / 0.004250 (0.070017) | 0.063003 / 0.037052 (0.025951) | 0.391842 / 0.258489 (0.133353) | 0.436955 / 0.293841 (0.143114) | 0.035291 / 0.128546 (-0.093255) | 0.009309 / 0.075646 (-0.066338) | 0.313097 / 0.419271 (-0.106174) | 0.060098 / 0.043533 (0.016565) | 0.350726 / 0.255139 (0.095587) | 0.402692 / 0.283200 (0.119493) | 0.029321 / 0.141683 (-0.112361) | 1.671806 / 1.452155 (0.219651) | 1.743760 / 1.492716 (0.251044) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.242281 / 0.018006 (0.224275) | 0.505054 / 0.000490 (0.504564) | 0.006595 / 0.000200 (0.006395) | 0.000091 / 0.000054 (0.000037) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.032174 / 0.037411 (-0.005238) | 0.094483 / 0.014526 (0.079957) | 0.108527 / 0.176557 (-0.068030) | 0.178983 / 0.737135 (-0.558152) | 0.113766 / 0.296338 (-0.182572) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.419764 / 0.215209 (0.204555) | 4.282650 / 2.077655 (2.204995) | 2.075325 / 1.504120 (0.571205) | 1.897668 / 1.541195 (0.356473) | 2.027109 / 1.468490 (0.558619) | 0.519983 / 4.584777 (-4.064794) | 4.134603 / 3.745712 (0.388891) | 6.586711 / 5.269862 (1.316849) | 3.811726 / 4.565676 (-0.753951) | 0.058628 / 0.424275 (-0.365647) | 0.007586 / 0.007607 (-0.000021) | 0.502180 / 0.226044 (0.276136) | 5.101588 / 2.268929 (2.832660) | 2.534295 / 55.444624 (-52.910330) | 2.220170 / 6.876477 (-4.656307) | 2.441110 / 2.142072 (0.299038) | 0.644775 / 4.805227 (-4.160452) | 0.144716 / 6.500664 (-6.355948) | 0.067018 / 0.075469 (-0.008451) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.431279 / 1.841788 (-0.410508) | 21.947814 / 8.074308 (13.873506) | 15.548236 / 10.191392 (5.356844) | 0.174774 / 0.680424 (-0.505650) | 0.021182 / 0.534201 (-0.513019) | 0.441320 / 0.579283 (-0.137963) | 0.476685 / 0.434364 (0.042321) | 0.506277 / 0.540337 (-0.034060) | 0.809943 / 1.386936 (-0.576993) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007172 / 0.011353 (-0.004181) | 0.004358 / 0.011008 (-0.006650) | 0.068604 / 0.038508 (0.030096) | 0.083956 / 0.023109 (0.060847) | 0.402579 / 0.275898 (0.126681) | 0.444714 / 0.323480 (0.121235) | 0.005940 / 0.007986 (-0.002046) | 0.003607 / 0.004328 (-0.000722) | 0.073134 / 0.004250 (0.068883) | 0.061722 / 0.037052 (0.024669) | 0.410957 / 0.258489 (0.152468) | 0.458819 / 0.293841 (0.164978) | 0.033710 / 0.128546 (-0.094836) | 0.010230 / 0.075646 (-0.065417) | 0.084678 / 0.419271 (-0.334593) | 0.058203 / 0.043533 (0.014670) | 0.444972 / 0.255139 (0.189833) | 0.470962 / 0.283200 (0.187763) | 0.029222 / 0.141683 (-0.112461) | 1.671460 / 1.452155 (0.219306) | 1.759471 / 1.492716 (0.266754) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.238894 / 0.018006 (0.220888) | 0.493605 / 0.000490 (0.493115) | 0.001979 / 0.000200 (0.001780) | 0.000084 / 0.000054 (0.000030) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.036498 / 0.037411 (-0.000913) | 0.095245 / 0.014526 (0.080719) | 0.112147 / 0.176557 (-0.064409) | 0.171128 / 0.737135 (-0.566007) | 0.115295 / 0.296338 (-0.181044) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.461067 / 0.215209 (0.245858) | 4.723932 / 2.077655 (2.646277) | 2.432697 / 1.504120 (0.928578) | 2.237302 / 1.541195 (0.696107) | 2.351320 / 1.468490 (0.882830) | 0.509963 / 4.584777 (-4.074813) | 4.194817 / 3.745712 (0.449105) | 6.689529 / 5.269862 (1.419667) | 3.351198 / 4.565676 (-1.214478) | 0.064563 / 0.424275 (-0.359712) | 0.008605 / 0.007607 (0.000998) | 0.575590 / 0.226044 (0.349546) | 5.644179 / 2.268929 (3.375250) | 3.021375 / 55.444624 (-52.423249) | 2.595305 / 6.876477 (-4.281172) | 2.839228 / 2.142072 (0.697156) | 0.657148 / 4.805227 (-4.148079) | 0.144831 / 6.500664 (-6.355834) | 0.067882 / 0.075469 (-0.007587) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.595580 / 1.841788 (-0.246208) | 22.431609 / 8.074308 (14.357301) | 15.700845 / 10.191392 (5.509453) | 0.164675 / 0.680424 (-0.515749) | 0.021322 / 0.534201 (-0.512879) | 0.455270 / 0.579283 (-0.124013) | 0.451547 / 0.434364 (0.017183) | 0.520955 / 0.540337 (-0.019383) | 0.687803 / 1.386936 (-0.699133) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#7d19574e9f44bd3b59a3e47ca7c4ea66305a8e6b \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.008171 / 0.011353 (-0.003182) | 0.005563 / 0.011008 (-0.005445) | 0.102265 / 0.038508 (0.063757) | 0.074755 / 0.023109 (0.051646) | 0.431317 / 0.275898 (0.155419) | 0.472179 / 0.323480 (0.148699) | 0.006153 / 0.007986 (-0.001833) | 0.003832 / 0.004328 (-0.000496) | 0.078480 / 0.004250 (0.074230) | 0.056250 / 0.037052 (0.019197) | 0.432938 / 0.258489 (0.174449) | 0.480983 / 0.293841 (0.187142) | 0.048861 / 0.128546 (-0.079685) | 0.016252 / 0.075646 (-0.059394) | 0.343508 / 0.419271 (-0.075763) | 0.065057 / 0.043533 (0.021524) | 0.468418 / 0.255139 (0.213279) | 0.463692 / 0.283200 (0.180492) | 0.032912 / 0.141683 (-0.108771) | 1.795194 / 1.452155 (0.343039) | 1.833047 / 1.492716 (0.340331) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.197980 / 0.018006 (0.179974) | 0.500662 / 0.000490 (0.500172) | 0.007380 / 0.000200 (0.007181) | 0.000110 / 0.000054 (0.000055) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.028323 / 0.037411 (-0.009089) | 0.089817 / 0.014526 (0.075291) | 0.102923 / 0.176557 (-0.073633) | 0.173851 / 0.737135 (-0.563284) | 0.104006 / 0.296338 (-0.192333) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.580277 / 0.215209 (0.365068) | 5.878739 / 2.077655 (3.801085) | 2.404673 / 1.504120 (0.900553) | 2.071765 / 1.541195 (0.530571) | 2.106024 / 1.468490 (0.637534) | 0.855217 / 4.584777 (-3.729560) | 4.918602 / 3.745712 (1.172890) | 5.354984 / 5.269862 (0.085122) | 3.141288 / 4.565676 (-1.424389) | 0.099553 / 0.424275 (-0.324723) | 0.008152 / 0.007607 (0.000545) | 0.709857 / 0.226044 (0.483813) | 7.144602 / 2.268929 (4.875673) | 3.137637 / 55.444624 (-52.306987) | 2.379851 / 6.876477 (-4.496626) | 2.346426 / 2.142072 (0.204353) | 1.033416 / 4.805227 (-3.771811) | 0.213120 / 6.500664 (-6.287544) | 0.076037 / 0.075469 (0.000568) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.597742 / 1.841788 (-0.244046) | 21.745366 / 8.074308 (13.671058) | 20.830698 / 10.191392 (10.639306) | 0.238727 / 0.680424 (-0.441697) | 0.027923 / 0.534201 (-0.506278) | 0.466073 / 0.579283 (-0.113210) | 0.548647 / 0.434364 (0.114283) | 0.549245 / 0.540337 (0.008908) | 0.977148 / 1.386936 (-0.409788) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.008252 / 0.011353 (-0.003101) | 0.004653 / 0.011008 (-0.006356) | 0.084012 / 0.038508 (0.045504) | 0.077418 / 0.023109 (0.054309) | 0.440748 / 0.275898 (0.164850) | 0.464279 / 0.323480 (0.140799) | 0.005762 / 0.007986 (-0.002224) | 0.004909 / 0.004328 (0.000581) | 0.086441 / 0.004250 (0.082190) | 0.057883 / 0.037052 (0.020831) | 0.466655 / 0.258489 (0.208166) | 0.479751 / 0.293841 (0.185910) | 0.047166 / 0.128546 (-0.081380) | 0.014480 / 0.075646 (-0.061166) | 0.092599 / 0.419271 (-0.326672) | 0.062454 / 0.043533 (0.018921) | 0.449753 / 0.255139 (0.194614) | 0.461876 / 0.283200 (0.178676) | 0.034828 / 0.141683 (-0.106855) | 1.752249 / 1.452155 (0.300095) | 1.865449 / 1.492716 (0.372732) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.245028 / 0.018006 (0.227022) | 0.509564 / 0.000490 (0.509074) | 0.003930 / 0.000200 (0.003730) | 0.000110 / 0.000054 (0.000056) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.034746 / 0.037411 (-0.002665) | 0.096563 / 0.014526 (0.082037) | 0.107581 / 0.176557 (-0.068975) | 0.184952 / 0.737135 (-0.552184) | 0.108747 / 0.296338 (-0.187591) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.613091 / 0.215209 (0.397882) | 5.994985 / 2.077655 (3.917330) | 2.711276 / 1.504120 (1.207156) | 2.415862 / 1.541195 (0.874668) | 2.391055 / 1.468490 (0.922565) | 0.868723 / 4.584777 (-3.716054) | 4.953992 / 3.745712 (1.208280) | 4.606542 / 5.269862 (-0.663319) | 2.942162 / 4.565676 (-1.623515) | 0.102737 / 0.424275 (-0.321538) | 0.008634 / 0.007607 (0.001027) | 0.722122 / 0.226044 (0.496078) | 7.245097 / 2.268929 (4.976168) | 3.428232 / 55.444624 (-52.016393) | 2.709539 / 6.876477 (-4.166938) | 2.857956 / 2.142072 (0.715884) | 1.045594 / 4.805227 (-3.759634) | 0.213344 / 6.500664 (-6.287320) | 0.073601 / 0.075469 (-0.001868) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.651954 / 1.841788 (-0.189834) | 22.458646 / 8.074308 (14.384338) | 19.583203 / 10.191392 (9.391811) | 0.246932 / 0.680424 (-0.433492) | 0.025730 / 0.534201 (-0.508471) | 0.473475 / 0.579283 (-0.105808) | 0.521411 / 0.434364 (0.087047) | 0.562038 / 0.540337 (0.021700) | 0.767673 / 1.386936 (-0.619263) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#3869d99628329c696f6975377f65e625dd8ef3e0 \"CML watermark\")\n", "The CI error is unrelated.", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006649 / 0.011353 (-0.004703) | 0.003963 / 0.011008 (-0.007045) | 0.084564 / 0.038508 (0.046056) | 0.075668 / 0.023109 (0.052559) | 0.314233 / 0.275898 (0.038335) | 0.343320 / 0.323480 (0.019841) | 0.005405 / 0.007986 (-0.002581) | 0.003356 / 0.004328 (-0.000973) | 0.065094 / 0.004250 (0.060844) | 0.058774 / 0.037052 (0.021722) | 0.320772 / 0.258489 (0.062283) | 0.353546 / 0.293841 (0.059705) | 0.030921 / 0.128546 (-0.097625) | 0.008463 / 0.075646 (-0.067184) | 0.287490 / 0.419271 (-0.131781) | 0.053188 / 0.043533 (0.009656) | 0.324023 / 0.255139 (0.068884) | 0.337828 / 0.283200 (0.054628) | 0.024764 / 0.141683 (-0.116918) | 1.458028 / 1.452155 (0.005873) | 1.521615 / 1.492716 (0.028899) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.209360 / 0.018006 (0.191353) | 0.461331 / 0.000490 (0.460841) | 0.000386 / 0.000200 (0.000186) | 0.000052 / 0.000054 (-0.000002) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.028405 / 0.037411 (-0.009006) | 0.081074 / 0.014526 (0.066548) | 0.094868 / 0.176557 (-0.081689) | 0.151050 / 0.737135 (-0.586085) | 0.095854 / 0.296338 (-0.200484) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.393957 / 0.215209 (0.178748) | 3.938649 / 2.077655 (1.860994) | 1.938190 / 1.504120 (0.434070) | 1.766458 / 1.541195 (0.225263) | 1.818028 / 1.468490 (0.349538) | 0.483926 / 4.584777 (-4.100851) | 3.641957 / 3.745712 (-0.103755) | 4.883845 / 5.269862 (-0.386016) | 2.960300 / 4.565676 (-1.605377) | 0.057227 / 0.424275 (-0.367048) | 0.007285 / 0.007607 (-0.000322) | 0.475928 / 0.226044 (0.249884) | 4.756757 / 2.268929 (2.487828) | 2.502659 / 55.444624 (-52.941966) | 2.178067 / 6.876477 (-4.698410) | 2.378298 / 2.142072 (0.236226) | 0.578639 / 4.805227 (-4.226588) | 0.132512 / 6.500664 (-6.368152) | 0.059656 / 0.075469 (-0.015813) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.272673 / 1.841788 (-0.569115) | 19.266884 / 8.074308 (11.192576) | 14.272930 / 10.191392 (4.081538) | 0.165897 / 0.680424 (-0.514527) | 0.018436 / 0.534201 (-0.515765) | 0.395177 / 0.579283 (-0.184107) | 0.420134 / 0.434364 (-0.014229) | 0.460781 / 0.540337 (-0.079557) | 0.645376 / 1.386936 (-0.741560) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006504 / 0.011353 (-0.004849) | 0.003942 / 0.011008 (-0.007066) | 0.064936 / 0.038508 (0.026428) | 0.075015 / 0.023109 (0.051905) | 0.396871 / 0.275898 (0.120973) | 0.423448 / 0.323480 (0.099968) | 0.005239 / 0.007986 (-0.002747) | 0.003265 / 0.004328 (-0.001063) | 0.064910 / 0.004250 (0.060660) | 0.055006 / 0.037052 (0.017953) | 0.392818 / 0.258489 (0.134329) | 0.429735 / 0.293841 (0.135894) | 0.031847 / 0.128546 (-0.096699) | 0.008626 / 0.075646 (-0.067021) | 0.071591 / 0.419271 (-0.347681) | 0.049006 / 0.043533 (0.005473) | 0.384913 / 0.255139 (0.129774) | 0.408969 / 0.283200 (0.125769) | 0.023573 / 0.141683 (-0.118110) | 1.490271 / 1.452155 (0.038117) | 1.564620 / 1.492716 (0.071904) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.225917 / 0.018006 (0.207911) | 0.450369 / 0.000490 (0.449880) | 0.000375 / 0.000200 (0.000175) | 0.000055 / 0.000054 (0.000000) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.031196 / 0.037411 (-0.006215) | 0.090486 / 0.014526 (0.075960) | 0.102326 / 0.176557 (-0.074231) | 0.157483 / 0.737135 (-0.579653) | 0.103670 / 0.296338 (-0.192668) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.417577 / 0.215209 (0.202368) | 4.170798 / 2.077655 (2.093143) | 2.123689 / 1.504120 (0.619569) | 1.948231 / 1.541195 (0.407037) | 2.040277 / 1.468490 (0.571787) | 0.497919 / 4.584777 (-4.086858) | 3.633270 / 3.745712 (-0.112442) | 4.851698 / 5.269862 (-0.418164) | 2.691992 / 4.565676 (-1.873684) | 0.058641 / 0.424275 (-0.365634) | 0.007719 / 0.007607 (0.000112) | 0.500652 / 0.226044 (0.274607) | 4.988657 / 2.268929 (2.719728) | 2.604488 / 55.444624 (-52.840136) | 2.329829 / 6.876477 (-4.546648) | 2.468239 / 2.142072 (0.326167) | 0.598724 / 4.805227 (-4.206503) | 0.135959 / 6.500664 (-6.364706) | 0.061088 / 0.075469 (-0.014381) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.352107 / 1.841788 (-0.489681) | 19.973976 / 8.074308 (11.899668) | 14.292812 / 10.191392 (4.101420) | 0.163855 / 0.680424 (-0.516568) | 0.018402 / 0.534201 (-0.515799) | 0.393128 / 0.579283 (-0.186155) | 0.407379 / 0.434364 (-0.026985) | 0.462324 / 0.540337 (-0.078013) | 0.607501 / 1.386936 (-0.779435) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#ae126ac974cad3050f90106e5909232140786811 \"CML watermark\")\n" ]

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[ "Sorry for asking a duplicate question about `num_proc`, I searched the forum and find the solution.\r\n\r\nBut I still can't make the trick with `torch.distributed.barrier()` to only map at the main process work. The [post on forum]( https://discuss.huggingface.co/t/slow-processing-with-map-when-using-deepspeed-or-fairscale/7229/7) didn't help.", "If it does the `map` twice then it means the hash of your map function is not some same between your two processes.\r\n\r\nCan you make sure your map functions have the same hash in different processes ?\r\n\r\n```python\r\nfrom datasets.fingerprint import Hasher\r\n\r\nprint(Hasher.hash(lambda x: cut_reorder_keys(x, num_stations_list=args.num_stations_list, is_pad=True, is_train=True)))\r\nprint(Hasher.hash(lambda x: random_shift(x, shift_range=(-160, 0), feature_scale=16)))\r\n```\r\n\r\nYou can also set the fingerprint used to reload the resulting dataset by passing `new_finegrprint=` in `map`, see https://huggingface.co/docs/datasets/v2.13.1/en/about_cache#the-cache. This will force the different processes to use the same fingerprint used to locate the resulting dataset in the cache.", "Thanks for help! I find the fingerprint between processes don't have same hash:\r\n```\r\nRank 0: Gpu 0 cut_reorder_keys fingerprint c7f47f40e9a67657\r\nRank 0: Gpu 0 random_shift fingerprint 240a0ce79831e7d4\r\n\r\nRank 1: Gpu 1 cut_reorder_keys fingerprint 20edd3d9cf284001\r\nRank 1: Gpu 1 random_shift fingerprint 819f7c1c18e7733f\r\n```\r\nBut my functions only process the example one by one and don't need rank or other arguments. After all it can work in the test for dataset and dataloader.\r\nI'll try to set `new_fingerprint` to see if it works and figure out the reason of different hash.", "I finally figure it out. The fingerprint of the function will change if other key-value pairs change in `args` even the `args.num_stations_list` is not changed.\r\n\r\n```python\r\nlambda x: cut_reorder_keys(x, num_stations_list=args.num_stations_list, is_pad=True, is_train=True)\r\n```\r\n\r\nMy `args` contains the key `rank` which refers the rank of its GPU, so the fingerprints change among the GPUs.\r\nI use `partial` in `functools` to generate a partial function that fixs the argument `num_stations_list=args.num_stations_list`, and the fingerprint of this partial function keeps among the GPUs. Finally I can reuse the mapped cache." ]

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[ "I would like this also as I have been working with a dataset with hierarchical classes. In fact, I encountered this very issue when trying to define the dataset with a script. I couldn't find a work around and reverted to hard coding the class names in the readme yaml.\r\n\r\n@david-waterworth do you envision also being able to define the hierarchical structure of the classes?", "@danielduckworth yes I did need to do that (but I ended up ditching datasets as it looks like this is a \"wont fix\"). ", "@david-waterworth Hmm, that's a shame. What are you using now? Also, I’m curious to know about the work you’re doing that involves hierarchical classes, if you don’t mind sharing." ]

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[ "This can also mean one of the files was not downloaded correctly.\r\n\r\nWe log an erroneous file's name before raising the reader's error, so this is how you can find the problematic file. Then, you should delete it and call `load_dataset` again.\r\n\r\n(I checked all the uploaded files, and they seem to be valid Parquet files, so I don't think this is a bug on their side)\r\n" ]

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[ "Hi!\r\n\r\nIt's hard to explain this behavior without more information. Can you profile the slower version with the following code\r\n```python\r\nimport cProfile, pstats\r\nfrom datasets import load_dataset\r\n\r\nwith cProfile.Profile() as profiler:\r\n ds = load_dataset(...)\r\n\r\nstats = pstats.Stats(profiler).sort_stats(\"cumtime\")\r\nstats.print_stats()\r\n```\r\nand share the output?" ]

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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6056). All of your documentation changes will be reflected on that endpoint.", "@lhoestq Reading the filenames is something I tried earlier, but I decided to use the yaml direction because:\r\n\r\n1. The yaml file name is constructed to retain information about the shard_size, and total number of shards, hence ensuring that the files uploaded are not just files that have the same name but actually represent a different configuration of shard_size, and total number of shards. \r\n2. Remembering the total file size is done easily in the yaml, whereas alternatively I am not sure how one could access the file size of the uploaded files without downloading them.\r\n3. I also had an issue earlier with the hashes not being consistent with which the yaml helped -- but this is no longer an issue as I found a way around it. \r\n\r\nIf 1 and 2 can be achieved without an additional yaml, then I would be willing to make those changes. Let me know of any ideas. 1. could be done by changing the data file names, but I'd rather not do that as to prevent breaking existing datasets that try to upload updates to their data. ", "If the file name depends on the shard's fingerprint **before** mapping then we can know if a shard has been uploaded before mapping and without requiring an extra YAML file. It should do the job imo\r\n\r\n> I also had an issue earlier with the hashes not being consistent with which the yaml helped -- but this is no longer an issue as I found a way around it.\r\n\r\nwhat was the issue ?", "> If the file name depends on the shard's fingerprint **before** mapping then we can know if a shard has been uploaded before mapping and without requiring an extra YAML file. It should do the job imo\r\n> \r\n> > I also had an issue earlier with the hashes not being consistent with which the yaml helped -- but this is no longer an issue as I found a way around it.\r\n> \r\n> what was the issue ?\r\n\r\nYou are right. I was having some other issue earlier that I need more input from you guys to overcome, and when I overcame it the yaml was just legacy from before. I'll update the PR. ", "> If the file name depends on the shard's fingerprint **before** mapping then we can know if a shard has been uploaded before mapping and without requiring an extra YAML file. It should do the job imo\r\n> \r\n> > I also had an issue earlier with the hashes not being consistent with which the yaml helped -- but this is no longer an issue as I found a way around it.\r\n> \r\n> what was the issue ?\r\n\r\nI remembered what it was, and why I needed the yaml. I needed it so it could remember the progress for a particular num_shards setup, as different num_shards would lead to different number of splits, and a user might switch between them while uploading, and I did not want the index to be conflated with one of another num_shards setup. \r\n\r\nAny idea how we deal with that without a yaml?", "If the user changes the num_shards parameters then we should re-upload everything.\r\n\r\nIt happens that the num_shards is part of the parquet file names, so it restarts the upload from scratch without having to write additional logic :)" ]

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[ "A duplicate of https://github.com/huggingface/datasets/issues/5929" ]

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[ "This would break a lot of existing code, so we can't really do this." ]

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[ "_The documentation is not available anymore as the PR was closed or merged._", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006658 / 0.011353 (-0.004695) | 0.004347 / 0.011008 (-0.006661) | 0.084179 / 0.038508 (0.045671) | 0.080842 / 0.023109 (0.057733) | 0.321642 / 0.275898 (0.045744) | 0.348758 / 0.323480 (0.025278) | 0.005624 / 0.007986 (-0.002362) | 0.003479 / 0.004328 (-0.000850) | 0.065125 / 0.004250 (0.060875) | 0.057624 / 0.037052 (0.020572) | 0.323643 / 0.258489 (0.065154) | 0.360939 / 0.293841 (0.067098) | 0.031005 / 0.128546 (-0.097541) | 0.008618 / 0.075646 (-0.067028) | 0.287443 / 0.419271 (-0.131828) | 0.052640 / 0.043533 (0.009107) | 0.316947 / 0.255139 (0.061808) | 0.330292 / 0.283200 (0.047093) | 0.024393 / 0.141683 (-0.117289) | 1.476734 / 1.452155 (0.024579) | 1.534505 / 1.492716 (0.041789) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.273808 / 0.018006 (0.255802) | 0.591146 / 0.000490 (0.590656) | 0.000322 / 0.000200 (0.000122) | 0.000053 / 0.000054 (-0.000001) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.029992 / 0.037411 (-0.007419) | 0.086654 / 0.014526 (0.072129) | 0.098590 / 0.176557 (-0.077967) | 0.157225 / 0.737135 (-0.579910) | 0.101816 / 0.296338 (-0.194522) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.382578 / 0.215209 (0.167368) | 3.803576 / 2.077655 (1.725922) | 1.875136 / 1.504120 (0.371016) | 1.704207 / 1.541195 (0.163012) | 1.765146 / 1.468490 (0.296656) | 0.482802 / 4.584777 (-4.101975) | 3.571772 / 3.745712 (-0.173940) | 3.245626 / 5.269862 (-2.024235) | 2.051612 / 4.565676 (-2.514064) | 0.056539 / 0.424275 (-0.367736) | 0.007199 / 0.007607 (-0.000408) | 0.462445 / 0.226044 (0.236401) | 4.623800 / 2.268929 (2.354872) | 2.318948 / 55.444624 (-53.125677) | 1.971442 / 6.876477 (-4.905035) | 2.225444 / 2.142072 (0.083371) | 0.575205 / 4.805227 (-4.230022) | 0.129243 / 6.500664 (-6.371421) | 0.059036 / 0.075469 (-0.016433) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.266827 / 1.841788 (-0.574960) | 20.323419 / 8.074308 (12.249110) | 14.577603 / 10.191392 (4.386210) | 0.162131 / 0.680424 (-0.518293) | 0.018529 / 0.534201 (-0.515672) | 0.395046 / 0.579283 (-0.184237) | 0.410870 / 0.434364 (-0.023494) | 0.455782 / 0.540337 (-0.084556) | 0.662851 / 1.386936 (-0.724085) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006867 / 0.011353 (-0.004486) | 0.004197 / 0.011008 (-0.006811) | 0.066060 / 0.038508 (0.027552) | 0.084145 / 0.023109 (0.061036) | 0.366740 / 0.275898 (0.090842) | 0.402362 / 0.323480 (0.078882) | 0.005785 / 0.007986 (-0.002200) | 0.003551 / 0.004328 (-0.000778) | 0.066177 / 0.004250 (0.061926) | 0.061521 / 0.037052 (0.024468) | 0.377807 / 0.258489 (0.119318) | 0.413490 / 0.293841 (0.119649) | 0.031918 / 0.128546 (-0.096628) | 0.008767 / 0.075646 (-0.066879) | 0.071437 / 0.419271 (-0.347835) | 0.049237 / 0.043533 (0.005704) | 0.365929 / 0.255139 (0.110790) | 0.393545 / 0.283200 (0.110346) | 0.024054 / 0.141683 (-0.117628) | 1.524599 / 1.452155 (0.072445) | 1.576592 / 1.492716 (0.083876) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.315181 / 0.018006 (0.297174) | 0.535501 / 0.000490 (0.535011) | 0.000410 / 0.000200 (0.000210) | 0.000054 / 0.000054 (-0.000000) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.032915 / 0.037411 (-0.004497) | 0.089310 / 0.014526 (0.074784) | 0.105136 / 0.176557 (-0.071421) | 0.158572 / 0.737135 (-0.578563) | 0.106850 / 0.296338 (-0.189489) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.419343 / 0.215209 (0.204134) | 4.200166 / 2.077655 (2.122511) | 2.180234 / 1.504120 (0.676114) | 2.016885 / 1.541195 (0.475690) | 2.131480 / 1.468490 (0.662990) | 0.484681 / 4.584777 (-4.100096) | 3.613535 / 3.745712 (-0.132177) | 5.762111 / 5.269862 (0.492249) | 3.190590 / 4.565676 (-1.375086) | 0.057403 / 0.424275 (-0.366872) | 0.007862 / 0.007607 (0.000255) | 0.490857 / 0.226044 (0.264813) | 4.911241 / 2.268929 (2.642313) | 2.650787 / 55.444624 (-52.793838) | 2.317060 / 6.876477 (-4.559416) | 2.579677 / 2.142072 (0.437605) | 0.587388 / 4.805227 (-4.217840) | 0.148109 / 6.500664 (-6.352555) | 0.061435 / 0.075469 (-0.014034) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.322181 / 1.841788 (-0.519606) | 20.647184 / 8.074308 (12.572875) | 14.907635 / 10.191392 (4.716243) | 0.156330 / 0.680424 (-0.524094) | 0.018719 / 0.534201 (-0.515482) | 0.397636 / 0.579283 (-0.181647) | 0.414107 / 0.434364 (-0.020257) | 0.460812 / 0.540337 (-0.079526) | 0.609568 / 1.386936 (-0.777368) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#74398c95b81a08a51457a2bef56efb7e608bded2 \"CML watermark\")\n", "This would mean when i update my examples to newer datasets version i need to make a change right? nothing backward breaking? ", "what would be the change i need to make? ", "@philschmid You just need to replace the occurrences of `datasets.filesystems.S3FileSystem` with `s3fs.S3FileSystem`. From the moment it was added until now, `datasets.filesystems.S3FileSystem` is a \"dummy\" subclass of `s3fs.S3FileSystem` that only changes its docstring.\r\n\r\n\r\n", "The CI is failing because I updated the YAML validation for https://github.com/huggingface/datasets/pull/6044.\r\nIt will be fixed once https://github.com/huggingface/datasets/pull/6044 is merged", "I just merged the other PR so you should be good now", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006303 / 0.011353 (-0.005049) | 0.003746 / 0.011008 (-0.007262) | 0.081083 / 0.038508 (0.042575) | 0.067973 / 0.023109 (0.044864) | 0.322221 / 0.275898 (0.046323) | 0.359432 / 0.323480 (0.035952) | 0.004891 / 0.007986 (-0.003095) | 0.002988 / 0.004328 (-0.001341) | 0.064068 / 0.004250 (0.059818) | 0.052042 / 0.037052 (0.014990) | 0.323387 / 0.258489 (0.064898) | 0.390416 / 0.293841 (0.096575) | 0.028090 / 0.128546 (-0.100457) | 0.008009 / 0.075646 (-0.067638) | 0.262288 / 0.419271 (-0.156984) | 0.044986 / 0.043533 (0.001453) | 0.322319 / 0.255139 (0.067180) | 0.345323 / 0.283200 (0.062123) | 0.021798 / 0.141683 (-0.119885) | 1.417259 / 1.452155 (-0.034895) | 1.490050 / 1.492716 (-0.002667) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.195902 / 0.018006 (0.177896) | 0.490808 / 0.000490 (0.490318) | 0.002969 / 0.000200 (0.002770) | 0.000126 / 0.000054 (0.000072) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.025221 / 0.037411 (-0.012190) | 0.075341 / 0.014526 (0.060815) | 0.086703 / 0.176557 (-0.089853) | 0.146953 / 0.737135 (-0.590182) | 0.086610 / 0.296338 (-0.209728) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.434890 / 0.215209 (0.219681) | 4.352283 / 2.077655 (2.274629) | 2.293098 / 1.504120 (0.788979) | 2.123023 / 1.541195 (0.581829) | 2.179722 / 1.468490 (0.711232) | 0.503851 / 4.584777 (-4.080926) | 3.087991 / 3.745712 (-0.657721) | 2.898689 / 5.269862 (-2.371173) | 1.902813 / 4.565676 (-2.662864) | 0.058079 / 0.424275 (-0.366196) | 0.006600 / 0.007607 (-0.001007) | 0.509243 / 0.226044 (0.283199) | 5.080204 / 2.268929 (2.811275) | 2.753594 / 55.444624 (-52.691030) | 2.417385 / 6.876477 (-4.459091) | 2.635470 / 2.142072 (0.493398) | 0.591059 / 4.805227 (-4.214168) | 0.126360 / 6.500664 (-6.374304) | 0.062108 / 0.075469 (-0.013361) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.254398 / 1.841788 (-0.587390) | 18.866729 / 8.074308 (10.792420) | 14.120008 / 10.191392 (3.928616) | 0.152388 / 0.680424 (-0.528035) | 0.016997 / 0.534201 (-0.517204) | 0.336435 / 0.579283 (-0.242848) | 0.364612 / 0.434364 (-0.069752) | 0.391434 / 0.540337 (-0.148903) | 0.567180 / 1.386936 (-0.819756) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006477 / 0.011353 (-0.004876) | 0.003723 / 0.011008 (-0.007285) | 0.062712 / 0.038508 (0.024204) | 0.069380 / 0.023109 (0.046271) | 0.393394 / 0.275898 (0.117496) | 0.446903 / 0.323480 (0.123423) | 0.004833 / 0.007986 (-0.003153) | 0.002946 / 0.004328 (-0.001382) | 0.062076 / 0.004250 (0.057826) | 0.051589 / 0.037052 (0.014537) | 0.388536 / 0.258489 (0.130047) | 0.451406 / 0.293841 (0.157565) | 0.027824 / 0.128546 (-0.100722) | 0.008040 / 0.075646 (-0.067606) | 0.067085 / 0.419271 (-0.352187) | 0.042269 / 0.043533 (-0.001264) | 0.363419 / 0.255139 (0.108280) | 0.435201 / 0.283200 (0.152001) | 0.021275 / 0.141683 (-0.120408) | 1.439838 / 1.452155 (-0.012316) | 1.477279 / 1.492716 (-0.015437) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.229667 / 0.018006 (0.211661) | 0.434101 / 0.000490 (0.433611) | 0.000652 / 0.000200 (0.000452) | 0.000060 / 0.000054 (0.000005) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.026141 / 0.037411 (-0.011271) | 0.078950 / 0.014526 (0.064424) | 0.090143 / 0.176557 (-0.086413) | 0.143941 / 0.737135 (-0.593195) | 0.090465 / 0.296338 (-0.205873) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.432042 / 0.215209 (0.216833) | 4.322134 / 2.077655 (2.244479) | 2.242897 / 1.504120 (0.738777) | 2.076351 / 1.541195 (0.535157) | 2.166739 / 1.468490 (0.698249) | 0.500833 / 4.584777 (-4.083944) | 3.140117 / 3.745712 (-0.605595) | 4.383050 / 5.269862 (-0.886812) | 2.548245 / 4.565676 (-2.017432) | 0.057521 / 0.424275 (-0.366754) | 0.006946 / 0.007607 (-0.000662) | 0.509613 / 0.226044 (0.283569) | 5.114052 / 2.268929 (2.845123) | 2.682112 / 55.444624 (-52.762512) | 2.362385 / 6.876477 (-4.514092) | 2.531787 / 2.142072 (0.389715) | 0.595085 / 4.805227 (-4.210142) | 0.130198 / 6.500664 (-6.370466) | 0.064057 / 0.075469 (-0.011412) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.346254 / 1.841788 (-0.495534) | 19.036911 / 8.074308 (10.962603) | 14.478689 / 10.191392 (4.287297) | 0.147541 / 0.680424 (-0.532883) | 0.016851 / 0.534201 (-0.517350) | 0.333901 / 0.579283 (-0.245382) | 0.380012 / 0.434364 (-0.054352) | 0.396021 / 0.540337 (-0.144317) | 0.540612 / 1.386936 (-0.846324) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#02dd4ccaf7971cd71d658ce9f62bc0c5cfc1e3ad \"CML watermark\")\n", "CI failure is unrelated. Merging.", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.009498 / 0.011353 (-0.001855) | 0.005639 / 0.011008 (-0.005369) | 0.108731 / 0.038508 (0.070223) | 0.094052 / 0.023109 (0.070943) | 0.454375 / 0.275898 (0.178477) | 0.486852 / 0.323480 (0.163372) | 0.006627 / 0.007986 (-0.001359) | 0.004712 / 0.004328 (0.000383) | 0.082006 / 0.004250 (0.077756) | 0.079394 / 0.037052 (0.042342) | 0.450982 / 0.258489 (0.192493) | 0.502659 / 0.293841 (0.208818) | 0.049741 / 0.128546 (-0.078806) | 0.014482 / 0.075646 (-0.061164) | 0.362661 / 0.419271 (-0.056611) | 0.068225 / 0.043533 (0.024692) | 0.456219 / 0.255139 (0.201080) | 0.483919 / 0.283200 (0.200719) | 0.044490 / 0.141683 (-0.097193) | 1.809420 / 1.452155 (0.357265) | 1.908859 / 1.492716 (0.416143) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.267350 / 0.018006 (0.249344) | 0.600403 / 0.000490 (0.599913) | 0.003665 / 0.000200 (0.003465) | 0.000162 / 0.000054 (0.000107) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.032499 / 0.037411 (-0.004912) | 0.104829 / 0.014526 (0.090303) | 0.115809 / 0.176557 (-0.060747) | 0.191561 / 0.737135 (-0.545574) | 0.113454 / 0.296338 (-0.182885) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.599165 / 0.215209 (0.383956) | 5.802947 / 2.077655 (3.725292) | 2.477330 / 1.504120 (0.973210) | 2.231147 / 1.541195 (0.689952) | 2.365688 / 1.468490 (0.897197) | 0.853912 / 4.584777 (-3.730865) | 5.529472 / 3.745712 (1.783760) | 6.145286 / 5.269862 (0.875424) | 3.415871 / 4.565676 (-1.149805) | 0.099889 / 0.424275 (-0.324386) | 0.008933 / 0.007607 (0.001325) | 0.704643 / 0.226044 (0.478598) | 7.178101 / 2.268929 (4.909173) | 3.367120 / 55.444624 (-52.077504) | 2.795177 / 6.876477 (-4.081300) | 2.796798 / 2.142072 (0.654726) | 1.039097 / 4.805227 (-3.766130) | 0.232784 / 6.500664 (-6.267881) | 0.083608 / 0.075469 (0.008138) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.646827 / 1.841788 (-0.194961) | 25.003419 / 8.074308 (16.929111) | 22.165746 / 10.191392 (11.974354) | 0.246179 / 0.680424 (-0.434245) | 0.029304 / 0.534201 (-0.504897) | 0.500767 / 0.579283 (-0.078516) | 0.606501 / 0.434364 (0.172137) | 0.564092 / 0.540337 (0.023755) | 0.857568 / 1.386936 (-0.529368) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.009206 / 0.011353 (-0.002146) | 0.005084 / 0.011008 (-0.005925) | 0.081402 / 0.038508 (0.042894) | 0.088028 / 0.023109 (0.064919) | 0.539509 / 0.275898 (0.263611) | 0.590759 / 0.323480 (0.267280) | 0.006527 / 0.007986 (-0.001459) | 0.004375 / 0.004328 (0.000047) | 0.082327 / 0.004250 (0.078076) | 0.065442 / 0.037052 (0.028390) | 0.548254 / 0.258489 (0.289765) | 0.598388 / 0.293841 (0.304547) | 0.049409 / 0.128546 (-0.079137) | 0.014366 / 0.075646 (-0.061280) | 0.094568 / 0.419271 (-0.324703) | 0.063685 / 0.043533 (0.020152) | 0.545359 / 0.255139 (0.290220) | 0.573358 / 0.283200 (0.290159) | 0.036864 / 0.141683 (-0.104819) | 1.817985 / 1.452155 (0.365830) | 1.925188 / 1.492716 (0.432472) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.303205 / 0.018006 (0.285199) | 0.620981 / 0.000490 (0.620491) | 0.004910 / 0.000200 (0.004710) | 0.000104 / 0.000054 (0.000050) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.033791 / 0.037411 (-0.003620) | 0.114974 / 0.014526 (0.100448) | 0.117682 / 0.176557 (-0.058875) | 0.177188 / 0.737135 (-0.559947) | 0.126425 / 0.296338 (-0.169914) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.636932 / 0.215209 (0.421723) | 6.289054 / 2.077655 (4.211399) | 2.920772 / 1.504120 (1.416652) | 2.672080 / 1.541195 (1.130885) | 2.712271 / 1.468490 (1.243781) | 0.889305 / 4.584777 (-3.695472) | 5.536018 / 3.745712 (1.790306) | 4.687564 / 5.269862 (-0.582298) | 3.204239 / 4.565676 (-1.361437) | 0.095546 / 0.424275 (-0.328729) | 0.008838 / 0.007607 (0.001231) | 0.714584 / 0.226044 (0.488540) | 7.482663 / 2.268929 (5.213735) | 3.621392 / 55.444624 (-51.823232) | 2.987777 / 6.876477 (-3.888700) | 3.312636 / 2.142072 (1.170564) | 1.033721 / 4.805227 (-3.771506) | 0.206292 / 6.500664 (-6.294372) | 0.079423 / 0.075469 (0.003953) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.798645 / 1.841788 (-0.043143) | 25.544329 / 8.074308 (17.470021) | 23.041318 / 10.191392 (12.849926) | 0.259067 / 0.680424 (-0.421357) | 0.029839 / 0.534201 (-0.504362) | 0.495583 / 0.579283 (-0.083700) | 0.598755 / 0.434364 (0.164391) | 0.574864 / 0.540337 (0.034527) | 0.831160 / 1.386936 (-0.555776) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#4200443045e694a045446950e8b235c7beb6239e \"CML watermark\")\n" ]

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[ "Hi! `_select_contiguous` fetches a (zero-copy) slice of the dataset's Arrow table to build a shard, so I don't think this part is the problem. To me, the issue seems to be the step where we embed external image files' bytes (a lot of file reads). You can use `.map` with multiprocessing to perform this step before `push_to_hub` in a faster manner and cache it to disk:\r\n```python\r\nfrom datasets.table import embed_table_storage\r\n# load_dataset(...)\r\nformat = dataset.format\r\ndataset = dataset.with_format(\"arrow\")\r\ndataset = dataset.map(embed_table_storage, batched=True)\r\ndataset = dataset.with_format(**format)\r\n# push_to_hub(...)\r\n```\r\n\r\n(In Datasets 3.0, these external bytes will be written to an Arrow file when generating a dataset to avoid this \"embed\" step)", "Hi, thanks, this solution saves some time.\r\nBut can't we avoid embedding all external image files bytes with each push, skipping the images that have already been pushed into the repo?\r\n\r\nEdit: Ok I missed the part of cache it manually on the disk the first time, this solves the problem. Thank you" ]

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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6049). All of your documentation changes will be reflected on that endpoint.", "I've updated the `ruff`'s pre-commit version as part of https://github.com/huggingface/datasets/pull/6434, so feel free to close this PR." ]

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[ "The `audiofolder` loader is not available in version `2.3.2`, hence the error. Please run the `pip install -U datasets` command to update the `datasets` installation to make `load_dataset(\"audiofolder\", ...)` work." ]

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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6047). All of your documentation changes will be reflected on that endpoint.", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006384 / 0.011353 (-0.004969) | 0.003872 / 0.011008 (-0.007136) | 0.083454 / 0.038508 (0.044946) | 0.069120 / 0.023109 (0.046011) | 0.312573 / 0.275898 (0.036675) | 0.345814 / 0.323480 (0.022334) | 0.005729 / 0.007986 (-0.002257) | 0.003225 / 0.004328 (-0.001103) | 0.063950 / 0.004250 (0.059700) | 0.053998 / 0.037052 (0.016946) | 0.316492 / 0.258489 (0.058003) | 0.350738 / 0.293841 (0.056897) | 0.030770 / 0.128546 (-0.097776) | 0.008474 / 0.075646 (-0.067173) | 0.286989 / 0.419271 (-0.132282) | 0.052473 / 0.043533 (0.008940) | 0.314361 / 0.255139 (0.059222) | 0.335170 / 0.283200 (0.051970) | 0.022885 / 0.141683 (-0.118798) | 1.465430 / 1.452155 (0.013275) | 1.527799 / 1.492716 (0.035083) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.209377 / 0.018006 (0.191371) | 0.455583 / 0.000490 (0.455094) | 0.003352 / 0.000200 (0.003152) | 0.000080 / 0.000054 (0.000025) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.026284 / 0.037411 (-0.011127) | 0.080710 / 0.014526 (0.066185) | 0.091741 / 0.176557 (-0.084816) | 0.147602 / 0.737135 (-0.589534) | 0.091173 / 0.296338 (-0.205166) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.386592 / 0.215209 (0.171383) | 3.856665 / 2.077655 (1.779011) | 1.835745 / 1.504120 (0.331625) | 1.671814 / 1.541195 (0.130619) | 1.711224 / 1.468490 (0.242734) | 0.484704 / 4.584777 (-4.100073) | 3.649239 / 3.745712 (-0.096473) | 3.784051 / 5.269862 (-1.485810) | 2.241195 / 4.565676 (-2.324482) | 0.056613 / 0.424275 (-0.367662) | 0.007140 / 0.007607 (-0.000467) | 0.464585 / 0.226044 (0.238540) | 4.616537 / 2.268929 (2.347609) | 2.371969 / 55.444624 (-53.072656) | 1.977754 / 6.876477 (-4.898723) | 2.083385 / 2.142072 (-0.058687) | 0.582330 / 4.805227 (-4.222897) | 0.132744 / 6.500664 (-6.367920) | 0.059822 / 0.075469 (-0.015647) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.259566 / 1.841788 (-0.582221) | 18.990166 / 8.074308 (10.915858) | 13.992069 / 10.191392 (3.800677) | 0.160001 / 0.680424 (-0.520423) | 0.018622 / 0.534201 (-0.515579) | 0.392921 / 0.579283 (-0.186362) | 0.418225 / 0.434364 (-0.016139) | 0.471252 / 0.540337 (-0.069086) | 0.653227 / 1.386936 (-0.733709) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006641 / 0.011353 (-0.004712) | 0.003738 / 0.011008 (-0.007271) | 0.064053 / 0.038508 (0.025545) | 0.069467 / 0.023109 (0.046357) | 0.360625 / 0.275898 (0.084727) | 0.394291 / 0.323480 (0.070811) | 0.005236 / 0.007986 (-0.002750) | 0.003304 / 0.004328 (-0.001024) | 0.064078 / 0.004250 (0.059827) | 0.054605 / 0.037052 (0.017552) | 0.374567 / 0.258489 (0.116078) | 0.411227 / 0.293841 (0.117386) | 0.031614 / 0.128546 (-0.096933) | 0.008323 / 0.075646 (-0.067324) | 0.070616 / 0.419271 (-0.348656) | 0.050077 / 0.043533 (0.006544) | 0.362229 / 0.255139 (0.107090) | 0.388310 / 0.283200 (0.105110) | 0.024053 / 0.141683 (-0.117630) | 1.508913 / 1.452155 (0.056759) | 1.562140 / 1.492716 (0.069423) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.230172 / 0.018006 (0.212165) | 0.449363 / 0.000490 (0.448873) | 0.002374 / 0.000200 (0.002174) | 0.000097 / 0.000054 (0.000043) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.029813 / 0.037411 (-0.007598) | 0.087298 / 0.014526 (0.072772) | 0.096712 / 0.176557 (-0.079845) | 0.152864 / 0.737135 (-0.584271) | 0.098204 / 0.296338 (-0.198135) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.408664 / 0.215209 (0.193455) | 4.075068 / 2.077655 (1.997414) | 2.096365 / 1.504120 (0.592245) | 1.936096 / 1.541195 (0.394901) | 1.961872 / 1.468490 (0.493382) | 0.483383 / 4.584777 (-4.101394) | 3.686926 / 3.745712 (-0.058787) | 4.798824 / 5.269862 (-0.471037) | 2.652279 / 4.565676 (-1.913398) | 0.056695 / 0.424275 (-0.367580) | 0.007592 / 0.007607 (-0.000016) | 0.484710 / 0.226044 (0.258665) | 4.842153 / 2.268929 (2.573225) | 2.636828 / 55.444624 (-52.807796) | 2.243666 / 6.876477 (-4.632811) | 2.375972 / 2.142072 (0.233899) | 0.578544 / 4.805227 (-4.226683) | 0.132579 / 6.500664 (-6.368085) | 0.061287 / 0.075469 (-0.014182) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.360287 / 1.841788 (-0.481501) | 19.464110 / 8.074308 (11.389802) | 14.530875 / 10.191392 (4.339483) | 0.149479 / 0.680424 (-0.530944) | 0.018471 / 0.534201 (-0.515730) | 0.395399 / 0.579283 (-0.183884) | 0.412897 / 0.434364 (-0.021467) | 0.465194 / 0.540337 (-0.075144) | 0.611752 / 1.386936 (-0.775184) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#79a535de98b590da7bc223a6498c59790882f14a \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.008986 / 0.011353 (-0.002367) | 0.005104 / 0.011008 (-0.005905) | 0.108371 / 0.038508 (0.069863) | 0.091655 / 0.023109 (0.068546) | 0.430183 / 0.275898 (0.154285) | 0.481387 / 0.323480 (0.157907) | 0.006662 / 0.007986 (-0.001324) | 0.004681 / 0.004328 (0.000353) | 0.089325 / 0.004250 (0.085075) | 0.065096 / 0.037052 (0.028044) | 0.435021 / 0.258489 (0.176532) | 0.478635 / 0.293841 (0.184794) | 0.047628 / 0.128546 (-0.080918) | 0.013496 / 0.075646 (-0.062150) | 0.389661 / 0.419271 (-0.029611) | 0.082260 / 0.043533 (0.038727) | 0.474165 / 0.255139 (0.219026) | 0.464877 / 0.283200 (0.181677) | 0.039784 / 0.141683 (-0.101899) | 1.874694 / 1.452155 (0.422539) | 1.980183 / 1.492716 (0.487467) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.254044 / 0.018006 (0.236038) | 0.631495 / 0.000490 (0.631005) | 0.000628 / 0.000200 (0.000428) | 0.000086 / 0.000054 (0.000032) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.038773 / 0.037411 (0.001362) | 0.103681 / 0.014526 (0.089156) | 0.125081 / 0.176557 (-0.051476) | 0.198345 / 0.737135 (-0.538790) | 0.122217 / 0.296338 (-0.174121) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.611677 / 0.215209 (0.396468) | 6.220790 / 2.077655 (4.143135) | 2.729858 / 1.504120 (1.225739) | 2.351944 / 1.541195 (0.810749) | 2.449137 / 1.468490 (0.980647) | 0.896842 / 4.584777 (-3.687935) | 5.537491 / 3.745712 (1.791778) | 8.480182 / 5.269862 (3.210320) | 5.251404 / 4.565676 (0.685728) | 0.100449 / 0.424275 (-0.323826) | 0.009008 / 0.007607 (0.001401) | 0.750060 / 0.226044 (0.524016) | 7.390940 / 2.268929 (5.122011) | 3.478256 / 55.444624 (-51.966369) | 2.883597 / 6.876477 (-3.992880) | 3.082256 / 2.142072 (0.940183) | 1.114339 / 4.805227 (-3.690889) | 0.225389 / 6.500664 (-6.275275) | 0.083972 / 0.075469 (0.008503) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.741522 / 1.841788 (-0.100266) | 25.674700 / 8.074308 (17.600392) | 24.324412 / 10.191392 (14.133020) | 0.257878 / 0.680424 (-0.422546) | 0.038384 / 0.534201 (-0.495817) | 0.508302 / 0.579283 (-0.070981) | 0.612979 / 0.434364 (0.178615) | 0.584366 / 0.540337 (0.044029) | 0.881115 / 1.386936 (-0.505821) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.009114 / 0.011353 (-0.002239) | 0.005333 / 0.011008 (-0.005675) | 0.094944 / 0.038508 (0.056436) | 0.099178 / 0.023109 (0.076068) | 0.529813 / 0.275898 (0.253915) | 0.551282 / 0.323480 (0.227802) | 0.006442 / 0.007986 (-0.001543) | 0.004283 / 0.004328 (-0.000045) | 0.084257 / 0.004250 (0.080007) | 0.067557 / 0.037052 (0.030504) | 0.514733 / 0.258489 (0.256244) | 0.568200 / 0.293841 (0.274359) | 0.050969 / 0.128546 (-0.077577) | 0.014495 / 0.075646 (-0.061151) | 0.097089 / 0.419271 (-0.322182) | 0.063142 / 0.043533 (0.019609) | 0.513327 / 0.255139 (0.258188) | 0.520593 / 0.283200 (0.237394) | 0.036824 / 0.141683 (-0.104859) | 1.954875 / 1.452155 (0.502720) | 1.976307 / 1.492716 (0.483591) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.304070 / 0.018006 (0.286063) | 0.611073 / 0.000490 (0.610583) | 0.005027 / 0.000200 (0.004827) | 0.000113 / 0.000054 (0.000059) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.037993 / 0.037411 (0.000582) | 0.115876 / 0.014526 (0.101350) | 0.118087 / 0.176557 (-0.058469) | 0.186437 / 0.737135 (-0.550699) | 0.129883 / 0.296338 (-0.166456) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.658292 / 0.215209 (0.443083) | 6.618257 / 2.077655 (4.540602) | 3.203786 / 1.504120 (1.699667) | 2.858714 / 1.541195 (1.317519) | 2.940974 / 1.468490 (1.472484) | 0.856238 / 4.584777 (-3.728538) | 5.427708 / 3.745712 (1.681996) | 4.810048 / 5.269862 (-0.459813) | 3.120006 / 4.565676 (-1.445671) | 0.098098 / 0.424275 (-0.326177) | 0.010077 / 0.007607 (0.002470) | 0.790890 / 0.226044 (0.564845) | 7.956679 / 2.268929 (5.687750) | 3.955710 / 55.444624 (-51.488914) | 3.446419 / 6.876477 (-3.430057) | 3.541228 / 2.142072 (1.399156) | 1.013420 / 4.805227 (-3.791808) | 0.213741 / 6.500664 (-6.286923) | 0.080857 / 0.075469 (0.005388) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.813265 / 1.841788 (-0.028522) | 25.965199 / 8.074308 (17.890891) | 21.892761 / 10.191392 (11.701369) | 0.257843 / 0.680424 (-0.422580) | 0.029388 / 0.534201 (-0.504813) | 0.510609 / 0.579283 (-0.068674) | 0.626579 / 0.434364 (0.192215) | 0.576865 / 0.540337 (0.036528) | 0.826610 / 1.386936 (-0.560326) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#a1a9c00249b330f97f66ceb86c2939261091f4fe \"CML watermark\")\n" ]

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[ "hii @lhoestq can you assign this issue to me?\r\n", "You can reply \"#self-assign\" to this issue to automatically get assigned to it :)\r\nLet me know if you have any questions or if I can help", "#2289 ", "Actually i am quite new to figure it out how everything goes and done \r\n\r\n> You can reply \"#self-assign\" to this issue to automatically get assigned to it :)\r\n> Let me know if you have any questions or if I can help\r\n\r\nwhen i wrote #self-assign it automatically got converted to some number is it correct or i have done it some wrong way, I am quite new to open source thus wanna try to learn and explore it", "#2289 #self-assign ", "Ah yea github tries to replace the #self-assign with an issue link. I guess you can try to copy-paste instead to see if it works\r\n\r\nAnyway let me assign you manually", "thanks a lot @lhoestq ! though i have a very lil idea of the issue, i am new. as i said before, but gonna try my best shot to do it.\r\ncan you please suggest some tips or anything from your side, how basically we approach it will be really helpfull.\r\nWill try my best!", "The HfFileSystem from the `huggingface_hub` package can already read the HTTP_PROXY and HTTPS_PROXY environment variables. So the remaining thing missing is the `user_agent` that the user may include in a `DownloadConfig` object. The user agent can be used for regular http calls but also calls to the HfFileSystem.\r\n\r\n- for http, the `user_agent` isn't passed from `DownloadConfig` to `get_datasets_user_agent` in `_prepare_single_hop_path_and_storage_options` in `streaming_download_manager.py` so we need to include it\r\n- for HfFileSystem I think it requires a PR in https://github.com/huggingface/huggingface_hub to include it in the `HfFileSystem.__init__`" ]

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[ "_The documentation is not available anymore as the PR was closed or merged._", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006557 / 0.011353 (-0.004796) | 0.004096 / 0.011008 (-0.006913) | 0.083577 / 0.038508 (0.045069) | 0.072092 / 0.023109 (0.048983) | 0.319192 / 0.275898 (0.043294) | 0.351845 / 0.323480 (0.028365) | 0.005475 / 0.007986 (-0.002511) | 0.003419 / 0.004328 (-0.000910) | 0.064562 / 0.004250 (0.060311) | 0.057930 / 0.037052 (0.020878) | 0.326085 / 0.258489 (0.067596) | 0.368316 / 0.293841 (0.074475) | 0.030502 / 0.128546 (-0.098044) | 0.008504 / 0.075646 (-0.067142) | 0.287217 / 0.419271 (-0.132054) | 0.052337 / 0.043533 (0.008804) | 0.319011 / 0.255139 (0.063872) | 0.352711 / 0.283200 (0.069511) | 0.023278 / 0.141683 (-0.118405) | 1.482578 / 1.452155 (0.030423) | 1.553391 / 1.492716 (0.060675) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.199628 / 0.018006 (0.181622) | 0.464571 / 0.000490 (0.464081) | 0.003512 / 0.000200 (0.003312) | 0.000072 / 0.000054 (0.000018) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.029109 / 0.037411 (-0.008302) | 0.082203 / 0.014526 (0.067677) | 0.096223 / 0.176557 (-0.080333) | 0.155598 / 0.737135 (-0.581537) | 0.097738 / 0.296338 (-0.198600) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.386135 / 0.215209 (0.170926) | 3.837157 / 2.077655 (1.759502) | 1.836869 / 1.504120 (0.332750) | 1.680592 / 1.541195 (0.139398) | 1.769456 / 1.468490 (0.300966) | 0.493150 / 4.584777 (-4.091627) | 3.589797 / 3.745712 (-0.155915) | 3.330000 / 5.269862 (-1.939861) | 2.059856 / 4.565676 (-2.505821) | 0.057951 / 0.424275 (-0.366324) | 0.007340 / 0.007607 (-0.000267) | 0.463203 / 0.226044 (0.237159) | 4.631514 / 2.268929 (2.362585) | 2.329887 / 55.444624 (-53.114738) | 2.008815 / 6.876477 (-4.867662) | 2.199067 / 2.142072 (0.056995) | 0.591417 / 4.805227 (-4.213810) | 0.137154 / 6.500664 (-6.363510) | 0.061326 / 0.075469 (-0.014143) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.269676 / 1.841788 (-0.572111) | 19.375167 / 8.074308 (11.300858) | 13.945419 / 10.191392 (3.754027) | 0.146482 / 0.680424 (-0.533942) | 0.018257 / 0.534201 (-0.515944) | 0.391684 / 0.579283 (-0.187599) | 0.411454 / 0.434364 (-0.022910) | 0.466260 / 0.540337 (-0.074077) | 0.655571 / 1.386936 (-0.731365) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006619 / 0.011353 (-0.004734) | 0.004102 / 0.011008 (-0.006907) | 0.064848 / 0.038508 (0.026340) | 0.074822 / 0.023109 (0.051713) | 0.366535 / 0.275898 (0.090637) | 0.395873 / 0.323480 (0.072394) | 0.005315 / 0.007986 (-0.002670) | 0.003270 / 0.004328 (-0.001059) | 0.064829 / 0.004250 (0.060578) | 0.056094 / 0.037052 (0.019042) | 0.370355 / 0.258489 (0.111866) | 0.406837 / 0.293841 (0.112996) | 0.031634 / 0.128546 (-0.096912) | 0.008569 / 0.075646 (-0.067077) | 0.071126 / 0.419271 (-0.348145) | 0.048629 / 0.043533 (0.005096) | 0.365175 / 0.255139 (0.110036) | 0.385234 / 0.283200 (0.102034) | 0.023295 / 0.141683 (-0.118388) | 1.466907 / 1.452155 (0.014752) | 1.523118 / 1.492716 (0.030401) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.227872 / 0.018006 (0.209866) | 0.451573 / 0.000490 (0.451083) | 0.000379 / 0.000200 (0.000179) | 0.000055 / 0.000054 (0.000001) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.029496 / 0.037411 (-0.007915) | 0.086614 / 0.014526 (0.072088) | 0.098165 / 0.176557 (-0.078392) | 0.152218 / 0.737135 (-0.584917) | 0.101215 / 0.296338 (-0.195123) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.407519 / 0.215209 (0.192310) | 4.074704 / 2.077655 (1.997049) | 2.113185 / 1.504120 (0.609065) | 1.947461 / 1.541195 (0.406266) | 1.998521 / 1.468490 (0.530031) | 0.487463 / 4.584777 (-4.097313) | 3.465423 / 3.745712 (-0.280289) | 3.376498 / 5.269862 (-1.893363) | 2.001533 / 4.565676 (-2.564144) | 0.057052 / 0.424275 (-0.367223) | 0.007325 / 0.007607 (-0.000283) | 0.485648 / 0.226044 (0.259604) | 4.860191 / 2.268929 (2.591262) | 2.550340 / 55.444624 (-52.894284) | 2.231136 / 6.876477 (-4.645341) | 2.262539 / 2.142072 (0.120467) | 0.591422 / 4.805227 (-4.213805) | 0.132875 / 6.500664 (-6.367789) | 0.062154 / 0.075469 (-0.013315) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.321834 / 1.841788 (-0.519954) | 19.734750 / 8.074308 (11.660442) | 14.681049 / 10.191392 (4.489657) | 0.148894 / 0.680424 (-0.531530) | 0.018414 / 0.534201 (-0.515787) | 0.393377 / 0.579283 (-0.185906) | 0.402795 / 0.434364 (-0.031569) | 0.478624 / 0.540337 (-0.061714) | 0.656767 / 1.386936 (-0.730169) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#a5a84a1fa226a4cafb3bb4387dc4b212a46caf31 \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007012 / 0.011353 (-0.004341) | 0.004120 / 0.011008 (-0.006888) | 0.083720 / 0.038508 (0.045212) | 0.083105 / 0.023109 (0.059996) | 0.323803 / 0.275898 (0.047905) | 0.340345 / 0.323480 (0.016865) | 0.005872 / 0.007986 (-0.002113) | 0.003528 / 0.004328 (-0.000801) | 0.065185 / 0.004250 (0.060935) | 0.063092 / 0.037052 (0.026040) | 0.314900 / 0.258489 (0.056411) | 0.349251 / 0.293841 (0.055410) | 0.031612 / 0.128546 (-0.096934) | 0.008541 / 0.075646 (-0.067105) | 0.289865 / 0.419271 (-0.129407) | 0.055264 / 0.043533 (0.011731) | 0.309152 / 0.255139 (0.054013) | 0.332625 / 0.283200 (0.049425) | 0.024306 / 0.141683 (-0.117377) | 1.489191 / 1.452155 (0.037037) | 1.562447 / 1.492716 (0.069731) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.236681 / 0.018006 (0.218675) | 0.567767 / 0.000490 (0.567277) | 0.003022 / 0.000200 (0.002822) | 0.000218 / 0.000054 (0.000164) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.028698 / 0.037411 (-0.008714) | 0.081681 / 0.014526 (0.067155) | 0.099109 / 0.176557 (-0.077447) | 0.154381 / 0.737135 (-0.582754) | 0.098691 / 0.296338 (-0.197648) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.397985 / 0.215209 (0.182776) | 3.962499 / 2.077655 (1.884844) | 1.936158 / 1.504120 (0.432038) | 1.762339 / 1.541195 (0.221144) | 1.837451 / 1.468490 (0.368961) | 0.485655 / 4.584777 (-4.099122) | 3.538341 / 3.745712 (-0.207371) | 5.110095 / 5.269862 (-0.159767) | 3.066152 / 4.565676 (-1.499524) | 0.057505 / 0.424275 (-0.366770) | 0.007334 / 0.007607 (-0.000273) | 0.475622 / 0.226044 (0.249578) | 4.754091 / 2.268929 (2.485162) | 2.431379 / 55.444624 (-53.013246) | 2.106178 / 6.876477 (-4.770298) | 2.364305 / 2.142072 (0.222232) | 0.614038 / 4.805227 (-4.191190) | 0.148530 / 6.500664 (-6.352134) | 0.061033 / 0.075469 (-0.014436) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.242345 / 1.841788 (-0.599443) | 19.017266 / 8.074308 (10.942958) | 13.477782 / 10.191392 (3.286390) | 0.158513 / 0.680424 (-0.521911) | 0.018757 / 0.534201 (-0.515444) | 0.393773 / 0.579283 (-0.185510) | 0.416933 / 0.434364 (-0.017431) | 0.460012 / 0.540337 (-0.080326) | 0.637010 / 1.386936 (-0.749926) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006689 / 0.011353 (-0.004664) | 0.004168 / 0.011008 (-0.006840) | 0.065009 / 0.038508 (0.026501) | 0.073766 / 0.023109 (0.050657) | 0.369585 / 0.275898 (0.093687) | 0.407945 / 0.323480 (0.084465) | 0.005583 / 0.007986 (-0.002403) | 0.003494 / 0.004328 (-0.000835) | 0.065032 / 0.004250 (0.060782) | 0.057166 / 0.037052 (0.020114) | 0.370656 / 0.258489 (0.112166) | 0.428381 / 0.293841 (0.134540) | 0.031653 / 0.128546 (-0.096893) | 0.008731 / 0.075646 (-0.066915) | 0.071624 / 0.419271 (-0.347648) | 0.049364 / 0.043533 (0.005832) | 0.361824 / 0.255139 (0.106685) | 0.387615 / 0.283200 (0.104415) | 0.023228 / 0.141683 (-0.118455) | 1.476204 / 1.452155 (0.024049) | 1.553522 / 1.492716 (0.060806) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.266955 / 0.018006 (0.248948) | 0.556566 / 0.000490 (0.556076) | 0.000399 / 0.000200 (0.000199) | 0.000056 / 0.000054 (0.000001) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.033104 / 0.037411 (-0.004307) | 0.088067 / 0.014526 (0.073541) | 0.103333 / 0.176557 (-0.073224) | 0.157061 / 0.737135 (-0.580074) | 0.105007 / 0.296338 (-0.191331) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.420826 / 0.215209 (0.205617) | 4.201656 / 2.077655 (2.124001) | 2.208336 / 1.504120 (0.704216) | 2.043780 / 1.541195 (0.502585) | 2.156215 / 1.468490 (0.687725) | 0.490485 / 4.584777 (-4.094292) | 3.611446 / 3.745712 (-0.134267) | 5.293140 / 5.269862 (0.023279) | 2.739778 / 4.565676 (-1.825899) | 0.058175 / 0.424275 (-0.366100) | 0.007633 / 0.007607 (0.000026) | 0.500773 / 0.226044 (0.274729) | 5.000900 / 2.268929 (2.731971) | 2.721200 / 55.444624 (-52.723424) | 2.349381 / 6.876477 (-4.527095) | 2.386261 / 2.142072 (0.244188) | 0.583174 / 4.805227 (-4.222053) | 0.134558 / 6.500664 (-6.366106) | 0.062157 / 0.075469 (-0.013312) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.351087 / 1.841788 (-0.490701) | 20.305703 / 8.074308 (12.231395) | 14.548518 / 10.191392 (4.357126) | 0.173720 / 0.680424 (-0.506704) | 0.018100 / 0.534201 (-0.516101) | 0.395187 / 0.579283 (-0.184097) | 0.414619 / 0.434364 (-0.019745) | 0.462515 / 0.540337 (-0.077823) | 0.617822 / 1.386936 (-0.769114) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#033d0a9de5c825fc9a6a9ce3c3d80eaab3493720 \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006909 / 0.011353 (-0.004444) | 0.003954 / 0.011008 (-0.007054) | 0.084329 / 0.038508 (0.045821) | 0.074919 / 0.023109 (0.051809) | 0.319350 / 0.275898 (0.043451) | 0.347264 / 0.323480 (0.023785) | 0.005326 / 0.007986 (-0.002660) | 0.003323 / 0.004328 (-0.001006) | 0.064286 / 0.004250 (0.060036) | 0.054748 / 0.037052 (0.017696) | 0.324784 / 0.258489 (0.066295) | 0.361445 / 0.293841 (0.067605) | 0.031239 / 0.128546 (-0.097308) | 0.008361 / 0.075646 (-0.067286) | 0.287482 / 0.419271 (-0.131789) | 0.052093 / 0.043533 (0.008560) | 0.321454 / 0.255139 (0.066315) | 0.337999 / 0.283200 (0.054800) | 0.025807 / 0.141683 (-0.115876) | 1.501838 / 1.452155 (0.049683) | 1.574484 / 1.492716 (0.081767) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.193220 / 0.018006 (0.175214) | 0.448105 / 0.000490 (0.447615) | 0.002949 / 0.000200 (0.002749) | 0.000071 / 0.000054 (0.000016) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.028517 / 0.037411 (-0.008894) | 0.087281 / 0.014526 (0.072755) | 0.098295 / 0.176557 (-0.078262) | 0.156972 / 0.737135 (-0.580163) | 0.101250 / 0.296338 (-0.195088) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.383734 / 0.215209 (0.168525) | 3.821293 / 2.077655 (1.743638) | 1.866487 / 1.504120 (0.362367) | 1.722195 / 1.541195 (0.181000) | 1.843762 / 1.468490 (0.375272) | 0.484813 / 4.584777 (-4.099964) | 3.535381 / 3.745712 (-0.210331) | 5.502338 / 5.269862 (0.232477) | 3.256078 / 4.565676 (-1.309599) | 0.057312 / 0.424275 (-0.366963) | 0.007305 / 0.007607 (-0.000302) | 0.461523 / 0.226044 (0.235479) | 4.611828 / 2.268929 (2.342899) | 2.337180 / 55.444624 (-53.107445) | 2.040956 / 6.876477 (-4.835521) | 2.241233 / 2.142072 (0.099160) | 0.583727 / 4.805227 (-4.221500) | 0.132427 / 6.500664 (-6.368237) | 0.060306 / 0.075469 (-0.015163) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.282223 / 1.841788 (-0.559565) | 19.439745 / 8.074308 (11.365437) | 13.627657 / 10.191392 (3.436265) | 0.158975 / 0.680424 (-0.521449) | 0.018599 / 0.534201 (-0.515601) | 0.391136 / 0.579283 (-0.188147) | 0.410947 / 0.434364 (-0.023417) | 0.453889 / 0.540337 (-0.086448) | 0.620928 / 1.386936 (-0.766008) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006428 / 0.011353 (-0.004925) | 0.003980 / 0.011008 (-0.007028) | 0.065006 / 0.038508 (0.026498) | 0.076541 / 0.023109 (0.053432) | 0.358518 / 0.275898 (0.082620) | 0.394397 / 0.323480 (0.070917) | 0.005845 / 0.007986 (-0.002140) | 0.003258 / 0.004328 (-0.001071) | 0.064436 / 0.004250 (0.060186) | 0.056691 / 0.037052 (0.019639) | 0.367369 / 0.258489 (0.108880) | 0.420345 / 0.293841 (0.126504) | 0.031047 / 0.128546 (-0.097499) | 0.008430 / 0.075646 (-0.067216) | 0.071280 / 0.419271 (-0.347991) | 0.048872 / 0.043533 (0.005339) | 0.360073 / 0.255139 (0.104934) | 0.384150 / 0.283200 (0.100951) | 0.023189 / 0.141683 (-0.118494) | 1.500251 / 1.452155 (0.048096) | 1.545910 / 1.492716 (0.053194) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.224861 / 0.018006 (0.206855) | 0.439901 / 0.000490 (0.439411) | 0.000372 / 0.000200 (0.000172) | 0.000054 / 0.000054 (-0.000001) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.029914 / 0.037411 (-0.007497) | 0.086916 / 0.014526 (0.072390) | 0.099527 / 0.176557 (-0.077029) | 0.153031 / 0.737135 (-0.584104) | 0.100008 / 0.296338 (-0.196330) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.420305 / 0.215209 (0.205096) | 4.198224 / 2.077655 (2.120569) | 2.223807 / 1.504120 (0.719687) | 2.058475 / 1.541195 (0.517280) | 2.140405 / 1.468490 (0.671915) | 0.481224 / 4.584777 (-4.103553) | 3.593767 / 3.745712 (-0.151945) | 5.536710 / 5.269862 (0.266849) | 3.162048 / 4.565676 (-1.403629) | 0.056662 / 0.424275 (-0.367614) | 0.007301 / 0.007607 (-0.000306) | 0.507494 / 0.226044 (0.281450) | 5.047824 / 2.268929 (2.778896) | 2.715167 / 55.444624 (-52.729458) | 2.334916 / 6.876477 (-4.541560) | 2.406615 / 2.142072 (0.264543) | 0.572761 / 4.805227 (-4.232466) | 0.131248 / 6.500664 (-6.369416) | 0.062401 / 0.075469 (-0.013068) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.375896 / 1.841788 (-0.465892) | 19.836638 / 8.074308 (11.762329) | 14.246645 / 10.191392 (4.055253) | 0.164975 / 0.680424 (-0.515449) | 0.018293 / 0.534201 (-0.515908) | 0.394196 / 0.579283 (-0.185087) | 0.405895 / 0.434364 (-0.028469) | 0.459221 / 0.540337 (-0.081116) | 0.609898 / 1.386936 (-0.777038) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#f89210ad839c2225b64822dfa248f68ab29ad46f \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.008463 / 0.011353 (-0.002890) | 0.004754 / 0.011008 (-0.006254) | 0.103574 / 0.038508 (0.065066) | 0.083541 / 0.023109 (0.060432) | 0.402498 / 0.275898 (0.126600) | 0.434944 / 0.323480 (0.111465) | 0.005766 / 0.007986 (-0.002219) | 0.003823 / 0.004328 (-0.000505) | 0.078433 / 0.004250 (0.074183) | 0.056948 / 0.037052 (0.019895) | 0.392539 / 0.258489 (0.134050) | 0.447226 / 0.293841 (0.153385) | 0.045845 / 0.128546 (-0.082701) | 0.014043 / 0.075646 (-0.061603) | 0.355768 / 0.419271 (-0.063503) | 0.065492 / 0.043533 (0.021960) | 0.408047 / 0.255139 (0.152908) | 0.468313 / 0.283200 (0.185113) | 0.033779 / 0.141683 (-0.107904) | 1.772198 / 1.452155 (0.320043) | 1.889127 / 1.492716 (0.396411) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.207107 / 0.018006 (0.189101) | 0.533261 / 0.000490 (0.532771) | 0.000864 / 0.000200 (0.000664) | 0.000105 / 0.000054 (0.000051) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.032139 / 0.037411 (-0.005272) | 0.102002 / 0.014526 (0.087476) | 0.108780 / 0.176557 (-0.067777) | 0.202857 / 0.737135 (-0.534278) | 0.110378 / 0.296338 (-0.185960) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.582814 / 0.215209 (0.367605) | 5.870683 / 2.077655 (3.793028) | 2.510290 / 1.504120 (1.006171) | 2.146337 / 1.541195 (0.605142) | 2.239278 / 1.468490 (0.770788) | 0.861205 / 4.584777 (-3.723572) | 5.177394 / 3.745712 (1.431682) | 8.550713 / 5.269862 (3.280852) | 4.867715 / 4.565676 (0.302038) | 0.096665 / 0.424275 (-0.327610) | 0.008702 / 0.007607 (0.001095) | 0.748908 / 0.226044 (0.522863) | 7.302815 / 2.268929 (5.033887) | 3.205045 / 55.444624 (-52.239580) | 2.743914 / 6.876477 (-4.132562) | 2.831240 / 2.142072 (0.689167) | 1.103912 / 4.805227 (-3.701315) | 0.246075 / 6.500664 (-6.254589) | 0.092092 / 0.075469 (0.016623) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.591331 / 1.841788 (-0.250457) | 23.085848 / 8.074308 (15.011540) | 22.887963 / 10.191392 (12.696571) | 0.212735 / 0.680424 (-0.467689) | 0.027400 / 0.534201 (-0.506801) | 0.493822 / 0.579283 (-0.085461) | 0.574485 / 0.434364 (0.140121) | 0.574873 / 0.540337 (0.034536) | 0.826178 / 1.386936 (-0.560758) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.009155 / 0.011353 (-0.002198) | 0.004976 / 0.011008 (-0.006032) | 0.079308 / 0.038508 (0.040799) | 0.093959 / 0.023109 (0.070850) | 0.449110 / 0.275898 (0.173212) | 0.493356 / 0.323480 (0.169876) | 0.006317 / 0.007986 (-0.001669) | 0.004179 / 0.004328 (-0.000150) | 0.076991 / 0.004250 (0.072740) | 0.061977 / 0.037052 (0.024924) | 0.493823 / 0.258489 (0.235333) | 0.491609 / 0.293841 (0.197768) | 0.049552 / 0.128546 (-0.078994) | 0.015174 / 0.075646 (-0.060472) | 0.090431 / 0.419271 (-0.328841) | 0.061597 / 0.043533 (0.018064) | 0.467672 / 0.255139 (0.212533) | 0.490542 / 0.283200 (0.207342) | 0.035048 / 0.141683 (-0.106635) | 1.807939 / 1.452155 (0.355784) | 1.854859 / 1.492716 (0.362142) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.236672 / 0.018006 (0.218666) | 0.542236 / 0.000490 (0.541746) | 0.016334 / 0.000200 (0.016134) | 0.000220 / 0.000054 (0.000165) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.032051 / 0.037411 (-0.005360) | 0.115352 / 0.014526 (0.100826) | 0.125115 / 0.176557 (-0.051441) | 0.173670 / 0.737135 (-0.563466) | 0.117832 / 0.296338 (-0.178507) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.631513 / 0.215209 (0.416304) | 6.371688 / 2.077655 (4.294033) | 2.867240 / 1.504120 (1.363120) | 2.454907 / 1.541195 (0.913713) | 2.518860 / 1.468490 (1.050370) | 0.879973 / 4.584777 (-3.704804) | 5.170263 / 3.745712 (1.424551) | 7.986429 / 5.269862 (2.716567) | 4.828095 / 4.565676 (0.262418) | 0.097808 / 0.424275 (-0.326468) | 0.010541 / 0.007607 (0.002934) | 0.745601 / 0.226044 (0.519557) | 7.631683 / 2.268929 (5.362755) | 3.524255 / 55.444624 (-51.920369) | 2.866199 / 6.876477 (-4.010278) | 2.982483 / 2.142072 (0.840410) | 1.148957 / 4.805227 (-3.656270) | 0.217067 / 6.500664 (-6.283598) | 0.074357 / 0.075469 (-0.001112) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.714917 / 1.841788 (-0.126871) | 24.151348 / 8.074308 (16.077040) | 21.993604 / 10.191392 (11.802212) | 0.234883 / 0.680424 (-0.445541) | 0.028182 / 0.534201 (-0.506019) | 0.474050 / 0.579283 (-0.105233) | 0.557012 / 0.434364 (0.122648) | 0.537823 / 0.540337 (-0.002514) | 0.741488 / 1.386936 (-0.645448) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#c2e5a7a01a952a17d0424e93c3be2b4a5ffca7da \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007640 / 0.011353 (-0.003713) | 0.004776 / 0.011008 (-0.006232) | 0.101582 / 0.038508 (0.063074) | 0.085113 / 0.023109 (0.062003) | 0.376000 / 0.275898 (0.100102) | 0.421117 / 0.323480 (0.097637) | 0.006095 / 0.007986 (-0.001891) | 0.003884 / 0.004328 (-0.000445) | 0.077263 / 0.004250 (0.073013) | 0.065262 / 0.037052 (0.028210) | 0.384041 / 0.258489 (0.125552) | 0.442229 / 0.293841 (0.148388) | 0.035706 / 0.128546 (-0.092840) | 0.009996 / 0.075646 (-0.065651) | 0.344925 / 0.419271 (-0.074346) | 0.062358 / 0.043533 (0.018825) | 0.371738 / 0.255139 (0.116599) | 0.407093 / 0.283200 (0.123894) | 0.026996 / 0.141683 (-0.114687) | 1.762705 / 1.452155 (0.310550) | 1.846777 / 1.492716 (0.354061) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.219660 / 0.018006 (0.201653) | 0.521795 / 0.000490 (0.521305) | 0.005344 / 0.000200 (0.005145) | 0.000098 / 0.000054 (0.000044) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.036027 / 0.037411 (-0.001385) | 0.100309 / 0.014526 (0.085784) | 0.113041 / 0.176557 (-0.063515) | 0.190037 / 0.737135 (-0.547099) | 0.114552 / 0.296338 (-0.181786) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.466364 / 0.215209 (0.251154) | 4.638745 / 2.077655 (2.561090) | 2.317875 / 1.504120 (0.813755) | 2.099241 / 1.541195 (0.558046) | 2.149827 / 1.468490 (0.681337) | 0.578913 / 4.584777 (-4.005864) | 4.281866 / 3.745712 (0.536154) | 3.778453 / 5.269862 (-1.491408) | 2.411704 / 4.565676 (-2.153972) | 0.068556 / 0.424275 (-0.355719) | 0.008779 / 0.007607 (0.001172) | 0.553165 / 0.226044 (0.327121) | 5.524520 / 2.268929 (3.255591) | 2.848444 / 55.444624 (-52.596181) | 2.468591 / 6.876477 (-4.407885) | 2.652117 / 2.142072 (0.510045) | 0.694124 / 4.805227 (-4.111103) | 0.157087 / 6.500664 (-6.343577) | 0.070706 / 0.075469 (-0.004763) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.492031 / 1.841788 (-0.349757) | 23.086596 / 8.074308 (15.012288) | 16.791351 / 10.191392 (6.599959) | 0.203932 / 0.680424 (-0.476492) | 0.021736 / 0.534201 (-0.512464) | 0.468344 / 0.579283 (-0.110939) | 0.493790 / 0.434364 (0.059426) | 0.563226 / 0.540337 (0.022889) | 0.780384 / 1.386936 (-0.606553) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007980 / 0.011353 (-0.003373) | 0.004696 / 0.011008 (-0.006312) | 0.076712 / 0.038508 (0.038204) | 0.095915 / 0.023109 (0.072805) | 0.433615 / 0.275898 (0.157717) | 0.482477 / 0.323480 (0.158997) | 0.007029 / 0.007986 (-0.000957) | 0.003842 / 0.004328 (-0.000487) | 0.076331 / 0.004250 (0.072081) | 0.069755 / 0.037052 (0.032703) | 0.458914 / 0.258489 (0.200425) | 0.486155 / 0.293841 (0.192314) | 0.036966 / 0.128546 (-0.091580) | 0.010082 / 0.075646 (-0.065564) | 0.083886 / 0.419271 (-0.335385) | 0.059329 / 0.043533 (0.015796) | 0.453782 / 0.255139 (0.198643) | 0.459508 / 0.283200 (0.176308) | 0.028400 / 0.141683 (-0.113283) | 1.796406 / 1.452155 (0.344251) | 1.881161 / 1.492716 (0.388445) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.235053 / 0.018006 (0.217047) | 0.501907 / 0.000490 (0.501417) | 0.005211 / 0.000200 (0.005011) | 0.000101 / 0.000054 (0.000046) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.037752 / 0.037411 (0.000341) | 0.107299 / 0.014526 (0.092773) | 0.120307 / 0.176557 (-0.056250) | 0.187542 / 0.737135 (-0.549593) | 0.121805 / 0.296338 (-0.174533) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.490039 / 0.215209 (0.274830) | 4.919169 / 2.077655 (2.841515) | 2.520610 / 1.504120 (1.016490) | 2.324473 / 1.541195 (0.783279) | 2.421195 / 1.468490 (0.952705) | 0.576314 / 4.584777 (-4.008463) | 4.304752 / 3.745712 (0.559040) | 3.881151 / 5.269862 (-1.388710) | 2.409777 / 4.565676 (-2.155900) | 0.067400 / 0.424275 (-0.356875) | 0.009235 / 0.007607 (0.001627) | 0.586601 / 0.226044 (0.360556) | 5.850080 / 2.268929 (3.581152) | 3.064859 / 55.444624 (-52.379766) | 2.701734 / 6.876477 (-4.174743) | 2.926190 / 2.142072 (0.784117) | 0.698511 / 4.805227 (-4.106716) | 0.158273 / 6.500664 (-6.342392) | 0.074530 / 0.075469 (-0.000939) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.607113 / 1.841788 (-0.234674) | 23.499279 / 8.074308 (15.424971) | 17.049509 / 10.191392 (6.858117) | 0.175689 / 0.680424 (-0.504735) | 0.021762 / 0.534201 (-0.512439) | 0.491450 / 0.579283 (-0.087833) | 0.487557 / 0.434364 (0.053193) | 0.570104 / 0.540337 (0.029766) | 0.761527 / 1.386936 (-0.625409) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#7096c59e6a8f4d5b16f3b906075f9e2ed83bbb25 \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.008725 / 0.011353 (-0.002628) | 0.005156 / 0.011008 (-0.005852) | 0.095147 / 0.038508 (0.056639) | 0.084916 / 0.023109 (0.061807) | 0.390769 / 0.275898 (0.114871) | 0.434716 / 0.323480 (0.111237) | 0.005982 / 0.007986 (-0.002004) | 0.004323 / 0.004328 (-0.000006) | 0.074712 / 0.004250 (0.070461) | 0.058889 / 0.037052 (0.021837) | 0.403997 / 0.258489 (0.145508) | 0.443361 / 0.293841 (0.149520) | 0.045908 / 0.128546 (-0.082639) | 0.013562 / 0.075646 (-0.062085) | 0.330683 / 0.419271 (-0.088588) | 0.064821 / 0.043533 (0.021288) | 0.407202 / 0.255139 (0.152063) | 0.409930 / 0.283200 (0.126730) | 0.032693 / 0.141683 (-0.108990) | 1.630181 / 1.452155 (0.178026) | 1.729680 / 1.492716 (0.236963) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.261240 / 0.018006 (0.243234) | 0.581850 / 0.000490 (0.581360) | 0.002997 / 0.000200 (0.002797) | 0.000107 / 0.000054 (0.000053) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.029279 / 0.037411 (-0.008133) | 0.085004 / 0.014526 (0.070478) | 0.127782 / 0.176557 (-0.048774) | 0.168852 / 0.737135 (-0.568283) | 0.098697 / 0.296338 (-0.197641) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.546417 / 0.215209 (0.331208) | 5.602186 / 2.077655 (3.524531) | 2.597049 / 1.504120 (1.092930) | 2.384880 / 1.541195 (0.843685) | 2.444516 / 1.468490 (0.976026) | 0.796562 / 4.584777 (-3.788214) | 5.239440 / 3.745712 (1.493727) | 7.087768 / 5.269862 (1.817906) | 4.308476 / 4.565676 (-0.257200) | 0.091215 / 0.424275 (-0.333060) | 0.007942 / 0.007607 (0.000335) | 0.690059 / 0.226044 (0.464015) | 6.727809 / 2.268929 (4.458880) | 3.294522 / 55.444624 (-52.150103) | 2.604088 / 6.876477 (-4.272389) | 2.786970 / 2.142072 (0.644898) | 0.918817 / 4.805227 (-3.886410) | 0.191451 / 6.500664 (-6.309213) | 0.069557 / 0.075469 (-0.005912) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.486377 / 1.841788 (-0.355411) | 22.363470 / 8.074308 (14.289162) | 19.963684 / 10.191392 (9.772292) | 0.204161 / 0.680424 (-0.476263) | 0.034570 / 0.534201 (-0.499631) | 0.467937 / 0.579283 (-0.111346) | 0.564870 / 0.434364 (0.130506) | 0.511133 / 0.540337 (-0.029204) | 0.777084 / 1.386936 (-0.609852) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.008612 / 0.011353 (-0.002741) | 0.004993 / 0.011008 (-0.006015) | 0.080769 / 0.038508 (0.042261) | 0.075923 / 0.023109 (0.052814) | 0.442271 / 0.275898 (0.166373) | 0.495625 / 0.323480 (0.172146) | 0.006467 / 0.007986 (-0.001518) | 0.004001 / 0.004328 (-0.000328) | 0.077309 / 0.004250 (0.073059) | 0.063466 / 0.037052 (0.026414) | 0.452460 / 0.258489 (0.193971) | 0.494063 / 0.293841 (0.200223) | 0.045751 / 0.128546 (-0.082796) | 0.013402 / 0.075646 (-0.062245) | 0.085760 / 0.419271 (-0.333511) | 0.056532 / 0.043533 (0.012999) | 0.440596 / 0.255139 (0.185457) | 0.459540 / 0.283200 (0.176340) | 0.035897 / 0.141683 (-0.105786) | 1.728264 / 1.452155 (0.276109) | 1.808142 / 1.492716 (0.315426) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.285094 / 0.018006 (0.267088) | 0.598440 / 0.000490 (0.597950) | 0.003476 / 0.000200 (0.003276) | 0.000103 / 0.000054 (0.000048) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.035106 / 0.037411 (-0.002305) | 0.091724 / 0.014526 (0.077198) | 0.122803 / 0.176557 (-0.053754) | 0.182114 / 0.737135 (-0.555022) | 0.116196 / 0.296338 (-0.180143) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.585420 / 0.215209 (0.370211) | 5.790370 / 2.077655 (3.712715) | 2.833247 / 1.504120 (1.329127) | 2.627949 / 1.541195 (1.086755) | 2.643050 / 1.468490 (1.174560) | 0.792036 / 4.584777 (-3.792741) | 5.145084 / 3.745712 (1.399372) | 4.423679 / 5.269862 (-0.846182) | 2.802778 / 4.565676 (-1.762898) | 0.093983 / 0.424275 (-0.330292) | 0.009260 / 0.007607 (0.001652) | 0.720302 / 0.226044 (0.494258) | 7.116959 / 2.268929 (4.848031) | 3.574782 / 55.444624 (-51.869843) | 3.009330 / 6.876477 (-3.867147) | 3.126488 / 2.142072 (0.984415) | 0.949144 / 4.805227 (-3.856083) | 0.195143 / 6.500664 (-6.305521) | 0.072490 / 0.075469 (-0.002979) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.626368 / 1.841788 (-0.215419) | 23.683021 / 8.074308 (15.608713) | 20.085297 / 10.191392 (9.893905) | 0.267057 / 0.680424 (-0.413367) | 0.028306 / 0.534201 (-0.505894) | 0.478448 / 0.579283 (-0.100835) | 0.597619 / 0.434364 (0.163256) | 0.544737 / 0.540337 (0.004399) | 0.761805 / 1.386936 (-0.625131) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#7ac53b590916c8d859fabcc2ef23c12add7f22f7 \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.009359 / 0.011353 (-0.001994) | 0.004848 / 0.011008 (-0.006160) | 0.099471 / 0.038508 (0.060963) | 0.079483 / 0.023109 (0.056373) | 0.375281 / 0.275898 (0.099383) | 0.415566 / 0.323480 (0.092086) | 0.006317 / 0.007986 (-0.001669) | 0.005145 / 0.004328 (0.000817) | 0.080345 / 0.004250 (0.076094) | 0.064540 / 0.037052 (0.027487) | 0.385897 / 0.258489 (0.127408) | 0.432576 / 0.293841 (0.138735) | 0.055109 / 0.128546 (-0.073437) | 0.014166 / 0.075646 (-0.061480) | 0.350870 / 0.419271 (-0.068402) | 0.087483 / 0.043533 (0.043950) | 0.402288 / 0.255139 (0.147149) | 0.391997 / 0.283200 (0.108798) | 0.045233 / 0.141683 (-0.096450) | 1.795002 / 1.452155 (0.342847) | 1.839063 / 1.492716 (0.346347) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.220851 / 0.018006 (0.202845) | 0.513391 / 0.000490 (0.512901) | 0.003740 / 0.000200 (0.003540) | 0.000107 / 0.000054 (0.000053) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.035287 / 0.037411 (-0.002124) | 0.090670 / 0.014526 (0.076144) | 0.115651 / 0.176557 (-0.060905) | 0.180469 / 0.737135 (-0.556667) | 0.106955 / 0.296338 (-0.189384) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.632381 / 0.215209 (0.417172) | 6.185151 / 2.077655 (4.107497) | 2.548263 / 1.504120 (1.044143) | 2.194931 / 1.541195 (0.653737) | 2.368685 / 1.468490 (0.900194) | 0.956467 / 4.584777 (-3.628310) | 5.280904 / 3.745712 (1.535192) | 4.783057 / 5.269862 (-0.486805) | 3.218493 / 4.565676 (-1.347184) | 0.103545 / 0.424275 (-0.320730) | 0.008424 / 0.007607 (0.000817) | 0.736303 / 0.226044 (0.510259) | 7.354305 / 2.268929 (5.085376) | 3.280670 / 55.444624 (-52.163954) | 2.478628 / 6.876477 (-4.397848) | 2.623290 / 2.142072 (0.481217) | 1.033064 / 4.805227 (-3.772163) | 0.206496 / 6.500664 (-6.294168) | 0.066449 / 0.075469 (-0.009020) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.508756 / 1.841788 (-0.333031) | 21.866012 / 8.074308 (13.791704) | 21.887761 / 10.191392 (11.696369) | 0.231415 / 0.680424 (-0.449008) | 0.028917 / 0.534201 (-0.505284) | 0.468761 / 0.579283 (-0.110522) | 0.568236 / 0.434364 (0.133872) | 0.550156 / 0.540337 (0.009818) | 0.783197 / 1.386936 (-0.603739) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.009413 / 0.011353 (-0.001939) | 0.004951 / 0.011008 (-0.006058) | 0.071402 / 0.038508 (0.032893) | 0.068455 / 0.023109 (0.045346) | 0.425216 / 0.275898 (0.149318) | 0.431928 / 0.323480 (0.108448) | 0.006477 / 0.007986 (-0.001509) | 0.003891 / 0.004328 (-0.000437) | 0.076898 / 0.004250 (0.072647) | 0.057522 / 0.037052 (0.020470) | 0.449585 / 0.258489 (0.191096) | 0.431356 / 0.293841 (0.137515) | 0.049728 / 0.128546 (-0.078818) | 0.014456 / 0.075646 (-0.061190) | 0.084618 / 0.419271 (-0.334653) | 0.064482 / 0.043533 (0.020949) | 0.456377 / 0.255139 (0.201238) | 0.433949 / 0.283200 (0.150749) | 0.036577 / 0.141683 (-0.105106) | 1.819742 / 1.452155 (0.367588) | 1.694691 / 1.492716 (0.201975) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.224610 / 0.018006 (0.206604) | 0.494586 / 0.000490 (0.494096) | 0.004506 / 0.000200 (0.004307) | 0.000119 / 0.000054 (0.000065) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.033172 / 0.037411 (-0.004239) | 0.100562 / 0.014526 (0.086036) | 0.116499 / 0.176557 (-0.060058) | 0.153717 / 0.737135 (-0.583418) | 0.140047 / 0.296338 (-0.156291) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.635922 / 0.215209 (0.420713) | 6.359792 / 2.077655 (4.282137) | 2.689083 / 1.504120 (1.184963) | 2.330574 / 1.541195 (0.789380) | 2.583535 / 1.468490 (1.115044) | 0.902737 / 4.584777 (-3.682040) | 5.136586 / 3.745712 (1.390874) | 4.570824 / 5.269862 (-0.699037) | 3.029953 / 4.565676 (-1.535724) | 0.103961 / 0.424275 (-0.320314) | 0.007908 / 0.007607 (0.000301) | 0.723290 / 0.226044 (0.497246) | 7.678599 / 2.268929 (5.409671) | 3.342522 / 55.444624 (-52.102102) | 2.774659 / 6.876477 (-4.101817) | 2.966496 / 2.142072 (0.824423) | 1.025395 / 4.805227 (-3.779832) | 0.222246 / 6.500664 (-6.278418) | 0.072455 / 0.075469 (-0.003014) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.603637 / 1.841788 (-0.238151) | 21.387722 / 8.074308 (13.313414) | 22.855221 / 10.191392 (12.663829) | 0.222147 / 0.680424 (-0.458277) | 0.030763 / 0.534201 (-0.503438) | 0.472586 / 0.579283 (-0.106697) | 0.560161 / 0.434364 (0.125797) | 0.551941 / 0.540337 (0.011604) | 0.711254 / 1.386936 (-0.675682) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#85cf123e553ff282b43ad1d1877ba2c40d206d52 \"CML watermark\")\n" ]

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[ "_The documentation is not available anymore as the PR was closed or merged._", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006543 / 0.011353 (-0.004809) | 0.004085 / 0.011008 (-0.006924) | 0.083989 / 0.038508 (0.045481) | 0.074733 / 0.023109 (0.051623) | 0.310839 / 0.275898 (0.034941) | 0.333540 / 0.323480 (0.010060) | 0.005566 / 0.007986 (-0.002419) | 0.003461 / 0.004328 (-0.000868) | 0.065194 / 0.004250 (0.060943) | 0.057007 / 0.037052 (0.019954) | 0.325633 / 0.258489 (0.067144) | 0.351665 / 0.293841 (0.057824) | 0.030561 / 0.128546 (-0.097985) | 0.008579 / 0.075646 (-0.067068) | 0.287457 / 0.419271 (-0.131815) | 0.063554 / 0.043533 (0.020021) | 0.309182 / 0.255139 (0.054043) | 0.327809 / 0.283200 (0.044609) | 0.034470 / 0.141683 (-0.107213) | 1.452098 / 1.452155 (-0.000057) | 1.527130 / 1.492716 (0.034414) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.241736 / 0.018006 (0.223729) | 0.552432 / 0.000490 (0.551943) | 0.004085 / 0.000200 (0.003885) | 0.000089 / 0.000054 (0.000035) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.027290 / 0.037411 (-0.010121) | 0.081250 / 0.014526 (0.066724) | 0.094739 / 0.176557 (-0.081818) | 0.150424 / 0.737135 (-0.586711) | 0.095488 / 0.296338 (-0.200851) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.377245 / 0.215209 (0.162036) | 3.781021 / 2.077655 (1.703366) | 1.820092 / 1.504120 (0.315972) | 1.654420 / 1.541195 (0.113225) | 1.751256 / 1.468490 (0.282766) | 0.475161 / 4.584777 (-4.109616) | 3.603462 / 3.745712 (-0.142251) | 5.437837 / 5.269862 (0.167975) | 3.305598 / 4.565676 (-1.260079) | 0.055856 / 0.424275 (-0.368419) | 0.007259 / 0.007607 (-0.000348) | 0.454205 / 0.226044 (0.228161) | 4.544157 / 2.268929 (2.275229) | 2.296776 / 55.444624 (-53.147848) | 1.951017 / 6.876477 (-4.925459) | 2.128759 / 2.142072 (-0.013313) | 0.590354 / 4.805227 (-4.214873) | 0.129974 / 6.500664 (-6.370690) | 0.059506 / 0.075469 (-0.015963) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.285866 / 1.841788 (-0.555921) | 19.419446 / 8.074308 (11.345138) | 13.985108 / 10.191392 (3.793716) | 0.146803 / 0.680424 (-0.533620) | 0.018176 / 0.534201 (-0.516025) | 0.392345 / 0.579283 (-0.186938) | 0.405394 / 0.434364 (-0.028970) | 0.454649 / 0.540337 (-0.085688) | 0.633075 / 1.386936 (-0.753861) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006497 / 0.011353 (-0.004855) | 0.004092 / 0.011008 (-0.006916) | 0.064908 / 0.038508 (0.026400) | 0.073494 / 0.023109 (0.050385) | 0.382227 / 0.275898 (0.106329) | 0.407320 / 0.323480 (0.083840) | 0.005653 / 0.007986 (-0.002332) | 0.003500 / 0.004328 (-0.000829) | 0.064570 / 0.004250 (0.060320) | 0.058733 / 0.037052 (0.021681) | 0.385702 / 0.258489 (0.127213) | 0.426463 / 0.293841 (0.132622) | 0.031073 / 0.128546 (-0.097473) | 0.008710 / 0.075646 (-0.066936) | 0.071378 / 0.419271 (-0.347893) | 0.050141 / 0.043533 (0.006608) | 0.377769 / 0.255139 (0.122630) | 0.395016 / 0.283200 (0.111816) | 0.025158 / 0.141683 (-0.116525) | 1.470503 / 1.452155 (0.018348) | 1.532742 / 1.492716 (0.040026) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.214249 / 0.018006 (0.196243) | 0.583580 / 0.000490 (0.583090) | 0.004027 / 0.000200 (0.003828) | 0.000104 / 0.000054 (0.000050) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.030186 / 0.037411 (-0.007226) | 0.086927 / 0.014526 (0.072401) | 0.102060 / 0.176557 (-0.074497) | 0.156281 / 0.737135 (-0.580855) | 0.100825 / 0.296338 (-0.195514) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.419942 / 0.215209 (0.204733) | 4.183797 / 2.077655 (2.106142) | 2.205079 / 1.504120 (0.700959) | 2.071219 / 1.541195 (0.530024) | 2.194047 / 1.468490 (0.725557) | 0.478768 / 4.584777 (-4.106009) | 3.584864 / 3.745712 (-0.160848) | 3.371635 / 5.269862 (-1.898227) | 2.022134 / 4.565676 (-2.543542) | 0.056553 / 0.424275 (-0.367722) | 0.007231 / 0.007607 (-0.000376) | 0.493158 / 0.226044 (0.267113) | 4.934370 / 2.268929 (2.665441) | 2.699593 / 55.444624 (-52.745031) | 2.396371 / 6.876477 (-4.480105) | 2.438052 / 2.142072 (0.295979) | 0.589578 / 4.805227 (-4.215649) | 0.147234 / 6.500664 (-6.353430) | 0.062049 / 0.075469 (-0.013420) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.318246 / 1.841788 (-0.523542) | 19.829025 / 8.074308 (11.754717) | 14.314825 / 10.191392 (4.123433) | 0.168309 / 0.680424 (-0.512115) | 0.018596 / 0.534201 (-0.515605) | 0.397540 / 0.579283 (-0.181743) | 0.421280 / 0.434364 (-0.013084) | 0.479917 / 0.540337 (-0.060421) | 0.643494 / 1.386936 (-0.743442) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#5be59becaa65f1fa08129091b8c778823e4a50ac \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.008349 / 0.011353 (-0.003004) | 0.005362 / 0.011008 (-0.005646) | 0.100777 / 0.038508 (0.062269) | 0.078719 / 0.023109 (0.055609) | 0.398105 / 0.275898 (0.122207) | 0.444189 / 0.323480 (0.120709) | 0.006834 / 0.007986 (-0.001152) | 0.004642 / 0.004328 (0.000314) | 0.076284 / 0.004250 (0.072034) | 0.062738 / 0.037052 (0.025685) | 0.409532 / 0.258489 (0.151043) | 0.447218 / 0.293841 (0.153377) | 0.052996 / 0.128546 (-0.075550) | 0.012977 / 0.075646 (-0.062669) | 0.347687 / 0.419271 (-0.071585) | 0.068076 / 0.043533 (0.024543) | 0.394526 / 0.255139 (0.139387) | 0.434110 / 0.283200 (0.150910) | 0.041719 / 0.141683 (-0.099963) | 1.759109 / 1.452155 (0.306955) | 1.866049 / 1.492716 (0.373333) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.287633 / 0.018006 (0.269627) | 0.611540 / 0.000490 (0.611051) | 0.005388 / 0.000200 (0.005188) | 0.000096 / 0.000054 (0.000042) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.027394 / 0.037411 (-0.010017) | 0.089796 / 0.014526 (0.075270) | 0.106931 / 0.176557 (-0.069625) | 0.173560 / 0.737135 (-0.563575) | 0.106948 / 0.296338 (-0.189391) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.575156 / 0.215209 (0.359947) | 5.674170 / 2.077655 (3.596516) | 2.463090 / 1.504120 (0.958971) | 2.128245 / 1.541195 (0.587050) | 2.118982 / 1.468490 (0.650492) | 0.876976 / 4.584777 (-3.707801) | 5.238229 / 3.745712 (1.492517) | 4.548788 / 5.269862 (-0.721074) | 2.905243 / 4.565676 (-1.660433) | 0.090750 / 0.424275 (-0.333525) | 0.008266 / 0.007607 (0.000659) | 0.693305 / 0.226044 (0.467260) | 7.126970 / 2.268929 (4.858041) | 3.152131 / 55.444624 (-52.292494) | 2.532118 / 6.876477 (-4.344359) | 2.678442 / 2.142072 (0.536369) | 0.932745 / 4.805227 (-3.872483) | 0.196290 / 6.500664 (-6.304374) | 0.074082 / 0.075469 (-0.001387) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.599636 / 1.841788 (-0.242152) | 23.271435 / 8.074308 (15.197127) | 19.696709 / 10.191392 (9.505317) | 0.222668 / 0.680424 (-0.457756) | 0.029088 / 0.534201 (-0.505113) | 0.492477 / 0.579283 (-0.086806) | 0.580578 / 0.434364 (0.146214) | 0.558852 / 0.540337 (0.018514) | 0.762083 / 1.386936 (-0.624853) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.009021 / 0.011353 (-0.002332) | 0.005011 / 0.011008 (-0.005997) | 0.076504 / 0.038508 (0.037996) | 0.077303 / 0.023109 (0.054193) | 0.480660 / 0.275898 (0.204762) | 0.493944 / 0.323480 (0.170464) | 0.006339 / 0.007986 (-0.001646) | 0.004302 / 0.004328 (-0.000026) | 0.076228 / 0.004250 (0.071978) | 0.060805 / 0.037052 (0.023753) | 0.477539 / 0.258489 (0.219050) | 0.496799 / 0.293841 (0.202958) | 0.049495 / 0.128546 (-0.079052) | 0.013333 / 0.075646 (-0.062313) | 0.087217 / 0.419271 (-0.332055) | 0.061451 / 0.043533 (0.017918) | 0.485169 / 0.255139 (0.230030) | 0.487348 / 0.283200 (0.204149) | 0.035874 / 0.141683 (-0.105809) | 1.829137 / 1.452155 (0.376982) | 1.906151 / 1.492716 (0.413435) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.304526 / 0.018006 (0.286520) | 0.627499 / 0.000490 (0.627009) | 0.003786 / 0.000200 (0.003586) | 0.000098 / 0.000054 (0.000043) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.035512 / 0.037411 (-0.001899) | 0.096684 / 0.014526 (0.082158) | 0.111879 / 0.176557 (-0.064678) | 0.171489 / 0.737135 (-0.565647) | 0.112175 / 0.296338 (-0.184164) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.604791 / 0.215209 (0.389582) | 6.089137 / 2.077655 (4.011482) | 2.883237 / 1.504120 (1.379117) | 2.561109 / 1.541195 (1.019914) | 2.542400 / 1.468490 (1.073910) | 0.852828 / 4.584777 (-3.731949) | 5.236812 / 3.745712 (1.491100) | 4.756429 / 5.269862 (-0.513432) | 2.885660 / 4.565676 (-1.680016) | 0.095643 / 0.424275 (-0.328632) | 0.008403 / 0.007607 (0.000796) | 0.727707 / 0.226044 (0.501663) | 7.428002 / 2.268929 (5.159074) | 3.816051 / 55.444624 (-51.628573) | 2.971057 / 6.876477 (-3.905420) | 2.915965 / 2.142072 (0.773893) | 1.006553 / 4.805227 (-3.798674) | 0.201840 / 6.500664 (-6.298824) | 0.080795 / 0.075469 (0.005326) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.794951 / 1.841788 (-0.046837) | 23.624556 / 8.074308 (15.550248) | 21.856195 / 10.191392 (11.664802) | 0.253043 / 0.680424 (-0.427381) | 0.031201 / 0.534201 (-0.503000) | 0.461641 / 0.579283 (-0.117642) | 0.577789 / 0.434364 (0.143425) | 0.569197 / 0.540337 (0.028860) | 0.780111 / 1.386936 (-0.606825) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#4904f14459c862f0ab525ec034a636177be5dee4 \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007646 / 0.011353 (-0.003707) | 0.004750 / 0.011008 (-0.006258) | 0.097981 / 0.038508 (0.059473) | 0.088989 / 0.023109 (0.065880) | 0.377732 / 0.275898 (0.101834) | 0.406805 / 0.323480 (0.083325) | 0.006389 / 0.007986 (-0.001597) | 0.003854 / 0.004328 (-0.000474) | 0.073977 / 0.004250 (0.069727) | 0.066497 / 0.037052 (0.029444) | 0.371498 / 0.258489 (0.113009) | 0.417352 / 0.293841 (0.123511) | 0.036326 / 0.128546 (-0.092220) | 0.009876 / 0.075646 (-0.065770) | 0.330142 / 0.419271 (-0.089130) | 0.062423 / 0.043533 (0.018890) | 0.369375 / 0.255139 (0.114236) | 0.406048 / 0.283200 (0.122848) | 0.026564 / 0.141683 (-0.115119) | 1.713295 / 1.452155 (0.261140) | 1.797493 / 1.492716 (0.304777) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.231889 / 0.018006 (0.213882) | 0.512497 / 0.000490 (0.512007) | 0.000390 / 0.000200 (0.000190) | 0.000069 / 0.000054 (0.000015) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.033978 / 0.037411 (-0.003433) | 0.100117 / 0.014526 (0.085592) | 0.112460 / 0.176557 (-0.064097) | 0.179936 / 0.737135 (-0.557200) | 0.114277 / 0.296338 (-0.182061) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.461320 / 0.215209 (0.246111) | 4.563180 / 2.077655 (2.485526) | 2.249474 / 1.504120 (0.745354) | 2.100450 / 1.541195 (0.559255) | 2.231080 / 1.468490 (0.762590) | 0.567907 / 4.584777 (-4.016870) | 4.117233 / 3.745712 (0.371521) | 4.943159 / 5.269862 (-0.326703) | 3.112299 / 4.565676 (-1.453377) | 0.065500 / 0.424275 (-0.358775) | 0.008407 / 0.007607 (0.000800) | 0.545928 / 0.226044 (0.319883) | 5.508058 / 2.268929 (3.239129) | 2.834645 / 55.444624 (-52.609980) | 2.440328 / 6.876477 (-4.436148) | 2.680483 / 2.142072 (0.538410) | 0.697191 / 4.805227 (-4.108036) | 0.176646 / 6.500664 (-6.324018) | 0.073608 / 0.075469 (-0.001861) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.451865 / 1.841788 (-0.389922) | 22.752595 / 8.074308 (14.678287) | 15.543338 / 10.191392 (5.351946) | 0.214644 / 0.680424 (-0.465780) | 0.022050 / 0.534201 (-0.512151) | 0.463898 / 0.579283 (-0.115385) | 0.481691 / 0.434364 (0.047327) | 0.549715 / 0.540337 (0.009378) | 0.773595 / 1.386936 (-0.613341) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007541 / 0.011353 (-0.003812) | 0.004715 / 0.011008 (-0.006293) | 0.076782 / 0.038508 (0.038274) | 0.086242 / 0.023109 (0.063133) | 0.458053 / 0.275898 (0.182155) | 0.503097 / 0.323480 (0.179617) | 0.006262 / 0.007986 (-0.001724) | 0.003882 / 0.004328 (-0.000447) | 0.075669 / 0.004250 (0.071419) | 0.066004 / 0.037052 (0.028952) | 0.469439 / 0.258489 (0.210950) | 0.529744 / 0.293841 (0.235903) | 0.037228 / 0.128546 (-0.091319) | 0.009794 / 0.075646 (-0.065852) | 0.082464 / 0.419271 (-0.336808) | 0.058797 / 0.043533 (0.015264) | 0.452069 / 0.255139 (0.196930) | 0.488246 / 0.283200 (0.205046) | 0.029324 / 0.141683 (-0.112359) | 1.742237 / 1.452155 (0.290082) | 1.839676 / 1.492716 (0.346959) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.228106 / 0.018006 (0.210100) | 0.491632 / 0.000490 (0.491142) | 0.004993 / 0.000200 (0.004793) | 0.000114 / 0.000054 (0.000060) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.035413 / 0.037411 (-0.001999) | 0.104617 / 0.014526 (0.090091) | 0.121948 / 0.176557 (-0.054609) | 0.186233 / 0.737135 (-0.550902) | 0.121574 / 0.296338 (-0.174764) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.473849 / 0.215209 (0.258640) | 4.788312 / 2.077655 (2.710657) | 2.470535 / 1.504120 (0.966415) | 2.270393 / 1.541195 (0.729198) | 2.361096 / 1.468490 (0.892606) | 0.556184 / 4.584777 (-4.028593) | 4.216852 / 3.745712 (0.471140) | 3.901718 / 5.269862 (-1.368143) | 2.355209 / 4.565676 (-2.210467) | 0.066708 / 0.424275 (-0.357567) | 0.008709 / 0.007607 (0.001102) | 0.571714 / 0.226044 (0.345669) | 5.663150 / 2.268929 (3.394221) | 3.025769 / 55.444624 (-52.418855) | 2.652554 / 6.876477 (-4.223923) | 2.750555 / 2.142072 (0.608483) | 0.681536 / 4.805227 (-4.123691) | 0.157187 / 6.500664 (-6.343477) | 0.073533 / 0.075469 (-0.001936) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.604630 / 1.841788 (-0.237158) | 22.735629 / 8.074308 (14.661321) | 16.762347 / 10.191392 (6.570955) | 0.175514 / 0.680424 (-0.504910) | 0.021497 / 0.534201 (-0.512704) | 0.461438 / 0.579283 (-0.117845) | 0.476184 / 0.434364 (0.041820) | 0.571048 / 0.540337 (0.030710) | 0.747086 / 1.386936 (-0.639850) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#6ea38fc40ee2b10d3b5c6df09b09ad05e02a2cff \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006889 / 0.011353 (-0.004464) | 0.004241 / 0.011008 (-0.006767) | 0.084542 / 0.038508 (0.046034) | 0.080484 / 0.023109 (0.057374) | 0.309356 / 0.275898 (0.033458) | 0.338548 / 0.323480 (0.015068) | 0.004904 / 0.007986 (-0.003082) | 0.005220 / 0.004328 (0.000892) | 0.065501 / 0.004250 (0.061251) | 0.062095 / 0.037052 (0.025043) | 0.317332 / 0.258489 (0.058843) | 0.364797 / 0.293841 (0.070956) | 0.030492 / 0.128546 (-0.098054) | 0.008991 / 0.075646 (-0.066656) | 0.288274 / 0.419271 (-0.130998) | 0.052582 / 0.043533 (0.009049) | 0.310838 / 0.255139 (0.055699) | 0.346304 / 0.283200 (0.063104) | 0.027968 / 0.141683 (-0.113715) | 1.509727 / 1.452155 (0.057573) | 1.577410 / 1.492716 (0.084694) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.269725 / 0.018006 (0.251719) | 0.627685 / 0.000490 (0.627195) | 0.000419 / 0.000200 (0.000219) | 0.000060 / 0.000054 (0.000006) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.031022 / 0.037411 (-0.006389) | 0.081858 / 0.014526 (0.067332) | 0.099477 / 0.176557 (-0.077080) | 0.162981 / 0.737135 (-0.574154) | 0.101987 / 0.296338 (-0.194351) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.386297 / 0.215209 (0.171088) | 3.845321 / 2.077655 (1.767666) | 1.834446 / 1.504120 (0.330326) | 1.699730 / 1.541195 (0.158536) | 1.764342 / 1.468490 (0.295852) | 0.486423 / 4.584777 (-4.098354) | 3.527595 / 3.745712 (-0.218117) | 4.137034 / 5.269862 (-1.132827) | 2.590457 / 4.565676 (-1.975219) | 0.057598 / 0.424275 (-0.366677) | 0.007318 / 0.007607 (-0.000289) | 0.460775 / 0.226044 (0.234730) | 4.627576 / 2.268929 (2.358647) | 2.402566 / 55.444624 (-53.042059) | 2.011392 / 6.876477 (-4.865085) | 2.223915 / 2.142072 (0.081842) | 0.623217 / 4.805227 (-4.182011) | 0.148875 / 6.500664 (-6.351789) | 0.059799 / 0.075469 (-0.015671) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.290768 / 1.841788 (-0.551020) | 20.455083 / 8.074308 (12.380775) | 13.469846 / 10.191392 (3.278454) | 0.170329 / 0.680424 (-0.510095) | 0.018409 / 0.534201 (-0.515792) | 0.394356 / 0.579283 (-0.184927) | 0.422685 / 0.434364 (-0.011679) | 0.476241 / 0.540337 (-0.064096) | 0.662682 / 1.386936 (-0.724254) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006724 / 0.011353 (-0.004629) | 0.004508 / 0.011008 (-0.006500) | 0.065304 / 0.038508 (0.026796) | 0.080243 / 0.023109 (0.057133) | 0.384545 / 0.275898 (0.108647) | 0.415234 / 0.323480 (0.091754) | 0.006361 / 0.007986 (-0.001624) | 0.004193 / 0.004328 (-0.000135) | 0.065940 / 0.004250 (0.061689) | 0.063633 / 0.037052 (0.026581) | 0.392799 / 0.258489 (0.134310) | 0.443618 / 0.293841 (0.149777) | 0.031134 / 0.128546 (-0.097412) | 0.009058 / 0.075646 (-0.066588) | 0.071051 / 0.419271 (-0.348221) | 0.049096 / 0.043533 (0.005563) | 0.379526 / 0.255139 (0.124387) | 0.403370 / 0.283200 (0.120171) | 0.026378 / 0.141683 (-0.115305) | 1.457879 / 1.452155 (0.005724) | 1.562890 / 1.492716 (0.070174) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.304416 / 0.018006 (0.286410) | 0.626046 / 0.000490 (0.625557) | 0.000469 / 0.000200 (0.000269) | 0.000057 / 0.000054 (0.000002) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.032979 / 0.037411 (-0.004433) | 0.086769 / 0.014526 (0.072243) | 0.108188 / 0.176557 (-0.068369) | 0.163077 / 0.737135 (-0.574058) | 0.106276 / 0.296338 (-0.190062) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.406922 / 0.215209 (0.191713) | 4.052828 / 2.077655 (1.975174) | 2.084802 / 1.504120 (0.580682) | 1.927263 / 1.541195 (0.386069) | 1.956078 / 1.468490 (0.487587) | 0.480110 / 4.584777 (-4.104667) | 3.553022 / 3.745712 (-0.192691) | 3.554450 / 5.269862 (-1.715411) | 2.082681 / 4.565676 (-2.482995) | 0.056711 / 0.424275 (-0.367564) | 0.007374 / 0.007607 (-0.000234) | 0.480555 / 0.226044 (0.254510) | 4.795851 / 2.268929 (2.526923) | 2.606675 / 55.444624 (-52.837949) | 2.249964 / 6.876477 (-4.626512) | 2.274234 / 2.142072 (0.132162) | 0.571767 / 4.805227 (-4.233461) | 0.133312 / 6.500664 (-6.367352) | 0.061703 / 0.075469 (-0.013766) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.354308 / 1.841788 (-0.487479) | 20.959352 / 8.074308 (12.885044) | 14.158420 / 10.191392 (3.967028) | 0.197959 / 0.680424 (-0.482465) | 0.018412 / 0.534201 (-0.515789) | 0.394307 / 0.579283 (-0.184976) | 0.402455 / 0.434364 (-0.031909) | 0.463314 / 0.540337 (-0.077024) | 0.621050 / 1.386936 (-0.765886) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#d7298d4d1b169442a8d0bc8c1667298bb89ca501 \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007179 / 0.011353 (-0.004174) | 0.004318 / 0.011008 (-0.006690) | 0.085209 / 0.038508 (0.046701) | 0.089989 / 0.023109 (0.066880) | 0.328188 / 0.275898 (0.052290) | 0.346027 / 0.323480 (0.022547) | 0.005711 / 0.007986 (-0.002275) | 0.003703 / 0.004328 (-0.000625) | 0.065419 / 0.004250 (0.061169) | 0.065354 / 0.037052 (0.028301) | 0.314531 / 0.258489 (0.056042) | 0.354357 / 0.293841 (0.060516) | 0.030918 / 0.128546 (-0.097628) | 0.008632 / 0.075646 (-0.067015) | 0.286817 / 0.419271 (-0.132455) | 0.065267 / 0.043533 (0.021735) | 0.310918 / 0.255139 (0.055779) | 0.330497 / 0.283200 (0.047298) | 0.035695 / 0.141683 (-0.105988) | 1.471101 / 1.452155 (0.018947) | 1.538658 / 1.492716 (0.045942) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.254314 / 0.018006 (0.236308) | 0.591413 / 0.000490 (0.590923) | 0.006082 / 0.000200 (0.005882) | 0.000091 / 0.000054 (0.000037) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.031843 / 0.037411 (-0.005568) | 0.089968 / 0.014526 (0.075442) | 0.101838 / 0.176557 (-0.074718) | 0.164401 / 0.737135 (-0.572734) | 0.103785 / 0.296338 (-0.192554) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.380486 / 0.215209 (0.165277) | 3.798868 / 2.077655 (1.721213) | 1.824645 / 1.504120 (0.320525) | 1.660804 / 1.541195 (0.119610) | 1.784793 / 1.468490 (0.316303) | 0.487222 / 4.584777 (-4.097555) | 3.560580 / 3.745712 (-0.185132) | 5.392662 / 5.269862 (0.122800) | 3.295327 / 4.565676 (-1.270350) | 0.057699 / 0.424275 (-0.366576) | 0.007559 / 0.007607 (-0.000048) | 0.459655 / 0.226044 (0.233611) | 4.587583 / 2.268929 (2.318654) | 2.304845 / 55.444624 (-53.139779) | 1.966433 / 6.876477 (-4.910044) | 2.254591 / 2.142072 (0.112519) | 0.582978 / 4.805227 (-4.222250) | 0.133455 / 6.500664 (-6.367210) | 0.061924 / 0.075469 (-0.013546) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.275685 / 1.841788 (-0.566103) | 20.814545 / 8.074308 (12.740237) | 13.753567 / 10.191392 (3.562175) | 0.164076 / 0.680424 (-0.516348) | 0.018768 / 0.534201 (-0.515433) | 0.390991 / 0.579283 (-0.188293) | 0.404417 / 0.434364 (-0.029947) | 0.457522 / 0.540337 (-0.082815) | 0.624654 / 1.386936 (-0.762282) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007435 / 0.011353 (-0.003918) | 0.004255 / 0.011008 (-0.006754) | 0.066134 / 0.038508 (0.027626) | 0.086035 / 0.023109 (0.062925) | 0.364688 / 0.275898 (0.088790) | 0.403895 / 0.323480 (0.080415) | 0.005868 / 0.007986 (-0.002117) | 0.003634 / 0.004328 (-0.000694) | 0.065803 / 0.004250 (0.061553) | 0.065113 / 0.037052 (0.028061) | 0.370057 / 0.258489 (0.111568) | 0.412634 / 0.293841 (0.118793) | 0.031660 / 0.128546 (-0.096886) | 0.008699 / 0.075646 (-0.066947) | 0.070618 / 0.419271 (-0.348654) | 0.050814 / 0.043533 (0.007281) | 0.362320 / 0.255139 (0.107181) | 0.383863 / 0.283200 (0.100663) | 0.027980 / 0.141683 (-0.113703) | 1.486389 / 1.452155 (0.034234) | 1.595534 / 1.492716 (0.102817) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.300991 / 0.018006 (0.282985) | 0.565265 / 0.000490 (0.564775) | 0.000400 / 0.000200 (0.000200) | 0.000053 / 0.000054 (-0.000001) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.034942 / 0.037411 (-0.002470) | 0.092498 / 0.014526 (0.077972) | 0.106737 / 0.176557 (-0.069819) | 0.165400 / 0.737135 (-0.571735) | 0.107809 / 0.296338 (-0.188529) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.412156 / 0.215209 (0.196947) | 4.116747 / 2.077655 (2.039092) | 2.199612 / 1.504120 (0.695492) | 2.049310 / 1.541195 (0.508115) | 2.174342 / 1.468490 (0.705852) | 0.482794 / 4.584777 (-4.101983) | 3.561344 / 3.745712 (-0.184368) | 3.465935 / 5.269862 (-1.803926) | 2.076595 / 4.565676 (-2.489081) | 0.056242 / 0.424275 (-0.368033) | 0.007371 / 0.007607 (-0.000236) | 0.489135 / 0.226044 (0.263091) | 4.895691 / 2.268929 (2.626763) | 2.626936 / 55.444624 (-52.817688) | 2.306658 / 6.876477 (-4.569818) | 2.421705 / 2.142072 (0.279633) | 0.599547 / 4.805227 (-4.205680) | 0.133627 / 6.500664 (-6.367037) | 0.063830 / 0.075469 (-0.011639) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.383039 / 1.841788 (-0.458748) | 21.005346 / 8.074308 (12.931038) | 14.911083 / 10.191392 (4.719691) | 0.190995 / 0.680424 (-0.489429) | 0.018510 / 0.534201 (-0.515691) | 0.396346 / 0.579283 (-0.182937) | 0.411496 / 0.434364 (-0.022868) | 0.470972 / 0.540337 (-0.069366) | 0.615670 / 1.386936 (-0.771266) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#d6d2ba47759d8acbf3d750b1cc4d89b195b1f9c9 \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007249 / 0.011353 (-0.004104) | 0.004261 / 0.011008 (-0.006747) | 0.100645 / 0.038508 (0.062137) | 0.078522 / 0.023109 (0.055413) | 0.423526 / 0.275898 (0.147628) | 0.439541 / 0.323480 (0.116061) | 0.005812 / 0.007986 (-0.002173) | 0.003615 / 0.004328 (-0.000713) | 0.075908 / 0.004250 (0.071658) | 0.062490 / 0.037052 (0.025437) | 0.414941 / 0.258489 (0.156452) | 0.447267 / 0.293841 (0.153426) | 0.035127 / 0.128546 (-0.093419) | 0.009642 / 0.075646 (-0.066004) | 0.354093 / 0.419271 (-0.065179) | 0.060970 / 0.043533 (0.017437) | 0.418579 / 0.255139 (0.163440) | 0.427972 / 0.283200 (0.144772) | 0.025838 / 0.141683 (-0.115845) | 1.778349 / 1.452155 (0.326194) | 1.845965 / 1.492716 (0.353249) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.227304 / 0.018006 (0.209298) | 0.571833 / 0.000490 (0.571343) | 0.001328 / 0.000200 (0.001128) | 0.000071 / 0.000054 (0.000017) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.031343 / 0.037411 (-0.006068) | 0.096400 / 0.014526 (0.081875) | 0.106881 / 0.176557 (-0.069676) | 0.175449 / 0.737135 (-0.561686) | 0.108751 / 0.296338 (-0.187588) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.480204 / 0.215209 (0.264995) | 4.622063 / 2.077655 (2.544408) | 2.211505 / 1.504120 (0.707385) | 2.065154 / 1.541195 (0.523959) | 2.159446 / 1.468490 (0.690956) | 0.584571 / 4.584777 (-4.000206) | 4.392449 / 3.745712 (0.646737) | 4.790166 / 5.269862 (-0.479695) | 2.840615 / 4.565676 (-1.725062) | 0.070845 / 0.424275 (-0.353430) | 0.009112 / 0.007607 (0.001505) | 0.580251 / 0.226044 (0.354207) | 5.660311 / 2.268929 (3.391382) | 2.836136 / 55.444624 (-52.608489) | 2.412859 / 6.876477 (-4.463618) | 2.556710 / 2.142072 (0.414637) | 0.691946 / 4.805227 (-4.113282) | 0.160123 / 6.500664 (-6.340541) | 0.072593 / 0.075469 (-0.002876) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.547339 / 1.841788 (-0.294448) | 21.724793 / 8.074308 (13.650485) | 16.315304 / 10.191392 (6.123912) | 0.188733 / 0.680424 (-0.491690) | 0.022109 / 0.534201 (-0.512092) | 0.481623 / 0.579283 (-0.097660) | 0.464316 / 0.434364 (0.029952) | 0.557953 / 0.540337 (0.017615) | 0.756023 / 1.386936 (-0.630913) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.008637 / 0.011353 (-0.002716) | 0.005286 / 0.011008 (-0.005723) | 0.091387 / 0.038508 (0.052879) | 0.114092 / 0.023109 (0.090983) | 0.457547 / 0.275898 (0.181649) | 0.506878 / 0.323480 (0.183398) | 0.006849 / 0.007986 (-0.001137) | 0.004255 / 0.004328 (-0.000073) | 0.079556 / 0.004250 (0.075306) | 0.077729 / 0.037052 (0.040677) | 0.454094 / 0.258489 (0.195605) | 0.515812 / 0.293841 (0.221971) | 0.038271 / 0.128546 (-0.090275) | 0.010110 / 0.075646 (-0.065536) | 0.094254 / 0.419271 (-0.325017) | 0.065392 / 0.043533 (0.021860) | 0.459749 / 0.255139 (0.204610) | 0.489829 / 0.283200 (0.206629) | 0.040393 / 0.141683 (-0.101290) | 1.810414 / 1.452155 (0.358259) | 1.913212 / 1.492716 (0.420496) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.236898 / 0.018006 (0.218891) | 0.513118 / 0.000490 (0.512628) | 0.004432 / 0.000200 (0.004232) | 0.000115 / 0.000054 (0.000060) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.035074 / 0.037411 (-0.002337) | 0.102384 / 0.014526 (0.087858) | 0.117326 / 0.176557 (-0.059231) | 0.182596 / 0.737135 (-0.554539) | 0.116384 / 0.296338 (-0.179955) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.514544 / 0.215209 (0.299335) | 5.152930 / 2.077655 (3.075275) | 2.624477 / 1.504120 (1.120357) | 2.363209 / 1.541195 (0.822014) | 2.436060 / 1.468490 (0.967570) | 0.592523 / 4.584777 (-3.992254) | 4.209668 / 3.745712 (0.463956) | 6.284372 / 5.269862 (1.014511) | 3.667303 / 4.565676 (-0.898374) | 0.067017 / 0.424275 (-0.357259) | 0.008607 / 0.007607 (0.001000) | 0.600840 / 0.226044 (0.374796) | 5.992630 / 2.268929 (3.723701) | 3.114532 / 55.444624 (-52.330093) | 2.693242 / 6.876477 (-4.183235) | 2.767187 / 2.142072 (0.625115) | 0.687591 / 4.805227 (-4.117636) | 0.158477 / 6.500664 (-6.342187) | 0.075504 / 0.075469 (0.000034) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.605039 / 1.841788 (-0.236749) | 21.524730 / 8.074308 (13.450422) | 17.014643 / 10.191392 (6.823251) | 0.201580 / 0.680424 (-0.478843) | 0.023028 / 0.534201 (-0.511173) | 0.483801 / 0.579283 (-0.095482) | 0.490221 / 0.434364 (0.055857) | 0.589292 / 0.540337 (0.048955) | 0.758532 / 1.386936 (-0.628404) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#8c9c24d1d90f0c2db043ae2bc39f7c292454a58c \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.008080 / 0.011353 (-0.003273) | 0.004859 / 0.011008 (-0.006149) | 0.101895 / 0.038508 (0.063387) | 0.091168 / 0.023109 (0.068059) | 0.378914 / 0.275898 (0.103016) | 0.417172 / 0.323480 (0.093692) | 0.006314 / 0.007986 (-0.001672) | 0.004069 / 0.004328 (-0.000259) | 0.076566 / 0.004250 (0.072315) | 0.070986 / 0.037052 (0.033934) | 0.380935 / 0.258489 (0.122446) | 0.417131 / 0.293841 (0.123290) | 0.036343 / 0.128546 (-0.092203) | 0.009996 / 0.075646 (-0.065650) | 0.346386 / 0.419271 (-0.072886) | 0.063162 / 0.043533 (0.019630) | 0.372620 / 0.255139 (0.117481) | 0.404902 / 0.283200 (0.121702) | 0.028217 / 0.141683 (-0.113466) | 1.793875 / 1.452155 (0.341721) | 1.836284 / 1.492716 (0.343568) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.223830 / 0.018006 (0.205823) | 0.503643 / 0.000490 (0.503153) | 0.004957 / 0.000200 (0.004757) | 0.000107 / 0.000054 (0.000053) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.035455 / 0.037411 (-0.001957) | 0.108015 / 0.014526 (0.093489) | 0.116887 / 0.176557 (-0.059669) | 0.188174 / 0.737135 (-0.548961) | 0.117217 / 0.296338 (-0.179121) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.471681 / 0.215209 (0.256472) | 4.694509 / 2.077655 (2.616855) | 2.369539 / 1.504120 (0.865419) | 2.176839 / 1.541195 (0.635644) | 2.300536 / 1.468490 (0.832045) | 0.575689 / 4.584777 (-4.009088) | 4.232765 / 3.745712 (0.487053) | 4.766775 / 5.269862 (-0.503087) | 2.864667 / 4.565676 (-1.701010) | 0.069390 / 0.424275 (-0.354885) | 0.008822 / 0.007607 (0.001214) | 0.559620 / 0.226044 (0.333576) | 5.580401 / 2.268929 (3.311472) | 2.920293 / 55.444624 (-52.524331) | 2.552166 / 6.876477 (-4.324311) | 2.795890 / 2.142072 (0.653818) | 0.687863 / 4.805227 (-4.117364) | 0.159129 / 6.500664 (-6.341535) | 0.073475 / 0.075469 (-0.001994) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.505892 / 1.841788 (-0.335896) | 24.127650 / 8.074308 (16.053342) | 16.758238 / 10.191392 (6.566846) | 0.200555 / 0.680424 (-0.479869) | 0.021596 / 0.534201 (-0.512605) | 0.480668 / 0.579283 (-0.098615) | 0.483528 / 0.434364 (0.049164) | 0.571241 / 0.540337 (0.030903) | 0.790547 / 1.386936 (-0.596390) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007997 / 0.011353 (-0.003356) | 0.004842 / 0.011008 (-0.006166) | 0.077190 / 0.038508 (0.038681) | 0.092765 / 0.023109 (0.069656) | 0.457475 / 0.275898 (0.181577) | 0.523914 / 0.323480 (0.200434) | 0.006349 / 0.007986 (-0.001637) | 0.003902 / 0.004328 (-0.000427) | 0.075860 / 0.004250 (0.071609) | 0.069708 / 0.037052 (0.032656) | 0.459612 / 0.258489 (0.201123) | 0.555028 / 0.293841 (0.261187) | 0.036854 / 0.128546 (-0.091692) | 0.010078 / 0.075646 (-0.065568) | 0.083871 / 0.419271 (-0.335400) | 0.061221 / 0.043533 (0.017689) | 0.435737 / 0.255139 (0.180598) | 0.509700 / 0.283200 (0.226500) | 0.038091 / 0.141683 (-0.103592) | 1.777161 / 1.452155 (0.325006) | 1.859603 / 1.492716 (0.366886) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.250020 / 0.018006 (0.232014) | 0.486198 / 0.000490 (0.485708) | 0.007080 / 0.000200 (0.006880) | 0.000114 / 0.000054 (0.000060) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.038163 / 0.037411 (0.000751) | 0.110812 / 0.014526 (0.096286) | 0.122489 / 0.176557 (-0.054068) | 0.188215 / 0.737135 (-0.548920) | 0.122375 / 0.296338 (-0.173963) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.484534 / 0.215209 (0.269325) | 4.828654 / 2.077655 (2.751000) | 2.545102 / 1.504120 (1.040982) | 2.368867 / 1.541195 (0.827672) | 2.458042 / 1.468490 (0.989552) | 0.576372 / 4.584777 (-4.008404) | 4.814033 / 3.745712 (1.068321) | 6.175972 / 5.269862 (0.906110) | 4.033422 / 4.565676 (-0.532254) | 0.068544 / 0.424275 (-0.355731) | 0.008906 / 0.007607 (0.001299) | 0.581767 / 0.226044 (0.355723) | 5.808623 / 2.268929 (3.539695) | 3.120312 / 55.444624 (-52.324313) | 2.774834 / 6.876477 (-4.101642) | 2.770413 / 2.142072 (0.628340) | 0.692715 / 4.805227 (-4.112512) | 0.158883 / 6.500664 (-6.341782) | 0.075894 / 0.075469 (0.000425) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.631250 / 1.841788 (-0.210538) | 24.693250 / 8.074308 (16.618942) | 17.434790 / 10.191392 (7.243398) | 0.196456 / 0.680424 (-0.483968) | 0.022505 / 0.534201 (-0.511696) | 0.474788 / 0.579283 (-0.104495) | 0.500947 / 0.434364 (0.066583) | 0.553596 / 0.540337 (0.013259) | 0.737767 / 1.386936 (-0.649169) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#f87d6e6394bf4b390ccc82235eb7667f874e5d43 \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006629 / 0.011353 (-0.004724) | 0.004115 / 0.011008 (-0.006894) | 0.083934 / 0.038508 (0.045426) | 0.074952 / 0.023109 (0.051843) | 0.313069 / 0.275898 (0.037171) | 0.345878 / 0.323480 (0.022398) | 0.006034 / 0.007986 (-0.001952) | 0.003413 / 0.004328 (-0.000916) | 0.065130 / 0.004250 (0.060880) | 0.057363 / 0.037052 (0.020310) | 0.314483 / 0.258489 (0.055994) | 0.352626 / 0.293841 (0.058785) | 0.031325 / 0.128546 (-0.097221) | 0.008577 / 0.075646 (-0.067069) | 0.288137 / 0.419271 (-0.131135) | 0.053651 / 0.043533 (0.010118) | 0.313006 / 0.255139 (0.057867) | 0.338668 / 0.283200 (0.055468) | 0.023709 / 0.141683 (-0.117974) | 1.481209 / 1.452155 (0.029054) | 1.559801 / 1.492716 (0.067085) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.211543 / 0.018006 (0.193537) | 0.452185 / 0.000490 (0.451696) | 0.003177 / 0.000200 (0.002977) | 0.000078 / 0.000054 (0.000024) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.028821 / 0.037411 (-0.008591) | 0.083290 / 0.014526 (0.068765) | 0.097478 / 0.176557 (-0.079079) | 0.153506 / 0.737135 (-0.583629) | 0.097054 / 0.296338 (-0.199284) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.385847 / 0.215209 (0.170638) | 3.835629 / 2.077655 (1.757974) | 1.880938 / 1.504120 (0.376819) | 1.711848 / 1.541195 (0.170653) | 1.785099 / 1.468490 (0.316609) | 0.486256 / 4.584777 (-4.098521) | 3.629026 / 3.745712 (-0.116686) | 3.321578 / 5.269862 (-1.948283) | 2.024314 / 4.565676 (-2.541363) | 0.058097 / 0.424275 (-0.366179) | 0.007724 / 0.007607 (0.000117) | 0.458293 / 0.226044 (0.232249) | 4.581314 / 2.268929 (2.312386) | 2.314379 / 55.444624 (-53.130246) | 1.966089 / 6.876477 (-4.910387) | 2.203824 / 2.142072 (0.061752) | 0.611581 / 4.805227 (-4.193647) | 0.149166 / 6.500664 (-6.351498) | 0.059825 / 0.075469 (-0.015644) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.235546 / 1.841788 (-0.606242) | 19.747439 / 8.074308 (11.673131) | 14.628383 / 10.191392 (4.436991) | 0.193074 / 0.680424 (-0.487350) | 0.020327 / 0.534201 (-0.513874) | 0.397051 / 0.579283 (-0.182232) | 0.418491 / 0.434364 (-0.015873) | 0.462055 / 0.540337 (-0.078282) | 0.637524 / 1.386936 (-0.749412) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007069 / 0.011353 (-0.004284) | 0.004106 / 0.011008 (-0.006902) | 0.065818 / 0.038508 (0.027310) | 0.077101 / 0.023109 (0.053991) | 0.363323 / 0.275898 (0.087425) | 0.399463 / 0.323480 (0.075983) | 0.005540 / 0.007986 (-0.002446) | 0.003480 / 0.004328 (-0.000849) | 0.065176 / 0.004250 (0.060926) | 0.060867 / 0.037052 (0.023815) | 0.365763 / 0.258489 (0.107273) | 0.407789 / 0.293841 (0.113949) | 0.032018 / 0.128546 (-0.096528) | 0.008550 / 0.075646 (-0.067096) | 0.071750 / 0.419271 (-0.347521) | 0.050625 / 0.043533 (0.007092) | 0.361434 / 0.255139 (0.106295) | 0.384799 / 0.283200 (0.101599) | 0.026104 / 0.141683 (-0.115579) | 1.496093 / 1.452155 (0.043938) | 1.592909 / 1.492716 (0.100193) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.185794 / 0.018006 (0.167787) | 0.453379 / 0.000490 (0.452890) | 0.004365 / 0.000200 (0.004165) | 0.000092 / 0.000054 (0.000038) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.031666 / 0.037411 (-0.005746) | 0.088323 / 0.014526 (0.073798) | 0.104602 / 0.176557 (-0.071954) | 0.159827 / 0.737135 (-0.577308) | 0.103725 / 0.296338 (-0.192614) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.413509 / 0.215209 (0.198300) | 4.126071 / 2.077655 (2.048416) | 2.137088 / 1.504120 (0.632968) | 1.981034 / 1.541195 (0.439839) | 2.063660 / 1.468490 (0.595170) | 0.478798 / 4.584777 (-4.105979) | 3.642801 / 3.745712 (-0.102911) | 3.428994 / 5.269862 (-1.840867) | 2.031902 / 4.565676 (-2.533774) | 0.056244 / 0.424275 (-0.368032) | 0.007365 / 0.007607 (-0.000242) | 0.484371 / 0.226044 (0.258327) | 4.838537 / 2.268929 (2.569608) | 2.559497 / 55.444624 (-52.885127) | 2.251863 / 6.876477 (-4.624614) | 2.339227 / 2.142072 (0.197155) | 0.607228 / 4.805227 (-4.198000) | 0.133877 / 6.500664 (-6.366787) | 0.062049 / 0.075469 (-0.013420) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.350389 / 1.841788 (-0.491399) | 20.060359 / 8.074308 (11.986051) | 14.305675 / 10.191392 (4.114283) | 0.165642 / 0.680424 (-0.514782) | 0.018206 / 0.534201 (-0.515994) | 0.396907 / 0.579283 (-0.182376) | 0.431896 / 0.434364 (-0.002468) | 0.475778 / 0.540337 (-0.064559) | 0.644688 / 1.386936 (-0.742248) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#8f6fa96ae5de873a49ef28739e8f64edf8b18cae \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.009048 / 0.011353 (-0.002305) | 0.005787 / 0.011008 (-0.005221) | 0.111617 / 0.038508 (0.073109) | 0.087603 / 0.023109 (0.064494) | 0.446481 / 0.275898 (0.170583) | 0.491726 / 0.323480 (0.168247) | 0.007052 / 0.007986 (-0.000934) | 0.004481 / 0.004328 (0.000152) | 0.084331 / 0.004250 (0.080081) | 0.072006 / 0.037052 (0.034953) | 0.454238 / 0.258489 (0.195749) | 0.496749 / 0.293841 (0.202908) | 0.049027 / 0.128546 (-0.079520) | 0.014005 / 0.075646 (-0.061641) | 0.372550 / 0.419271 (-0.046722) | 0.071414 / 0.043533 (0.027881) | 0.459432 / 0.255139 (0.204293) | 0.467332 / 0.283200 (0.184133) | 0.037539 / 0.141683 (-0.104144) | 1.869179 / 1.452155 (0.417024) | 1.983641 / 1.492716 (0.490925) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.265426 / 0.018006 (0.247419) | 0.672527 / 0.000490 (0.672037) | 0.001152 / 0.000200 (0.000953) | 0.000181 / 0.000054 (0.000127) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.032967 / 0.037411 (-0.004445) | 0.103023 / 0.014526 (0.088497) | 0.115978 / 0.176557 (-0.060578) | 0.191698 / 0.737135 (-0.545438) | 0.117867 / 0.296338 (-0.178471) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.602208 / 0.215209 (0.386999) | 6.147784 / 2.077655 (4.070129) | 2.768933 / 1.504120 (1.264813) | 2.415619 / 1.541195 (0.874424) | 2.456159 / 1.468490 (0.987669) | 0.836270 / 4.584777 (-3.748507) | 5.447754 / 3.745712 (1.702042) | 7.751825 / 5.269862 (2.481963) | 4.591892 / 4.565676 (0.026215) | 0.108269 / 0.424275 (-0.316006) | 0.009626 / 0.007607 (0.002019) | 0.719260 / 0.226044 (0.493216) | 7.313442 / 2.268929 (5.044514) | 3.490739 / 55.444624 (-51.953885) | 2.743543 / 6.876477 (-4.132934) | 3.035071 / 2.142072 (0.892999) | 1.042791 / 4.805227 (-3.762436) | 0.217080 / 6.500664 (-6.283584) | 0.084286 / 0.075469 (0.008817) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.655427 / 1.841788 (-0.186361) | 25.386536 / 8.074308 (17.312228) | 21.740666 / 10.191392 (11.549274) | 0.246388 / 0.680424 (-0.434036) | 0.029723 / 0.534201 (-0.504478) | 0.491537 / 0.579283 (-0.087746) | 0.603495 / 0.434364 (0.169131) | 0.573938 / 0.540337 (0.033600) | 0.981875 / 1.386936 (-0.405061) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.009664 / 0.011353 (-0.001689) | 0.006446 / 0.011008 (-0.004562) | 0.085113 / 0.038508 (0.046605) | 0.094533 / 0.023109 (0.071424) | 0.498388 / 0.275898 (0.222490) | 0.540127 / 0.323480 (0.216647) | 0.007316 / 0.007986 (-0.000670) | 0.004252 / 0.004328 (-0.000077) | 0.086292 / 0.004250 (0.082041) | 0.067956 / 0.037052 (0.030903) | 0.507664 / 0.258489 (0.249175) | 0.554324 / 0.293841 (0.260483) | 0.050107 / 0.128546 (-0.078439) | 0.014277 / 0.075646 (-0.061370) | 0.098838 / 0.419271 (-0.320433) | 0.066053 / 0.043533 (0.022521) | 0.491090 / 0.255139 (0.235951) | 0.537432 / 0.283200 (0.254232) | 0.035937 / 0.141683 (-0.105746) | 1.820715 / 1.452155 (0.368561) | 1.996268 / 1.492716 (0.503552) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.300859 / 0.018006 (0.282852) | 0.610958 / 0.000490 (0.610468) | 0.000474 / 0.000200 (0.000274) | 0.000098 / 0.000054 (0.000044) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.036372 / 0.037411 (-0.001039) | 0.109115 / 0.014526 (0.094589) | 0.122802 / 0.176557 (-0.053755) | 0.187092 / 0.737135 (-0.550044) | 0.123432 / 0.296338 (-0.172906) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.646979 / 0.215209 (0.431770) | 6.577713 / 2.077655 (4.500058) | 3.004606 / 1.504120 (1.500486) | 2.661183 / 1.541195 (1.119989) | 2.726717 / 1.468490 (1.258227) | 0.889497 / 4.584777 (-3.695280) | 5.485055 / 3.745712 (1.739343) | 4.852043 / 5.269862 (-0.417819) | 3.177392 / 4.565676 (-1.388285) | 0.099796 / 0.424275 (-0.324479) | 0.009868 / 0.007607 (0.002261) | 0.819919 / 0.226044 (0.593874) | 7.911255 / 2.268929 (5.642326) | 3.839877 / 55.444624 (-51.604747) | 3.088663 / 6.876477 (-3.787813) | 3.371184 / 2.142072 (1.229112) | 1.072762 / 4.805227 (-3.732466) | 0.224536 / 6.500664 (-6.276128) | 0.083415 / 0.075469 (0.007946) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.754426 / 1.841788 (-0.087361) | 25.546690 / 8.074308 (17.472382) | 22.998252 / 10.191392 (12.806860) | 0.258019 / 0.680424 (-0.422405) | 0.030104 / 0.534201 (-0.504097) | 0.518406 / 0.579283 (-0.060877) | 0.605753 / 0.434364 (0.171389) | 0.599630 / 0.540337 (0.059292) | 0.819042 / 1.386936 (-0.567894) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#350f4fd6caabbdfacb5fbf9193ab255c3d0daa4c \"CML watermark\")\n" ]

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[ "Hello @exs-avianello, I have reproduced the bug successfully and have understood the problem. But I am confused regarding this part of the statement, \"`pandas.DataFrame.to_csv` is always called with a buf-like `path_or_buf`\".\r\n\r\nCan you please elaborate on it?\r\n\r\nThanks!", "Hi @aryanxk02 ! Sure, what I actually meant is that when passing a path-like `path_or_buf` here\r\n\r\nhttps://github.com/huggingface/datasets/blob/14f6edd9222e577dccb962ed5338b79b73502fa5/src/datasets/arrow_dataset.py#L4708-L4714 \r\n\r\nit gets converted to a file object behind the scenes here\r\n\r\nhttps://github.com/huggingface/datasets/blob/14f6edd9222e577dccb962ed5338b79b73502fa5/src/datasets/io/csv.py#L92-L94\r\n\r\nand the eventual pandas `.to_csv()` calls that write to it always get `path_or_buf=None`, making pandas ignore the `compression` kwarg in the `to_csv_kwargs`\r\n\r\nhttps://github.com/huggingface/datasets/blob/14f6edd9222e577dccb962ed5338b79b73502fa5/src/datasets/io/csv.py#L107-L109", "@exs-avianello When `path_or_buf` is set to None, the `to_csv()` method will return the CSV data as a string instead of saving it to a file. Hence the compression doesn't take place. I think setting `path_or_buf=self.path_or_buf` should work. What you say?" ]

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[ "_The documentation is not available anymore as the PR was closed or merged._", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.008634 / 0.011353 (-0.002719) | 0.005147 / 0.011008 (-0.005861) | 0.102865 / 0.038508 (0.064357) | 0.080245 / 0.023109 (0.057136) | 0.401288 / 0.275898 (0.125390) | 0.419708 / 0.323480 (0.096228) | 0.006342 / 0.007986 (-0.001644) | 0.003998 / 0.004328 (-0.000330) | 0.078880 / 0.004250 (0.074630) | 0.068199 / 0.037052 (0.031147) | 0.389573 / 0.258489 (0.131084) | 0.417292 / 0.293841 (0.123451) | 0.048856 / 0.128546 (-0.079691) | 0.014165 / 0.075646 (-0.061481) | 0.348063 / 0.419271 (-0.071209) | 0.067547 / 0.043533 (0.024014) | 0.402251 / 0.255139 (0.147112) | 0.419478 / 0.283200 (0.136278) | 0.034846 / 0.141683 (-0.106837) | 1.773493 / 1.452155 (0.321338) | 1.930546 / 1.492716 (0.437830) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.211835 / 0.018006 (0.193829) | 0.545311 / 0.000490 (0.544821) | 0.006766 / 0.000200 (0.006566) | 0.000104 / 0.000054 (0.000050) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.035406 / 0.037411 (-0.002006) | 0.100769 / 0.014526 (0.086243) | 0.108667 / 0.176557 (-0.067890) | 0.193099 / 0.737135 (-0.544036) | 0.113539 / 0.296338 (-0.182799) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.586935 / 0.215209 (0.371726) | 5.895245 / 2.077655 (3.817591) | 2.528375 / 1.504120 (1.024255) | 2.228617 / 1.541195 (0.687423) | 2.295799 / 1.468490 (0.827309) | 0.859272 / 4.584777 (-3.725505) | 5.033434 / 3.745712 (1.287722) | 7.546587 / 5.269862 (2.276726) | 4.457137 / 4.565676 (-0.108539) | 0.099626 / 0.424275 (-0.324649) | 0.009296 / 0.007607 (0.001689) | 0.713498 / 0.226044 (0.487454) | 7.409385 / 2.268929 (5.140456) | 3.361418 / 55.444624 (-52.083206) | 2.681111 / 6.876477 (-4.195366) | 2.849598 / 2.142072 (0.707526) | 1.114863 / 4.805227 (-3.690364) | 0.215494 / 6.500664 (-6.285170) | 0.075807 / 0.075469 (0.000338) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.606458 / 1.841788 (-0.235330) | 23.751096 / 8.074308 (15.676788) | 21.279110 / 10.191392 (11.087718) | 0.220785 / 0.680424 (-0.459639) | 0.032688 / 0.534201 (-0.501513) | 0.530948 / 0.579283 (-0.048335) | 0.630056 / 0.434364 (0.195693) | 0.572743 / 0.540337 (0.032405) | 0.771853 / 1.386936 (-0.615083) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.008693 / 0.011353 (-0.002660) | 0.004750 / 0.011008 (-0.006259) | 0.079764 / 0.038508 (0.041256) | 0.082096 / 0.023109 (0.058987) | 0.467198 / 0.275898 (0.191300) | 0.532361 / 0.323480 (0.208881) | 0.005836 / 0.007986 (-0.002149) | 0.004333 / 0.004328 (0.000005) | 0.080444 / 0.004250 (0.076194) | 0.065883 / 0.037052 (0.028831) | 0.464871 / 0.258489 (0.206382) | 0.575026 / 0.293841 (0.281185) | 0.057807 / 0.128546 (-0.070739) | 0.017462 / 0.075646 (-0.058185) | 0.093667 / 0.419271 (-0.325605) | 0.071466 / 0.043533 (0.027933) | 0.495846 / 0.255139 (0.240707) | 0.526100 / 0.283200 (0.242900) | 0.034852 / 0.141683 (-0.106831) | 1.884152 / 1.452155 (0.431998) | 1.922681 / 1.492716 (0.429965) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.250969 / 0.018006 (0.232963) | 0.504979 / 0.000490 (0.504489) | 0.000466 / 0.000200 (0.000266) | 0.000083 / 0.000054 (0.000028) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.032411 / 0.037411 (-0.005000) | 0.093184 / 0.014526 (0.078658) | 0.110798 / 0.176557 (-0.065759) | 0.165741 / 0.737135 (-0.571394) | 0.111022 / 0.296338 (-0.185317) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.661284 / 0.215209 (0.446075) | 6.622388 / 2.077655 (4.544733) | 3.095705 / 1.504120 (1.591585) | 2.745698 / 1.541195 (1.204503) | 2.694103 / 1.468490 (1.225612) | 0.862154 / 4.584777 (-3.722623) | 5.109985 / 3.745712 (1.364273) | 5.040362 / 5.269862 (-0.229499) | 3.072837 / 4.565676 (-1.492840) | 0.110421 / 0.424275 (-0.313854) | 0.008476 / 0.007607 (0.000869) | 0.910020 / 0.226044 (0.683975) | 8.123626 / 2.268929 (5.854698) | 3.813811 / 55.444624 (-51.630813) | 3.017244 / 6.876477 (-3.859232) | 3.061222 / 2.142072 (0.919150) | 1.073548 / 4.805227 (-3.731680) | 0.216327 / 6.500664 (-6.284338) | 0.072977 / 0.075469 (-0.002492) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.722482 / 1.841788 (-0.119305) | 23.706716 / 8.074308 (15.632407) | 23.192134 / 10.191392 (13.000742) | 0.276733 / 0.680424 (-0.403691) | 0.033538 / 0.534201 (-0.500663) | 0.602083 / 0.579283 (0.022799) | 0.578718 / 0.434364 (0.144354) | 0.558311 / 0.540337 (0.017974) | 0.740341 / 1.386936 (-0.646595) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#7ac575b8ed57dac60d7ba33a616894f38601f84a \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006862 / 0.011353 (-0.004491) | 0.004223 / 0.011008 (-0.006786) | 0.085931 / 0.038508 (0.047423) | 0.081437 / 0.023109 (0.058328) | 0.349542 / 0.275898 (0.073644) | 0.379881 / 0.323480 (0.056401) | 0.005651 / 0.007986 (-0.002334) | 0.003662 / 0.004328 (-0.000666) | 0.065251 / 0.004250 (0.061001) | 0.061599 / 0.037052 (0.024547) | 0.359681 / 0.258489 (0.101192) | 0.392502 / 0.293841 (0.098661) | 0.031300 / 0.128546 (-0.097246) | 0.008591 / 0.075646 (-0.067055) | 0.288577 / 0.419271 (-0.130694) | 0.062920 / 0.043533 (0.019388) | 0.348989 / 0.255139 (0.093850) | 0.362769 / 0.283200 (0.079569) | 0.030087 / 0.141683 (-0.111596) | 1.480748 / 1.452155 (0.028594) | 1.580413 / 1.492716 (0.087697) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.205804 / 0.018006 (0.187798) | 0.455386 / 0.000490 (0.454897) | 0.003134 / 0.000200 (0.002934) | 0.000077 / 0.000054 (0.000023) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.030252 / 0.037411 (-0.007159) | 0.087566 / 0.014526 (0.073041) | 0.098209 / 0.176557 (-0.078347) | 0.155816 / 0.737135 (-0.581319) | 0.098938 / 0.296338 (-0.197401) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.386688 / 0.215209 (0.171479) | 3.852777 / 2.077655 (1.775123) | 1.938688 / 1.504120 (0.434568) | 1.779234 / 1.541195 (0.238039) | 1.864262 / 1.468490 (0.395772) | 0.482472 / 4.584777 (-4.102305) | 3.658060 / 3.745712 (-0.087652) | 5.206489 / 5.269862 (-0.063373) | 3.262498 / 4.565676 (-1.303179) | 0.057523 / 0.424275 (-0.366752) | 0.007365 / 0.007607 (-0.000242) | 0.466886 / 0.226044 (0.240841) | 4.671026 / 2.268929 (2.402097) | 2.380357 / 55.444624 (-53.064268) | 2.096590 / 6.876477 (-4.779887) | 2.274415 / 2.142072 (0.132342) | 0.579705 / 4.805227 (-4.225522) | 0.134522 / 6.500664 (-6.366142) | 0.062232 / 0.075469 (-0.013237) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.245965 / 1.841788 (-0.595823) | 20.115180 / 8.074308 (12.040872) | 14.602983 / 10.191392 (4.411591) | 0.146890 / 0.680424 (-0.533533) | 0.018424 / 0.534201 (-0.515777) | 0.393941 / 0.579283 (-0.185342) | 0.413785 / 0.434364 (-0.020579) | 0.453344 / 0.540337 (-0.086993) | 0.655446 / 1.386936 (-0.731490) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006807 / 0.011353 (-0.004546) | 0.004083 / 0.011008 (-0.006925) | 0.065389 / 0.038508 (0.026881) | 0.081056 / 0.023109 (0.057947) | 0.362823 / 0.275898 (0.086925) | 0.401928 / 0.323480 (0.078448) | 0.005452 / 0.007986 (-0.002533) | 0.003413 / 0.004328 (-0.000915) | 0.065238 / 0.004250 (0.060987) | 0.057264 / 0.037052 (0.020211) | 0.375713 / 0.258489 (0.117224) | 0.407858 / 0.293841 (0.114017) | 0.031580 / 0.128546 (-0.096966) | 0.008643 / 0.075646 (-0.067003) | 0.071693 / 0.419271 (-0.347578) | 0.049392 / 0.043533 (0.005859) | 0.370194 / 0.255139 (0.115055) | 0.384647 / 0.283200 (0.101447) | 0.024805 / 0.141683 (-0.116877) | 1.509511 / 1.452155 (0.057356) | 1.560193 / 1.492716 (0.067477) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.234442 / 0.018006 (0.216436) | 0.458818 / 0.000490 (0.458329) | 0.000407 / 0.000200 (0.000207) | 0.000060 / 0.000054 (0.000006) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.031661 / 0.037411 (-0.005750) | 0.093143 / 0.014526 (0.078618) | 0.102205 / 0.176557 (-0.074352) | 0.155850 / 0.737135 (-0.581286) | 0.104345 / 0.296338 (-0.191994) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.419641 / 0.215209 (0.204432) | 4.200808 / 2.077655 (2.123153) | 2.218227 / 1.504120 (0.714107) | 2.052604 / 1.541195 (0.511409) | 2.150611 / 1.468490 (0.682121) | 0.482665 / 4.584777 (-4.102112) | 3.606541 / 3.745712 (-0.139172) | 3.310637 / 5.269862 (-1.959224) | 2.070200 / 4.565676 (-2.495476) | 0.056586 / 0.424275 (-0.367689) | 0.007826 / 0.007607 (0.000218) | 0.491037 / 0.226044 (0.264992) | 4.901538 / 2.268929 (2.632610) | 2.676402 / 55.444624 (-52.768223) | 2.363935 / 6.876477 (-4.512542) | 2.587813 / 2.142072 (0.445741) | 0.579302 / 4.805227 (-4.225926) | 0.132792 / 6.500664 (-6.367873) | 0.061865 / 0.075469 (-0.013604) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.354315 / 1.841788 (-0.487473) | 20.874516 / 8.074308 (12.800208) | 14.863559 / 10.191392 (4.672167) | 0.183635 / 0.680424 (-0.496789) | 0.018636 / 0.534201 (-0.515565) | 0.395317 / 0.579283 (-0.183966) | 0.410598 / 0.434364 (-0.023766) | 0.476485 / 0.540337 (-0.063853) | 0.643246 / 1.386936 (-0.743690) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#4472a8795c603a95eef7c8f15cb04f1290cc8d11 \"CML watermark\")\n" ]

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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6041). All of your documentation changes will be reflected on that endpoint.", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007587 / 0.011353 (-0.003766) | 0.004469 / 0.011008 (-0.006540) | 0.098028 / 0.038508 (0.059520) | 0.086378 / 0.023109 (0.063269) | 0.412290 / 0.275898 (0.136392) | 0.449912 / 0.323480 (0.126432) | 0.004769 / 0.007986 (-0.003217) | 0.003708 / 0.004328 (-0.000621) | 0.075541 / 0.004250 (0.071290) | 0.063821 / 0.037052 (0.026768) | 0.417213 / 0.258489 (0.158724) | 0.471954 / 0.293841 (0.178113) | 0.036243 / 0.128546 (-0.092303) | 0.009540 / 0.075646 (-0.066106) | 0.339043 / 0.419271 (-0.080228) | 0.061853 / 0.043533 (0.018320) | 0.418510 / 0.255139 (0.163371) | 0.462372 / 0.283200 (0.179173) | 0.027328 / 0.141683 (-0.114355) | 1.745114 / 1.452155 (0.292959) | 1.879839 / 1.492716 (0.387123) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.211042 / 0.018006 (0.193035) | 0.512865 / 0.000490 (0.512375) | 0.008744 / 0.000200 (0.008544) | 0.000121 / 0.000054 (0.000066) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.032493 / 0.037411 (-0.004918) | 0.096472 / 0.014526 (0.081946) | 0.110340 / 0.176557 (-0.066216) | 0.183195 / 0.737135 (-0.553940) | 0.112829 / 0.296338 (-0.183510) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.478040 / 0.215209 (0.262830) | 4.743776 / 2.077655 (2.666121) | 2.389770 / 1.504120 (0.885650) | 2.168468 / 1.541195 (0.627274) | 2.238154 / 1.468490 (0.769663) | 0.572308 / 4.584777 (-4.012469) | 4.154783 / 3.745712 (0.409071) | 3.771509 / 5.269862 (-1.498353) | 2.384828 / 4.565676 (-2.180848) | 0.068122 / 0.424275 (-0.356153) | 0.008573 / 0.007607 (0.000965) | 0.560300 / 0.226044 (0.334256) | 5.591163 / 2.268929 (3.322235) | 2.929660 / 55.444624 (-52.514965) | 2.517721 / 6.876477 (-4.358756) | 2.762285 / 2.142072 (0.620213) | 0.687193 / 4.805227 (-4.118034) | 0.157839 / 6.500664 (-6.342825) | 0.071862 / 0.075469 (-0.003607) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.484788 / 1.841788 (-0.357000) | 21.696071 / 8.074308 (13.621763) | 15.476166 / 10.191392 (5.284774) | 0.185034 / 0.680424 (-0.495390) | 0.021181 / 0.534201 (-0.513020) | 0.463324 / 0.579283 (-0.115959) | 0.502455 / 0.434364 (0.068091) | 0.559880 / 0.540337 (0.019543) | 0.767281 / 1.386936 (-0.619655) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007572 / 0.011353 (-0.003781) | 0.004331 / 0.011008 (-0.006677) | 0.075023 / 0.038508 (0.036515) | 0.085474 / 0.023109 (0.062365) | 0.464900 / 0.275898 (0.189002) | 0.503348 / 0.323480 (0.179868) | 0.006885 / 0.007986 (-0.001101) | 0.003647 / 0.004328 (-0.000681) | 0.074874 / 0.004250 (0.070623) | 0.071076 / 0.037052 (0.034024) | 0.465495 / 0.258489 (0.207006) | 0.506418 / 0.293841 (0.212577) | 0.038900 / 0.128546 (-0.089647) | 0.009467 / 0.075646 (-0.066180) | 0.082547 / 0.419271 (-0.336724) | 0.058457 / 0.043533 (0.014924) | 0.459114 / 0.255139 (0.203975) | 0.484872 / 0.283200 (0.201673) | 0.027443 / 0.141683 (-0.114240) | 1.713996 / 1.452155 (0.261841) | 1.893639 / 1.492716 (0.400922) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.248693 / 0.018006 (0.230687) | 0.488805 / 0.000490 (0.488315) | 0.000421 / 0.000200 (0.000221) | 0.000067 / 0.000054 (0.000012) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.034886 / 0.037411 (-0.002525) | 0.103215 / 0.014526 (0.088689) | 0.116422 / 0.176557 (-0.060134) | 0.182789 / 0.737135 (-0.554346) | 0.117788 / 0.296338 (-0.178550) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.482782 / 0.215209 (0.267573) | 4.802895 / 2.077655 (2.725241) | 2.489823 / 1.504120 (0.985703) | 2.324005 / 1.541195 (0.782810) | 2.457674 / 1.468490 (0.989184) | 0.566980 / 4.584777 (-4.017797) | 4.117359 / 3.745712 (0.371647) | 3.841180 / 5.269862 (-1.428681) | 2.322410 / 4.565676 (-2.243266) | 0.066367 / 0.424275 (-0.357908) | 0.008501 / 0.007607 (0.000894) | 0.561453 / 0.226044 (0.335408) | 5.694861 / 2.268929 (3.425932) | 3.129829 / 55.444624 (-52.314796) | 2.647375 / 6.876477 (-4.229102) | 2.673071 / 2.142072 (0.530998) | 0.676120 / 4.805227 (-4.129108) | 0.153483 / 6.500664 (-6.347181) | 0.070797 / 0.075469 (-0.004672) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.575697 / 1.841788 (-0.266091) | 22.447462 / 8.074308 (14.373154) | 15.964906 / 10.191392 (5.773514) | 0.218343 / 0.680424 (-0.462081) | 0.021051 / 0.534201 (-0.513150) | 0.466079 / 0.579283 (-0.113204) | 0.493190 / 0.434364 (0.058826) | 0.565929 / 0.540337 (0.025592) | 0.768638 / 1.386936 (-0.618298) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#104bafffef7ddc775ec2d0b10b2b262466041eb7 \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006268 / 0.011353 (-0.005085) | 0.003715 / 0.011008 (-0.007293) | 0.080628 / 0.038508 (0.042120) | 0.070294 / 0.023109 (0.047185) | 0.404749 / 0.275898 (0.128851) | 0.434130 / 0.323480 (0.110650) | 0.005533 / 0.007986 (-0.002452) | 0.002980 / 0.004328 (-0.001349) | 0.063016 / 0.004250 (0.058766) | 0.051667 / 0.037052 (0.014615) | 0.403859 / 0.258489 (0.145370) | 0.437913 / 0.293841 (0.144073) | 0.027518 / 0.128546 (-0.101029) | 0.007991 / 0.075646 (-0.067655) | 0.260723 / 0.419271 (-0.158548) | 0.046580 / 0.043533 (0.003047) | 0.405453 / 0.255139 (0.150314) | 0.428390 / 0.283200 (0.145190) | 0.022774 / 0.141683 (-0.118909) | 1.488204 / 1.452155 (0.036049) | 1.536557 / 1.492716 (0.043841) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.185864 / 0.018006 (0.167858) | 0.431388 / 0.000490 (0.430898) | 0.003743 / 0.000200 (0.003543) | 0.000065 / 0.000054 (0.000011) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.024062 / 0.037411 (-0.013350) | 0.075749 / 0.014526 (0.061224) | 0.083519 / 0.176557 (-0.093037) | 0.147965 / 0.737135 (-0.589170) | 0.085635 / 0.296338 (-0.210703) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.400455 / 0.215209 (0.185246) | 4.084294 / 2.077655 (2.006640) | 1.928795 / 1.504120 (0.424675) | 1.743205 / 1.541195 (0.202010) | 1.811233 / 1.468490 (0.342743) | 0.504976 / 4.584777 (-4.079801) | 3.073134 / 3.745712 (-0.672578) | 2.816357 / 5.269862 (-2.453505) | 1.857462 / 4.565676 (-2.708214) | 0.058329 / 0.424275 (-0.365946) | 0.006850 / 0.007607 (-0.000757) | 0.466017 / 0.226044 (0.239973) | 4.660158 / 2.268929 (2.391230) | 2.396614 / 55.444624 (-53.048010) | 2.007491 / 6.876477 (-4.868986) | 2.206997 / 2.142072 (0.064925) | 0.592233 / 4.805227 (-4.212994) | 0.125364 / 6.500664 (-6.375300) | 0.061166 / 0.075469 (-0.014303) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.290148 / 1.841788 (-0.551640) | 18.317462 / 8.074308 (10.243154) | 13.465142 / 10.191392 (3.273750) | 0.149696 / 0.680424 (-0.530728) | 0.017120 / 0.534201 (-0.517081) | 0.334818 / 0.579283 (-0.244465) | 0.363976 / 0.434364 (-0.070388) | 0.388271 / 0.540337 (-0.152066) | 0.542383 / 1.386936 (-0.844553) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006029 / 0.011353 (-0.005324) | 0.003656 / 0.011008 (-0.007352) | 0.063518 / 0.038508 (0.025010) | 0.058214 / 0.023109 (0.035105) | 0.435987 / 0.275898 (0.160089) | 0.442769 / 0.323480 (0.119289) | 0.004675 / 0.007986 (-0.003310) | 0.002911 / 0.004328 (-0.001418) | 0.063020 / 0.004250 (0.058769) | 0.049422 / 0.037052 (0.012369) | 0.435521 / 0.258489 (0.177032) | 0.478251 / 0.293841 (0.184411) | 0.027294 / 0.128546 (-0.101252) | 0.008073 / 0.075646 (-0.067574) | 0.068397 / 0.419271 (-0.350875) | 0.044796 / 0.043533 (0.001263) | 0.416646 / 0.255139 (0.161507) | 0.435021 / 0.283200 (0.151821) | 0.024686 / 0.141683 (-0.116997) | 1.495650 / 1.452155 (0.043496) | 1.495846 / 1.492716 (0.003130) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.211205 / 0.018006 (0.193199) | 0.414497 / 0.000490 (0.414007) | 0.001704 / 0.000200 (0.001504) | 0.000073 / 0.000054 (0.000019) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.025237 / 0.037411 (-0.012174) | 0.077291 / 0.014526 (0.062765) | 0.085736 / 0.176557 (-0.090821) | 0.141059 / 0.737135 (-0.596076) | 0.087620 / 0.296338 (-0.208719) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.421995 / 0.215209 (0.206786) | 4.158503 / 2.077655 (2.080849) | 2.313598 / 1.504120 (0.809479) | 2.183553 / 1.541195 (0.642359) | 2.279656 / 1.468490 (0.811166) | 0.500146 / 4.584777 (-4.084631) | 3.092654 / 3.745712 (-0.653059) | 4.371616 / 5.269862 (-0.898245) | 2.605096 / 4.565676 (-1.960581) | 0.057658 / 0.424275 (-0.366617) | 0.006574 / 0.007607 (-0.001033) | 0.491455 / 0.226044 (0.265411) | 4.926730 / 2.268929 (2.657801) | 2.635749 / 55.444624 (-52.808875) | 2.255780 / 6.876477 (-4.620697) | 2.305547 / 2.142072 (0.163474) | 0.589027 / 4.805227 (-4.216200) | 0.126229 / 6.500664 (-6.374435) | 0.063268 / 0.075469 (-0.012201) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.299102 / 1.841788 (-0.542686) | 18.547417 / 8.074308 (10.473109) | 13.860030 / 10.191392 (3.668638) | 0.145482 / 0.680424 (-0.534942) | 0.016543 / 0.534201 (-0.517658) | 0.330788 / 0.579283 (-0.248496) | 0.362020 / 0.434364 (-0.072344) | 0.380635 / 0.540337 (-0.159703) | 0.517375 / 1.386936 (-0.869561) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#bf602e0193baca21e283babbac9622ae36d1e6b6 \"CML watermark\")\n" ]

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[ "_The documentation is not available anymore as the PR was closed or merged._", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006087 / 0.011353 (-0.005265) | 0.003567 / 0.011008 (-0.007442) | 0.079668 / 0.038508 (0.041160) | 0.063647 / 0.023109 (0.040538) | 0.323082 / 0.275898 (0.047184) | 0.348679 / 0.323480 (0.025199) | 0.004726 / 0.007986 (-0.003259) | 0.002955 / 0.004328 (-0.001373) | 0.062724 / 0.004250 (0.058473) | 0.050194 / 0.037052 (0.013142) | 0.321407 / 0.258489 (0.062918) | 0.355053 / 0.293841 (0.061212) | 0.026992 / 0.128546 (-0.101554) | 0.007994 / 0.075646 (-0.067653) | 0.260562 / 0.419271 (-0.158710) | 0.050933 / 0.043533 (0.007400) | 0.316644 / 0.255139 (0.061505) | 0.336759 / 0.283200 (0.053560) | 0.022581 / 0.141683 (-0.119101) | 1.481259 / 1.452155 (0.029104) | 1.535191 / 1.492716 (0.042475) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.194111 / 0.018006 (0.176104) | 0.448146 / 0.000490 (0.447656) | 0.000321 / 0.000200 (0.000121) | 0.000056 / 0.000054 (0.000001) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.023908 / 0.037411 (-0.013503) | 0.073316 / 0.014526 (0.058790) | 0.085588 / 0.176557 (-0.090968) | 0.145377 / 0.737135 (-0.591759) | 0.084788 / 0.296338 (-0.211550) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.439327 / 0.215209 (0.224118) | 4.384833 / 2.077655 (2.307179) | 2.322943 / 1.504120 (0.818823) | 2.147737 / 1.541195 (0.606542) | 2.226725 / 1.468490 (0.758235) | 0.502957 / 4.584777 (-4.081820) | 3.098106 / 3.745712 (-0.647606) | 4.194642 / 5.269862 (-1.075220) | 2.598820 / 4.565676 (-1.966856) | 0.057942 / 0.424275 (-0.366333) | 0.006857 / 0.007607 (-0.000750) | 0.511517 / 0.226044 (0.285472) | 5.121797 / 2.268929 (2.852868) | 2.756506 / 55.444624 (-52.688118) | 2.424602 / 6.876477 (-4.451875) | 2.608342 / 2.142072 (0.466270) | 0.589498 / 4.805227 (-4.215729) | 0.126065 / 6.500664 (-6.374600) | 0.061456 / 0.075469 (-0.014013) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.239928 / 1.841788 (-0.601860) | 18.423532 / 8.074308 (10.349224) | 13.935148 / 10.191392 (3.743756) | 0.129913 / 0.680424 (-0.550511) | 0.016744 / 0.534201 (-0.517457) | 0.333468 / 0.579283 (-0.245815) | 0.359615 / 0.434364 (-0.074749) | 0.383678 / 0.540337 (-0.156659) | 0.533007 / 1.386936 (-0.853929) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.005980 / 0.011353 (-0.005373) | 0.003640 / 0.011008 (-0.007368) | 0.062500 / 0.038508 (0.023992) | 0.059843 / 0.023109 (0.036733) | 0.360993 / 0.275898 (0.085095) | 0.401981 / 0.323480 (0.078501) | 0.005495 / 0.007986 (-0.002490) | 0.002862 / 0.004328 (-0.001467) | 0.062491 / 0.004250 (0.058240) | 0.050778 / 0.037052 (0.013726) | 0.371007 / 0.258489 (0.112518) | 0.405154 / 0.293841 (0.111313) | 0.027390 / 0.128546 (-0.101156) | 0.008042 / 0.075646 (-0.067604) | 0.067590 / 0.419271 (-0.351681) | 0.042485 / 0.043533 (-0.001048) | 0.361305 / 0.255139 (0.106166) | 0.388669 / 0.283200 (0.105469) | 0.024143 / 0.141683 (-0.117540) | 1.451508 / 1.452155 (-0.000647) | 1.490431 / 1.492716 (-0.002285) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.175976 / 0.018006 (0.157970) | 0.428923 / 0.000490 (0.428434) | 0.002099 / 0.000200 (0.001899) | 0.000068 / 0.000054 (0.000014) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.026346 / 0.037411 (-0.011065) | 0.078084 / 0.014526 (0.063558) | 0.087287 / 0.176557 (-0.089269) | 0.144179 / 0.737135 (-0.592957) | 0.088286 / 0.296338 (-0.208053) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.450436 / 0.215209 (0.235227) | 4.488801 / 2.077655 (2.411146) | 2.479303 / 1.504120 (0.975184) | 2.305396 / 1.541195 (0.764201) | 2.370370 / 1.468490 (0.901879) | 0.502355 / 4.584777 (-4.082422) | 3.094733 / 3.745712 (-0.650979) | 4.062367 / 5.269862 (-1.207495) | 2.587506 / 4.565676 (-1.978170) | 0.058245 / 0.424275 (-0.366030) | 0.006487 / 0.007607 (-0.001120) | 0.524147 / 0.226044 (0.298102) | 5.236876 / 2.268929 (2.967947) | 2.897134 / 55.444624 (-52.547490) | 2.574631 / 6.876477 (-4.301846) | 2.620307 / 2.142072 (0.478235) | 0.586963 / 4.805227 (-4.218265) | 0.125761 / 6.500664 (-6.374903) | 0.062264 / 0.075469 (-0.013205) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.299668 / 1.841788 (-0.542120) | 19.004441 / 8.074308 (10.930133) | 13.841867 / 10.191392 (3.650475) | 0.159674 / 0.680424 (-0.520750) | 0.016699 / 0.534201 (-0.517502) | 0.331868 / 0.579283 (-0.247415) | 0.344604 / 0.434364 (-0.089760) | 0.379391 / 0.540337 (-0.160947) | 0.514790 / 1.386936 (-0.872146) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#47a006a90e9711b33db70b0ef2d2cefaadfa2179 \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.005792 / 0.011353 (-0.005561) | 0.003519 / 0.011008 (-0.007489) | 0.079133 / 0.038508 (0.040625) | 0.057858 / 0.023109 (0.034749) | 0.314206 / 0.275898 (0.038308) | 0.346939 / 0.323480 (0.023459) | 0.004583 / 0.007986 (-0.003403) | 0.002824 / 0.004328 (-0.001504) | 0.061652 / 0.004250 (0.057402) | 0.048520 / 0.037052 (0.011467) | 0.318018 / 0.258489 (0.059529) | 0.350350 / 0.293841 (0.056509) | 0.026284 / 0.128546 (-0.102262) | 0.007827 / 0.075646 (-0.067819) | 0.259624 / 0.419271 (-0.159647) | 0.052318 / 0.043533 (0.008786) | 0.317400 / 0.255139 (0.062261) | 0.340530 / 0.283200 (0.057331) | 0.025181 / 0.141683 (-0.116501) | 1.459208 / 1.452155 (0.007053) | 1.529158 / 1.492716 (0.036442) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.169692 / 0.018006 (0.151686) | 0.432638 / 0.000490 (0.432148) | 0.003675 / 0.000200 (0.003475) | 0.000071 / 0.000054 (0.000017) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.022956 / 0.037411 (-0.014456) | 0.071860 / 0.014526 (0.057334) | 0.082159 / 0.176557 (-0.094398) | 0.142560 / 0.737135 (-0.594576) | 0.082333 / 0.296338 (-0.214006) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.397923 / 0.215209 (0.182714) | 3.958757 / 2.077655 (1.881102) | 1.925837 / 1.504120 (0.421717) | 1.758114 / 1.541195 (0.216919) | 1.808845 / 1.468490 (0.340354) | 0.501116 / 4.584777 (-4.083661) | 3.007739 / 3.745712 (-0.737973) | 3.295755 / 5.269862 (-1.974106) | 2.123843 / 4.565676 (-2.441833) | 0.057174 / 0.424275 (-0.367101) | 0.006426 / 0.007607 (-0.001182) | 0.468196 / 0.226044 (0.242152) | 4.677392 / 2.268929 (2.408464) | 2.334179 / 55.444624 (-53.110446) | 1.989283 / 6.876477 (-4.887194) | 2.140091 / 2.142072 (-0.001981) | 0.590700 / 4.805227 (-4.214527) | 0.124066 / 6.500664 (-6.376598) | 0.059931 / 0.075469 (-0.015538) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.224547 / 1.841788 (-0.617240) | 17.866979 / 8.074308 (9.792671) | 13.142009 / 10.191392 (2.950617) | 0.147081 / 0.680424 (-0.533343) | 0.016777 / 0.534201 (-0.517424) | 0.327766 / 0.579283 (-0.251517) | 0.343988 / 0.434364 (-0.090376) | 0.383268 / 0.540337 (-0.157070) | 0.528109 / 1.386936 (-0.858827) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006145 / 0.011353 (-0.005208) | 0.003634 / 0.011008 (-0.007374) | 0.062887 / 0.038508 (0.024379) | 0.062659 / 0.023109 (0.039550) | 0.362962 / 0.275898 (0.087064) | 0.405149 / 0.323480 (0.081669) | 0.004821 / 0.007986 (-0.003164) | 0.002888 / 0.004328 (-0.001441) | 0.062982 / 0.004250 (0.058732) | 0.051929 / 0.037052 (0.014877) | 0.366825 / 0.258489 (0.108336) | 0.409830 / 0.293841 (0.115989) | 0.027263 / 0.128546 (-0.101283) | 0.007972 / 0.075646 (-0.067674) | 0.067413 / 0.419271 (-0.351858) | 0.044233 / 0.043533 (0.000700) | 0.365087 / 0.255139 (0.109948) | 0.393845 / 0.283200 (0.110646) | 0.027740 / 0.141683 (-0.113943) | 1.497896 / 1.452155 (0.045741) | 1.549419 / 1.492716 (0.056703) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.225510 / 0.018006 (0.207503) | 0.417054 / 0.000490 (0.416564) | 0.002184 / 0.000200 (0.001984) | 0.000075 / 0.000054 (0.000020) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.025503 / 0.037411 (-0.011908) | 0.076164 / 0.014526 (0.061638) | 0.086110 / 0.176557 (-0.090446) | 0.140387 / 0.737135 (-0.596748) | 0.086956 / 0.296338 (-0.209382) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.469667 / 0.215209 (0.254458) | 4.689915 / 2.077655 (2.612261) | 2.685000 / 1.504120 (1.180880) | 2.516160 / 1.541195 (0.974965) | 2.531733 / 1.468490 (1.063243) | 0.501675 / 4.584777 (-4.083102) | 3.000579 / 3.745712 (-0.745133) | 2.853376 / 5.269862 (-2.416486) | 1.810677 / 4.565676 (-2.754999) | 0.057632 / 0.424275 (-0.366643) | 0.006390 / 0.007607 (-0.001217) | 0.543986 / 0.226044 (0.317941) | 5.432837 / 2.268929 (3.163908) | 3.138797 / 55.444624 (-52.305827) | 2.813141 / 6.876477 (-4.063336) | 2.803681 / 2.142072 (0.661609) | 0.588736 / 4.805227 (-4.216491) | 0.125696 / 6.500664 (-6.374968) | 0.062492 / 0.075469 (-0.012977) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.337163 / 1.841788 (-0.504624) | 18.611715 / 8.074308 (10.537407) | 13.953016 / 10.191392 (3.761624) | 0.154670 / 0.680424 (-0.525754) | 0.016523 / 0.534201 (-0.517678) | 0.333898 / 0.579283 (-0.245385) | 0.336520 / 0.434364 (-0.097844) | 0.389032 / 0.540337 (-0.151305) | 0.529202 / 1.386936 (-0.857734) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#01d4b3330f2cc243a3f3b0cd61ec5558466c40fd \"CML watermark\")\n" ]

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[ "Instead of writing the loading script, you can use the built-in loader to [load JSON files](https://huggingface.co/docs/datasets/loading#json):\r\n```python\r\nfrom datasets import load_dataset\r\nds = load_dataset(\"json\", data_files={\"train\": os.path.join(data_dir[\"train\"]), \"dev\": os.path.join(data_dir[\"dev\"])})\r\n```" ]

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[ "These docs are outdated (version 1.2.1 is over two years old). Please refer to [this](https://huggingface.co/docs/datasets/dataset_script) version instead.\r\n\r\nInitially, we hosted datasets in this repo, but now you can find them [on the HF Hub](https://huggingface.co/datasets) (e.g. the [`ag_news`](https://huggingface.co/datasets/ag_news/blob/main/ag_news.py) script)", "Sorry I thought I'd selected the latest version." ]

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[ "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.005746 / 0.011353 (-0.005607) | 0.003461 / 0.011008 (-0.007548) | 0.078672 / 0.038508 (0.040164) | 0.056800 / 0.023109 (0.033691) | 0.312853 / 0.275898 (0.036955) | 0.346715 / 0.323480 (0.023235) | 0.004516 / 0.007986 (-0.003469) | 0.002872 / 0.004328 (-0.001457) | 0.061264 / 0.004250 (0.057013) | 0.046606 / 0.037052 (0.009553) | 0.320080 / 0.258489 (0.061591) | 0.350390 / 0.293841 (0.056550) | 0.026445 / 0.128546 (-0.102101) | 0.007710 / 0.075646 (-0.067936) | 0.259519 / 0.419271 (-0.159752) | 0.043935 / 0.043533 (0.000402) | 0.320015 / 0.255139 (0.064876) | 0.339799 / 0.283200 (0.056599) | 0.018638 / 0.141683 (-0.123044) | 1.463393 / 1.452155 (0.011239) | 1.496977 / 1.492716 (0.004261) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.185175 / 0.018006 (0.167168) | 0.420734 / 0.000490 (0.420245) | 0.002569 / 0.000200 (0.002369) | 0.000067 / 0.000054 (0.000012) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.022335 / 0.037411 (-0.015077) | 0.071686 / 0.014526 (0.057161) | 0.079906 / 0.176557 (-0.096650) | 0.140386 / 0.737135 (-0.596749) | 0.079712 / 0.296338 (-0.216627) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.392643 / 0.215209 (0.177434) | 3.917934 / 2.077655 (1.840279) | 1.906808 / 1.504120 (0.402688) | 1.729564 / 1.541195 (0.188369) | 1.751533 / 1.468490 (0.283043) | 0.496810 / 4.584777 (-4.087967) | 3.047405 / 3.745712 (-0.698307) | 4.361766 / 5.269862 (-0.908095) | 2.660845 / 4.565676 (-1.904832) | 0.056951 / 0.424275 (-0.367324) | 0.006277 / 0.007607 (-0.001330) | 0.466357 / 0.226044 (0.240312) | 4.660457 / 2.268929 (2.391529) | 2.328590 / 55.444624 (-53.116034) | 1.986140 / 6.876477 (-4.890337) | 2.096182 / 2.142072 (-0.045891) | 0.581685 / 4.805227 (-4.223542) | 0.123643 / 6.500664 (-6.377021) | 0.060286 / 0.075469 (-0.015183) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.237024 / 1.841788 (-0.604763) | 17.778533 / 8.074308 (9.704225) | 13.202205 / 10.191392 (3.010813) | 0.141301 / 0.680424 (-0.539123) | 0.016453 / 0.534201 (-0.517748) | 0.329173 / 0.579283 (-0.250110) | 0.349945 / 0.434364 (-0.084419) | 0.375319 / 0.540337 (-0.165018) | 0.530394 / 1.386936 (-0.856542) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.005863 / 0.011353 (-0.005489) | 0.003578 / 0.011008 (-0.007430) | 0.062719 / 0.038508 (0.024211) | 0.056192 / 0.023109 (0.033082) | 0.422812 / 0.275898 (0.146914) | 0.454316 / 0.323480 (0.130836) | 0.004446 / 0.007986 (-0.003540) | 0.002808 / 0.004328 (-0.001521) | 0.062819 / 0.004250 (0.058569) | 0.046243 / 0.037052 (0.009190) | 0.445858 / 0.258489 (0.187369) | 0.463750 / 0.293841 (0.169909) | 0.027504 / 0.128546 (-0.101042) | 0.007897 / 0.075646 (-0.067749) | 0.068248 / 0.419271 (-0.351024) | 0.041921 / 0.043533 (-0.001612) | 0.413314 / 0.255139 (0.158175) | 0.441619 / 0.283200 (0.158419) | 0.019246 / 0.141683 (-0.122437) | 1.457069 / 1.452155 (0.004914) | 1.524168 / 1.492716 (0.031452) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.237785 / 0.018006 (0.219779) | 0.418455 / 0.000490 (0.417965) | 0.002301 / 0.000200 (0.002101) | 0.000065 / 0.000054 (0.000011) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.025630 / 0.037411 (-0.011781) | 0.076673 / 0.014526 (0.062147) | 0.084877 / 0.176557 (-0.091680) | 0.137528 / 0.737135 (-0.599607) | 0.085261 / 0.296338 (-0.211077) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.419040 / 0.215209 (0.203831) | 4.183022 / 2.077655 (2.105368) | 2.157852 / 1.504120 (0.653732) | 1.966177 / 1.541195 (0.424982) | 2.019612 / 1.468490 (0.551122) | 0.497415 / 4.584777 (-4.087362) | 3.102873 / 3.745712 (-0.642839) | 4.526336 / 5.269862 (-0.743525) | 2.991503 / 4.565676 (-1.574174) | 0.057235 / 0.424275 (-0.367040) | 0.006735 / 0.007607 (-0.000872) | 0.498255 / 0.226044 (0.272211) | 4.957364 / 2.268929 (2.688435) | 2.632643 / 55.444624 (-52.811981) | 2.249788 / 6.876477 (-4.626688) | 2.289134 / 2.142072 (0.147062) | 0.583581 / 4.805227 (-4.221646) | 0.126046 / 6.500664 (-6.374618) | 0.062966 / 0.075469 (-0.012504) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.295215 / 1.841788 (-0.546573) | 18.554020 / 8.074308 (10.479711) | 13.683273 / 10.191392 (3.491881) | 0.132266 / 0.680424 (-0.548158) | 0.016376 / 0.534201 (-0.517825) | 0.334495 / 0.579283 (-0.244788) | 0.347106 / 0.434364 (-0.087258) | 0.387531 / 0.540337 (-0.152806) | 0.525745 / 1.386936 (-0.861191) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#f22aa0bf179602e4bf3f44a9de5d180579bb377e \"CML watermark\")\n", "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6036). All of your documentation changes will be reflected on that endpoint.", "I don't think `transformers` should have any dataset indexing code. So before deprecating I'd be in favor of finding a suitable replacement. Not sure about the stats of the RAG model that uses `datasets` indexing though", "The RAG downloads stats are decent (over 20k downloads last month).\r\n\r\nI think it's suboptimal to maintain an API that only a single model uses. One option is to put this code into a separate lib. However, `langchain` and `docarray` already provide a unified interface to vector stores, so I don't see this as an impactful project. Considering how specific this model is, I think we should go with the simplest solution and combine an index with a dataset in Transformers (this wouldn't require too much code).", "What about migrating to the [datasets-server](https://github.com/huggingface/datasets-server) search feature instead? Would make more sense from a product perspective ", "I don't think it's a good idea:\r\n- using datasets-server would require to upload the data and to not control the indexing, whereas the current feature is about using a local index that you control\r\n- faiss indexes are vector indexes that are not supported by datasets-server, and they are also very customised. For instance RAG uses DPR embeddings and cosine similarity\r\n- FTS is only done for the first 5GB of data for now in datasets-server\r\n\r\nI think a better option would be to integrate with open source search tools such as docarray.\r\nAnd if we want to make the datasets-server search available in python we can build an integration in docarray and/or in huggingface_hub.", "`llama_index` is another popular tool in this space.\r\n\r\n@lhoestq \r\n> I think a better option would be to integrate with open source search tools such as docarray.\r\nAnd if we want to make the datasets-server search available in python we can build an integration in docarray and/or in huggingface_hub.\r\n\r\nI don't think these integrations would be popular unless we integrate them with the Hub \"UI-wise\" (e.g., through a widget), so they can wait IMO. Also, FAISS supports `fsspec` already with the callback reader/writer, so this doesn't require a specific integration. ", "After discussing it a bit with @lhoestq, do we need to deprecate the search API? While I understand it's imperfect, it looks like this will result in significant work to update it everywhere, so I'd favor keeping it until there's an obviously better alternative; this way we can focus on different things in the meantime.", "FAISS/ES are simple to use (probably the main reason why they are so popular), so creating \"better alternatives\" is not easy - they usually add more complexity (as is the case here, `langchain`, etc.)\r\n\r\nSo, instead of waiting for better alternatives, IMO it makes more sense to wait for the RAG model to be deprecated in Transformers (less than 1,000 cumulated downloads over all checkpoints in the past 30 days) before deprecating this API here.\r\n\r\nIn the meantime, we should make it clear that the vector search API is in maintenance mode (no new features, etc.).\r\n\r\nHow does that sound?" ]

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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6035). All of your documentation changes will be reflected on that endpoint." ]

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[ "Even if a dataset is cached, we still make requests to check whether the cache is up-to-date. [This](https://huggingface.co/docs/datasets/v2.13.1/en/loading#offline) section in the docs explains how to avoid them and directly load the cached version.", "Thanks - that works! However it doesn't resolve the original issue (but I am not sure if it is a WSL problem)", "We use `requests` to make HTTP requests (and `aiohttp` in the streaming mode), so I don't think we can provide much help regarding the socket issue (it probably has something to do with WSL). " ]

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[ "`HfApi` comes from the `huggingface_hub` package. You can use [this](https://huggingface.co/docs/huggingface_hub/v0.16.3/en/package_reference/utilities#huggingface_hub.configure_http_backend) utility to change the `huggingface_hub`'s `Session` proxies (see the example).\r\n\r\nWe plan to implement https://github.com/huggingface/datasets/issues/5080 and make this behavior more consistent eventually.", "> this\r\n\r\nThanks. I will try `huggingface_hub.configure_http_backend` to change session's config.", "@mariosasko are you saying if I do the following:\r\n\r\n```\r\ndef backend_factory() -> requests.Session:\r\n session = requests.Session()\r\n session.proxies = {\r\n \"https\": \"127.0.0.1:8887\",\r\n \"http\": \"127.0.0.1:8887\",\r\n }\r\n session.verify = \"/etc/ssl/certs/ca-certificates.crt\"\r\n return session\r\n\r\n# Set it as the default session factory\r\nconfigure_http_backend(backend_factory=backend_factory)\r\n```\r\n\r\nwhich works nicely with transformer library:\r\n\r\n```\r\ndef download_gpt_2_model():\r\n tokenizer = GPT2Tokenizer.from_pretrained(\r\n \"gpt2\", force_download=True, resume_download=False\r\n )\r\n text = \"Replace me by any text you'd like.\"\r\n encoded_input = tokenizer(text, return_tensors=\"pt\")\r\n print(encoded_input)\r\n\r\n model = GPT2Model.from_pretrained(\r\n \"gpt2\", force_download=True, resume_download=False\r\n )\r\n output = model(**encoded_input)\r\n```\r\n\r\nshould work for datasets library as well ?\r\n\r\nIn my case if I just do:\r\n\r\n```\r\ndef download_sts12_sts_dataset():\r\n dataset = load_dataset(\r\n \"mteb/sts12-sts\",\r\n download_mode=\"force_redownload\",\r\n verification_mode=\"basic_checks\",\r\n revision=\"main\",\r\n )\r\n\r\n```\r\nI am getting:\r\n`ConnectionError: Couldn't reach https://huggingface.co/datasets/mteb/sts12-sts/resolve/main/dataset_infos.json (ConnectTimeout(MaxRetryError(\"HTTPSConnectionPool(host='huggingface.co', port=443): Max retries exceeded with url: /datasets/mteb/sts12-sts/resolve/main/dataset_infos.json (Caused by ConnectTimeoutError(<urllib3.connection.HTTPSConnection object at 0x7f429e87a3a0>, 'Connection to huggingface.co timed out. (connect timeout=100)'))\")))`\r\n\r\nwhich is typical when the proxy server is not defined. Looks like what is set in configure_http_backend(backend_factory=backend_factory) is ignore.\r\n\r\nIf I use env variable instead, it is working \r\n```\r\ndef download_sts12_sts_dataset():\r\n\r\n os.environ[\"https_proxy\"] = \"127.0.0.1:8887\"\r\n os.environ[\"http_proxy\"] = \"127.0.0.1:8887\"\r\n os.environ[\"REQUESTS_CA_BUNDLE\"] = \"/etc/ssl/certs/ca-certificates.crt\"\r\n\r\n dataset = load_dataset(\r\n \"mteb/sts12-sts\",\r\n download_mode=\"force_redownload\",\r\n verification_mode=\"basic_checks\",\r\n revision=\"main\",\r\n )\r\n```\r\n\r\nShould I add something ?\r\n\r\nI am using `huggingface_hub 0.15.1`, `datasets 2.13.0`, `transformers 4.30.2`", "`huggingface_hub.configure_http_backend` works for `transformers` because they only use the `huggingface_hub` lib for downloads. Our download logic is a bit more complex (e.g., we also support downloading non-Hub files), so we are not aligned with them yet. In the meantime, it's best to use the env vars.", "@mariosasko I fully understand that the logic for dataset is different. I see 2 issues with the current implementation of the env variables:\r\n\r\n- having the same https_proxy/http_prox/no_proxy env variables for all tools is not good in some case. For example I have 2 differents proxy server. In 2019 we had discussion with the Tensorflow teams and they recommended to do the following: TFDS_HTTP_PROXY, TFDS_HTTPS_PROXY ...\r\n- with recent version of requests, it is not possible to deactivate TLS interception (verify=false) by using env variable. This is useful to debug things and in some case TLS is not working and you need to ignore verifying the SSL certificate (probably not recommended) \r\n\r\nOne of the best way is to able to pass our requests.Session() directly\r\n```\r\nimport openai\r\nsession = requests.Session()\r\nsession.cert = CERT\r\nsession.verify = False\r\nopenai.requestssession = session\r\n```\r\n\r\nMy 2 cents in this discussion" ]

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[ "Yes, this is intended." ]

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[ "_The documentation is not available anymore as the PR was closed or merged._", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.005855 / 0.011353 (-0.005498) | 0.003556 / 0.011008 (-0.007452) | 0.079430 / 0.038508 (0.040922) | 0.056754 / 0.023109 (0.033645) | 0.311718 / 0.275898 (0.035820) | 0.346731 / 0.323480 (0.023251) | 0.004414 / 0.007986 (-0.003571) | 0.002835 / 0.004328 (-0.001493) | 0.062138 / 0.004250 (0.057888) | 0.044259 / 0.037052 (0.007206) | 0.314681 / 0.258489 (0.056192) | 0.359802 / 0.293841 (0.065961) | 0.026684 / 0.128546 (-0.101862) | 0.008023 / 0.075646 (-0.067623) | 0.260148 / 0.419271 (-0.159123) | 0.043734 / 0.043533 (0.000202) | 0.312081 / 0.255139 (0.056942) | 0.340004 / 0.283200 (0.056805) | 0.019559 / 0.141683 (-0.122124) | 1.488758 / 1.452155 (0.036604) | 1.510828 / 1.492716 (0.018111) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.181376 / 0.018006 (0.163370) | 0.441726 / 0.000490 (0.441236) | 0.001722 / 0.000200 (0.001522) | 0.000066 / 0.000054 (0.000012) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.023760 / 0.037411 (-0.013651) | 0.071847 / 0.014526 (0.057321) | 0.082642 / 0.176557 (-0.093915) | 0.145555 / 0.737135 (-0.591580) | 0.084554 / 0.296338 (-0.211784) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.401688 / 0.215209 (0.186479) | 4.000994 / 2.077655 (1.923339) | 2.047109 / 1.504120 (0.542989) | 1.891874 / 1.541195 (0.350679) | 1.970599 / 1.468490 (0.502109) | 0.500646 / 4.584777 (-4.084131) | 3.006623 / 3.745712 (-0.739089) | 4.248359 / 5.269862 (-1.021503) | 2.613946 / 4.565676 (-1.951730) | 0.057921 / 0.424275 (-0.366354) | 0.006407 / 0.007607 (-0.001200) | 0.470676 / 0.226044 (0.244631) | 4.722280 / 2.268929 (2.453352) | 2.448530 / 55.444624 (-52.996095) | 2.175841 / 6.876477 (-4.700635) | 2.352287 / 2.142072 (0.210214) | 0.589049 / 4.805227 (-4.216179) | 0.125145 / 6.500664 (-6.375519) | 0.060829 / 0.075469 (-0.014640) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.189225 / 1.841788 (-0.652563) | 16.753085 / 8.074308 (8.678777) | 13.086512 / 10.191392 (2.895120) | 0.132371 / 0.680424 (-0.548052) | 0.016933 / 0.534201 (-0.517268) | 0.328258 / 0.579283 (-0.251025) | 0.344074 / 0.434364 (-0.090290) | 0.374042 / 0.540337 (-0.166296) | 0.515307 / 1.386936 (-0.871629) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.005963 / 0.011353 (-0.005390) | 0.003484 / 0.011008 (-0.007525) | 0.062618 / 0.038508 (0.024110) | 0.057217 / 0.023109 (0.034108) | 0.426760 / 0.275898 (0.150862) | 0.464422 / 0.323480 (0.140942) | 0.005276 / 0.007986 (-0.002709) | 0.002872 / 0.004328 (-0.001456) | 0.062636 / 0.004250 (0.058385) | 0.045953 / 0.037052 (0.008900) | 0.433221 / 0.258489 (0.174732) | 0.475087 / 0.293841 (0.181246) | 0.027217 / 0.128546 (-0.101329) | 0.007965 / 0.075646 (-0.067681) | 0.067749 / 0.419271 (-0.351522) | 0.041235 / 0.043533 (-0.002298) | 0.425424 / 0.255139 (0.170285) | 0.453390 / 0.283200 (0.170190) | 0.020217 / 0.141683 (-0.121466) | 1.436354 / 1.452155 (-0.015801) | 1.492372 / 1.492716 (-0.000345) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.226896 / 0.018006 (0.208889) | 0.411935 / 0.000490 (0.411445) | 0.000356 / 0.000200 (0.000156) | 0.000054 / 0.000054 (-0.000000) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.024705 / 0.037411 (-0.012706) | 0.076232 / 0.014526 (0.061706) | 0.086949 / 0.176557 (-0.089608) | 0.141867 / 0.737135 (-0.595269) | 0.088199 / 0.296338 (-0.208140) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.419748 / 0.215209 (0.204539) | 4.198597 / 2.077655 (2.120942) | 2.338477 / 1.504120 (0.834357) | 2.195741 / 1.541195 (0.654547) | 2.278145 / 1.468490 (0.809655) | 0.502365 / 4.584777 (-4.082412) | 2.987773 / 3.745712 (-0.757939) | 2.896526 / 5.269862 (-2.373336) | 1.841610 / 4.565676 (-2.724067) | 0.058032 / 0.424275 (-0.366243) | 0.006470 / 0.007607 (-0.001137) | 0.496969 / 0.226044 (0.270925) | 4.960984 / 2.268929 (2.692056) | 2.648615 / 55.444624 (-52.796009) | 2.286846 / 6.876477 (-4.589631) | 2.320176 / 2.142072 (0.178104) | 0.600550 / 4.805227 (-4.204678) | 0.125652 / 6.500664 (-6.375012) | 0.062177 / 0.075469 (-0.013292) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.293063 / 1.841788 (-0.548725) | 18.294204 / 8.074308 (10.219896) | 13.720502 / 10.191392 (3.529110) | 0.146480 / 0.680424 (-0.533944) | 0.016965 / 0.534201 (-0.517236) | 0.330137 / 0.579283 (-0.249146) | 0.352051 / 0.434364 (-0.082313) | 0.381754 / 0.540337 (-0.158584) | 0.517935 / 1.386936 (-0.869001) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#269fcd31a2e759c65ffd5952ecef13e6a0d92574 \"CML watermark\")\n" ]

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[ "_The documentation is not available anymore as the PR was closed or merged._", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007039 / 0.011353 (-0.004314) | 0.004175 / 0.011008 (-0.006833) | 0.085426 / 0.038508 (0.046918) | 0.079818 / 0.023109 (0.056709) | 0.321924 / 0.275898 (0.046026) | 0.345482 / 0.323480 (0.022002) | 0.005510 / 0.007986 (-0.002475) | 0.003452 / 0.004328 (-0.000877) | 0.065158 / 0.004250 (0.060907) | 0.058843 / 0.037052 (0.021791) | 0.316280 / 0.258489 (0.057791) | 0.351666 / 0.293841 (0.057825) | 0.031190 / 0.128546 (-0.097357) | 0.008500 / 0.075646 (-0.067147) | 0.289595 / 0.419271 (-0.129676) | 0.053798 / 0.043533 (0.010265) | 0.315804 / 0.255139 (0.060665) | 0.334957 / 0.283200 (0.051757) | 0.024350 / 0.141683 (-0.117332) | 1.515753 / 1.452155 (0.063599) | 1.556215 / 1.492716 (0.063499) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.210378 / 0.018006 (0.192372) | 0.469309 / 0.000490 (0.468820) | 0.002890 / 0.000200 (0.002690) | 0.000086 / 0.000054 (0.000031) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.030214 / 0.037411 (-0.007197) | 0.088492 / 0.014526 (0.073966) | 0.098684 / 0.176557 (-0.077873) | 0.156077 / 0.737135 (-0.581058) | 0.098814 / 0.296338 (-0.197525) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.404548 / 0.215209 (0.189339) | 4.026173 / 2.077655 (1.948518) | 2.043216 / 1.504120 (0.539096) | 1.880997 / 1.541195 (0.339802) | 1.975205 / 1.468490 (0.506715) | 0.489395 / 4.584777 (-4.095382) | 3.684097 / 3.745712 (-0.061615) | 5.126934 / 5.269862 (-0.142928) | 3.092153 / 4.565676 (-1.473524) | 0.057668 / 0.424275 (-0.366607) | 0.007372 / 0.007607 (-0.000235) | 0.479647 / 0.226044 (0.253603) | 4.780207 / 2.268929 (2.511278) | 2.533457 / 55.444624 (-52.911168) | 2.182126 / 6.876477 (-4.694351) | 2.431834 / 2.142072 (0.289761) | 0.591760 / 4.805227 (-4.213467) | 0.135450 / 6.500664 (-6.365214) | 0.063218 / 0.075469 (-0.012251) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.262053 / 1.841788 (-0.579734) | 20.246992 / 8.074308 (12.172684) | 14.638222 / 10.191392 (4.446830) | 0.150021 / 0.680424 (-0.530403) | 0.018680 / 0.534201 (-0.515521) | 0.395215 / 0.579283 (-0.184068) | 0.421270 / 0.434364 (-0.013094) | 0.458845 / 0.540337 (-0.081492) | 0.634488 / 1.386936 (-0.752448) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007080 / 0.011353 (-0.004273) | 0.004112 / 0.011008 (-0.006896) | 0.066426 / 0.038508 (0.027918) | 0.090088 / 0.023109 (0.066978) | 0.400191 / 0.275898 (0.124293) | 0.429614 / 0.323480 (0.106134) | 0.005428 / 0.007986 (-0.002558) | 0.003501 / 0.004328 (-0.000827) | 0.065056 / 0.004250 (0.060806) | 0.061643 / 0.037052 (0.024590) | 0.398619 / 0.258489 (0.140130) | 0.445497 / 0.293841 (0.151657) | 0.031703 / 0.128546 (-0.096843) | 0.008708 / 0.075646 (-0.066938) | 0.071561 / 0.419271 (-0.347711) | 0.050684 / 0.043533 (0.007151) | 0.385361 / 0.255139 (0.130222) | 0.409349 / 0.283200 (0.126149) | 0.027388 / 0.141683 (-0.114295) | 1.473021 / 1.452155 (0.020866) | 1.525246 / 1.492716 (0.032529) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.237710 / 0.018006 (0.219704) | 0.468719 / 0.000490 (0.468230) | 0.000385 / 0.000200 (0.000185) | 0.000054 / 0.000054 (-0.000000) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.032539 / 0.037411 (-0.004872) | 0.095324 / 0.014526 (0.080798) | 0.102248 / 0.176557 (-0.074308) | 0.156096 / 0.737135 (-0.581039) | 0.103458 / 0.296338 (-0.192881) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.416226 / 0.215209 (0.201017) | 4.141044 / 2.077655 (2.063389) | 2.143732 / 1.504120 (0.639612) | 2.001020 / 1.541195 (0.459825) | 2.091194 / 1.468490 (0.622704) | 0.489977 / 4.584777 (-4.094800) | 3.579615 / 3.745712 (-0.166097) | 3.438082 / 5.269862 (-1.831780) | 2.069031 / 4.565676 (-2.496645) | 0.056994 / 0.424275 (-0.367281) | 0.007362 / 0.007607 (-0.000245) | 0.493077 / 0.226044 (0.267033) | 4.922622 / 2.268929 (2.653694) | 2.627083 / 55.444624 (-52.817541) | 2.301141 / 6.876477 (-4.575336) | 2.356794 / 2.142072 (0.214722) | 0.583792 / 4.805227 (-4.221436) | 0.133707 / 6.500664 (-6.366958) | 0.062892 / 0.075469 (-0.012577) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.364908 / 1.841788 (-0.476880) | 20.641219 / 8.074308 (12.566911) | 14.848528 / 10.191392 (4.657136) | 0.174207 / 0.680424 (-0.506217) | 0.018206 / 0.534201 (-0.515995) | 0.413742 / 0.579283 (-0.165541) | 0.419940 / 0.434364 (-0.014424) | 0.458543 / 0.540337 (-0.081794) | 0.616518 / 1.386936 (-0.770418) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#18b2202c3e7cdde05920078f01864964556427da \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006875 / 0.011353 (-0.004478) | 0.003489 / 0.011008 (-0.007519) | 0.082077 / 0.038508 (0.043569) | 0.103011 / 0.023109 (0.079902) | 0.370572 / 0.275898 (0.094674) | 0.416400 / 0.323480 (0.092920) | 0.004048 / 0.007986 (-0.003938) | 0.003563 / 0.004328 (-0.000765) | 0.062666 / 0.004250 (0.058416) | 0.063664 / 0.037052 (0.026612) | 0.374206 / 0.258489 (0.115717) | 0.425590 / 0.293841 (0.131749) | 0.028174 / 0.128546 (-0.100373) | 0.007906 / 0.075646 (-0.067741) | 0.266251 / 0.419271 (-0.153020) | 0.045923 / 0.043533 (0.002390) | 0.376746 / 0.255139 (0.121607) | 0.401950 / 0.283200 (0.118750) | 0.024628 / 0.141683 (-0.117054) | 1.441903 / 1.452155 (-0.010252) | 1.537494 / 1.492716 (0.044777) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.214696 / 0.018006 (0.196690) | 0.425626 / 0.000490 (0.425137) | 0.003370 / 0.000200 (0.003170) | 0.000071 / 0.000054 (0.000017) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.023133 / 0.037411 (-0.014279) | 0.072374 / 0.014526 (0.057848) | 0.081255 / 0.176557 (-0.095301) | 0.146960 / 0.737135 (-0.590175) | 0.081748 / 0.296338 (-0.214590) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.390683 / 0.215209 (0.175473) | 3.893166 / 2.077655 (1.815511) | 1.884321 / 1.504120 (0.380201) | 1.701899 / 1.541195 (0.160704) | 1.737839 / 1.468490 (0.269349) | 0.497008 / 4.584777 (-4.087769) | 3.041211 / 3.745712 (-0.704501) | 3.519947 / 5.269862 (-1.749915) | 2.015085 / 4.565676 (-2.550592) | 0.057685 / 0.424275 (-0.366590) | 0.006415 / 0.007607 (-0.001192) | 0.465565 / 0.226044 (0.239520) | 4.635224 / 2.268929 (2.366295) | 2.297941 / 55.444624 (-53.146683) | 1.946670 / 6.876477 (-4.929807) | 2.078527 / 2.142072 (-0.063546) | 0.584101 / 4.805227 (-4.221126) | 0.126488 / 6.500664 (-6.374176) | 0.060819 / 0.075469 (-0.014650) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.223400 / 1.841788 (-0.618388) | 17.960923 / 8.074308 (9.886615) | 13.187683 / 10.191392 (2.996291) | 0.129258 / 0.680424 (-0.551166) | 0.016601 / 0.534201 (-0.517600) | 0.330028 / 0.579283 (-0.249255) | 0.353861 / 0.434364 (-0.080503) | 0.376022 / 0.540337 (-0.164315) | 0.518145 / 1.386936 (-0.868791) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006015 / 0.011353 (-0.005338) | 0.003605 / 0.011008 (-0.007403) | 0.062169 / 0.038508 (0.023661) | 0.056094 / 0.023109 (0.032985) | 0.353085 / 0.275898 (0.077187) | 0.393744 / 0.323480 (0.070265) | 0.004672 / 0.007986 (-0.003313) | 0.002859 / 0.004328 (-0.001469) | 0.062992 / 0.004250 (0.058742) | 0.049767 / 0.037052 (0.012714) | 0.356850 / 0.258489 (0.098361) | 0.403731 / 0.293841 (0.109890) | 0.026664 / 0.128546 (-0.101882) | 0.008026 / 0.075646 (-0.067621) | 0.067944 / 0.419271 (-0.351327) | 0.042133 / 0.043533 (-0.001400) | 0.353865 / 0.255139 (0.098726) | 0.383461 / 0.283200 (0.100261) | 0.021250 / 0.141683 (-0.120433) | 1.428102 / 1.452155 (-0.024053) | 1.481061 / 1.492716 (-0.011655) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.223552 / 0.018006 (0.205546) | 0.402390 / 0.000490 (0.401900) | 0.000721 / 0.000200 (0.000521) | 0.000059 / 0.000054 (0.000005) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.025065 / 0.037411 (-0.012347) | 0.075537 / 0.014526 (0.061011) | 0.083519 / 0.176557 (-0.093037) | 0.137068 / 0.737135 (-0.600068) | 0.084165 / 0.296338 (-0.212173) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.420176 / 0.215209 (0.204967) | 4.206226 / 2.077655 (2.128571) | 2.168089 / 1.504120 (0.663969) | 1.987299 / 1.541195 (0.446104) | 2.029489 / 1.468490 (0.560999) | 0.495822 / 4.584777 (-4.088955) | 3.106580 / 3.745712 (-0.639132) | 3.833215 / 5.269862 (-1.436647) | 2.450450 / 4.565676 (-2.115226) | 0.056979 / 0.424275 (-0.367296) | 0.006514 / 0.007607 (-0.001093) | 0.503646 / 0.226044 (0.277601) | 5.035035 / 2.268929 (2.766106) | 2.608245 / 55.444624 (-52.836379) | 2.245492 / 6.876477 (-4.630985) | 2.262868 / 2.142072 (0.120795) | 0.590736 / 4.805227 (-4.214491) | 0.124637 / 6.500664 (-6.376027) | 0.061442 / 0.075469 (-0.014027) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.316736 / 1.841788 (-0.525052) | 17.948635 / 8.074308 (9.874327) | 13.752442 / 10.191392 (3.561050) | 0.144107 / 0.680424 (-0.536317) | 0.017112 / 0.534201 (-0.517089) | 0.336537 / 0.579283 (-0.242746) | 0.347832 / 0.434364 (-0.086532) | 0.392944 / 0.540337 (-0.147393) | 0.534455 / 1.386936 (-0.852481) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#406b2212263c0d33f267e35b917f410ff6b3bc00 \"CML watermark\")\n" ]

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[ "_The documentation is not available anymore as the PR was closed or merged._", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006665 / 0.011353 (-0.004688) | 0.004376 / 0.011008 (-0.006633) | 0.085529 / 0.038508 (0.047021) | 0.076372 / 0.023109 (0.053263) | 0.310019 / 0.275898 (0.034121) | 0.341404 / 0.323480 (0.017924) | 0.005666 / 0.007986 (-0.002320) | 0.003763 / 0.004328 (-0.000566) | 0.064678 / 0.004250 (0.060427) | 0.059283 / 0.037052 (0.022231) | 0.316194 / 0.258489 (0.057704) | 0.349397 / 0.293841 (0.055557) | 0.031199 / 0.128546 (-0.097347) | 0.008724 / 0.075646 (-0.066923) | 0.300236 / 0.419271 (-0.119035) | 0.068872 / 0.043533 (0.025339) | 0.308521 / 0.255139 (0.053382) | 0.331292 / 0.283200 (0.048092) | 0.028236 / 0.141683 (-0.113447) | 1.501365 / 1.452155 (0.049211) | 1.554334 / 1.492716 (0.061618) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.238291 / 0.018006 (0.220285) | 0.565069 / 0.000490 (0.564580) | 0.001626 / 0.000200 (0.001426) | 0.000070 / 0.000054 (0.000015) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.029777 / 0.037411 (-0.007634) | 0.082873 / 0.014526 (0.068347) | 0.099619 / 0.176557 (-0.076937) | 0.156572 / 0.737135 (-0.580563) | 0.099887 / 0.296338 (-0.196452) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.401017 / 0.215209 (0.185808) | 3.827192 / 2.077655 (1.749537) | 1.861554 / 1.504120 (0.357434) | 1.699869 / 1.541195 (0.158674) | 1.720043 / 1.468490 (0.251553) | 0.486757 / 4.584777 (-4.098020) | 3.638125 / 3.745712 (-0.107587) | 5.844959 / 5.269862 (0.575097) | 3.454901 / 4.565676 (-1.110775) | 0.057650 / 0.424275 (-0.366625) | 0.007341 / 0.007607 (-0.000266) | 0.462698 / 0.226044 (0.236654) | 4.633472 / 2.268929 (2.364544) | 2.287607 / 55.444624 (-53.157017) | 2.057318 / 6.876477 (-4.819159) | 2.203657 / 2.142072 (0.061584) | 0.598136 / 4.805227 (-4.207091) | 0.134012 / 6.500664 (-6.366653) | 0.060824 / 0.075469 (-0.014645) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.277752 / 1.841788 (-0.564036) | 20.013398 / 8.074308 (11.939089) | 14.372993 / 10.191392 (4.181601) | 0.169991 / 0.680424 (-0.510433) | 0.018344 / 0.534201 (-0.515857) | 0.396985 / 0.579283 (-0.182299) | 0.416289 / 0.434364 (-0.018075) | 0.458658 / 0.540337 (-0.081680) | 0.692980 / 1.386936 (-0.693956) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006689 / 0.011353 (-0.004664) | 0.004393 / 0.011008 (-0.006615) | 0.064069 / 0.038508 (0.025561) | 0.080717 / 0.023109 (0.057607) | 0.370090 / 0.275898 (0.094191) | 0.400432 / 0.323480 (0.076952) | 0.005613 / 0.007986 (-0.002372) | 0.003641 / 0.004328 (-0.000687) | 0.064771 / 0.004250 (0.060520) | 0.057555 / 0.037052 (0.020502) | 0.392156 / 0.258489 (0.133667) | 0.409842 / 0.293841 (0.116001) | 0.031500 / 0.128546 (-0.097047) | 0.008786 / 0.075646 (-0.066860) | 0.070342 / 0.419271 (-0.348929) | 0.048646 / 0.043533 (0.005113) | 0.360914 / 0.255139 (0.105775) | 0.387626 / 0.283200 (0.104426) | 0.022787 / 0.141683 (-0.118896) | 1.508915 / 1.452155 (0.056761) | 1.539719 / 1.492716 (0.047002) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.257985 / 0.018006 (0.239979) | 0.550990 / 0.000490 (0.550501) | 0.000407 / 0.000200 (0.000207) | 0.000057 / 0.000054 (0.000003) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.030183 / 0.037411 (-0.007228) | 0.086882 / 0.014526 (0.072356) | 0.102382 / 0.176557 (-0.074175) | 0.154745 / 0.737135 (-0.582390) | 0.104008 / 0.296338 (-0.192331) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.426284 / 0.215209 (0.211075) | 4.240812 / 2.077655 (2.163158) | 2.261240 / 1.504120 (0.757120) | 2.085905 / 1.541195 (0.544710) | 2.160374 / 1.468490 (0.691883) | 0.481126 / 4.584777 (-4.103651) | 3.516234 / 3.745712 (-0.229478) | 3.325322 / 5.269862 (-1.944539) | 2.043307 / 4.565676 (-2.522369) | 0.056663 / 0.424275 (-0.367612) | 0.007786 / 0.007607 (0.000179) | 0.497614 / 0.226044 (0.271570) | 4.974529 / 2.268929 (2.705600) | 2.700018 / 55.444624 (-52.744606) | 2.393778 / 6.876477 (-4.482699) | 2.628202 / 2.142072 (0.486130) | 0.594316 / 4.805227 (-4.210911) | 0.147092 / 6.500664 (-6.353572) | 0.062207 / 0.075469 (-0.013262) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.315676 / 1.841788 (-0.526112) | 20.749251 / 8.074308 (12.674943) | 14.371553 / 10.191392 (4.180160) | 0.170249 / 0.680424 (-0.510175) | 0.018478 / 0.534201 (-0.515722) | 0.395710 / 0.579283 (-0.183573) | 0.409706 / 0.434364 (-0.024658) | 0.463454 / 0.540337 (-0.076884) | 0.615657 / 1.386936 (-0.771279) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#c5a752d8e8ca0a6ed118b024ba03c1b4a2881177 \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007224 / 0.011353 (-0.004129) | 0.004506 / 0.011008 (-0.006503) | 0.096729 / 0.038508 (0.058221) | 0.082394 / 0.023109 (0.059284) | 0.390954 / 0.275898 (0.115056) | 0.416647 / 0.323480 (0.093167) | 0.005894 / 0.007986 (-0.002092) | 0.003756 / 0.004328 (-0.000572) | 0.075800 / 0.004250 (0.071549) | 0.062683 / 0.037052 (0.025631) | 0.398959 / 0.258489 (0.140470) | 0.436624 / 0.293841 (0.142783) | 0.034650 / 0.128546 (-0.093896) | 0.009655 / 0.075646 (-0.065991) | 0.315761 / 0.419271 (-0.103511) | 0.060957 / 0.043533 (0.017424) | 0.385649 / 0.255139 (0.130510) | 0.394022 / 0.283200 (0.110822) | 0.024601 / 0.141683 (-0.117082) | 1.729586 / 1.452155 (0.277431) | 1.724153 / 1.492716 (0.231437) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.207070 / 0.018006 (0.189063) | 0.466502 / 0.000490 (0.466012) | 0.010739 / 0.000200 (0.010540) | 0.000214 / 0.000054 (0.000160) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.031633 / 0.037411 (-0.005779) | 0.095345 / 0.014526 (0.080819) | 0.105399 / 0.176557 (-0.071157) | 0.174173 / 0.737135 (-0.562962) | 0.104207 / 0.296338 (-0.192132) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.435312 / 0.215209 (0.220103) | 4.265600 / 2.077655 (2.187946) | 2.056500 / 1.504120 (0.552380) | 1.848023 / 1.541195 (0.306828) | 1.946156 / 1.468490 (0.477666) | 0.557788 / 4.584777 (-4.026989) | 4.070289 / 3.745712 (0.324577) | 3.608027 / 5.269862 (-1.661835) | 2.214556 / 4.565676 (-2.351121) | 0.062623 / 0.424275 (-0.361652) | 0.008083 / 0.007607 (0.000476) | 0.491782 / 0.226044 (0.265738) | 4.989963 / 2.268929 (2.721035) | 2.575867 / 55.444624 (-52.868757) | 2.208045 / 6.876477 (-4.668431) | 2.364184 / 2.142072 (0.222112) | 0.633925 / 4.805227 (-4.171302) | 0.144323 / 6.500664 (-6.356341) | 0.067505 / 0.075469 (-0.007965) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.467219 / 1.841788 (-0.374569) | 22.334967 / 8.074308 (14.260659) | 15.715747 / 10.191392 (5.524355) | 0.175443 / 0.680424 (-0.504980) | 0.026165 / 0.534201 (-0.508036) | 0.490675 / 0.579283 (-0.088608) | 0.509211 / 0.434364 (0.074847) | 0.586303 / 0.540337 (0.045965) | 0.785052 / 1.386936 (-0.601884) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007893 / 0.011353 (-0.003460) | 0.004577 / 0.011008 (-0.006431) | 0.075781 / 0.038508 (0.037273) | 0.095492 / 0.023109 (0.072382) | 0.433259 / 0.275898 (0.157361) | 0.469386 / 0.323480 (0.145906) | 0.006317 / 0.007986 (-0.001669) | 0.003708 / 0.004328 (-0.000621) | 0.074417 / 0.004250 (0.070167) | 0.068605 / 0.037052 (0.031552) | 0.448701 / 0.258489 (0.190212) | 0.469131 / 0.293841 (0.175290) | 0.036647 / 0.128546 (-0.091899) | 0.010077 / 0.075646 (-0.065570) | 0.082457 / 0.419271 (-0.336815) | 0.063255 / 0.043533 (0.019722) | 0.428144 / 0.255139 (0.173005) | 0.451872 / 0.283200 (0.168672) | 0.033953 / 0.141683 (-0.107730) | 1.781752 / 1.452155 (0.329597) | 1.869014 / 1.492716 (0.376297) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.223596 / 0.018006 (0.205590) | 0.470307 / 0.000490 (0.469818) | 0.005059 / 0.000200 (0.004859) | 0.000104 / 0.000054 (0.000049) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.038804 / 0.037411 (0.001393) | 0.117879 / 0.014526 (0.103353) | 0.140701 / 0.176557 (-0.035855) | 0.194672 / 0.737135 (-0.542463) | 0.132806 / 0.296338 (-0.163533) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.510109 / 0.215209 (0.294900) | 4.729457 / 2.077655 (2.651803) | 2.512113 / 1.504120 (1.007993) | 2.302553 / 1.541195 (0.761358) | 2.420462 / 1.468490 (0.951972) | 0.531682 / 4.584777 (-4.053095) | 4.061208 / 3.745712 (0.315496) | 3.588542 / 5.269862 (-1.681320) | 2.203187 / 4.565676 (-2.362489) | 0.065791 / 0.424275 (-0.358484) | 0.008839 / 0.007607 (0.001232) | 0.562041 / 0.226044 (0.335997) | 5.702340 / 2.268929 (3.433412) | 3.127609 / 55.444624 (-52.317015) | 2.823060 / 6.876477 (-4.053417) | 2.898675 / 2.142072 (0.756603) | 0.659589 / 4.805227 (-4.145638) | 0.148798 / 6.500664 (-6.351866) | 0.070787 / 0.075469 (-0.004682) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.478317 / 1.841788 (-0.363471) | 21.995400 / 8.074308 (13.921092) | 16.770729 / 10.191392 (6.579337) | 0.226333 / 0.680424 (-0.454091) | 0.021835 / 0.534201 (-0.512366) | 0.460373 / 0.579283 (-0.118910) | 0.479494 / 0.434364 (0.045130) | 0.529470 / 0.540337 (-0.010868) | 0.718066 / 1.386936 (-0.668870) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#9a717b8eb80b0e50b25818127f79a35e0866fb14 \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007824 / 0.011353 (-0.003529) | 0.004601 / 0.011008 (-0.006407) | 0.100025 / 0.038508 (0.061517) | 0.096046 / 0.023109 (0.072936) | 0.376226 / 0.275898 (0.100328) | 0.410905 / 0.323480 (0.087425) | 0.006048 / 0.007986 (-0.001938) | 0.003817 / 0.004328 (-0.000511) | 0.076624 / 0.004250 (0.072374) | 0.066390 / 0.037052 (0.029338) | 0.380098 / 0.258489 (0.121609) | 0.413603 / 0.293841 (0.119762) | 0.036546 / 0.128546 (-0.092001) | 0.009881 / 0.075646 (-0.065765) | 0.344338 / 0.419271 (-0.074934) | 0.061882 / 0.043533 (0.018350) | 0.368568 / 0.255139 (0.113429) | 0.397133 / 0.283200 (0.113934) | 0.027255 / 0.141683 (-0.114428) | 1.795099 / 1.452155 (0.342945) | 1.852443 / 1.492716 (0.359727) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.247436 / 0.018006 (0.229430) | 0.494119 / 0.000490 (0.493629) | 0.004359 / 0.000200 (0.004159) | 0.000089 / 0.000054 (0.000035) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.034765 / 0.037411 (-0.002647) | 0.104541 / 0.014526 (0.090015) | 0.113898 / 0.176557 (-0.062659) | 0.183634 / 0.737135 (-0.553501) | 0.116423 / 0.296338 (-0.179916) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.458747 / 0.215209 (0.243538) | 4.555740 / 2.077655 (2.478085) | 2.217240 / 1.504120 (0.713121) | 2.039879 / 1.541195 (0.498684) | 2.088581 / 1.468490 (0.620091) | 0.588063 / 4.584777 (-3.996714) | 4.238226 / 3.745712 (0.492514) | 4.768060 / 5.269862 (-0.501802) | 2.857117 / 4.565676 (-1.708560) | 0.068742 / 0.424275 (-0.355533) | 0.008667 / 0.007607 (0.001059) | 0.549294 / 0.226044 (0.323249) | 5.464635 / 2.268929 (3.195706) | 2.744435 / 55.444624 (-52.700189) | 2.347660 / 6.876477 (-4.528816) | 2.616816 / 2.142072 (0.474743) | 0.703701 / 4.805227 (-4.101526) | 0.159749 / 6.500664 (-6.340915) | 0.071990 / 0.075469 (-0.003479) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.486599 / 1.841788 (-0.355188) | 22.745438 / 8.074308 (14.671130) | 16.822332 / 10.191392 (6.630940) | 0.184730 / 0.680424 (-0.495694) | 0.021267 / 0.534201 (-0.512934) | 0.467108 / 0.579283 (-0.112176) | 0.472674 / 0.434364 (0.038311) | 0.548094 / 0.540337 (0.007756) | 0.735885 / 1.386936 (-0.651051) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007746 / 0.011353 (-0.003607) | 0.004585 / 0.011008 (-0.006423) | 0.076943 / 0.038508 (0.038435) | 0.087473 / 0.023109 (0.064363) | 0.480099 / 0.275898 (0.204201) | 0.495271 / 0.323480 (0.171791) | 0.006348 / 0.007986 (-0.001638) | 0.003902 / 0.004328 (-0.000426) | 0.077586 / 0.004250 (0.073335) | 0.066467 / 0.037052 (0.029415) | 0.468741 / 0.258489 (0.210252) | 0.506778 / 0.293841 (0.212937) | 0.036877 / 0.128546 (-0.091669) | 0.010102 / 0.075646 (-0.065545) | 0.084419 / 0.419271 (-0.334852) | 0.058721 / 0.043533 (0.015188) | 0.453633 / 0.255139 (0.198494) | 0.481171 / 0.283200 (0.197971) | 0.028716 / 0.141683 (-0.112967) | 1.853048 / 1.452155 (0.400893) | 1.885847 / 1.492716 (0.393130) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.192136 / 0.018006 (0.174130) | 0.484481 / 0.000490 (0.483991) | 0.002951 / 0.000200 (0.002751) | 0.000098 / 0.000054 (0.000044) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.037949 / 0.037411 (0.000538) | 0.108364 / 0.014526 (0.093838) | 0.119542 / 0.176557 (-0.057014) | 0.188542 / 0.737135 (-0.548593) | 0.122011 / 0.296338 (-0.174327) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.483135 / 0.215209 (0.267926) | 4.849715 / 2.077655 (2.772060) | 2.497736 / 1.504120 (0.993616) | 2.314243 / 1.541195 (0.773048) | 2.412739 / 1.468490 (0.944249) | 0.564137 / 4.584777 (-4.020639) | 4.242273 / 3.745712 (0.496561) | 6.337843 / 5.269862 (1.067982) | 3.923250 / 4.565676 (-0.642426) | 0.066464 / 0.424275 (-0.357811) | 0.009217 / 0.007607 (0.001610) | 0.575667 / 0.226044 (0.349623) | 5.746187 / 2.268929 (3.477258) | 3.069655 / 55.444624 (-52.374969) | 2.674798 / 6.876477 (-4.201679) | 2.956535 / 2.142072 (0.814463) | 0.701043 / 4.805227 (-4.104185) | 0.157241 / 6.500664 (-6.343423) | 0.073175 / 0.075469 (-0.002294) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.609943 / 1.841788 (-0.231844) | 23.478594 / 8.074308 (15.404286) | 17.454437 / 10.191392 (7.263045) | 0.186422 / 0.680424 (-0.494002) | 0.021703 / 0.534201 (-0.512498) | 0.471704 / 0.579283 (-0.107579) | 0.480553 / 0.434364 (0.046189) | 0.552881 / 0.540337 (0.012544) | 0.722515 / 1.386936 (-0.664421) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#84645f80049cd00d9e0d4908faf3c3203fdcf21d \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007542 / 0.011353 (-0.003811) | 0.004692 / 0.011008 (-0.006316) | 0.099155 / 0.038508 (0.060647) | 0.089365 / 0.023109 (0.066256) | 0.370870 / 0.275898 (0.094972) | 0.422152 / 0.323480 (0.098673) | 0.006223 / 0.007986 (-0.001763) | 0.003852 / 0.004328 (-0.000476) | 0.075438 / 0.004250 (0.071188) | 0.065973 / 0.037052 (0.028921) | 0.381513 / 0.258489 (0.123024) | 0.416196 / 0.293841 (0.122355) | 0.035483 / 0.128546 (-0.093063) | 0.009884 / 0.075646 (-0.065762) | 0.341290 / 0.419271 (-0.077982) | 0.060546 / 0.043533 (0.017014) | 0.365101 / 0.255139 (0.109962) | 0.391058 / 0.283200 (0.107859) | 0.026325 / 0.141683 (-0.115358) | 1.815168 / 1.452155 (0.363013) | 1.834711 / 1.492716 (0.341994) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.222177 / 0.018006 (0.204171) | 0.501151 / 0.000490 (0.500662) | 0.010202 / 0.000200 (0.010002) | 0.000102 / 0.000054 (0.000048) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.034043 / 0.037411 (-0.003368) | 0.097884 / 0.014526 (0.083358) | 0.114022 / 0.176557 (-0.062534) | 0.186200 / 0.737135 (-0.550935) | 0.115555 / 0.296338 (-0.180783) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.485857 / 0.215209 (0.270648) | 4.959263 / 2.077655 (2.881608) | 2.501085 / 1.504120 (0.996965) | 2.234660 / 1.541195 (0.693465) | 2.238585 / 1.468490 (0.770095) | 0.645431 / 4.584777 (-3.939345) | 4.434311 / 3.745712 (0.688599) | 4.771491 / 5.269862 (-0.498371) | 2.778963 / 4.565676 (-1.786714) | 0.075615 / 0.424275 (-0.348660) | 0.009502 / 0.007607 (0.001895) | 0.546539 / 0.226044 (0.320495) | 5.464242 / 2.268929 (3.195314) | 2.894101 / 55.444624 (-52.550524) | 2.513761 / 6.876477 (-4.362715) | 2.719843 / 2.142072 (0.577770) | 0.678828 / 4.805227 (-4.126399) | 0.157839 / 6.500664 (-6.342825) | 0.071305 / 0.075469 (-0.004164) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.496879 / 1.841788 (-0.344909) | 22.214452 / 8.074308 (14.140144) | 17.707541 / 10.191392 (7.516149) | 0.197008 / 0.680424 (-0.483416) | 0.024883 / 0.534201 (-0.509318) | 0.493611 / 0.579283 (-0.085672) | 0.500677 / 0.434364 (0.066313) | 0.569381 / 0.540337 (0.029044) | 0.773950 / 1.386936 (-0.612986) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007337 / 0.011353 (-0.004015) | 0.004572 / 0.011008 (-0.006436) | 0.091123 / 0.038508 (0.052615) | 0.079762 / 0.023109 (0.056652) | 0.450527 / 0.275898 (0.174629) | 0.525097 / 0.323480 (0.201617) | 0.005873 / 0.007986 (-0.002112) | 0.003797 / 0.004328 (-0.000532) | 0.076259 / 0.004250 (0.072009) | 0.062745 / 0.037052 (0.025692) | 0.465553 / 0.258489 (0.207064) | 0.546026 / 0.293841 (0.252186) | 0.035638 / 0.128546 (-0.092909) | 0.010086 / 0.075646 (-0.065560) | 0.109269 / 0.419271 (-0.310002) | 0.056765 / 0.043533 (0.013233) | 0.440887 / 0.255139 (0.185748) | 0.513325 / 0.283200 (0.230125) | 0.027206 / 0.141683 (-0.114476) | 1.863564 / 1.452155 (0.411409) | 1.918206 / 1.492716 (0.425490) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.266479 / 0.018006 (0.248473) | 0.487971 / 0.000490 (0.487481) | 0.012246 / 0.000200 (0.012046) | 0.000119 / 0.000054 (0.000065) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.035281 / 0.037411 (-0.002130) | 0.102991 / 0.014526 (0.088465) | 0.114638 / 0.176557 (-0.061919) | 0.184117 / 0.737135 (-0.553018) | 0.117943 / 0.296338 (-0.178396) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.497897 / 0.215209 (0.282688) | 4.973806 / 2.077655 (2.896151) | 2.596146 / 1.504120 (1.092026) | 2.419694 / 1.541195 (0.878499) | 2.525784 / 1.468490 (1.057294) | 0.568021 / 4.584777 (-4.016756) | 4.296431 / 3.745712 (0.550719) | 3.690682 / 5.269862 (-1.579179) | 2.345965 / 4.565676 (-2.219712) | 0.066859 / 0.424275 (-0.357416) | 0.009093 / 0.007607 (0.001486) | 0.582616 / 0.226044 (0.356571) | 5.826528 / 2.268929 (3.557600) | 3.253222 / 55.444624 (-52.191403) | 2.798447 / 6.876477 (-4.078030) | 3.054609 / 2.142072 (0.912537) | 0.678816 / 4.805227 (-4.126411) | 0.157966 / 6.500664 (-6.342698) | 0.073797 / 0.075469 (-0.001672) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.599480 / 1.841788 (-0.242308) | 23.249738 / 8.074308 (15.175430) | 16.965406 / 10.191392 (6.774014) | 0.171390 / 0.680424 (-0.509034) | 0.021810 / 0.534201 (-0.512391) | 0.483339 / 0.579283 (-0.095944) | 0.496615 / 0.434364 (0.062251) | 0.583786 / 0.540337 (0.043448) | 0.741699 / 1.386936 (-0.645237) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#7935cd2e564f5d1c66ed1acf731703724ba7a287 \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006054 / 0.011353 (-0.005299) | 0.003706 / 0.011008 (-0.007302) | 0.080060 / 0.038508 (0.041552) | 0.061479 / 0.023109 (0.038370) | 0.327981 / 0.275898 (0.052083) | 0.356930 / 0.323480 (0.033450) | 0.004671 / 0.007986 (-0.003315) | 0.002901 / 0.004328 (-0.001428) | 0.062425 / 0.004250 (0.058174) | 0.046310 / 0.037052 (0.009258) | 0.323657 / 0.258489 (0.065168) | 0.370130 / 0.293841 (0.076289) | 0.027151 / 0.128546 (-0.101395) | 0.007850 / 0.075646 (-0.067797) | 0.262300 / 0.419271 (-0.156971) | 0.045456 / 0.043533 (0.001923) | 0.325569 / 0.255139 (0.070430) | 0.352962 / 0.283200 (0.069762) | 0.020156 / 0.141683 (-0.121527) | 1.429404 / 1.452155 (-0.022750) | 1.615032 / 1.492716 (0.122316) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.187309 / 0.018006 (0.169303) | 0.428848 / 0.000490 (0.428358) | 0.003599 / 0.000200 (0.003399) | 0.000069 / 0.000054 (0.000015) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.023260 / 0.037411 (-0.014151) | 0.072467 / 0.014526 (0.057941) | 0.082398 / 0.176557 (-0.094159) | 0.142573 / 0.737135 (-0.594562) | 0.082570 / 0.296338 (-0.213768) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.426503 / 0.215209 (0.211294) | 4.267875 / 2.077655 (2.190220) | 2.189762 / 1.504120 (0.685642) | 2.027992 / 1.541195 (0.486798) | 2.053211 / 1.468490 (0.584721) | 0.503850 / 4.584777 (-4.080927) | 3.086444 / 3.745712 (-0.659268) | 3.319492 / 5.269862 (-1.950370) | 2.070714 / 4.565676 (-2.494962) | 0.057591 / 0.424275 (-0.366684) | 0.006407 / 0.007607 (-0.001200) | 0.501145 / 0.226044 (0.275100) | 5.017753 / 2.268929 (2.748825) | 2.643145 / 55.444624 (-52.801479) | 2.327440 / 6.876477 (-4.549037) | 2.460250 / 2.142072 (0.318178) | 0.589397 / 4.805227 (-4.215830) | 0.124948 / 6.500664 (-6.375716) | 0.060450 / 0.075469 (-0.015020) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.279870 / 1.841788 (-0.561918) | 18.115908 / 8.074308 (10.041600) | 13.570032 / 10.191392 (3.378640) | 0.132981 / 0.680424 (-0.547442) | 0.016942 / 0.534201 (-0.517259) | 0.333591 / 0.579283 (-0.245692) | 0.358844 / 0.434364 (-0.075520) | 0.395748 / 0.540337 (-0.144590) | 0.546213 / 1.386936 (-0.840723) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006062 / 0.011353 (-0.005291) | 0.003673 / 0.011008 (-0.007336) | 0.064726 / 0.038508 (0.026218) | 0.061854 / 0.023109 (0.038745) | 0.385343 / 0.275898 (0.109445) | 0.441284 / 0.323480 (0.117805) | 0.004830 / 0.007986 (-0.003156) | 0.002909 / 0.004328 (-0.001420) | 0.063874 / 0.004250 (0.059624) | 0.049331 / 0.037052 (0.012278) | 0.418484 / 0.258489 (0.159995) | 0.451397 / 0.293841 (0.157556) | 0.027665 / 0.128546 (-0.100881) | 0.008088 / 0.075646 (-0.067558) | 0.069625 / 0.419271 (-0.349646) | 0.043437 / 0.043533 (-0.000095) | 0.359789 / 0.255139 (0.104650) | 0.430206 / 0.283200 (0.147007) | 0.022308 / 0.141683 (-0.119375) | 1.461030 / 1.452155 (0.008875) | 1.513683 / 1.492716 (0.020966) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.230958 / 0.018006 (0.212952) | 0.417553 / 0.000490 (0.417063) | 0.000802 / 0.000200 (0.000602) | 0.000066 / 0.000054 (0.000011) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.025421 / 0.037411 (-0.011991) | 0.077156 / 0.014526 (0.062630) | 0.087533 / 0.176557 (-0.089024) | 0.138048 / 0.737135 (-0.599087) | 0.089358 / 0.296338 (-0.206981) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.439172 / 0.215209 (0.223963) | 4.409509 / 2.077655 (2.331854) | 2.491270 / 1.504120 (0.987150) | 2.308446 / 1.541195 (0.767252) | 2.378440 / 1.468490 (0.909950) | 0.499834 / 4.584777 (-4.084943) | 3.083168 / 3.745712 (-0.662544) | 2.867543 / 5.269862 (-2.402318) | 1.876354 / 4.565676 (-2.689323) | 0.057092 / 0.424275 (-0.367183) | 0.006955 / 0.007607 (-0.000653) | 0.513799 / 0.226044 (0.287754) | 5.126660 / 2.268929 (2.857731) | 2.917348 / 55.444624 (-52.527277) | 2.508035 / 6.876477 (-4.368441) | 2.698089 / 2.142072 (0.556016) | 0.586828 / 4.805227 (-4.218399) | 0.124740 / 6.500664 (-6.375924) | 0.062276 / 0.075469 (-0.013193) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.291624 / 1.841788 (-0.550164) | 18.199968 / 8.074308 (10.125660) | 13.888139 / 10.191392 (3.696747) | 0.162955 / 0.680424 (-0.517469) | 0.017343 / 0.534201 (-0.516858) | 0.334683 / 0.579283 (-0.244600) | 0.352708 / 0.434364 (-0.081656) | 0.400629 / 0.540337 (-0.139708) | 0.539497 / 1.386936 (-0.847439) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#e7976db7fe22c6b93a869488d07b8137ea6a0db4 \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007500 / 0.011353 (-0.003853) | 0.004498 / 0.011008 (-0.006510) | 0.100239 / 0.038508 (0.061731) | 0.083424 / 0.023109 (0.060315) | 0.366664 / 0.275898 (0.090766) | 0.406641 / 0.323480 (0.083161) | 0.004577 / 0.007986 (-0.003409) | 0.004809 / 0.004328 (0.000480) | 0.076898 / 0.004250 (0.072647) | 0.064021 / 0.037052 (0.026969) | 0.375836 / 0.258489 (0.117347) | 0.413008 / 0.293841 (0.119167) | 0.036010 / 0.128546 (-0.092537) | 0.009655 / 0.075646 (-0.065991) | 0.342595 / 0.419271 (-0.076677) | 0.061846 / 0.043533 (0.018313) | 0.376543 / 0.255139 (0.121404) | 0.395858 / 0.283200 (0.112659) | 0.026792 / 0.141683 (-0.114891) | 1.775569 / 1.452155 (0.323414) | 1.865077 / 1.492716 (0.372360) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.221521 / 0.018006 (0.203514) | 0.474604 / 0.000490 (0.474114) | 0.004354 / 0.000200 (0.004154) | 0.000090 / 0.000054 (0.000035) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.032947 / 0.037411 (-0.004464) | 0.100454 / 0.014526 (0.085928) | 0.111955 / 0.176557 (-0.064602) | 0.179752 / 0.737135 (-0.557383) | 0.114282 / 0.296338 (-0.182056) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.458261 / 0.215209 (0.243052) | 4.563536 / 2.077655 (2.485881) | 2.231928 / 1.504120 (0.727808) | 2.036751 / 1.541195 (0.495556) | 2.170413 / 1.468490 (0.701923) | 0.570825 / 4.584777 (-4.013952) | 4.505762 / 3.745712 (0.760050) | 5.033461 / 5.269862 (-0.236401) | 2.704989 / 4.565676 (-1.860687) | 0.067011 / 0.424275 (-0.357264) | 0.008568 / 0.007607 (0.000961) | 0.545151 / 0.226044 (0.319106) | 5.438984 / 2.268929 (3.170055) | 2.771818 / 55.444624 (-52.672806) | 2.393082 / 6.876477 (-4.483395) | 2.467173 / 2.142072 (0.325101) | 0.678849 / 4.805227 (-4.126379) | 0.160480 / 6.500664 (-6.340184) | 0.073681 / 0.075469 (-0.001788) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.532272 / 1.841788 (-0.309516) | 22.548741 / 8.074308 (14.474433) | 17.091044 / 10.191392 (6.899652) | 0.172100 / 0.680424 (-0.508324) | 0.022220 / 0.534201 (-0.511981) | 0.467871 / 0.579283 (-0.111412) | 0.491135 / 0.434364 (0.056771) | 0.548433 / 0.540337 (0.008096) | 0.733340 / 1.386936 (-0.653596) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007593 / 0.011353 (-0.003760) | 0.004656 / 0.011008 (-0.006352) | 0.076940 / 0.038508 (0.038431) | 0.085183 / 0.023109 (0.062073) | 0.447178 / 0.275898 (0.171280) | 0.469545 / 0.323480 (0.146065) | 0.006023 / 0.007986 (-0.001962) | 0.003808 / 0.004328 (-0.000520) | 0.076767 / 0.004250 (0.072517) | 0.065713 / 0.037052 (0.028661) | 0.445573 / 0.258489 (0.187084) | 0.481689 / 0.293841 (0.187848) | 0.036893 / 0.128546 (-0.091654) | 0.009976 / 0.075646 (-0.065670) | 0.084443 / 0.419271 (-0.334829) | 0.058829 / 0.043533 (0.015297) | 0.429291 / 0.255139 (0.174152) | 0.454016 / 0.283200 (0.170816) | 0.027289 / 0.141683 (-0.114394) | 1.806786 / 1.452155 (0.354632) | 1.887680 / 1.492716 (0.394964) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.241012 / 0.018006 (0.223006) | 0.470629 / 0.000490 (0.470139) | 0.003213 / 0.000200 (0.003013) | 0.000107 / 0.000054 (0.000052) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.036896 / 0.037411 (-0.000515) | 0.106932 / 0.014526 (0.092406) | 0.120333 / 0.176557 (-0.056223) | 0.186271 / 0.737135 (-0.550865) | 0.121581 / 0.296338 (-0.174758) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.507782 / 0.215209 (0.292573) | 5.062932 / 2.077655 (2.985278) | 2.689539 / 1.504120 (1.185419) | 2.482978 / 1.541195 (0.941784) | 2.561320 / 1.468490 (1.092830) | 0.570664 / 4.584777 (-4.014113) | 4.346051 / 3.745712 (0.600339) | 6.479374 / 5.269862 (1.209513) | 4.096483 / 4.565676 (-0.469194) | 0.067564 / 0.424275 (-0.356711) | 0.009147 / 0.007607 (0.001540) | 0.596059 / 0.226044 (0.370015) | 5.963223 / 2.268929 (3.694295) | 3.201039 / 55.444624 (-52.243585) | 2.816581 / 6.876477 (-4.059896) | 3.047821 / 2.142072 (0.905748) | 0.687749 / 4.805227 (-4.117478) | 0.158174 / 6.500664 (-6.342490) | 0.073329 / 0.075469 (-0.002140) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.601346 / 1.841788 (-0.240441) | 23.712210 / 8.074308 (15.637902) | 16.567272 / 10.191392 (6.375880) | 0.224745 / 0.680424 (-0.455679) | 0.021662 / 0.534201 (-0.512539) | 0.471427 / 0.579283 (-0.107856) | 0.498751 / 0.434364 (0.064387) | 0.572047 / 0.540337 (0.031710) | 0.821868 / 1.386936 (-0.565068) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#34d0c9027c750adc89f3d04a6bf2e9cb95915da4 \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006371 / 0.011353 (-0.004981) | 0.003749 / 0.011008 (-0.007259) | 0.084155 / 0.038508 (0.045647) | 0.072450 / 0.023109 (0.049340) | 0.308002 / 0.275898 (0.032104) | 0.340471 / 0.323480 (0.016991) | 0.005054 / 0.007986 (-0.002931) | 0.003176 / 0.004328 (-0.001152) | 0.064867 / 0.004250 (0.060616) | 0.054305 / 0.037052 (0.017252) | 0.321047 / 0.258489 (0.062558) | 0.345999 / 0.293841 (0.052158) | 0.030507 / 0.128546 (-0.098039) | 0.008299 / 0.075646 (-0.067347) | 0.287682 / 0.419271 (-0.131590) | 0.052048 / 0.043533 (0.008515) | 0.308322 / 0.255139 (0.053183) | 0.333220 / 0.283200 (0.050020) | 0.022698 / 0.141683 (-0.118985) | 1.474033 / 1.452155 (0.021879) | 1.544790 / 1.492716 (0.052074) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.200612 / 0.018006 (0.182606) | 0.450934 / 0.000490 (0.450445) | 0.005383 / 0.000200 (0.005183) | 0.000200 / 0.000054 (0.000145) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.027759 / 0.037411 (-0.009652) | 0.080935 / 0.014526 (0.066409) | 0.093041 / 0.176557 (-0.083516) | 0.148643 / 0.737135 (-0.588492) | 0.093463 / 0.296338 (-0.202876) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.381653 / 0.215209 (0.166444) | 3.810699 / 2.077655 (1.733044) | 1.866858 / 1.504120 (0.362738) | 1.716985 / 1.541195 (0.175790) | 1.788071 / 1.468490 (0.319581) | 0.481130 / 4.584777 (-4.103647) | 3.529798 / 3.745712 (-0.215914) | 3.982037 / 5.269862 (-1.287824) | 2.324866 / 4.565676 (-2.240811) | 0.056767 / 0.424275 (-0.367508) | 0.007306 / 0.007607 (-0.000301) | 0.459472 / 0.226044 (0.233428) | 4.602808 / 2.268929 (2.333879) | 2.332014 / 55.444624 (-53.112610) | 2.044858 / 6.876477 (-4.831619) | 2.204165 / 2.142072 (0.062093) | 0.577946 / 4.805227 (-4.227281) | 0.130900 / 6.500664 (-6.369764) | 0.059054 / 0.075469 (-0.016415) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.245211 / 1.841788 (-0.596576) | 19.176397 / 8.074308 (11.102089) | 13.995280 / 10.191392 (3.803888) | 0.171743 / 0.680424 (-0.508681) | 0.018038 / 0.534201 (-0.516163) | 0.392338 / 0.579283 (-0.186945) | 0.419370 / 0.434364 (-0.014994) | 0.477829 / 0.540337 (-0.062508) | 0.677409 / 1.386936 (-0.709527) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006513 / 0.011353 (-0.004840) | 0.003984 / 0.011008 (-0.007024) | 0.064516 / 0.038508 (0.026008) | 0.070504 / 0.023109 (0.047395) | 0.384509 / 0.275898 (0.108611) | 0.410564 / 0.323480 (0.087084) | 0.005310 / 0.007986 (-0.002675) | 0.003268 / 0.004328 (-0.001061) | 0.064684 / 0.004250 (0.060433) | 0.055367 / 0.037052 (0.018315) | 0.399108 / 0.258489 (0.140619) | 0.422740 / 0.293841 (0.128900) | 0.031624 / 0.128546 (-0.096922) | 0.008617 / 0.075646 (-0.067030) | 0.070929 / 0.419271 (-0.348342) | 0.049146 / 0.043533 (0.005613) | 0.385492 / 0.255139 (0.130353) | 0.407434 / 0.283200 (0.124234) | 0.021972 / 0.141683 (-0.119711) | 1.496135 / 1.452155 (0.043980) | 1.533739 / 1.492716 (0.041023) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.226218 / 0.018006 (0.208211) | 0.443176 / 0.000490 (0.442686) | 0.000376 / 0.000200 (0.000176) | 0.000055 / 0.000054 (0.000000) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.030315 / 0.037411 (-0.007097) | 0.086416 / 0.014526 (0.071890) | 0.097725 / 0.176557 (-0.078831) | 0.150407 / 0.737135 (-0.586728) | 0.099914 / 0.296338 (-0.196424) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.409807 / 0.215209 (0.194598) | 4.099086 / 2.077655 (2.021431) | 2.103160 / 1.504120 (0.599040) | 1.927927 / 1.541195 (0.386733) | 1.977751 / 1.468490 (0.509261) | 0.476995 / 4.584777 (-4.107781) | 3.521835 / 3.745712 (-0.223877) | 3.237695 / 5.269862 (-2.032167) | 1.995953 / 4.565676 (-2.569724) | 0.056208 / 0.424275 (-0.368068) | 0.007660 / 0.007607 (0.000053) | 0.483537 / 0.226044 (0.257492) | 4.833974 / 2.268929 (2.565046) | 2.589115 / 55.444624 (-52.855510) | 2.228076 / 6.876477 (-4.648401) | 2.395271 / 2.142072 (0.253198) | 0.577534 / 4.805227 (-4.227694) | 0.131432 / 6.500664 (-6.369232) | 0.060999 / 0.075469 (-0.014471) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.356043 / 1.841788 (-0.485745) | 19.470401 / 8.074308 (11.396093) | 14.091266 / 10.191392 (3.899874) | 0.166809 / 0.680424 (-0.513615) | 0.018782 / 0.534201 (-0.515419) | 0.394916 / 0.579283 (-0.184367) | 0.411378 / 0.434364 (-0.022986) | 0.466886 / 0.540337 (-0.073451) | 0.617369 / 1.386936 (-0.769567) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#601ae6c7baff33a600fd10b12940966024fd2221 \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007590 / 0.011353 (-0.003762) | 0.004068 / 0.011008 (-0.006941) | 0.105479 / 0.038508 (0.066971) | 0.085614 / 0.023109 (0.062505) | 0.384325 / 0.275898 (0.108427) | 0.467867 / 0.323480 (0.144387) | 0.004652 / 0.007986 (-0.003333) | 0.005445 / 0.004328 (0.001117) | 0.079604 / 0.004250 (0.075353) | 0.066031 / 0.037052 (0.028978) | 0.426184 / 0.258489 (0.167695) | 0.480712 / 0.293841 (0.186871) | 0.037837 / 0.128546 (-0.090709) | 0.009765 / 0.075646 (-0.065882) | 0.351316 / 0.419271 (-0.067955) | 0.063634 / 0.043533 (0.020101) | 0.420297 / 0.255139 (0.165158) | 0.449169 / 0.283200 (0.165969) | 0.030947 / 0.141683 (-0.110736) | 1.840184 / 1.452155 (0.388029) | 1.934074 / 1.492716 (0.441357) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.223483 / 0.018006 (0.205477) | 0.521086 / 0.000490 (0.520596) | 0.000379 / 0.000200 (0.000179) | 0.000065 / 0.000054 (0.000011) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.032011 / 0.037411 (-0.005400) | 0.101474 / 0.014526 (0.086948) | 0.108652 / 0.176557 (-0.067904) | 0.173340 / 0.737135 (-0.563796) | 0.114186 / 0.296338 (-0.182153) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.478020 / 0.215209 (0.262811) | 4.645400 / 2.077655 (2.567746) | 2.590763 / 1.504120 (1.086643) | 2.383002 / 1.541195 (0.841807) | 2.482550 / 1.468490 (1.014060) | 0.572417 / 4.584777 (-4.012360) | 4.233436 / 3.745712 (0.487724) | 4.858823 / 5.269862 (-0.411038) | 2.838913 / 4.565676 (-1.726764) | 0.070010 / 0.424275 (-0.354265) | 0.009602 / 0.007607 (0.001995) | 0.538735 / 0.226044 (0.312691) | 5.534340 / 2.268929 (3.265411) | 2.915006 / 55.444624 (-52.529619) | 2.625132 / 6.876477 (-4.251345) | 2.537838 / 2.142072 (0.395766) | 0.667870 / 4.805227 (-4.137357) | 0.146330 / 6.500664 (-6.354334) | 0.071631 / 0.075469 (-0.003838) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.594686 / 1.841788 (-0.247101) | 22.311113 / 8.074308 (14.236804) | 17.603983 / 10.191392 (7.412591) | 0.195995 / 0.680424 (-0.484428) | 0.022254 / 0.534201 (-0.511947) | 0.479661 / 0.579283 (-0.099622) | 0.463626 / 0.434364 (0.029262) | 0.483465 / 0.540337 (-0.056873) | 0.676141 / 1.386936 (-0.710795) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006146 / 0.011353 (-0.005207) | 0.004856 / 0.011008 (-0.006152) | 0.067506 / 0.038508 (0.028998) | 0.073968 / 0.023109 (0.050859) | 0.470013 / 0.275898 (0.194115) | 0.479022 / 0.323480 (0.155542) | 0.005972 / 0.007986 (-0.002014) | 0.003846 / 0.004328 (-0.000483) | 0.075141 / 0.004250 (0.070890) | 0.058597 / 0.037052 (0.021544) | 0.481454 / 0.258489 (0.222965) | 0.515634 / 0.293841 (0.221793) | 0.034979 / 0.128546 (-0.093567) | 0.010385 / 0.075646 (-0.065261) | 0.072649 / 0.419271 (-0.346622) | 0.058183 / 0.043533 (0.014650) | 0.462138 / 0.255139 (0.206999) | 0.476093 / 0.283200 (0.192893) | 0.032918 / 0.141683 (-0.108765) | 1.820530 / 1.452155 (0.368375) | 1.626360 / 1.492716 (0.133644) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.208970 / 0.018006 (0.190964) | 0.492478 / 0.000490 (0.491988) | 0.005487 / 0.000200 (0.005287) | 0.000140 / 0.000054 (0.000086) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.037896 / 0.037411 (0.000484) | 0.089752 / 0.014526 (0.075227) | 0.107445 / 0.176557 (-0.069111) | 0.181260 / 0.737135 (-0.555876) | 0.105700 / 0.296338 (-0.190639) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.495031 / 0.215209 (0.279821) | 4.806939 / 2.077655 (2.729284) | 2.227928 / 1.504120 (0.723808) | 2.067117 / 1.541195 (0.525922) | 2.348982 / 1.468490 (0.880492) | 0.567201 / 4.584777 (-4.017576) | 4.166592 / 3.745712 (0.420880) | 3.654329 / 5.269862 (-1.615533) | 2.331092 / 4.565676 (-2.234584) | 0.062212 / 0.424275 (-0.362063) | 0.008775 / 0.007607 (0.001168) | 0.515413 / 0.226044 (0.289369) | 5.449300 / 2.268929 (3.180371) | 3.206574 / 55.444624 (-52.238050) | 2.600455 / 6.876477 (-4.276022) | 3.041162 / 2.142072 (0.899089) | 0.681899 / 4.805227 (-4.123328) | 0.155400 / 6.500664 (-6.345265) | 0.073933 / 0.075469 (-0.001537) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.572329 / 1.841788 (-0.269459) | 23.638519 / 8.074308 (15.564211) | 17.145663 / 10.191392 (6.954271) | 0.232690 / 0.680424 (-0.447734) | 0.028620 / 0.534201 (-0.505581) | 0.488105 / 0.579283 (-0.091178) | 0.490365 / 0.434364 (0.056001) | 0.599501 / 0.540337 (0.059164) | 0.708101 / 1.386936 (-0.678835) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#4a761315900880a25b347ad19b78bd567cfce1f0 \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.005947 / 0.011353 (-0.005406) | 0.003577 / 0.011008 (-0.007431) | 0.081631 / 0.038508 (0.043122) | 0.058651 / 0.023109 (0.035541) | 0.342742 / 0.275898 (0.066843) | 0.384130 / 0.323480 (0.060650) | 0.004620 / 0.007986 (-0.003366) | 0.002885 / 0.004328 (-0.001444) | 0.063698 / 0.004250 (0.059448) | 0.048953 / 0.037052 (0.011901) | 0.367880 / 0.258489 (0.109391) | 0.407050 / 0.293841 (0.113209) | 0.027242 / 0.128546 (-0.101305) | 0.007914 / 0.075646 (-0.067733) | 0.262156 / 0.419271 (-0.157116) | 0.044750 / 0.043533 (0.001218) | 0.351613 / 0.255139 (0.096474) | 0.380284 / 0.283200 (0.097084) | 0.020080 / 0.141683 (-0.121603) | 1.498101 / 1.452155 (0.045946) | 1.543608 / 1.492716 (0.050892) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.180014 / 0.018006 (0.162008) | 0.436172 / 0.000490 (0.435682) | 0.003694 / 0.000200 (0.003494) | 0.000071 / 0.000054 (0.000017) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.024389 / 0.037411 (-0.013022) | 0.072874 / 0.014526 (0.058348) | 0.083469 / 0.176557 (-0.093088) | 0.144600 / 0.737135 (-0.592536) | 0.084229 / 0.296338 (-0.212110) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.391636 / 0.215209 (0.176427) | 3.906941 / 2.077655 (1.829286) | 1.901944 / 1.504120 (0.397825) | 1.762702 / 1.541195 (0.221507) | 1.817970 / 1.468490 (0.349480) | 0.500345 / 4.584777 (-4.084432) | 3.011351 / 3.745712 (-0.734361) | 4.417763 / 5.269862 (-0.852098) | 2.689744 / 4.565676 (-1.875933) | 0.057765 / 0.424275 (-0.366511) | 0.006412 / 0.007607 (-0.001195) | 0.468156 / 0.226044 (0.242112) | 4.664975 / 2.268929 (2.396047) | 2.323355 / 55.444624 (-53.121270) | 1.984280 / 6.876477 (-4.892197) | 2.165215 / 2.142072 (0.023142) | 0.586950 / 4.805227 (-4.218278) | 0.124363 / 6.500664 (-6.376301) | 0.060702 / 0.075469 (-0.014767) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.238870 / 1.841788 (-0.602917) | 18.587360 / 8.074308 (10.513052) | 13.831674 / 10.191392 (3.640282) | 0.143542 / 0.680424 (-0.536882) | 0.016913 / 0.534201 (-0.517288) | 0.332314 / 0.579283 (-0.246969) | 0.345419 / 0.434364 (-0.088945) | 0.381257 / 0.540337 (-0.159081) | 0.537844 / 1.386936 (-0.849092) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006294 / 0.011353 (-0.005059) | 0.003714 / 0.011008 (-0.007294) | 0.062684 / 0.038508 (0.024176) | 0.063520 / 0.023109 (0.040411) | 0.389591 / 0.275898 (0.113693) | 0.444278 / 0.323480 (0.120798) | 0.004825 / 0.007986 (-0.003160) | 0.003010 / 0.004328 (-0.001318) | 0.062767 / 0.004250 (0.058517) | 0.051739 / 0.037052 (0.014686) | 0.434299 / 0.258489 (0.175810) | 0.452003 / 0.293841 (0.158162) | 0.027375 / 0.128546 (-0.101171) | 0.008135 / 0.075646 (-0.067511) | 0.067401 / 0.419271 (-0.351871) | 0.042752 / 0.043533 (-0.000780) | 0.367633 / 0.255139 (0.112494) | 0.433039 / 0.283200 (0.149840) | 0.021086 / 0.141683 (-0.120597) | 1.488024 / 1.452155 (0.035870) | 1.507767 / 1.492716 (0.015050) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.230046 / 0.018006 (0.212040) | 0.428085 / 0.000490 (0.427595) | 0.002188 / 0.000200 (0.001988) | 0.000070 / 0.000054 (0.000015) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.026705 / 0.037411 (-0.010706) | 0.082466 / 0.014526 (0.067940) | 0.089378 / 0.176557 (-0.087179) | 0.147287 / 0.737135 (-0.589849) | 0.090426 / 0.296338 (-0.205913) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.430882 / 0.215209 (0.215672) | 4.296224 / 2.077655 (2.218569) | 2.229982 / 1.504120 (0.725862) | 2.048506 / 1.541195 (0.507311) | 2.129514 / 1.468490 (0.661024) | 0.502964 / 4.584777 (-4.081813) | 3.048125 / 3.745712 (-0.697587) | 4.208636 / 5.269862 (-1.061226) | 2.594015 / 4.565676 (-1.971661) | 0.057967 / 0.424275 (-0.366308) | 0.006875 / 0.007607 (-0.000732) | 0.513872 / 0.226044 (0.287828) | 5.126435 / 2.268929 (2.857506) | 2.691278 / 55.444624 (-52.753346) | 2.361723 / 6.876477 (-4.514754) | 2.511213 / 2.142072 (0.369141) | 0.593558 / 4.805227 (-4.211670) | 0.129332 / 6.500664 (-6.371332) | 0.064051 / 0.075469 (-0.011418) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.289049 / 1.841788 (-0.552739) | 18.912363 / 8.074308 (10.838055) | 14.226500 / 10.191392 (4.035108) | 0.131392 / 0.680424 (-0.549032) | 0.016750 / 0.534201 (-0.517451) | 0.330078 / 0.579283 (-0.249205) | 0.347588 / 0.434364 (-0.086776) | 0.383234 / 0.540337 (-0.157103) | 0.510967 / 1.386936 (-0.875969) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#d7892beb30bab0633b84398c5ea43d7e69fe38cc \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.005974 / 0.011353 (-0.005379) | 0.003691 / 0.011008 (-0.007317) | 0.079410 / 0.038508 (0.040902) | 0.061769 / 0.023109 (0.038660) | 0.323310 / 0.275898 (0.047412) | 0.354325 / 0.323480 (0.030845) | 0.004794 / 0.007986 (-0.003191) | 0.002899 / 0.004328 (-0.001430) | 0.062104 / 0.004250 (0.057854) | 0.048973 / 0.037052 (0.011921) | 0.326497 / 0.258489 (0.068008) | 0.361347 / 0.293841 (0.067506) | 0.026741 / 0.128546 (-0.101805) | 0.007936 / 0.075646 (-0.067710) | 0.259168 / 0.419271 (-0.160104) | 0.044859 / 0.043533 (0.001327) | 0.319342 / 0.255139 (0.064203) | 0.343711 / 0.283200 (0.060511) | 0.022298 / 0.141683 (-0.119384) | 1.451595 / 1.452155 (-0.000560) | 1.573730 / 1.492716 (0.081014) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.173086 / 0.018006 (0.155080) | 0.432400 / 0.000490 (0.431910) | 0.003739 / 0.000200 (0.003539) | 0.000073 / 0.000054 (0.000019) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.024477 / 0.037411 (-0.012934) | 0.073463 / 0.014526 (0.058937) | 0.083410 / 0.176557 (-0.093146) | 0.144760 / 0.737135 (-0.592376) | 0.084199 / 0.296338 (-0.212140) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.388251 / 0.215209 (0.173042) | 3.875375 / 2.077655 (1.797720) | 1.875515 / 1.504120 (0.371395) | 1.729282 / 1.541195 (0.188087) | 1.784732 / 1.468490 (0.316242) | 0.496985 / 4.584777 (-4.087792) | 3.030276 / 3.745712 (-0.715436) | 2.813192 / 5.269862 (-2.456669) | 1.868647 / 4.565676 (-2.697030) | 0.057376 / 0.424275 (-0.366899) | 0.006463 / 0.007607 (-0.001144) | 0.462153 / 0.226044 (0.236108) | 4.586583 / 2.268929 (2.317654) | 2.287730 / 55.444624 (-53.156894) | 1.972177 / 6.876477 (-4.904299) | 2.151592 / 2.142072 (0.009520) | 0.587169 / 4.805227 (-4.218058) | 0.127063 / 6.500664 (-6.373601) | 0.060297 / 0.075469 (-0.015172) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.267651 / 1.841788 (-0.574136) | 18.426011 / 8.074308 (10.351703) | 14.050470 / 10.191392 (3.859078) | 0.148063 / 0.680424 (-0.532361) | 0.017112 / 0.534201 (-0.517089) | 0.330051 / 0.579283 (-0.249232) | 0.358730 / 0.434364 (-0.075634) | 0.392365 / 0.540337 (-0.147972) | 0.534650 / 1.386936 (-0.852286) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.005936 / 0.011353 (-0.005417) | 0.003652 / 0.011008 (-0.007356) | 0.063066 / 0.038508 (0.024558) | 0.060617 / 0.023109 (0.037507) | 0.388293 / 0.275898 (0.112395) | 0.411422 / 0.323480 (0.087942) | 0.004691 / 0.007986 (-0.003295) | 0.002857 / 0.004328 (-0.001472) | 0.064198 / 0.004250 (0.059947) | 0.049124 / 0.037052 (0.012071) | 0.403601 / 0.258489 (0.145112) | 0.413619 / 0.293841 (0.119778) | 0.027279 / 0.128546 (-0.101267) | 0.008072 / 0.075646 (-0.067575) | 0.067890 / 0.419271 (-0.351381) | 0.041866 / 0.043533 (-0.001667) | 0.393438 / 0.255139 (0.138299) | 0.402865 / 0.283200 (0.119666) | 0.023381 / 0.141683 (-0.118302) | 1.496324 / 1.452155 (0.044170) | 1.538080 / 1.492716 (0.045364) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.212065 / 0.018006 (0.194059) | 0.410511 / 0.000490 (0.410021) | 0.001236 / 0.000200 (0.001036) | 0.000067 / 0.000054 (0.000012) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.026012 / 0.037411 (-0.011399) | 0.076592 / 0.014526 (0.062066) | 0.085963 / 0.176557 (-0.090594) | 0.137803 / 0.737135 (-0.599332) | 0.087594 / 0.296338 (-0.208745) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.434283 / 0.215209 (0.219074) | 4.345478 / 2.077655 (2.267824) | 2.400954 / 1.504120 (0.896834) | 2.282024 / 1.541195 (0.740829) | 2.414247 / 1.468490 (0.945757) | 0.501855 / 4.584777 (-4.082922) | 3.059433 / 3.745712 (-0.686279) | 2.811288 / 5.269862 (-2.458574) | 1.856839 / 4.565676 (-2.708838) | 0.058017 / 0.424275 (-0.366258) | 0.006844 / 0.007607 (-0.000763) | 0.515376 / 0.226044 (0.289332) | 5.148775 / 2.268929 (2.879847) | 2.930807 / 55.444624 (-52.513817) | 2.520532 / 6.876477 (-4.355944) | 2.746299 / 2.142072 (0.604227) | 0.590102 / 4.805227 (-4.215125) | 0.125747 / 6.500664 (-6.374917) | 0.061873 / 0.075469 (-0.013597) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.306247 / 1.841788 (-0.535541) | 18.366048 / 8.074308 (10.291740) | 13.855617 / 10.191392 (3.664225) | 0.150124 / 0.680424 (-0.530300) | 0.017189 / 0.534201 (-0.517012) | 0.336285 / 0.579283 (-0.242998) | 0.344985 / 0.434364 (-0.089379) | 0.397973 / 0.540337 (-0.142364) | 0.536142 / 1.386936 (-0.850794) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#1ae24cf12054b4a512f198979b1ca7707bb99d56 \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006401 / 0.011353 (-0.004952) | 0.003789 / 0.011008 (-0.007219) | 0.079516 / 0.038508 (0.041008) | 0.068279 / 0.023109 (0.045170) | 0.295691 / 0.275898 (0.019793) | 0.327208 / 0.323480 (0.003728) | 0.005070 / 0.007986 (-0.002915) | 0.003044 / 0.004328 (-0.001285) | 0.061411 / 0.004250 (0.057161) | 0.053227 / 0.037052 (0.016175) | 0.297368 / 0.258489 (0.038879) | 0.334740 / 0.293841 (0.040899) | 0.029459 / 0.128546 (-0.099087) | 0.008080 / 0.075646 (-0.067566) | 0.267344 / 0.419271 (-0.151927) | 0.049877 / 0.043533 (0.006344) | 0.293853 / 0.255139 (0.038714) | 0.319819 / 0.283200 (0.036620) | 0.022593 / 0.141683 (-0.119089) | 1.459054 / 1.452155 (0.006900) | 1.471250 / 1.492716 (-0.021466) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.194326 / 0.018006 (0.176320) | 0.443565 / 0.000490 (0.443075) | 0.003745 / 0.000200 (0.003545) | 0.000075 / 0.000054 (0.000021) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.026640 / 0.037411 (-0.010772) | 0.077630 / 0.014526 (0.063104) | 0.089364 / 0.176557 (-0.087192) | 0.147327 / 0.737135 (-0.589809) | 0.089603 / 0.296338 (-0.206735) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.373758 / 0.215209 (0.158549) | 3.746778 / 2.077655 (1.669123) | 1.814991 / 1.504120 (0.310871) | 1.645650 / 1.541195 (0.104455) | 1.690752 / 1.468490 (0.222262) | 0.472117 / 4.584777 (-4.112660) | 3.457346 / 3.745712 (-0.288367) | 3.138869 / 5.269862 (-2.130993) | 1.934924 / 4.565676 (-2.630753) | 0.055709 / 0.424275 (-0.368566) | 0.006680 / 0.007607 (-0.000927) | 0.446874 / 0.226044 (0.220829) | 4.458409 / 2.268929 (2.189480) | 2.253932 / 55.444624 (-53.190693) | 2.007240 / 6.876477 (-4.869237) | 2.081687 / 2.142072 (-0.060386) | 0.563379 / 4.805227 (-4.241848) | 0.128694 / 6.500664 (-6.371970) | 0.057409 / 0.075469 (-0.018060) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.212231 / 1.841788 (-0.629556) | 18.519121 / 8.074308 (10.444813) | 13.582243 / 10.191392 (3.390851) | 0.142488 / 0.680424 (-0.537936) | 0.017421 / 0.534201 (-0.516780) | 0.366864 / 0.579283 (-0.212419) | 0.401467 / 0.434364 (-0.032897) | 0.443659 / 0.540337 (-0.096679) | 0.618854 / 1.386936 (-0.768082) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006121 / 0.011353 (-0.005232) | 0.003690 / 0.011008 (-0.007318) | 0.060340 / 0.038508 (0.021832) | 0.067215 / 0.023109 (0.044106) | 0.382846 / 0.275898 (0.106948) | 0.415774 / 0.323480 (0.092294) | 0.004868 / 0.007986 (-0.003118) | 0.003108 / 0.004328 (-0.001221) | 0.060572 / 0.004250 (0.056321) | 0.050453 / 0.037052 (0.013401) | 0.400494 / 0.258489 (0.142005) | 0.424368 / 0.293841 (0.130527) | 0.030279 / 0.128546 (-0.098267) | 0.008151 / 0.075646 (-0.067495) | 0.066707 / 0.419271 (-0.352564) | 0.046118 / 0.043533 (0.002585) | 0.386697 / 0.255139 (0.131558) | 0.410156 / 0.283200 (0.126957) | 0.020688 / 0.141683 (-0.120995) | 1.418162 / 1.452155 (-0.033993) | 1.463057 / 1.492716 (-0.029659) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.216081 / 0.018006 (0.198075) | 0.440541 / 0.000490 (0.440051) | 0.000371 / 0.000200 (0.000171) | 0.000054 / 0.000054 (-0.000000) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.027763 / 0.037411 (-0.009648) | 0.082316 / 0.014526 (0.067791) | 0.094086 / 0.176557 (-0.082471) | 0.144738 / 0.737135 (-0.592398) | 0.094837 / 0.296338 (-0.201501) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.396277 / 0.215209 (0.181068) | 3.958791 / 2.077655 (1.881136) | 2.021367 / 1.504120 (0.517247) | 1.860112 / 1.541195 (0.318917) | 1.886032 / 1.468490 (0.417541) | 0.468536 / 4.584777 (-4.116241) | 3.417950 / 3.745712 (-0.327762) | 4.849991 / 5.269862 (-0.419871) | 2.773935 / 4.565676 (-1.791742) | 0.055813 / 0.424275 (-0.368462) | 0.007053 / 0.007607 (-0.000554) | 0.470167 / 0.226044 (0.244122) | 4.702969 / 2.268929 (2.434041) | 2.474161 / 55.444624 (-52.970464) | 2.171256 / 6.876477 (-4.705220) | 2.315373 / 2.142072 (0.173301) | 0.589195 / 4.805227 (-4.216032) | 0.128237 / 6.500664 (-6.372427) | 0.058641 / 0.075469 (-0.016828) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.292947 / 1.841788 (-0.548841) | 18.851300 / 8.074308 (10.776992) | 14.089764 / 10.191392 (3.898372) | 0.164853 / 0.680424 (-0.515571) | 0.017281 / 0.534201 (-0.516920) | 0.359112 / 0.579283 (-0.220171) | 0.386696 / 0.434364 (-0.047668) | 0.428222 / 0.540337 (-0.112115) | 0.568659 / 1.386936 (-0.818277) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#563864ded894b468e2ba3f677ef79c5ab3fe65df \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006051 / 0.011353 (-0.005301) | 0.003654 / 0.011008 (-0.007355) | 0.080081 / 0.038508 (0.041572) | 0.062925 / 0.023109 (0.039815) | 0.358097 / 0.275898 (0.082199) | 0.405728 / 0.323480 (0.082248) | 0.005359 / 0.007986 (-0.002627) | 0.002820 / 0.004328 (-0.001508) | 0.063108 / 0.004250 (0.058858) | 0.049627 / 0.037052 (0.012575) | 0.397870 / 0.258489 (0.139381) | 0.437157 / 0.293841 (0.143316) | 0.027707 / 0.128546 (-0.100839) | 0.007911 / 0.075646 (-0.067735) | 0.260991 / 0.419271 (-0.158280) | 0.044771 / 0.043533 (0.001238) | 0.340230 / 0.255139 (0.085091) | 0.384925 / 0.283200 (0.101725) | 0.021369 / 0.141683 (-0.120314) | 1.431439 / 1.452155 (-0.020715) | 1.478794 / 1.492716 (-0.013922) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.182626 / 0.018006 (0.164620) | 0.435551 / 0.000490 (0.435061) | 0.003015 / 0.000200 (0.002815) | 0.000064 / 0.000054 (0.000009) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.024703 / 0.037411 (-0.012708) | 0.073640 / 0.014526 (0.059114) | 0.084598 / 0.176557 (-0.091959) | 0.145810 / 0.737135 (-0.591325) | 0.085125 / 0.296338 (-0.211213) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.394539 / 0.215209 (0.179330) | 3.945882 / 2.077655 (1.868227) | 1.947166 / 1.504120 (0.443046) | 1.763305 / 1.541195 (0.222111) | 1.816208 / 1.468490 (0.347718) | 0.498880 / 4.584777 (-4.085897) | 3.098283 / 3.745712 (-0.647429) | 2.823474 / 5.269862 (-2.446388) | 1.873993 / 4.565676 (-2.691684) | 0.058097 / 0.424275 (-0.366179) | 0.006488 / 0.007607 (-0.001119) | 0.466711 / 0.226044 (0.240667) | 4.671520 / 2.268929 (2.402592) | 2.363381 / 55.444624 (-53.081243) | 2.052092 / 6.876477 (-4.824385) | 2.209212 / 2.142072 (0.067140) | 0.594650 / 4.805227 (-4.210577) | 0.125604 / 6.500664 (-6.375060) | 0.061511 / 0.075469 (-0.013958) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.226564 / 1.841788 (-0.615224) | 18.583605 / 8.074308 (10.509297) | 13.993091 / 10.191392 (3.801699) | 0.146185 / 0.680424 (-0.534239) | 0.016839 / 0.534201 (-0.517362) | 0.334116 / 0.579283 (-0.245167) | 0.360780 / 0.434364 (-0.073584) | 0.386008 / 0.540337 (-0.154329) | 0.643278 / 1.386936 (-0.743658) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006174 / 0.011353 (-0.005179) | 0.003658 / 0.011008 (-0.007350) | 0.063250 / 0.038508 (0.024742) | 0.063542 / 0.023109 (0.040433) | 0.366845 / 0.275898 (0.090947) | 0.409794 / 0.323480 (0.086314) | 0.005678 / 0.007986 (-0.002308) | 0.003061 / 0.004328 (-0.001268) | 0.063561 / 0.004250 (0.059311) | 0.052648 / 0.037052 (0.015596) | 0.378096 / 0.258489 (0.119607) | 0.410706 / 0.293841 (0.116865) | 0.027668 / 0.128546 (-0.100878) | 0.008045 / 0.075646 (-0.067601) | 0.068290 / 0.419271 (-0.350981) | 0.042602 / 0.043533 (-0.000930) | 0.364976 / 0.255139 (0.109837) | 0.395599 / 0.283200 (0.112400) | 0.022733 / 0.141683 (-0.118950) | 1.522473 / 1.452155 (0.070319) | 1.515891 / 1.492716 (0.023175) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.232554 / 0.018006 (0.214547) | 0.420702 / 0.000490 (0.420213) | 0.002161 / 0.000200 (0.001961) | 0.000064 / 0.000054 (0.000009) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.026276 / 0.037411 (-0.011135) | 0.078504 / 0.014526 (0.063978) | 0.088989 / 0.176557 (-0.087567) | 0.144044 / 0.737135 (-0.593091) | 0.091074 / 0.296338 (-0.205265) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.420189 / 0.215209 (0.204980) | 4.189596 / 2.077655 (2.111941) | 2.316425 / 1.504120 (0.812305) | 2.186877 / 1.541195 (0.645682) | 2.259065 / 1.468490 (0.790575) | 0.502827 / 4.584777 (-4.081950) | 3.135266 / 3.745712 (-0.610446) | 2.838808 / 5.269862 (-2.431053) | 1.876519 / 4.565676 (-2.689158) | 0.057802 / 0.424275 (-0.366473) | 0.006824 / 0.007607 (-0.000784) | 0.500213 / 0.226044 (0.274168) | 4.999798 / 2.268929 (2.730869) | 2.627713 / 55.444624 (-52.816911) | 2.344263 / 6.876477 (-4.532214) | 2.415449 / 2.142072 (0.273376) | 0.593082 / 4.805227 (-4.212145) | 0.125787 / 6.500664 (-6.374877) | 0.062699 / 0.075469 (-0.012770) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.308219 / 1.841788 (-0.533569) | 18.703099 / 8.074308 (10.628791) | 13.976234 / 10.191392 (3.784842) | 0.144037 / 0.680424 (-0.536387) | 0.016592 / 0.534201 (-0.517609) | 0.333078 / 0.579283 (-0.246206) | 0.342317 / 0.434364 (-0.092047) | 0.396837 / 0.540337 (-0.143500) | 0.532641 / 1.386936 (-0.854295) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#14f6edd9222e577dccb962ed5338b79b73502fa5 \"CML watermark\")\n" ]

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[ "_The documentation is not available anymore as the PR was closed or merged._", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.008698 / 0.011353 (-0.002655) | 0.005250 / 0.011008 (-0.005758) | 0.104101 / 0.038508 (0.065593) | 0.085021 / 0.023109 (0.061912) | 0.426653 / 0.275898 (0.150755) | 0.460449 / 0.323480 (0.136969) | 0.005222 / 0.007986 (-0.002763) | 0.006280 / 0.004328 (0.001951) | 0.083458 / 0.004250 (0.079207) | 0.066132 / 0.037052 (0.029079) | 0.433416 / 0.258489 (0.174927) | 0.482718 / 0.293841 (0.188877) | 0.048872 / 0.128546 (-0.079675) | 0.013699 / 0.075646 (-0.061948) | 0.365660 / 0.419271 (-0.053611) | 0.071008 / 0.043533 (0.027475) | 0.428688 / 0.255139 (0.173549) | 0.443554 / 0.283200 (0.160354) | 0.035901 / 0.141683 (-0.105782) | 1.829296 / 1.452155 (0.377141) | 1.862351 / 1.492716 (0.369635) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.236284 / 0.018006 (0.218278) | 0.584075 / 0.000490 (0.583585) | 0.004634 / 0.000200 (0.004434) | 0.000125 / 0.000054 (0.000070) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.034723 / 0.037411 (-0.002688) | 0.100989 / 0.014526 (0.086464) | 0.113722 / 0.176557 (-0.062834) | 0.187659 / 0.737135 (-0.549477) | 0.113937 / 0.296338 (-0.182401) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.587500 / 0.215209 (0.372291) | 5.847371 / 2.077655 (3.769716) | 2.599691 / 1.504120 (1.095571) | 2.246187 / 1.541195 (0.704992) | 2.419126 / 1.468490 (0.950636) | 0.847327 / 4.584777 (-3.737450) | 5.230438 / 3.745712 (1.484726) | 7.539021 / 5.269862 (2.269160) | 4.617473 / 4.565676 (0.051797) | 0.103620 / 0.424275 (-0.320655) | 0.009195 / 0.007607 (0.001588) | 0.714247 / 0.226044 (0.488203) | 7.331621 / 2.268929 (5.062693) | 3.416575 / 55.444624 (-52.028049) | 2.649467 / 6.876477 (-4.227009) | 2.928091 / 2.142072 (0.786018) | 1.002155 / 4.805227 (-3.803072) | 0.210790 / 6.500664 (-6.289874) | 0.081303 / 0.075469 (0.005834) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.655431 / 1.841788 (-0.186357) | 24.069595 / 8.074308 (15.995287) | 20.923766 / 10.191392 (10.732374) | 0.232021 / 0.680424 (-0.448403) | 0.026355 / 0.534201 (-0.507846) | 0.496830 / 0.579283 (-0.082453) | 0.582620 / 0.434364 (0.148257) | 0.551227 / 0.540337 (0.010890) | 0.756389 / 1.386936 (-0.630547) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.009329 / 0.011353 (-0.002024) | 0.005045 / 0.011008 (-0.005964) | 0.082116 / 0.038508 (0.043608) | 0.082420 / 0.023109 (0.059311) | 0.502513 / 0.275898 (0.226615) | 0.526098 / 0.323480 (0.202618) | 0.007468 / 0.007986 (-0.000517) | 0.005477 / 0.004328 (0.001148) | 0.082617 / 0.004250 (0.078367) | 0.070292 / 0.037052 (0.033239) | 0.503290 / 0.258489 (0.244801) | 0.541631 / 0.293841 (0.247790) | 0.050826 / 0.128546 (-0.077721) | 0.014699 / 0.075646 (-0.060948) | 0.094441 / 0.419271 (-0.324830) | 0.065034 / 0.043533 (0.021501) | 0.486778 / 0.255139 (0.231639) | 0.516907 / 0.283200 (0.233707) | 0.045140 / 0.141683 (-0.096543) | 1.831676 / 1.452155 (0.379521) | 1.910865 / 1.492716 (0.418149) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.286818 / 0.018006 (0.268812) | 0.558621 / 0.000490 (0.558131) | 0.002830 / 0.000200 (0.002630) | 0.000148 / 0.000054 (0.000094) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.036716 / 0.037411 (-0.000696) | 0.107830 / 0.014526 (0.093305) | 0.116368 / 0.176557 (-0.060188) | 0.178401 / 0.737135 (-0.558734) | 0.124729 / 0.296338 (-0.171609) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.633557 / 0.215209 (0.418348) | 6.423135 / 2.077655 (4.345480) | 2.981883 / 1.504120 (1.477763) | 2.755592 / 1.541195 (1.214398) | 2.769337 / 1.468490 (1.300847) | 0.836219 / 4.584777 (-3.748558) | 5.302030 / 3.745712 (1.556318) | 7.463960 / 5.269862 (2.194098) | 4.427254 / 4.565676 (-0.138422) | 0.095990 / 0.424275 (-0.328285) | 0.009264 / 0.007607 (0.001657) | 0.770642 / 0.226044 (0.544597) | 7.779667 / 2.268929 (5.510739) | 3.799115 / 55.444624 (-51.645509) | 3.212560 / 6.876477 (-3.663917) | 3.281657 / 2.142072 (1.139584) | 1.044981 / 4.805227 (-3.760246) | 0.210693 / 6.500664 (-6.289971) | 0.079466 / 0.075469 (0.003997) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.793155 / 1.841788 (-0.048632) | 24.691127 / 8.074308 (16.616819) | 22.083150 / 10.191392 (11.891758) | 0.242246 / 0.680424 (-0.438178) | 0.028001 / 0.534201 (-0.506200) | 0.494061 / 0.579283 (-0.085222) | 0.599288 / 0.434364 (0.164924) | 0.552101 / 0.540337 (0.011764) | 0.784093 / 1.386936 (-0.602843) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#cd429c39604af34bc3a3ba1f463329b23fcbc1e3 \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006658 / 0.011353 (-0.004695) | 0.004044 / 0.011008 (-0.006965) | 0.085844 / 0.038508 (0.047336) | 0.077147 / 0.023109 (0.054038) | 0.344387 / 0.275898 (0.068489) | 0.376718 / 0.323480 (0.053238) | 0.005537 / 0.007986 (-0.002448) | 0.003452 / 0.004328 (-0.000876) | 0.065326 / 0.004250 (0.061076) | 0.057639 / 0.037052 (0.020587) | 0.352363 / 0.258489 (0.093873) | 0.378939 / 0.293841 (0.085098) | 0.031259 / 0.128546 (-0.097287) | 0.008464 / 0.075646 (-0.067183) | 0.289076 / 0.419271 (-0.130195) | 0.052991 / 0.043533 (0.009459) | 0.346053 / 0.255139 (0.090914) | 0.362761 / 0.283200 (0.079561) | 0.023501 / 0.141683 (-0.118182) | 1.478312 / 1.452155 (0.026157) | 1.545437 / 1.492716 (0.052721) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.202964 / 0.018006 (0.184957) | 0.534793 / 0.000490 (0.534303) | 0.006025 / 0.000200 (0.005825) | 0.000225 / 0.000054 (0.000171) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.029418 / 0.037411 (-0.007993) | 0.084297 / 0.014526 (0.069771) | 0.096702 / 0.176557 (-0.079855) | 0.157355 / 0.737135 (-0.579781) | 0.097858 / 0.296338 (-0.198480) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.380728 / 0.215209 (0.165519) | 3.787712 / 2.077655 (1.710057) | 1.836393 / 1.504120 (0.332273) | 1.678415 / 1.541195 (0.137220) | 1.781800 / 1.468490 (0.313310) | 0.478677 / 4.584777 (-4.106100) | 3.614080 / 3.745712 (-0.131632) | 3.255637 / 5.269862 (-2.014225) | 2.063642 / 4.565676 (-2.502035) | 0.056470 / 0.424275 (-0.367805) | 0.007408 / 0.007607 (-0.000199) | 0.459155 / 0.226044 (0.233111) | 4.586679 / 2.268929 (2.317750) | 2.305737 / 55.444624 (-53.138888) | 1.954755 / 6.876477 (-4.921721) | 2.190809 / 2.142072 (0.048737) | 0.572426 / 4.805227 (-4.232802) | 0.130349 / 6.500664 (-6.370315) | 0.059346 / 0.075469 (-0.016124) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.253671 / 1.841788 (-0.588117) | 19.509015 / 8.074308 (11.434706) | 13.951349 / 10.191392 (3.759957) | 0.171038 / 0.680424 (-0.509386) | 0.018826 / 0.534201 (-0.515375) | 0.394642 / 0.579283 (-0.184642) | 0.419614 / 0.434364 (-0.014750) | 0.470931 / 0.540337 (-0.069406) | 0.643858 / 1.386936 (-0.743078) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006765 / 0.011353 (-0.004587) | 0.003955 / 0.011008 (-0.007053) | 0.064377 / 0.038508 (0.025869) | 0.076980 / 0.023109 (0.053871) | 0.368675 / 0.275898 (0.092777) | 0.403746 / 0.323480 (0.080267) | 0.005303 / 0.007986 (-0.002683) | 0.003257 / 0.004328 (-0.001072) | 0.064154 / 0.004250 (0.059903) | 0.056975 / 0.037052 (0.019923) | 0.376718 / 0.258489 (0.118229) | 0.416291 / 0.293841 (0.122450) | 0.031444 / 0.128546 (-0.097102) | 0.008532 / 0.075646 (-0.067115) | 0.070455 / 0.419271 (-0.348816) | 0.049032 / 0.043533 (0.005499) | 0.361413 / 0.255139 (0.106274) | 0.384648 / 0.283200 (0.101448) | 0.024050 / 0.141683 (-0.117633) | 1.514330 / 1.452155 (0.062176) | 1.585424 / 1.492716 (0.092708) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.214701 / 0.018006 (0.196695) | 0.447706 / 0.000490 (0.447216) | 0.000373 / 0.000200 (0.000173) | 0.000058 / 0.000054 (0.000003) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.031007 / 0.037411 (-0.006404) | 0.090545 / 0.014526 (0.076019) | 0.100611 / 0.176557 (-0.075945) | 0.154847 / 0.737135 (-0.582289) | 0.102864 / 0.296338 (-0.193475) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.427740 / 0.215209 (0.212531) | 4.273143 / 2.077655 (2.195488) | 2.294906 / 1.504120 (0.790786) | 2.138460 / 1.541195 (0.597265) | 2.274126 / 1.468490 (0.805636) | 0.486559 / 4.584777 (-4.098218) | 3.565554 / 3.745712 (-0.180158) | 3.377659 / 5.269862 (-1.892202) | 2.029883 / 4.565676 (-2.535793) | 0.057303 / 0.424275 (-0.366972) | 0.007314 / 0.007607 (-0.000293) | 0.504263 / 0.226044 (0.278219) | 5.041196 / 2.268929 (2.772268) | 2.819273 / 55.444624 (-52.625351) | 2.421479 / 6.876477 (-4.454998) | 2.503063 / 2.142072 (0.360991) | 0.581467 / 4.805227 (-4.223760) | 0.133532 / 6.500664 (-6.367132) | 0.062504 / 0.075469 (-0.012965) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.328765 / 1.841788 (-0.513022) | 20.131672 / 8.074308 (12.057363) | 14.312895 / 10.191392 (4.121503) | 0.191199 / 0.680424 (-0.489225) | 0.018522 / 0.534201 (-0.515679) | 0.393121 / 0.579283 (-0.186162) | 0.413122 / 0.434364 (-0.021242) | 0.469312 / 0.540337 (-0.071026) | 0.633140 / 1.386936 (-0.753796) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#dbf6c103f5844de40431478e7e4a64fbf2c2c067 \"CML watermark\")\n" ]

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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6026). All of your documentation changes will be reflected on that endpoint.", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006444 / 0.011353 (-0.004909) | 0.003768 / 0.011008 (-0.007240) | 0.079625 / 0.038508 (0.041117) | 0.064490 / 0.023109 (0.041381) | 0.313858 / 0.275898 (0.037960) | 0.350810 / 0.323480 (0.027330) | 0.004804 / 0.007986 (-0.003182) | 0.002904 / 0.004328 (-0.001425) | 0.061728 / 0.004250 (0.057477) | 0.052265 / 0.037052 (0.015213) | 0.321246 / 0.258489 (0.062757) | 0.353873 / 0.293841 (0.060032) | 0.027510 / 0.128546 (-0.101036) | 0.007942 / 0.075646 (-0.067704) | 0.260518 / 0.419271 (-0.158754) | 0.045686 / 0.043533 (0.002153) | 0.316821 / 0.255139 (0.061682) | 0.337086 / 0.283200 (0.053886) | 0.022188 / 0.141683 (-0.119495) | 1.427345 / 1.452155 (-0.024810) | 1.476059 / 1.492716 (-0.016657) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.189640 / 0.018006 (0.171634) | 0.429724 / 0.000490 (0.429235) | 0.005314 / 0.000200 (0.005114) | 0.000076 / 0.000054 (0.000021) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.024412 / 0.037411 (-0.013000) | 0.073488 / 0.014526 (0.058962) | 0.083843 / 0.176557 (-0.092714) | 0.147849 / 0.737135 (-0.589286) | 0.085465 / 0.296338 (-0.210873) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.405314 / 0.215209 (0.190105) | 4.071471 / 2.077655 (1.993816) | 1.916252 / 1.504120 (0.412132) | 1.721616 / 1.541195 (0.180422) | 1.807187 / 1.468490 (0.338697) | 0.498045 / 4.584777 (-4.086732) | 3.057526 / 3.745712 (-0.688187) | 4.451424 / 5.269862 (-0.818437) | 2.764020 / 4.565676 (-1.801656) | 0.057665 / 0.424275 (-0.366610) | 0.006679 / 0.007607 (-0.000928) | 0.485733 / 0.226044 (0.259688) | 4.844367 / 2.268929 (2.575438) | 2.435359 / 55.444624 (-53.009265) | 2.111478 / 6.876477 (-4.764999) | 2.377448 / 2.142072 (0.235375) | 0.587997 / 4.805227 (-4.217230) | 0.125545 / 6.500664 (-6.375120) | 0.061509 / 0.075469 (-0.013960) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.229210 / 1.841788 (-0.612577) | 18.553994 / 8.074308 (10.479686) | 14.037877 / 10.191392 (3.846485) | 0.144230 / 0.680424 (-0.536194) | 0.016891 / 0.534201 (-0.517310) | 0.329039 / 0.579283 (-0.250244) | 0.357269 / 0.434364 (-0.077095) | 0.384222 / 0.540337 (-0.156115) | 0.521292 / 1.386936 (-0.865644) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006359 / 0.011353 (-0.004994) | 0.003721 / 0.011008 (-0.007287) | 0.062047 / 0.038508 (0.023539) | 0.065267 / 0.023109 (0.042158) | 0.360164 / 0.275898 (0.084266) | 0.402292 / 0.323480 (0.078812) | 0.005603 / 0.007986 (-0.002382) | 0.002966 / 0.004328 (-0.001363) | 0.062580 / 0.004250 (0.058330) | 0.053634 / 0.037052 (0.016582) | 0.362210 / 0.258489 (0.103721) | 0.404285 / 0.293841 (0.110444) | 0.027567 / 0.128546 (-0.100979) | 0.008119 / 0.075646 (-0.067528) | 0.067577 / 0.419271 (-0.351694) | 0.042867 / 0.043533 (-0.000666) | 0.361576 / 0.255139 (0.106437) | 0.389061 / 0.283200 (0.105862) | 0.021923 / 0.141683 (-0.119760) | 1.446259 / 1.452155 (-0.005895) | 1.490724 / 1.492716 (-0.001992) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.206433 / 0.018006 (0.188427) | 0.424178 / 0.000490 (0.423688) | 0.002340 / 0.000200 (0.002140) | 0.000069 / 0.000054 (0.000015) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.024955 / 0.037411 (-0.012456) | 0.077446 / 0.014526 (0.062920) | 0.088540 / 0.176557 (-0.088017) | 0.141225 / 0.737135 (-0.595910) | 0.089747 / 0.296338 (-0.206592) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.443738 / 0.215209 (0.228529) | 4.208887 / 2.077655 (2.131233) | 2.155127 / 1.504120 (0.651007) | 2.028178 / 1.541195 (0.486983) | 2.084903 / 1.468490 (0.616413) | 0.497530 / 4.584777 (-4.087247) | 3.069012 / 3.745712 (-0.676700) | 3.025184 / 5.269862 (-2.244678) | 1.904687 / 4.565676 (-2.660990) | 0.057526 / 0.424275 (-0.366749) | 0.006482 / 0.007607 (-0.001125) | 0.494692 / 0.226044 (0.268647) | 4.944437 / 2.268929 (2.675508) | 2.655989 / 55.444624 (-52.788635) | 2.331677 / 6.876477 (-4.544800) | 2.382396 / 2.142072 (0.240324) | 0.582019 / 4.805227 (-4.223209) | 0.125866 / 6.500664 (-6.374799) | 0.062908 / 0.075469 (-0.012561) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.294612 / 1.841788 (-0.547176) | 19.016152 / 8.074308 (10.941844) | 14.088828 / 10.191392 (3.897436) | 0.160842 / 0.680424 (-0.519582) | 0.017054 / 0.534201 (-0.517146) | 0.333647 / 0.579283 (-0.245636) | 0.348094 / 0.434364 (-0.086270) | 0.394970 / 0.540337 (-0.145367) | 0.551141 / 1.386936 (-0.835795) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#9e9cfe886792b30b5000808072a0f91ec8536749 \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007442 / 0.011353 (-0.003911) | 0.004302 / 0.011008 (-0.006707) | 0.087159 / 0.038508 (0.048651) | 0.095094 / 0.023109 (0.071985) | 0.315422 / 0.275898 (0.039524) | 0.346672 / 0.323480 (0.023192) | 0.005811 / 0.007986 (-0.002174) | 0.003597 / 0.004328 (-0.000731) | 0.066400 / 0.004250 (0.062150) | 0.065947 / 0.037052 (0.028894) | 0.323269 / 0.258489 (0.064780) | 0.353309 / 0.293841 (0.059468) | 0.032268 / 0.128546 (-0.096278) | 0.008696 / 0.075646 (-0.066950) | 0.291486 / 0.419271 (-0.127786) | 0.054609 / 0.043533 (0.011076) | 0.321061 / 0.255139 (0.065922) | 0.336907 / 0.283200 (0.053707) | 0.027338 / 0.141683 (-0.114345) | 1.496442 / 1.452155 (0.044287) | 1.576946 / 1.492716 (0.084229) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.229140 / 0.018006 (0.211134) | 0.487500 / 0.000490 (0.487010) | 0.002425 / 0.000200 (0.002225) | 0.000089 / 0.000054 (0.000034) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.029351 / 0.037411 (-0.008060) | 0.089610 / 0.014526 (0.075084) | 0.097880 / 0.176557 (-0.078676) | 0.155947 / 0.737135 (-0.581189) | 0.098593 / 0.296338 (-0.197745) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.382911 / 0.215209 (0.167702) | 3.820363 / 2.077655 (1.742708) | 1.866385 / 1.504120 (0.362265) | 1.712910 / 1.541195 (0.171716) | 1.813863 / 1.468490 (0.345373) | 0.484884 / 4.584777 (-4.099893) | 3.678911 / 3.745712 (-0.066801) | 5.249908 / 5.269862 (-0.019953) | 3.099614 / 4.565676 (-1.466063) | 0.057449 / 0.424275 (-0.366826) | 0.007728 / 0.007607 (0.000120) | 0.462123 / 0.226044 (0.236078) | 4.603942 / 2.268929 (2.335014) | 2.380957 / 55.444624 (-53.063668) | 2.059621 / 6.876477 (-4.816856) | 2.293764 / 2.142072 (0.151691) | 0.636471 / 4.805227 (-4.168756) | 0.150112 / 6.500664 (-6.350552) | 0.063705 / 0.075469 (-0.011764) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.358099 / 1.841788 (-0.483689) | 20.193750 / 8.074308 (12.119442) | 14.297350 / 10.191392 (4.105958) | 0.164477 / 0.680424 (-0.515947) | 0.018259 / 0.534201 (-0.515942) | 0.399010 / 0.579283 (-0.180273) | 0.417306 / 0.434364 (-0.017058) | 0.456961 / 0.540337 (-0.083377) | 0.631068 / 1.386936 (-0.755868) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007324 / 0.011353 (-0.004028) | 0.004463 / 0.011008 (-0.006545) | 0.066148 / 0.038508 (0.027640) | 0.093909 / 0.023109 (0.070799) | 0.399122 / 0.275898 (0.123224) | 0.430226 / 0.323480 (0.106746) | 0.005505 / 0.007986 (-0.002481) | 0.003579 / 0.004328 (-0.000749) | 0.066529 / 0.004250 (0.062278) | 0.063471 / 0.037052 (0.026418) | 0.406351 / 0.258489 (0.147862) | 0.439987 / 0.293841 (0.146146) | 0.032640 / 0.128546 (-0.095906) | 0.008770 / 0.075646 (-0.066877) | 0.072592 / 0.419271 (-0.346680) | 0.050429 / 0.043533 (0.006896) | 0.390873 / 0.255139 (0.135734) | 0.412438 / 0.283200 (0.129239) | 0.027113 / 0.141683 (-0.114570) | 1.458281 / 1.452155 (0.006126) | 1.536819 / 1.492716 (0.044103) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.228309 / 0.018006 (0.210303) | 0.454042 / 0.000490 (0.453552) | 0.000387 / 0.000200 (0.000187) | 0.000055 / 0.000054 (0.000001) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.029573 / 0.037411 (-0.007838) | 0.086433 / 0.014526 (0.071907) | 0.097992 / 0.176557 (-0.078565) | 0.152464 / 0.737135 (-0.584671) | 0.099901 / 0.296338 (-0.196437) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.413807 / 0.215209 (0.198598) | 4.126395 / 2.077655 (2.048740) | 2.113544 / 1.504120 (0.609424) | 1.967829 / 1.541195 (0.426635) | 2.037123 / 1.468490 (0.568633) | 0.489403 / 4.584777 (-4.095374) | 3.689508 / 3.745712 (-0.056204) | 3.503909 / 5.269862 (-1.765952) | 2.113812 / 4.565676 (-2.451864) | 0.057988 / 0.424275 (-0.366287) | 0.007336 / 0.007607 (-0.000271) | 0.490840 / 0.226044 (0.264795) | 4.885040 / 2.268929 (2.616112) | 2.627864 / 55.444624 (-52.816760) | 2.231467 / 6.876477 (-4.645010) | 2.251307 / 2.142072 (0.109235) | 0.577370 / 4.805227 (-4.227857) | 0.131770 / 6.500664 (-6.368895) | 0.061313 / 0.075469 (-0.014156) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.362052 / 1.841788 (-0.479735) | 21.332694 / 8.074308 (13.258386) | 15.562019 / 10.191392 (5.370627) | 0.170874 / 0.680424 (-0.509550) | 0.019226 / 0.534201 (-0.514975) | 0.400311 / 0.579283 (-0.178972) | 0.423060 / 0.434364 (-0.011304) | 0.469946 / 0.540337 (-0.070391) | 0.647745 / 1.386936 (-0.739191) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#aec567c2f224f192e6e1f9799e3afc755eb517b2 \"CML watermark\")\n" ]

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[ "I've opened a PR with a fix. In the meantime, you can avoid the error by deleting `task_templates` with `dataset.info.task_templates = None` before the `interleave_datasets` call.\r\n` " ]

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[ "Ptal @lhoestq :) I tested this manually on a multi-node Databricks cluster", "Hm looks like the check_code_quality failures are unrelated to me change... https://github.com/huggingface/datasets/actions/runs/5536162850/jobs/10103451883?pr=6024", "_The documentation is not available anymore as the PR was closed or merged._", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.005952 / 0.011353 (-0.005400) | 0.003585 / 0.011008 (-0.007424) | 0.079163 / 0.038508 (0.040655) | 0.057926 / 0.023109 (0.034817) | 0.326647 / 0.275898 (0.050749) | 0.383485 / 0.323480 (0.060005) | 0.004530 / 0.007986 (-0.003456) | 0.002821 / 0.004328 (-0.001508) | 0.062071 / 0.004250 (0.057820) | 0.048023 / 0.037052 (0.010971) | 0.329368 / 0.258489 (0.070879) | 0.390877 / 0.293841 (0.097036) | 0.026959 / 0.128546 (-0.101588) | 0.007911 / 0.075646 (-0.067735) | 0.259956 / 0.419271 (-0.159315) | 0.044582 / 0.043533 (0.001049) | 0.320537 / 0.255139 (0.065398) | 0.373814 / 0.283200 (0.090614) | 0.020275 / 0.141683 (-0.121408) | 1.532128 / 1.452155 (0.079973) | 1.595031 / 1.492716 (0.102315) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.186127 / 0.018006 (0.168120) | 0.428586 / 0.000490 (0.428097) | 0.005180 / 0.000200 (0.004980) | 0.000069 / 0.000054 (0.000015) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.024876 / 0.037411 (-0.012536) | 0.072169 / 0.014526 (0.057643) | 0.082015 / 0.176557 (-0.094542) | 0.147467 / 0.737135 (-0.589668) | 0.082769 / 0.296338 (-0.213570) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.410625 / 0.215209 (0.195416) | 4.116742 / 2.077655 (2.039088) | 2.172291 / 1.504120 (0.668171) | 2.022462 / 1.541195 (0.481268) | 2.048142 / 1.468490 (0.579651) | 0.503152 / 4.584777 (-4.081625) | 3.019135 / 3.745712 (-0.726577) | 3.589451 / 5.269862 (-1.680410) | 2.206876 / 4.565676 (-2.358801) | 0.057687 / 0.424275 (-0.366588) | 0.006560 / 0.007607 (-0.001047) | 0.475585 / 0.226044 (0.249541) | 4.784344 / 2.268929 (2.515416) | 2.506322 / 55.444624 (-52.938302) | 2.168251 / 6.876477 (-4.708225) | 2.324453 / 2.142072 (0.182381) | 0.590609 / 4.805227 (-4.214618) | 0.124178 / 6.500664 (-6.376486) | 0.059197 / 0.075469 (-0.016272) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.212359 / 1.841788 (-0.629429) | 17.915843 / 8.074308 (9.841535) | 13.128330 / 10.191392 (2.936938) | 0.144805 / 0.680424 (-0.535618) | 0.016889 / 0.534201 (-0.517312) | 0.344056 / 0.579283 (-0.235227) | 0.359370 / 0.434364 (-0.074994) | 0.404199 / 0.540337 (-0.136138) | 0.549117 / 1.386936 (-0.837819) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.005914 / 0.011353 (-0.005439) | 0.003565 / 0.011008 (-0.007443) | 0.061575 / 0.038508 (0.023067) | 0.057677 / 0.023109 (0.034568) | 0.359753 / 0.275898 (0.083855) | 0.394135 / 0.323480 (0.070655) | 0.004648 / 0.007986 (-0.003338) | 0.002795 / 0.004328 (-0.001534) | 0.061877 / 0.004250 (0.057626) | 0.049673 / 0.037052 (0.012621) | 0.363120 / 0.258489 (0.104631) | 0.402685 / 0.293841 (0.108844) | 0.027021 / 0.128546 (-0.101525) | 0.008006 / 0.075646 (-0.067641) | 0.067398 / 0.419271 (-0.351874) | 0.044442 / 0.043533 (0.000909) | 0.364851 / 0.255139 (0.109712) | 0.387219 / 0.283200 (0.104019) | 0.027267 / 0.141683 (-0.114416) | 1.466675 / 1.452155 (0.014520) | 1.512607 / 1.492716 (0.019891) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.206156 / 0.018006 (0.188150) | 0.410877 / 0.000490 (0.410387) | 0.003061 / 0.000200 (0.002861) | 0.000068 / 0.000054 (0.000013) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.024869 / 0.037411 (-0.012542) | 0.075736 / 0.014526 (0.061210) | 0.083922 / 0.176557 (-0.092634) | 0.139510 / 0.737135 (-0.597626) | 0.087685 / 0.296338 (-0.208654) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.414473 / 0.215209 (0.199264) | 4.150633 / 2.077655 (2.072979) | 2.132892 / 1.504120 (0.628773) | 1.964072 / 1.541195 (0.422878) | 2.003353 / 1.468490 (0.534863) | 0.498012 / 4.584777 (-4.086765) | 3.010135 / 3.745712 (-0.735577) | 2.841130 / 5.269862 (-2.428732) | 1.826013 / 4.565676 (-2.739664) | 0.057443 / 0.424275 (-0.366832) | 0.006374 / 0.007607 (-0.001234) | 0.490337 / 0.226044 (0.264292) | 4.889628 / 2.268929 (2.620700) | 2.575626 / 55.444624 (-52.868998) | 2.246522 / 6.876477 (-4.629955) | 2.276183 / 2.142072 (0.134110) | 0.581465 / 4.805227 (-4.223763) | 0.123877 / 6.500664 (-6.376787) | 0.060339 / 0.075469 (-0.015130) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.333202 / 1.841788 (-0.508585) | 18.363558 / 8.074308 (10.289250) | 14.109356 / 10.191392 (3.917964) | 0.147358 / 0.680424 (-0.533066) | 0.016813 / 0.534201 (-0.517388) | 0.334815 / 0.579283 (-0.244468) | 0.366576 / 0.434364 (-0.067788) | 0.397223 / 0.540337 (-0.143115) | 0.547893 / 1.386936 (-0.839043) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#67ac60bcbebe9ddac70264951b1d584c93003cdf \"CML watermark\")\n" ]

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[ "_The documentation is not available anymore as the PR was closed or merged._", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007108 / 0.011353 (-0.004245) | 0.004446 / 0.011008 (-0.006562) | 0.084013 / 0.038508 (0.045505) | 0.084271 / 0.023109 (0.061162) | 0.324496 / 0.275898 (0.048598) | 0.347783 / 0.323480 (0.024303) | 0.004382 / 0.007986 (-0.003604) | 0.005200 / 0.004328 (0.000872) | 0.065117 / 0.004250 (0.060866) | 0.063368 / 0.037052 (0.026316) | 0.328731 / 0.258489 (0.070242) | 0.356676 / 0.293841 (0.062835) | 0.031155 / 0.128546 (-0.097392) | 0.008672 / 0.075646 (-0.066975) | 0.287573 / 0.419271 (-0.131698) | 0.053692 / 0.043533 (0.010160) | 0.308796 / 0.255139 (0.053657) | 0.330521 / 0.283200 (0.047321) | 0.025010 / 0.141683 (-0.116672) | 1.498968 / 1.452155 (0.046813) | 1.552096 / 1.492716 (0.059380) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.263580 / 0.018006 (0.245574) | 0.559765 / 0.000490 (0.559275) | 0.003450 / 0.000200 (0.003250) | 0.000079 / 0.000054 (0.000024) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.029403 / 0.037411 (-0.008008) | 0.088154 / 0.014526 (0.073628) | 0.100372 / 0.176557 (-0.076185) | 0.157777 / 0.737135 (-0.579359) | 0.102273 / 0.296338 (-0.194066) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.387027 / 0.215209 (0.171818) | 3.854260 / 2.077655 (1.776605) | 1.875159 / 1.504120 (0.371039) | 1.703734 / 1.541195 (0.162539) | 1.814305 / 1.468490 (0.345815) | 0.482524 / 4.584777 (-4.102253) | 3.463602 / 3.745712 (-0.282110) | 4.004766 / 5.269862 (-1.265095) | 2.406751 / 4.565676 (-2.158925) | 0.057069 / 0.424275 (-0.367206) | 0.007448 / 0.007607 (-0.000159) | 0.465801 / 0.226044 (0.239757) | 4.636700 / 2.268929 (2.367771) | 2.329475 / 55.444624 (-53.115150) | 1.998330 / 6.876477 (-4.878146) | 2.264617 / 2.142072 (0.122544) | 0.577998 / 4.805227 (-4.227230) | 0.130846 / 6.500664 (-6.369818) | 0.059713 / 0.075469 (-0.015756) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.275931 / 1.841788 (-0.565857) | 20.396288 / 8.074308 (12.321980) | 13.875242 / 10.191392 (3.683850) | 0.164367 / 0.680424 (-0.516057) | 0.018573 / 0.534201 (-0.515628) | 0.397516 / 0.579283 (-0.181767) | 0.398977 / 0.434364 (-0.035387) | 0.462386 / 0.540337 (-0.077951) | 0.610129 / 1.386936 (-0.776807) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006912 / 0.011353 (-0.004441) | 0.004212 / 0.011008 (-0.006797) | 0.065707 / 0.038508 (0.027199) | 0.090435 / 0.023109 (0.067325) | 0.380539 / 0.275898 (0.104641) | 0.412692 / 0.323480 (0.089212) | 0.005545 / 0.007986 (-0.002441) | 0.003657 / 0.004328 (-0.000672) | 0.065380 / 0.004250 (0.061130) | 0.062901 / 0.037052 (0.025848) | 0.385931 / 0.258489 (0.127442) | 0.416272 / 0.293841 (0.122431) | 0.031974 / 0.128546 (-0.096572) | 0.008783 / 0.075646 (-0.066863) | 0.071424 / 0.419271 (-0.347847) | 0.049454 / 0.043533 (0.005921) | 0.374231 / 0.255139 (0.119092) | 0.386530 / 0.283200 (0.103331) | 0.025404 / 0.141683 (-0.116279) | 1.469869 / 1.452155 (0.017715) | 1.548629 / 1.492716 (0.055913) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.218413 / 0.018006 (0.200406) | 0.573863 / 0.000490 (0.573373) | 0.004156 / 0.000200 (0.003956) | 0.000097 / 0.000054 (0.000043) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.032610 / 0.037411 (-0.004801) | 0.088270 / 0.014526 (0.073744) | 0.106821 / 0.176557 (-0.069735) | 0.164498 / 0.737135 (-0.572638) | 0.106881 / 0.296338 (-0.189457) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.433730 / 0.215209 (0.218520) | 4.323902 / 2.077655 (2.246247) | 2.308607 / 1.504120 (0.804487) | 2.138888 / 1.541195 (0.597693) | 2.246760 / 1.468490 (0.778269) | 0.486863 / 4.584777 (-4.097914) | 3.561826 / 3.745712 (-0.183886) | 5.592685 / 5.269862 (0.322824) | 3.318560 / 4.565676 (-1.247116) | 0.057348 / 0.424275 (-0.366927) | 0.007434 / 0.007607 (-0.000174) | 0.506767 / 0.226044 (0.280723) | 5.083097 / 2.268929 (2.814168) | 2.780618 / 55.444624 (-52.664006) | 2.456924 / 6.876477 (-4.419553) | 2.564184 / 2.142072 (0.422112) | 0.580693 / 4.805227 (-4.224534) | 0.134471 / 6.500664 (-6.366194) | 0.062883 / 0.075469 (-0.012586) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.346618 / 1.841788 (-0.495169) | 20.547998 / 8.074308 (12.473690) | 14.404159 / 10.191392 (4.212767) | 0.176612 / 0.680424 (-0.503812) | 0.018372 / 0.534201 (-0.515829) | 0.395636 / 0.579283 (-0.183647) | 0.410661 / 0.434364 (-0.023703) | 0.468782 / 0.540337 (-0.071555) | 0.637476 / 1.386936 (-0.749460) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#0172d4dac0ca823e8bd293cfd4d28e78d92efe42 \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.009896 / 0.011353 (-0.001457) | 0.004658 / 0.011008 (-0.006351) | 0.101185 / 0.038508 (0.062677) | 0.075480 / 0.023109 (0.052371) | 0.410620 / 0.275898 (0.134722) | 0.470639 / 0.323480 (0.147159) | 0.007042 / 0.007986 (-0.000943) | 0.003909 / 0.004328 (-0.000419) | 0.079676 / 0.004250 (0.075425) | 0.066921 / 0.037052 (0.029869) | 0.423624 / 0.258489 (0.165135) | 0.473008 / 0.293841 (0.179167) | 0.048492 / 0.128546 (-0.080054) | 0.012833 / 0.075646 (-0.062813) | 0.335286 / 0.419271 (-0.083985) | 0.083506 / 0.043533 (0.039973) | 0.401918 / 0.255139 (0.146779) | 0.467975 / 0.283200 (0.184775) | 0.050025 / 0.141683 (-0.091658) | 1.679392 / 1.452155 (0.227237) | 1.852812 / 1.492716 (0.360095) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.248067 / 0.018006 (0.230061) | 0.584818 / 0.000490 (0.584328) | 0.021558 / 0.000200 (0.021358) | 0.000104 / 0.000054 (0.000050) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.028572 / 0.037411 (-0.008839) | 0.097212 / 0.014526 (0.082686) | 0.121675 / 0.176557 (-0.054881) | 0.186597 / 0.737135 (-0.550538) | 0.122285 / 0.296338 (-0.174053) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.586279 / 0.215209 (0.371070) | 5.634402 / 2.077655 (3.556747) | 2.560648 / 1.504120 (1.056528) | 2.288796 / 1.541195 (0.747601) | 2.402580 / 1.468490 (0.934090) | 0.801453 / 4.584777 (-3.783324) | 5.036654 / 3.745712 (1.290942) | 8.319972 / 5.269862 (3.050110) | 4.665620 / 4.565676 (0.099944) | 0.107292 / 0.424275 (-0.316983) | 0.009206 / 0.007607 (0.001599) | 0.766505 / 0.226044 (0.540461) | 7.333784 / 2.268929 (5.064856) | 3.601875 / 55.444624 (-51.842749) | 2.886388 / 6.876477 (-3.990089) | 3.231797 / 2.142072 (1.089725) | 1.179509 / 4.805227 (-3.625718) | 0.224656 / 6.500664 (-6.276008) | 0.084749 / 0.075469 (0.009280) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.772345 / 1.841788 (-0.069443) | 24.138788 / 8.074308 (16.064480) | 20.712416 / 10.191392 (10.521024) | 0.254655 / 0.680424 (-0.425769) | 0.028858 / 0.534201 (-0.505343) | 0.499314 / 0.579283 (-0.079969) | 0.605797 / 0.434364 (0.171433) | 0.567628 / 0.540337 (0.027290) | 0.752288 / 1.386936 (-0.634648) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.010134 / 0.011353 (-0.001219) | 0.004630 / 0.011008 (-0.006378) | 0.082282 / 0.038508 (0.043774) | 0.081722 / 0.023109 (0.058613) | 0.465018 / 0.275898 (0.189120) | 0.516392 / 0.323480 (0.192912) | 0.006618 / 0.007986 (-0.001368) | 0.004310 / 0.004328 (-0.000018) | 0.078990 / 0.004250 (0.074739) | 0.077729 / 0.037052 (0.040677) | 0.464892 / 0.258489 (0.206403) | 0.510551 / 0.293841 (0.216710) | 0.050750 / 0.128546 (-0.077796) | 0.014402 / 0.075646 (-0.061244) | 0.092587 / 0.419271 (-0.326685) | 0.074769 / 0.043533 (0.031237) | 0.468591 / 0.255139 (0.213452) | 0.508138 / 0.283200 (0.224938) | 0.047774 / 0.141683 (-0.093909) | 1.798354 / 1.452155 (0.346199) | 1.851431 / 1.492716 (0.358714) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.282528 / 0.018006 (0.264522) | 0.588286 / 0.000490 (0.587797) | 0.004892 / 0.000200 (0.004692) | 0.000136 / 0.000054 (0.000082) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.037048 / 0.037411 (-0.000364) | 0.101513 / 0.014526 (0.086987) | 0.133238 / 0.176557 (-0.043319) | 0.234799 / 0.737135 (-0.502336) | 0.120636 / 0.296338 (-0.175703) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.615377 / 0.215209 (0.400168) | 6.225717 / 2.077655 (4.148062) | 2.974137 / 1.504120 (1.470018) | 2.642168 / 1.541195 (1.100973) | 2.706051 / 1.468490 (1.237561) | 0.837171 / 4.584777 (-3.747606) | 5.143368 / 3.745712 (1.397656) | 4.560241 / 5.269862 (-0.709621) | 2.838375 / 4.565676 (-1.727301) | 0.092505 / 0.424275 (-0.331770) | 0.008962 / 0.007607 (0.001355) | 0.726361 / 0.226044 (0.500317) | 7.323998 / 2.268929 (5.055070) | 3.650531 / 55.444624 (-51.794094) | 2.960886 / 6.876477 (-3.915591) | 3.003889 / 2.142072 (0.861816) | 0.979264 / 4.805227 (-3.825963) | 0.204531 / 6.500664 (-6.296133) | 0.078285 / 0.075469 (0.002816) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.774225 / 1.841788 (-0.067563) | 26.399536 / 8.074308 (18.325228) | 22.312890 / 10.191392 (12.121498) | 0.244651 / 0.680424 (-0.435773) | 0.026950 / 0.534201 (-0.507251) | 0.493037 / 0.579283 (-0.086246) | 0.620399 / 0.434364 (0.186036) | 0.748985 / 0.540337 (0.208648) | 0.799766 / 1.386936 (-0.587170) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#a49ac2864177ec4fb34c43b59a6e49de1f21f973 \"CML watermark\")\n" ]

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[ "Thanks for reporting! I've opened a PR with a fix." ]

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[ "_The documentation is not available anymore as the PR was closed or merged._", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007697 / 0.011353 (-0.003656) | 0.004233 / 0.011008 (-0.006776) | 0.087890 / 0.038508 (0.049382) | 0.065305 / 0.023109 (0.042196) | 0.366919 / 0.275898 (0.091020) | 0.399656 / 0.323480 (0.076176) | 0.006753 / 0.007986 (-0.001232) | 0.003428 / 0.004328 (-0.000900) | 0.070180 / 0.004250 (0.065930) | 0.054164 / 0.037052 (0.017112) | 0.377130 / 0.258489 (0.118641) | 0.403456 / 0.293841 (0.109615) | 0.042639 / 0.128546 (-0.085907) | 0.012396 / 0.075646 (-0.063250) | 0.314235 / 0.419271 (-0.105036) | 0.061976 / 0.043533 (0.018443) | 0.376959 / 0.255139 (0.121820) | 0.433313 / 0.283200 (0.150113) | 0.031253 / 0.141683 (-0.110430) | 1.555749 / 1.452155 (0.103594) | 1.643905 / 1.492716 (0.151189) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.208630 / 0.018006 (0.190624) | 0.519532 / 0.000490 (0.519042) | 0.003719 / 0.000200 (0.003519) | 0.000099 / 0.000054 (0.000045) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.027403 / 0.037411 (-0.010008) | 0.080990 / 0.014526 (0.066464) | 0.090424 / 0.176557 (-0.086133) | 0.153922 / 0.737135 (-0.583213) | 0.098156 / 0.296338 (-0.198183) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.519453 / 0.215209 (0.304244) | 5.100089 / 2.077655 (3.022434) | 2.212165 / 1.504120 (0.708045) | 1.894405 / 1.541195 (0.353210) | 1.922914 / 1.468490 (0.454424) | 0.762443 / 4.584777 (-3.822334) | 4.669214 / 3.745712 (0.923502) | 5.016066 / 5.269862 (-0.253796) | 3.128821 / 4.565676 (-1.436856) | 0.091541 / 0.424275 (-0.332734) | 0.007582 / 0.007607 (-0.000026) | 0.652753 / 0.226044 (0.426709) | 6.601375 / 2.268929 (4.332446) | 3.076948 / 55.444624 (-52.367677) | 2.250544 / 6.876477 (-4.625933) | 2.404059 / 2.142072 (0.261987) | 0.994917 / 4.805227 (-3.810311) | 0.200318 / 6.500664 (-6.300346) | 0.069354 / 0.075469 (-0.006115) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.482559 / 1.841788 (-0.359229) | 20.722092 / 8.074308 (12.647784) | 17.703217 / 10.191392 (7.511825) | 0.215370 / 0.680424 (-0.465053) | 0.028208 / 0.534201 (-0.505993) | 0.425992 / 0.579283 (-0.153291) | 0.492785 / 0.434364 (0.058421) | 0.474154 / 0.540337 (-0.066183) | 0.644599 / 1.386936 (-0.742337) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.008372 / 0.011353 (-0.002981) | 0.004543 / 0.011008 (-0.006465) | 0.070564 / 0.038508 (0.032056) | 0.066855 / 0.023109 (0.043746) | 0.386724 / 0.275898 (0.110826) | 0.432184 / 0.323480 (0.108704) | 0.005250 / 0.007986 (-0.002736) | 0.003630 / 0.004328 (-0.000698) | 0.069310 / 0.004250 (0.065060) | 0.055759 / 0.037052 (0.018707) | 0.375789 / 0.258489 (0.117299) | 0.417335 / 0.293841 (0.123494) | 0.043424 / 0.128546 (-0.085122) | 0.013106 / 0.075646 (-0.062541) | 0.087836 / 0.419271 (-0.331436) | 0.057770 / 0.043533 (0.014237) | 0.396694 / 0.255139 (0.141555) | 0.439350 / 0.283200 (0.156150) | 0.031660 / 0.141683 (-0.110023) | 1.571339 / 1.452155 (0.119185) | 1.667169 / 1.492716 (0.174452) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.180534 / 0.018006 (0.162528) | 0.540027 / 0.000490 (0.539537) | 0.003573 / 0.000200 (0.003373) | 0.000141 / 0.000054 (0.000086) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.031380 / 0.037411 (-0.006032) | 0.083762 / 0.014526 (0.069236) | 0.098166 / 0.176557 (-0.078390) | 0.160761 / 0.737135 (-0.576374) | 0.097683 / 0.296338 (-0.198656) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.568074 / 0.215209 (0.352865) | 5.660544 / 2.077655 (3.582889) | 2.416698 / 1.504120 (0.912578) | 2.177096 / 1.541195 (0.635901) | 2.206178 / 1.468490 (0.737688) | 0.844864 / 4.584777 (-3.739912) | 4.793636 / 3.745712 (1.047923) | 7.062387 / 5.269862 (1.792525) | 4.201228 / 4.565676 (-0.364449) | 0.091997 / 0.424275 (-0.332279) | 0.007881 / 0.007607 (0.000274) | 0.679466 / 0.226044 (0.453422) | 6.580268 / 2.268929 (4.311340) | 3.229907 / 55.444624 (-52.214717) | 2.524877 / 6.876477 (-4.351600) | 2.463796 / 2.142072 (0.321723) | 0.975627 / 4.805227 (-3.829600) | 0.186670 / 6.500664 (-6.313994) | 0.065307 / 0.075469 (-0.010163) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.501447 / 1.841788 (-0.340340) | 21.231037 / 8.074308 (13.156729) | 17.591671 / 10.191392 (7.400279) | 0.212745 / 0.680424 (-0.467679) | 0.026100 / 0.534201 (-0.508101) | 0.428391 / 0.579283 (-0.150892) | 0.535268 / 0.434364 (0.100904) | 0.506733 / 0.540337 (-0.033604) | 0.660832 / 1.386936 (-0.726104) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#962537d7ee9191438ef47a4185d0ba626b2ee949 \"CML watermark\")\n" ]

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[ "This scenario currently requires explicitly passing the target features (to avoid the error): \r\n```python\r\nimport datasets\r\n\r\n...\r\n\r\nfeatures = dataset.features\r\nfeatures[\"output\"] = = [{\"test\": datasets.Value(\"int64\")}]\r\ntest2 = dataset.map(lambda row, idx: test_func(row, idx), with_indices=True, num_proc=32, features=features)\r\n```", "I just encountered the same error in the same situation (multiprocessing with variable length outputs).\r\n\r\nThe funny (or dangerous?) thing is, that this error only showed up when testing with a small test dataset (16 examples, ValueError with `num_proc` >1) but the same code works fine for the full dataset (~70k examples).\r\n\r\n@mariosasko Any idea on how to do that with a nested feature with lists of variable lengths containing dicts?\r\n\r\nEDIT: Was able to narrow it down: >200 Examples: no error, <150 Examples: Error. \r\nNow idea what to make of this but pretty obvious that this is a bug....", "This error also occurs while concatenating the datasets." ]

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[ "_The documentation is not available anymore as the PR was closed or merged._", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007782 / 0.011353 (-0.003571) | 0.004451 / 0.011008 (-0.006557) | 0.099928 / 0.038508 (0.061420) | 0.081534 / 0.023109 (0.058425) | 0.379382 / 0.275898 (0.103484) | 0.410652 / 0.323480 (0.087172) | 0.005967 / 0.007986 (-0.002019) | 0.003702 / 0.004328 (-0.000627) | 0.076359 / 0.004250 (0.072109) | 0.066721 / 0.037052 (0.029669) | 0.383595 / 0.258489 (0.125106) | 0.423854 / 0.293841 (0.130013) | 0.032796 / 0.128546 (-0.095750) | 0.009728 / 0.075646 (-0.065918) | 0.344347 / 0.419271 (-0.074925) | 0.056320 / 0.043533 (0.012788) | 0.379974 / 0.255139 (0.124835) | 0.401294 / 0.283200 (0.118094) | 0.024110 / 0.141683 (-0.117572) | 1.804194 / 1.452155 (0.352039) | 1.860240 / 1.492716 (0.367523) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.233803 / 0.018006 (0.215797) | 0.506893 / 0.000490 (0.506404) | 0.003894 / 0.000200 (0.003694) | 0.000090 / 0.000054 (0.000035) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.033328 / 0.037411 (-0.004083) | 0.098661 / 0.014526 (0.084136) | 0.114971 / 0.176557 (-0.061586) | 0.186815 / 0.737135 (-0.550321) | 0.115490 / 0.296338 (-0.180848) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.422590 / 0.215209 (0.207381) | 4.277189 / 2.077655 (2.199535) | 2.095565 / 1.504120 (0.591445) | 2.040825 / 1.541195 (0.499630) | 2.162562 / 1.468490 (0.694072) | 0.578602 / 4.584777 (-4.006175) | 4.203474 / 3.745712 (0.457762) | 6.674595 / 5.269862 (1.404734) | 3.913251 / 4.565676 (-0.652426) | 0.067777 / 0.424275 (-0.356498) | 0.008716 / 0.007607 (0.001109) | 0.548704 / 0.226044 (0.322660) | 5.162120 / 2.268929 (2.893192) | 2.600250 / 55.444624 (-52.844374) | 2.232730 / 6.876477 (-4.643747) | 2.485617 / 2.142072 (0.343544) | 0.650872 / 4.805227 (-4.154355) | 0.148022 / 6.500664 (-6.352642) | 0.064795 / 0.075469 (-0.010674) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.399439 / 1.841788 (-0.442349) | 22.438959 / 8.074308 (14.364651) | 16.447831 / 10.191392 (6.256439) | 0.202003 / 0.680424 (-0.478421) | 0.026200 / 0.534201 (-0.508001) | 0.472966 / 0.579283 (-0.106317) | 0.491621 / 0.434364 (0.057257) | 0.551580 / 0.540337 (0.011242) | 0.751420 / 1.386936 (-0.635516) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007241 / 0.011353 (-0.004112) | 0.004434 / 0.011008 (-0.006574) | 0.075872 / 0.038508 (0.037364) | 0.080094 / 0.023109 (0.056985) | 0.459244 / 0.275898 (0.183346) | 0.492482 / 0.323480 (0.169002) | 0.005791 / 0.007986 (-0.002194) | 0.003657 / 0.004328 (-0.000671) | 0.075214 / 0.004250 (0.070964) | 0.064208 / 0.037052 (0.027156) | 0.464195 / 0.258489 (0.205706) | 0.497809 / 0.293841 (0.203968) | 0.036301 / 0.128546 (-0.092245) | 0.009855 / 0.075646 (-0.065791) | 0.080826 / 0.419271 (-0.338445) | 0.056700 / 0.043533 (0.013167) | 0.452850 / 0.255139 (0.197711) | 0.490738 / 0.283200 (0.207538) | 0.024145 / 0.141683 (-0.117538) | 1.689911 / 1.452155 (0.237757) | 1.789803 / 1.492716 (0.297087) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.247741 / 0.018006 (0.229735) | 0.486769 / 0.000490 (0.486279) | 0.000418 / 0.000200 (0.000218) | 0.000060 / 0.000054 (0.000005) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.036317 / 0.037411 (-0.001094) | 0.104943 / 0.014526 (0.090417) | 0.120972 / 0.176557 (-0.055585) | 0.188461 / 0.737135 (-0.548674) | 0.120926 / 0.296338 (-0.175412) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.465788 / 0.215209 (0.250579) | 4.662369 / 2.077655 (2.584714) | 2.442241 / 1.504120 (0.938121) | 2.266328 / 1.541195 (0.725133) | 2.438998 / 1.468490 (0.970508) | 0.531384 / 4.584777 (-4.053393) | 4.125286 / 3.745712 (0.379574) | 3.920912 / 5.269862 (-1.348950) | 2.292149 / 4.565676 (-2.273528) | 0.070146 / 0.424275 (-0.354129) | 0.008887 / 0.007607 (0.001280) | 0.598181 / 0.226044 (0.372137) | 5.726454 / 2.268929 (3.457526) | 3.081836 / 55.444624 (-52.362788) | 2.683508 / 6.876477 (-4.192969) | 2.587350 / 2.142072 (0.445278) | 0.604736 / 4.805227 (-4.200491) | 0.141303 / 6.500664 (-6.359362) | 0.065020 / 0.075469 (-0.010449) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.481850 / 1.841788 (-0.359938) | 22.259592 / 8.074308 (14.185284) | 16.304290 / 10.191392 (6.112898) | 0.173514 / 0.680424 (-0.506909) | 0.021590 / 0.534201 (-0.512611) | 0.471753 / 0.579283 (-0.107531) | 0.472132 / 0.434364 (0.037768) | 0.563344 / 0.540337 (0.023007) | 0.738509 / 1.386936 (-0.648427) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#1cb7ae56dbd814945a4982c63bf0e50859a7b93a \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.005910 / 0.011353 (-0.005443) | 0.004372 / 0.011008 (-0.006636) | 0.081583 / 0.038508 (0.043075) | 0.069598 / 0.023109 (0.046488) | 0.346360 / 0.275898 (0.070462) | 0.360733 / 0.323480 (0.037254) | 0.004725 / 0.007986 (-0.003261) | 0.003106 / 0.004328 (-0.001222) | 0.059916 / 0.004250 (0.055666) | 0.053242 / 0.037052 (0.016189) | 0.353551 / 0.258489 (0.095062) | 0.373052 / 0.293841 (0.079211) | 0.029036 / 0.128546 (-0.099510) | 0.007894 / 0.075646 (-0.067753) | 0.284131 / 0.419271 (-0.135140) | 0.049348 / 0.043533 (0.005815) | 0.347409 / 0.255139 (0.092270) | 0.355029 / 0.283200 (0.071830) | 0.022511 / 0.141683 (-0.119171) | 1.454495 / 1.452155 (0.002340) | 1.439551 / 1.492716 (-0.053166) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.218889 / 0.018006 (0.200883) | 0.478734 / 0.000490 (0.478244) | 0.003758 / 0.000200 (0.003558) | 0.000083 / 0.000054 (0.000029) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.025759 / 0.037411 (-0.011653) | 0.082511 / 0.014526 (0.067985) | 0.087578 / 0.176557 (-0.088979) | 0.137760 / 0.737135 (-0.599375) | 0.093312 / 0.296338 (-0.203027) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.378963 / 0.215209 (0.163754) | 3.645846 / 2.077655 (1.568191) | 1.741135 / 1.504120 (0.237015) | 1.599166 / 1.541195 (0.057972) | 1.610817 / 1.468490 (0.142327) | 0.459209 / 4.584777 (-4.125568) | 3.484857 / 3.745712 (-0.260855) | 3.928109 / 5.269862 (-1.341752) | 2.419784 / 4.565676 (-2.145892) | 0.051987 / 0.424275 (-0.372288) | 0.006495 / 0.007607 (-0.001112) | 0.427311 / 0.226044 (0.201267) | 4.226378 / 2.268929 (1.957450) | 2.212331 / 55.444624 (-53.232293) | 1.916213 / 6.876477 (-4.960264) | 1.978809 / 2.142072 (-0.163263) | 0.547351 / 4.805227 (-4.257876) | 0.121110 / 6.500664 (-6.379554) | 0.054163 / 0.075469 (-0.021306) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.228594 / 1.841788 (-0.613193) | 19.410901 / 8.074308 (11.336593) | 13.014722 / 10.191392 (2.823330) | 0.156449 / 0.680424 (-0.523975) | 0.021032 / 0.534201 (-0.513169) | 0.403976 / 0.579283 (-0.175307) | 0.413885 / 0.434364 (-0.020479) | 0.470465 / 0.540337 (-0.069873) | 0.641322 / 1.386936 (-0.745614) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007210 / 0.011353 (-0.004143) | 0.003824 / 0.011008 (-0.007185) | 0.058227 / 0.038508 (0.019719) | 0.076211 / 0.023109 (0.053102) | 0.336626 / 0.275898 (0.060728) | 0.420542 / 0.323480 (0.097062) | 0.006178 / 0.007986 (-0.001808) | 0.003332 / 0.004328 (-0.000997) | 0.058073 / 0.004250 (0.053823) | 0.062485 / 0.037052 (0.025432) | 0.386175 / 0.258489 (0.127686) | 0.415659 / 0.293841 (0.121818) | 0.031264 / 0.128546 (-0.097282) | 0.007502 / 0.075646 (-0.068144) | 0.072079 / 0.419271 (-0.347192) | 0.055860 / 0.043533 (0.012327) | 0.343508 / 0.255139 (0.088369) | 0.437844 / 0.283200 (0.154645) | 0.032852 / 0.141683 (-0.108831) | 1.409241 / 1.452155 (-0.042913) | 1.623949 / 1.492716 (0.131233) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.207511 / 0.018006 (0.189504) | 0.464149 / 0.000490 (0.463660) | 0.003248 / 0.000200 (0.003048) | 0.000226 / 0.000054 (0.000172) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.030767 / 0.037411 (-0.006645) | 0.079169 / 0.014526 (0.064643) | 0.093111 / 0.176557 (-0.083445) | 0.153369 / 0.737135 (-0.583767) | 0.092939 / 0.296338 (-0.203400) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.375602 / 0.215209 (0.160392) | 3.968612 / 2.077655 (1.890957) | 2.081749 / 1.504120 (0.577629) | 1.899772 / 1.541195 (0.358577) | 1.847923 / 1.468490 (0.379433) | 0.442867 / 4.584777 (-4.141910) | 3.646664 / 3.745712 (-0.099048) | 5.870600 / 5.269862 (0.600739) | 3.356698 / 4.565676 (-1.208979) | 0.051422 / 0.424275 (-0.372853) | 0.006006 / 0.007607 (-0.001601) | 0.442439 / 0.226044 (0.216395) | 4.466256 / 2.268929 (2.197328) | 2.483832 / 55.444624 (-52.960792) | 2.105612 / 6.876477 (-4.770865) | 2.060650 / 2.142072 (-0.081422) | 0.531119 / 4.805227 (-4.274108) | 0.123436 / 6.500664 (-6.377228) | 0.059838 / 0.075469 (-0.015632) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.283042 / 1.841788 (-0.558746) | 19.688251 / 8.074308 (11.613943) | 13.346386 / 10.191392 (3.154994) | 0.197463 / 0.680424 (-0.482961) | 0.018484 / 0.534201 (-0.515717) | 0.391727 / 0.579283 (-0.187556) | 0.425061 / 0.434364 (-0.009303) | 0.448177 / 0.540337 (-0.092160) | 0.653694 / 1.386936 (-0.733242) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#01604752fe89d290479fa406b1a24ac1f346826e \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.008966 / 0.011353 (-0.002387) | 0.005195 / 0.011008 (-0.005813) | 0.102879 / 0.038508 (0.064371) | 0.090902 / 0.023109 (0.067792) | 0.434397 / 0.275898 (0.158498) | 0.454013 / 0.323480 (0.130534) | 0.008507 / 0.007986 (0.000521) | 0.005000 / 0.004328 (0.000671) | 0.075789 / 0.004250 (0.071538) | 0.067608 / 0.037052 (0.030555) | 0.435091 / 0.258489 (0.176602) | 0.469411 / 0.293841 (0.175570) | 0.050859 / 0.128546 (-0.077687) | 0.013560 / 0.075646 (-0.062086) | 0.345473 / 0.419271 (-0.073799) | 0.094974 / 0.043533 (0.051441) | 0.429626 / 0.255139 (0.174487) | 0.434290 / 0.283200 (0.151090) | 0.052269 / 0.141683 (-0.089413) | 1.700549 / 1.452155 (0.248395) | 1.890693 / 1.492716 (0.397976) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.296618 / 0.018006 (0.278612) | 0.613908 / 0.000490 (0.613419) | 0.000484 / 0.000200 (0.000284) | 0.000086 / 0.000054 (0.000032) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.034346 / 0.037411 (-0.003065) | 0.096836 / 0.014526 (0.082310) | 0.113332 / 0.176557 (-0.063224) | 0.194464 / 0.737135 (-0.542671) | 0.111732 / 0.296338 (-0.184606) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.624954 / 0.215209 (0.409745) | 6.442193 / 2.077655 (4.364538) | 2.818331 / 1.504120 (1.314211) | 2.529607 / 1.541195 (0.988413) | 2.549026 / 1.468490 (1.080536) | 0.967367 / 4.584777 (-3.617410) | 5.446885 / 3.745712 (1.701173) | 6.259099 / 5.269862 (0.989237) | 3.652936 / 4.565676 (-0.912740) | 0.106420 / 0.424275 (-0.317855) | 0.011293 / 0.007607 (0.003686) | 0.772026 / 0.226044 (0.545982) | 7.823986 / 2.268929 (5.555057) | 3.725328 / 55.444624 (-51.719297) | 2.851489 / 6.876477 (-4.024988) | 3.013722 / 2.142072 (0.871649) | 1.045090 / 4.805227 (-3.760137) | 0.213174 / 6.500664 (-6.287490) | 0.077104 / 0.075469 (0.001635) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.657135 / 1.841788 (-0.184652) | 24.547604 / 8.074308 (16.473296) | 19.989533 / 10.191392 (9.798141) | 0.257139 / 0.680424 (-0.423285) | 0.028448 / 0.534201 (-0.505753) | 0.490801 / 0.579283 (-0.088482) | 0.628072 / 0.434364 (0.193708) | 0.584873 / 0.540337 (0.044536) | 0.825258 / 1.386936 (-0.561678) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.009258 / 0.011353 (-0.002095) | 0.005660 / 0.011008 (-0.005348) | 0.080577 / 0.038508 (0.042069) | 0.095786 / 0.023109 (0.072676) | 0.473334 / 0.275898 (0.197436) | 0.527962 / 0.323480 (0.204482) | 0.006537 / 0.007986 (-0.001449) | 0.004411 / 0.004328 (0.000083) | 0.080702 / 0.004250 (0.076452) | 0.077020 / 0.037052 (0.039968) | 0.483205 / 0.258489 (0.224716) | 0.556916 / 0.293841 (0.263076) | 0.047670 / 0.128546 (-0.080877) | 0.016647 / 0.075646 (-0.058999) | 0.090653 / 0.419271 (-0.328619) | 0.062122 / 0.043533 (0.018589) | 0.498326 / 0.255139 (0.243187) | 0.546572 / 0.283200 (0.263372) | 0.037525 / 0.141683 (-0.104157) | 1.869520 / 1.452155 (0.417365) | 1.915335 / 1.492716 (0.422619) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.248287 / 0.018006 (0.230281) | 0.611440 / 0.000490 (0.610950) | 0.004102 / 0.000200 (0.003902) | 0.000132 / 0.000054 (0.000078) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.038228 / 0.037411 (0.000817) | 0.103510 / 0.014526 (0.088984) | 0.114337 / 0.176557 (-0.062219) | 0.189662 / 0.737135 (-0.547473) | 0.119078 / 0.296338 (-0.177260) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.606622 / 0.215209 (0.391413) | 6.053900 / 2.077655 (3.976246) | 2.857972 / 1.504120 (1.353852) | 2.549756 / 1.541195 (1.008561) | 2.584557 / 1.468490 (1.116067) | 0.930431 / 4.584777 (-3.654346) | 5.524077 / 3.745712 (1.778365) | 7.858406 / 5.269862 (2.588545) | 4.890697 / 4.565676 (0.325020) | 0.095356 / 0.424275 (-0.328919) | 0.008614 / 0.007607 (0.001007) | 0.774227 / 0.226044 (0.548182) | 7.470215 / 2.268929 (5.201287) | 3.784820 / 55.444624 (-51.659805) | 3.199364 / 6.876477 (-3.677113) | 3.212002 / 2.142072 (1.069929) | 1.054104 / 4.805227 (-3.751123) | 0.226044 / 6.500664 (-6.274620) | 0.092237 / 0.075469 (0.016768) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.801054 / 1.841788 (-0.040734) | 24.220404 / 8.074308 (16.146096) | 21.652936 / 10.191392 (11.461544) | 0.247004 / 0.680424 (-0.433420) | 0.029651 / 0.534201 (-0.504550) | 0.475702 / 0.579283 (-0.103581) | 0.621121 / 0.434364 (0.186757) | 0.570489 / 0.540337 (0.030151) | 0.768840 / 1.386936 (-0.618096) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#b2fc21eda345643fb57d1d1167ebed9043310911 \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.009223 / 0.011353 (-0.002130) | 0.005750 / 0.011008 (-0.005258) | 0.105264 / 0.038508 (0.066756) | 0.088478 / 0.023109 (0.065369) | 0.461119 / 0.275898 (0.185221) | 0.481115 / 0.323480 (0.157636) | 0.006366 / 0.007986 (-0.001619) | 0.004515 / 0.004328 (0.000186) | 0.079296 / 0.004250 (0.075045) | 0.063483 / 0.037052 (0.026430) | 0.444490 / 0.258489 (0.186001) | 0.496474 / 0.293841 (0.202634) | 0.048568 / 0.128546 (-0.079978) | 0.013574 / 0.075646 (-0.062073) | 0.379213 / 0.419271 (-0.040059) | 0.086464 / 0.043533 (0.042932) | 0.437526 / 0.255139 (0.182387) | 0.447117 / 0.283200 (0.163917) | 0.049502 / 0.141683 (-0.092180) | 1.749146 / 1.452155 (0.296992) | 1.831082 / 1.492716 (0.338365) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.268205 / 0.018006 (0.250199) | 0.627406 / 0.000490 (0.626917) | 0.005439 / 0.000200 (0.005239) | 0.000128 / 0.000054 (0.000074) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.030564 / 0.037411 (-0.006848) | 0.096365 / 0.014526 (0.081840) | 0.117484 / 0.176557 (-0.059072) | 0.189104 / 0.737135 (-0.548032) | 0.118073 / 0.296338 (-0.178266) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.618229 / 0.215209 (0.403019) | 6.437853 / 2.077655 (4.360199) | 2.789946 / 1.504120 (1.285826) | 2.339245 / 1.541195 (0.798050) | 2.588779 / 1.468490 (1.120289) | 0.921008 / 4.584777 (-3.663769) | 5.402940 / 3.745712 (1.657227) | 4.818783 / 5.269862 (-0.451078) | 3.162259 / 4.565676 (-1.403417) | 0.108501 / 0.424275 (-0.315774) | 0.009384 / 0.007607 (0.001777) | 0.766811 / 0.226044 (0.540766) | 7.624629 / 2.268929 (5.355701) | 3.442420 / 55.444624 (-52.002204) | 2.759967 / 6.876477 (-4.116510) | 3.049644 / 2.142072 (0.907572) | 1.113308 / 4.805227 (-3.691919) | 0.223923 / 6.500664 (-6.276741) | 0.079156 / 0.075469 (0.003687) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.683318 / 1.841788 (-0.158470) | 25.062141 / 8.074308 (16.987833) | 21.777131 / 10.191392 (11.585739) | 0.266939 / 0.680424 (-0.413485) | 0.029670 / 0.534201 (-0.504531) | 0.476761 / 0.579283 (-0.102522) | 0.622080 / 0.434364 (0.187716) | 0.601781 / 0.540337 (0.061443) | 0.785126 / 1.386936 (-0.601811) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.010198 / 0.011353 (-0.001155) | 0.005777 / 0.011008 (-0.005231) | 0.083003 / 0.038508 (0.044495) | 0.093411 / 0.023109 (0.070302) | 0.496178 / 0.275898 (0.220280) | 0.554670 / 0.323480 (0.231190) | 0.008351 / 0.007986 (0.000365) | 0.004678 / 0.004328 (0.000350) | 0.083631 / 0.004250 (0.079381) | 0.075538 / 0.037052 (0.038485) | 0.492410 / 0.258489 (0.233921) | 0.545209 / 0.293841 (0.251368) | 0.048365 / 0.128546 (-0.080181) | 0.014219 / 0.075646 (-0.061427) | 0.100749 / 0.419271 (-0.318523) | 0.063431 / 0.043533 (0.019898) | 0.511115 / 0.255139 (0.255976) | 0.532965 / 0.283200 (0.249765) | 0.037968 / 0.141683 (-0.103715) | 1.940268 / 1.452155 (0.488113) | 2.032934 / 1.492716 (0.540217) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.238179 / 0.018006 (0.220172) | 0.605767 / 0.000490 (0.605277) | 0.004033 / 0.000200 (0.003833) | 0.000125 / 0.000054 (0.000071) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.036436 / 0.037411 (-0.000975) | 0.108034 / 0.014526 (0.093509) | 0.118624 / 0.176557 (-0.057933) | 0.183079 / 0.737135 (-0.554056) | 0.121739 / 0.296338 (-0.174600) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.630538 / 0.215209 (0.415329) | 6.552184 / 2.077655 (4.474529) | 3.003412 / 1.504120 (1.499292) | 2.669026 / 1.541195 (1.127832) | 2.791109 / 1.468490 (1.322619) | 0.884003 / 4.584777 (-3.700774) | 5.538660 / 3.745712 (1.792947) | 5.126708 / 5.269862 (-0.143154) | 3.120825 / 4.565676 (-1.444852) | 0.101178 / 0.424275 (-0.323097) | 0.009027 / 0.007607 (0.001420) | 0.785914 / 0.226044 (0.559869) | 7.994720 / 2.268929 (5.725792) | 4.061996 / 55.444624 (-51.382629) | 3.263230 / 6.876477 (-3.613247) | 3.288622 / 2.142072 (1.146550) | 1.141867 / 4.805227 (-3.663360) | 0.255287 / 6.500664 (-6.245378) | 0.100637 / 0.075469 (0.025168) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.769821 / 1.841788 (-0.071967) | 24.994008 / 8.074308 (16.919700) | 21.765971 / 10.191392 (11.574579) | 0.268493 / 0.680424 (-0.411931) | 0.028047 / 0.534201 (-0.506154) | 0.489472 / 0.579283 (-0.089811) | 0.594809 / 0.434364 (0.160445) | 0.613578 / 0.540337 (0.073241) | 0.879360 / 1.386936 (-0.507576) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#b85b1154aef2a9ab4d558f60d91623f2cc1583c4 \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006003 / 0.011353 (-0.005350) | 0.003590 / 0.011008 (-0.007418) | 0.084657 / 0.038508 (0.046149) | 0.057884 / 0.023109 (0.034775) | 0.318347 / 0.275898 (0.042449) | 0.345976 / 0.323480 (0.022496) | 0.004706 / 0.007986 (-0.003279) | 0.002921 / 0.004328 (-0.001407) | 0.061850 / 0.004250 (0.057600) | 0.050558 / 0.037052 (0.013505) | 0.320877 / 0.258489 (0.062388) | 0.356062 / 0.293841 (0.062222) | 0.027511 / 0.128546 (-0.101035) | 0.007954 / 0.075646 (-0.067693) | 0.260290 / 0.419271 (-0.158981) | 0.051207 / 0.043533 (0.007674) | 0.334423 / 0.255139 (0.079284) | 0.338575 / 0.283200 (0.055375) | 0.022330 / 0.141683 (-0.119353) | 1.445446 / 1.452155 (-0.006709) | 1.500626 / 1.492716 (0.007910) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.192440 / 0.018006 (0.174433) | 0.428455 / 0.000490 (0.427965) | 0.000318 / 0.000200 (0.000118) | 0.000056 / 0.000054 (0.000002) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.022933 / 0.037411 (-0.014478) | 0.072795 / 0.014526 (0.058269) | 0.081149 / 0.176557 (-0.095407) | 0.142941 / 0.737135 (-0.594195) | 0.082410 / 0.296338 (-0.213928) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.405220 / 0.215209 (0.190011) | 4.048585 / 2.077655 (1.970931) | 2.027908 / 1.504120 (0.523788) | 1.887828 / 1.541195 (0.346633) | 2.131780 / 1.468490 (0.663290) | 0.502847 / 4.584777 (-4.081930) | 3.069498 / 3.745712 (-0.676215) | 4.094774 / 5.269862 (-1.175088) | 2.544004 / 4.565676 (-2.021673) | 0.059540 / 0.424275 (-0.364735) | 0.006501 / 0.007607 (-0.001106) | 0.477218 / 0.226044 (0.251173) | 4.764961 / 2.268929 (2.496032) | 2.434594 / 55.444624 (-53.010030) | 2.104833 / 6.876477 (-4.771644) | 2.263059 / 2.142072 (0.120987) | 0.591755 / 4.805227 (-4.213472) | 0.131167 / 6.500664 (-6.369497) | 0.061808 / 0.075469 (-0.013661) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.345364 / 1.841788 (-0.496424) | 18.122584 / 8.074308 (10.048276) | 13.318689 / 10.191392 (3.127297) | 0.144526 / 0.680424 (-0.535898) | 0.016997 / 0.534201 (-0.517204) | 0.336036 / 0.579283 (-0.243247) | 0.359532 / 0.434364 (-0.074832) | 0.386945 / 0.540337 (-0.153392) | 0.538659 / 1.386936 (-0.848277) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006088 / 0.011353 (-0.005265) | 0.003684 / 0.011008 (-0.007324) | 0.062340 / 0.038508 (0.023832) | 0.058461 / 0.023109 (0.035352) | 0.360134 / 0.275898 (0.084236) | 0.393298 / 0.323480 (0.069818) | 0.004664 / 0.007986 (-0.003322) | 0.002909 / 0.004328 (-0.001420) | 0.062668 / 0.004250 (0.058418) | 0.050145 / 0.037052 (0.013092) | 0.361897 / 0.258489 (0.103408) | 0.402008 / 0.293841 (0.108167) | 0.027491 / 0.128546 (-0.101055) | 0.008113 / 0.075646 (-0.067534) | 0.068114 / 0.419271 (-0.351157) | 0.043303 / 0.043533 (-0.000230) | 0.360569 / 0.255139 (0.105430) | 0.387144 / 0.283200 (0.103944) | 0.020194 / 0.141683 (-0.121489) | 1.418066 / 1.452155 (-0.034089) | 1.475640 / 1.492716 (-0.017076) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.200291 / 0.018006 (0.182285) | 0.432298 / 0.000490 (0.431809) | 0.003303 / 0.000200 (0.003103) | 0.000075 / 0.000054 (0.000020) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.027749 / 0.037411 (-0.009662) | 0.081890 / 0.014526 (0.067364) | 0.094319 / 0.176557 (-0.082238) | 0.148646 / 0.737135 (-0.588490) | 0.091830 / 0.296338 (-0.204509) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.433546 / 0.215209 (0.218337) | 4.326855 / 2.077655 (2.249200) | 2.230186 / 1.504120 (0.726066) | 2.052524 / 1.541195 (0.511329) | 2.117270 / 1.468490 (0.648779) | 0.500331 / 4.584777 (-4.084446) | 3.113662 / 3.745712 (-0.632050) | 2.931540 / 5.269862 (-2.338322) | 1.853615 / 4.565676 (-2.712062) | 0.058250 / 0.424275 (-0.366025) | 0.006546 / 0.007607 (-0.001061) | 0.508850 / 0.226044 (0.282806) | 5.081809 / 2.268929 (2.812880) | 2.687037 / 55.444624 (-52.757588) | 2.369317 / 6.876477 (-4.507160) | 2.383549 / 2.142072 (0.241477) | 0.587039 / 4.805227 (-4.218188) | 0.125858 / 6.500664 (-6.374806) | 0.062522 / 0.075469 (-0.012947) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.294929 / 1.841788 (-0.546858) | 18.056312 / 8.074308 (9.982004) | 13.755117 / 10.191392 (3.563725) | 0.132037 / 0.680424 (-0.548387) | 0.016866 / 0.534201 (-0.517335) | 0.339040 / 0.579283 (-0.240243) | 0.364371 / 0.434364 (-0.069993) | 0.399533 / 0.540337 (-0.140804) | 0.564524 / 1.386936 (-0.822412) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#64b811c13a7982015d7e078e3d693ce5359a05a2 \"CML watermark\")\n", "@lhoestq This bar comes from: https://github.com/huggingface/datasets/blob/b8067c0262073891180869f700ebef5ac3dc5cce/src/datasets/builder.py#L1156-L1166\r\n\r\nDo you prefer not showing it or, e.g., having `desc=\"Generating splits\"`?", "No strong opinion. Since there is a \"Generating\" progress bar already, maybe it can be \"Preparing splits\" (ref to download_and_prepare)", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006348 / 0.011353 (-0.005005) | 0.003721 / 0.011008 (-0.007287) | 0.084039 / 0.038508 (0.045531) | 0.067627 / 0.023109 (0.044517) | 0.308372 / 0.275898 (0.032474) | 0.335131 / 0.323480 (0.011652) | 0.005157 / 0.007986 (-0.002829) | 0.003266 / 0.004328 (-0.001062) | 0.065374 / 0.004250 (0.061124) | 0.055550 / 0.037052 (0.018498) | 0.314001 / 0.258489 (0.055512) | 0.350510 / 0.293841 (0.056669) | 0.030859 / 0.128546 (-0.097688) | 0.008286 / 0.075646 (-0.067361) | 0.287122 / 0.419271 (-0.132149) | 0.051494 / 0.043533 (0.007961) | 0.309868 / 0.255139 (0.054729) | 0.325845 / 0.283200 (0.042645) | 0.022622 / 0.141683 (-0.119061) | 1.468730 / 1.452155 (0.016575) | 1.547871 / 1.492716 (0.055155) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.202763 / 0.018006 (0.184757) | 0.456403 / 0.000490 (0.455914) | 0.003116 / 0.000200 (0.002916) | 0.000079 / 0.000054 (0.000024) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.027297 / 0.037411 (-0.010114) | 0.081204 / 0.014526 (0.066678) | 0.094274 / 0.176557 (-0.082282) | 0.154391 / 0.737135 (-0.582744) | 0.094312 / 0.296338 (-0.202026) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.387382 / 0.215209 (0.172173) | 3.865597 / 2.077655 (1.787943) | 1.855959 / 1.504120 (0.351839) | 1.685411 / 1.541195 (0.144216) | 1.732127 / 1.468490 (0.263637) | 0.482230 / 4.584777 (-4.102547) | 3.664947 / 3.745712 (-0.080765) | 5.114379 / 5.269862 (-0.155482) | 3.102803 / 4.565676 (-1.462873) | 0.056509 / 0.424275 (-0.367766) | 0.007230 / 0.007607 (-0.000377) | 0.456788 / 0.226044 (0.230744) | 4.575831 / 2.268929 (2.306902) | 2.335249 / 55.444624 (-53.109375) | 2.003805 / 6.876477 (-4.872672) | 2.141788 / 2.142072 (-0.000285) | 0.577501 / 4.805227 (-4.227726) | 0.130264 / 6.500664 (-6.370400) | 0.058889 / 0.075469 (-0.016580) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.252673 / 1.841788 (-0.589115) | 18.676897 / 8.074308 (10.602589) | 13.988101 / 10.191392 (3.796709) | 0.151376 / 0.680424 (-0.529048) | 0.018104 / 0.534201 (-0.516097) | 0.388413 / 0.579283 (-0.190870) | 0.414841 / 0.434364 (-0.019523) | 0.456078 / 0.540337 (-0.084259) | 0.641715 / 1.386936 (-0.745221) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006315 / 0.011353 (-0.005038) | 0.003847 / 0.011008 (-0.007162) | 0.063989 / 0.038508 (0.025481) | 0.068244 / 0.023109 (0.045135) | 0.416201 / 0.275898 (0.140303) | 0.438446 / 0.323480 (0.114966) | 0.005820 / 0.007986 (-0.002166) | 0.003165 / 0.004328 (-0.001163) | 0.064143 / 0.004250 (0.059892) | 0.056529 / 0.037052 (0.019477) | 0.414916 / 0.258489 (0.156427) | 0.450771 / 0.293841 (0.156930) | 0.030611 / 0.128546 (-0.097935) | 0.008289 / 0.075646 (-0.067357) | 0.070725 / 0.419271 (-0.348546) | 0.047998 / 0.043533 (0.004465) | 0.405609 / 0.255139 (0.150470) | 0.421895 / 0.283200 (0.138696) | 0.022135 / 0.141683 (-0.119548) | 1.444238 / 1.452155 (-0.007916) | 1.515823 / 1.492716 (0.023107) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.227043 / 0.018006 (0.209037) | 0.439732 / 0.000490 (0.439242) | 0.001267 / 0.000200 (0.001067) | 0.000070 / 0.000054 (0.000016) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.029082 / 0.037411 (-0.008329) | 0.086201 / 0.014526 (0.071675) | 0.098653 / 0.176557 (-0.077903) | 0.152574 / 0.737135 (-0.584561) | 0.100696 / 0.296338 (-0.195642) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.411243 / 0.215209 (0.196034) | 4.100170 / 2.077655 (2.022515) | 2.118310 / 1.504120 (0.614190) | 1.935646 / 1.541195 (0.394451) | 1.970798 / 1.468490 (0.502307) | 0.478635 / 4.584777 (-4.106142) | 3.589396 / 3.745712 (-0.156316) | 3.312462 / 5.269862 (-1.957399) | 1.963081 / 4.565676 (-2.602595) | 0.056392 / 0.424275 (-0.367883) | 0.007134 / 0.007607 (-0.000473) | 0.485131 / 0.226044 (0.259086) | 4.838946 / 2.268929 (2.570017) | 2.624550 / 55.444624 (-52.820075) | 2.223046 / 6.876477 (-4.653431) | 2.230642 / 2.142072 (0.088570) | 0.594892 / 4.805227 (-4.210335) | 0.130523 / 6.500664 (-6.370141) | 0.059585 / 0.075469 (-0.015884) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.329941 / 1.841788 (-0.511847) | 19.199057 / 8.074308 (11.124748) | 14.166009 / 10.191392 (3.974617) | 0.190595 / 0.680424 (-0.489829) | 0.018419 / 0.534201 (-0.515782) | 0.392031 / 0.579283 (-0.187252) | 0.409395 / 0.434364 (-0.024969) | 0.475930 / 0.540337 (-0.064408) | 0.654412 / 1.386936 (-0.732524) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#42fdfbd567674d075c3a9148ec3c95221eb62cfe \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007500 / 0.011353 (-0.003853) | 0.004328 / 0.011008 (-0.006681) | 0.086718 / 0.038508 (0.048209) | 0.098638 / 0.023109 (0.075529) | 0.335308 / 0.275898 (0.059409) | 0.369163 / 0.323480 (0.045683) | 0.005733 / 0.007986 (-0.002253) | 0.003738 / 0.004328 (-0.000590) | 0.066452 / 0.004250 (0.062202) | 0.066245 / 0.037052 (0.029192) | 0.337609 / 0.258489 (0.079120) | 0.388584 / 0.293841 (0.094744) | 0.031742 / 0.128546 (-0.096804) | 0.008721 / 0.075646 (-0.066925) | 0.290820 / 0.419271 (-0.128452) | 0.053323 / 0.043533 (0.009790) | 0.329192 / 0.255139 (0.074053) | 0.350560 / 0.283200 (0.067360) | 0.025402 / 0.141683 (-0.116281) | 1.476174 / 1.452155 (0.024020) | 1.578194 / 1.492716 (0.085478) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.256160 / 0.018006 (0.238154) | 0.560315 / 0.000490 (0.559825) | 0.005287 / 0.000200 (0.005088) | 0.000094 / 0.000054 (0.000040) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.029164 / 0.037411 (-0.008247) | 0.084881 / 0.014526 (0.070356) | 0.100979 / 0.176557 (-0.075577) | 0.156539 / 0.737135 (-0.580597) | 0.101510 / 0.296338 (-0.194828) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.381138 / 0.215209 (0.165929) | 3.791573 / 2.077655 (1.713918) | 1.841954 / 1.504120 (0.337834) | 1.672463 / 1.541195 (0.131268) | 1.785769 / 1.468490 (0.317279) | 0.483263 / 4.584777 (-4.101514) | 3.617391 / 3.745712 (-0.128322) | 5.607794 / 5.269862 (0.337933) | 3.359530 / 4.565676 (-1.206147) | 0.056826 / 0.424275 (-0.367449) | 0.007375 / 0.007607 (-0.000232) | 0.455853 / 0.226044 (0.229809) | 4.548965 / 2.268929 (2.280037) | 2.412716 / 55.444624 (-53.031908) | 1.991456 / 6.876477 (-4.885021) | 2.242851 / 2.142072 (0.100778) | 0.573070 / 4.805227 (-4.232157) | 0.134658 / 6.500664 (-6.366006) | 0.061539 / 0.075469 (-0.013930) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.278306 / 1.841788 (-0.563481) | 20.634317 / 8.074308 (12.560009) | 15.164246 / 10.191392 (4.972854) | 0.167487 / 0.680424 (-0.512937) | 0.019006 / 0.534201 (-0.515195) | 0.394617 / 0.579283 (-0.184666) | 0.423385 / 0.434364 (-0.010979) | 0.469968 / 0.540337 (-0.070370) | 0.630058 / 1.386936 (-0.756878) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006793 / 0.011353 (-0.004559) | 0.004260 / 0.011008 (-0.006748) | 0.065398 / 0.038508 (0.026890) | 0.077850 / 0.023109 (0.054741) | 0.371754 / 0.275898 (0.095855) | 0.400652 / 0.323480 (0.077172) | 0.005729 / 0.007986 (-0.002256) | 0.003660 / 0.004328 (-0.000669) | 0.065119 / 0.004250 (0.060869) | 0.060714 / 0.037052 (0.023661) | 0.384592 / 0.258489 (0.126103) | 0.412806 / 0.293841 (0.118965) | 0.031865 / 0.128546 (-0.096681) | 0.008807 / 0.075646 (-0.066839) | 0.071156 / 0.419271 (-0.348115) | 0.049571 / 0.043533 (0.006038) | 0.367381 / 0.255139 (0.112242) | 0.386713 / 0.283200 (0.103513) | 0.024838 / 0.141683 (-0.116845) | 1.492986 / 1.452155 (0.040831) | 1.559243 / 1.492716 (0.066526) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.269737 / 0.018006 (0.251730) | 0.565177 / 0.000490 (0.564687) | 0.000404 / 0.000200 (0.000204) | 0.000060 / 0.000054 (0.000006) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.031631 / 0.037411 (-0.005780) | 0.087289 / 0.014526 (0.072764) | 0.102798 / 0.176557 (-0.073759) | 0.158977 / 0.737135 (-0.578158) | 0.105495 / 0.296338 (-0.190843) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.425067 / 0.215209 (0.209858) | 4.243121 / 2.077655 (2.165466) | 2.234567 / 1.504120 (0.730447) | 2.070810 / 1.541195 (0.529615) | 2.176802 / 1.468490 (0.708312) | 0.484987 / 4.584777 (-4.099790) | 3.647000 / 3.745712 (-0.098712) | 3.574843 / 5.269862 (-1.695019) | 2.092581 / 4.565676 (-2.473095) | 0.057299 / 0.424275 (-0.366976) | 0.007480 / 0.007607 (-0.000128) | 0.507838 / 0.226044 (0.281794) | 5.076594 / 2.268929 (2.807666) | 2.718858 / 55.444624 (-52.725766) | 2.362793 / 6.876477 (-4.513684) | 2.451962 / 2.142072 (0.309890) | 0.581355 / 4.805227 (-4.223872) | 0.133723 / 6.500664 (-6.366941) | 0.061896 / 0.075469 (-0.013573) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.325814 / 1.841788 (-0.515974) | 20.614502 / 8.074308 (12.540194) | 14.769422 / 10.191392 (4.578029) | 0.193797 / 0.680424 (-0.486627) | 0.018379 / 0.534201 (-0.515822) | 0.394153 / 0.579283 (-0.185130) | 0.409585 / 0.434364 (-0.024779) | 0.479107 / 0.540337 (-0.061231) | 0.668397 / 1.386936 (-0.718539) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#b2d892237169bad5512c91cae453d257ebefc201 \"CML watermark\")\n", "In the end, I decided to remove the progress bar to avoid having it displayed when loading a cached dataset.", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006673 / 0.011353 (-0.004680) | 0.004162 / 0.011008 (-0.006846) | 0.084017 / 0.038508 (0.045509) | 0.079536 / 0.023109 (0.056426) | 0.313594 / 0.275898 (0.037695) | 0.349200 / 0.323480 (0.025720) | 0.005544 / 0.007986 (-0.002441) | 0.003472 / 0.004328 (-0.000857) | 0.064742 / 0.004250 (0.060491) | 0.056857 / 0.037052 (0.019805) | 0.318635 / 0.258489 (0.060146) | 0.354378 / 0.293841 (0.060537) | 0.030856 / 0.128546 (-0.097690) | 0.008759 / 0.075646 (-0.066887) | 0.287760 / 0.419271 (-0.131511) | 0.052307 / 0.043533 (0.008775) | 0.316396 / 0.255139 (0.061257) | 0.351408 / 0.283200 (0.068208) | 0.024914 / 0.141683 (-0.116769) | 1.484592 / 1.452155 (0.032437) | 1.560662 / 1.492716 (0.067945) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.280938 / 0.018006 (0.262932) | 0.580236 / 0.000490 (0.579747) | 0.003369 / 0.000200 (0.003169) | 0.000090 / 0.000054 (0.000036) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.028736 / 0.037411 (-0.008675) | 0.082916 / 0.014526 (0.068390) | 0.097761 / 0.176557 (-0.078796) | 0.153515 / 0.737135 (-0.583620) | 0.099282 / 0.296338 (-0.197057) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.401244 / 0.215209 (0.186035) | 4.019866 / 2.077655 (1.942211) | 2.029642 / 1.504120 (0.525522) | 1.849591 / 1.541195 (0.308396) | 1.946829 / 1.468490 (0.478339) | 0.479750 / 4.584777 (-4.105027) | 3.482822 / 3.745712 (-0.262890) | 3.955859 / 5.269862 (-1.314003) | 2.370747 / 4.565676 (-2.194930) | 0.056905 / 0.424275 (-0.367370) | 0.007319 / 0.007607 (-0.000288) | 0.485310 / 0.226044 (0.259266) | 4.858228 / 2.268929 (2.589299) | 2.500476 / 55.444624 (-52.944148) | 2.171156 / 6.876477 (-4.705320) | 2.427266 / 2.142072 (0.285194) | 0.570199 / 4.805227 (-4.235029) | 0.130855 / 6.500664 (-6.369809) | 0.060269 / 0.075469 (-0.015200) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.258044 / 1.841788 (-0.583743) | 20.218657 / 8.074308 (12.144349) | 13.597970 / 10.191392 (3.406578) | 0.167656 / 0.680424 (-0.512768) | 0.018137 / 0.534201 (-0.516064) | 0.395309 / 0.579283 (-0.183975) | 0.406325 / 0.434364 (-0.028039) | 0.467457 / 0.540337 (-0.072880) | 0.613636 / 1.386936 (-0.773300) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006846 / 0.011353 (-0.004507) | 0.004207 / 0.011008 (-0.006802) | 0.064525 / 0.038508 (0.026017) | 0.081329 / 0.023109 (0.058220) | 0.399838 / 0.275898 (0.123940) | 0.431305 / 0.323480 (0.107825) | 0.005859 / 0.007986 (-0.002127) | 0.003568 / 0.004328 (-0.000760) | 0.065262 / 0.004250 (0.061011) | 0.064796 / 0.037052 (0.027744) | 0.406858 / 0.258489 (0.148369) | 0.440971 / 0.293841 (0.147130) | 0.031421 / 0.128546 (-0.097125) | 0.008777 / 0.075646 (-0.066870) | 0.071418 / 0.419271 (-0.347853) | 0.049263 / 0.043533 (0.005730) | 0.384279 / 0.255139 (0.129140) | 0.410745 / 0.283200 (0.127546) | 0.024467 / 0.141683 (-0.117216) | 1.522379 / 1.452155 (0.070224) | 1.581636 / 1.492716 (0.088920) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.276161 / 0.018006 (0.258155) | 0.548842 / 0.000490 (0.548352) | 0.004523 / 0.000200 (0.004324) | 0.000098 / 0.000054 (0.000043) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.030747 / 0.037411 (-0.006664) | 0.087493 / 0.014526 (0.072967) | 0.106563 / 0.176557 (-0.069993) | 0.162949 / 0.737135 (-0.574186) | 0.105303 / 0.296338 (-0.191036) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.425854 / 0.215209 (0.210645) | 4.244797 / 2.077655 (2.167142) | 2.269006 / 1.504120 (0.764886) | 2.097428 / 1.541195 (0.556234) | 2.181038 / 1.468490 (0.712548) | 0.477286 / 4.584777 (-4.107491) | 3.591452 / 3.745712 (-0.154260) | 3.481281 / 5.269862 (-1.788580) | 2.066895 / 4.565676 (-2.498782) | 0.056576 / 0.424275 (-0.367699) | 0.007409 / 0.007607 (-0.000199) | 0.498411 / 0.226044 (0.272367) | 4.994873 / 2.268929 (2.725945) | 2.749148 / 55.444624 (-52.695476) | 2.378544 / 6.876477 (-4.497932) | 2.452859 / 2.142072 (0.310786) | 0.571340 / 4.805227 (-4.233887) | 0.132174 / 6.500664 (-6.368490) | 0.061507 / 0.075469 (-0.013962) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.370773 / 1.841788 (-0.471015) | 20.493342 / 8.074308 (12.419034) | 14.809886 / 10.191392 (4.618494) | 0.175730 / 0.680424 (-0.504693) | 0.018617 / 0.534201 (-0.515583) | 0.393808 / 0.579283 (-0.185476) | 0.416419 / 0.434364 (-0.017945) | 0.477183 / 0.540337 (-0.063155) | 0.668060 / 1.386936 (-0.718876) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#2de7a2a4af5d94b0f98a7a6db94e78984af40602 \"CML watermark\")\n", "Nice one :)" ]

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[ "We no longer host datasets in this repo. You should use the HF Hub instead." ]

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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6016). All of your documentation changes will be reflected on that endpoint.", "It we could have something similar to Polars, that would be great.\r\n\r\nThis is what Polars outputs: \r\n* `__repr__`/`__str__` :\r\n```\r\nshape: (67_349, 3)\r\n┌───────┬───────────────────────────────────┬───────┐\r\n│ idx ┆ sentence ┆ label │\r\n│ --- ┆ --- ┆ --- │\r\n│ i32 ┆ str ┆ i64 │\r\n╞═══════╪═══════════════════════════════════╪═══════╡\r\n│ 0 ┆ hide new secretions from the par… ┆ 0 │\r\n│ 1 ┆ contains no wit , only labored g… ┆ 0 │\r\n│ 2 ┆ that loves its characters and co… ┆ 1 │\r\n│ 3 ┆ remains utterly satisfied to rem… ┆ 0 │\r\n│ … ┆ … ┆ … │\r\n│ 67345 ┆ anguish , anger and frustration ┆ 0 │\r\n│ 67346 ┆ at achieving the modest , crowd-… ┆ 1 │\r\n│ 67347 ┆ a patient viewer ┆ 1 │\r\n│ 67348 ┆ this new jangle of noise , mayhe… ┆ 0 │\r\n└───────┴───────────────────────────────────┴───────┘\r\n```\r\n\r\n* `_repr_html_`:\r\n<img width=\"251\" alt=\"Screenshot 2023-07-12 at 18 25 58\" src=\"https://github.com/huggingface/datasets/assets/47462742/5d04519d-f302-4411-9fbc-7445bdf53b23\">\r\n\r\n" ]

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[ "_The documentation is not available anymore as the PR was closed or merged._", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007633 / 0.011353 (-0.003720) | 0.004666 / 0.011008 (-0.006343) | 0.097768 / 0.038508 (0.059260) | 0.085153 / 0.023109 (0.062044) | 0.400315 / 0.275898 (0.124417) | 0.452903 / 0.323480 (0.129423) | 0.006227 / 0.007986 (-0.001759) | 0.003814 / 0.004328 (-0.000515) | 0.074586 / 0.004250 (0.070336) | 0.064295 / 0.037052 (0.027242) | 0.408082 / 0.258489 (0.149593) | 0.446921 / 0.293841 (0.153080) | 0.034593 / 0.128546 (-0.093953) | 0.009191 / 0.075646 (-0.066456) | 0.337099 / 0.419271 (-0.082173) | 0.075320 / 0.043533 (0.031787) | 0.403488 / 0.255139 (0.148349) | 0.435309 / 0.283200 (0.152109) | 0.035675 / 0.141683 (-0.106008) | 1.732642 / 1.452155 (0.280487) | 1.770238 / 1.492716 (0.277522) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.235879 / 0.018006 (0.217873) | 0.500330 / 0.000490 (0.499841) | 0.005221 / 0.000200 (0.005021) | 0.000150 / 0.000054 (0.000096) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.032479 / 0.037411 (-0.004933) | 0.095873 / 0.014526 (0.081348) | 0.107118 / 0.176557 (-0.069438) | 0.173809 / 0.737135 (-0.563326) | 0.109832 / 0.296338 (-0.186507) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.444342 / 0.215209 (0.229133) | 4.459010 / 2.077655 (2.381355) | 2.209687 / 1.504120 (0.705567) | 2.007556 / 1.541195 (0.466362) | 2.113683 / 1.468490 (0.645193) | 0.544281 / 4.584777 (-4.040496) | 4.037151 / 3.745712 (0.291439) | 4.852644 / 5.269862 (-0.417217) | 3.134126 / 4.565676 (-1.431550) | 0.066815 / 0.424275 (-0.357460) | 0.008836 / 0.007607 (0.001229) | 0.560904 / 0.226044 (0.334859) | 5.302760 / 2.268929 (3.033832) | 2.750182 / 55.444624 (-52.694442) | 2.322595 / 6.876477 (-4.553882) | 2.547486 / 2.142072 (0.405414) | 0.665766 / 4.805227 (-4.139461) | 0.151613 / 6.500664 (-6.349051) | 0.071155 / 0.075469 (-0.004314) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.473717 / 1.841788 (-0.368071) | 22.584179 / 8.074308 (14.509871) | 15.888001 / 10.191392 (5.696609) | 0.181073 / 0.680424 (-0.499351) | 0.021395 / 0.534201 (-0.512806) | 0.452693 / 0.579283 (-0.126590) | 0.447709 / 0.434364 (0.013345) | 0.529599 / 0.540337 (-0.010738) | 0.699241 / 1.386936 (-0.687695) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007917 / 0.011353 (-0.003436) | 0.004544 / 0.011008 (-0.006464) | 0.074566 / 0.038508 (0.036058) | 0.087530 / 0.023109 (0.064421) | 0.419753 / 0.275898 (0.143854) | 0.452352 / 0.323480 (0.128872) | 0.005882 / 0.007986 (-0.002104) | 0.003904 / 0.004328 (-0.000425) | 0.073539 / 0.004250 (0.069289) | 0.071320 / 0.037052 (0.034267) | 0.432899 / 0.258489 (0.174409) | 0.470365 / 0.293841 (0.176524) | 0.036198 / 0.128546 (-0.092348) | 0.009342 / 0.075646 (-0.066304) | 0.080970 / 0.419271 (-0.338301) | 0.058769 / 0.043533 (0.015236) | 0.413397 / 0.255139 (0.158258) | 0.448362 / 0.283200 (0.165162) | 0.034177 / 0.141683 (-0.107506) | 1.706217 / 1.452155 (0.254063) | 1.776743 / 1.492716 (0.284026) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.198779 / 0.018006 (0.180773) | 0.499862 / 0.000490 (0.499372) | 0.003891 / 0.000200 (0.003692) | 0.000108 / 0.000054 (0.000053) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.034671 / 0.037411 (-0.002740) | 0.103165 / 0.014526 (0.088639) | 0.115813 / 0.176557 (-0.060744) | 0.177407 / 0.737135 (-0.559728) | 0.117733 / 0.296338 (-0.178606) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.476859 / 0.215209 (0.261650) | 4.823063 / 2.077655 (2.745409) | 2.524133 / 1.504120 (1.020013) | 2.374482 / 1.541195 (0.833288) | 2.518047 / 1.468490 (1.049557) | 0.559131 / 4.584777 (-4.025646) | 4.126213 / 3.745712 (0.380501) | 6.488570 / 5.269862 (1.218708) | 3.816540 / 4.565676 (-0.749137) | 0.064742 / 0.424275 (-0.359533) | 0.008476 / 0.007607 (0.000869) | 0.576432 / 0.226044 (0.350387) | 5.835133 / 2.268929 (3.566205) | 3.237833 / 55.444624 (-52.206791) | 2.726596 / 6.876477 (-4.149880) | 2.799212 / 2.142072 (0.657139) | 0.661628 / 4.805227 (-4.143599) | 0.153997 / 6.500664 (-6.346667) | 0.070621 / 0.075469 (-0.004848) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.648505 / 1.841788 (-0.193282) | 22.454019 / 8.074308 (14.379711) | 16.077098 / 10.191392 (5.885706) | 0.217875 / 0.680424 (-0.462549) | 0.021285 / 0.534201 (-0.512916) | 0.459837 / 0.579283 (-0.119446) | 0.476211 / 0.434364 (0.041847) | 0.525903 / 0.540337 (-0.014435) | 0.717224 / 1.386936 (-0.669712) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#b767e9c3ef30f9da30d47cfcaccf9a7ac2500c43 \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.008929 / 0.011353 (-0.002424) | 0.004188 / 0.011008 (-0.006820) | 0.097030 / 0.038508 (0.058522) | 0.071363 / 0.023109 (0.048254) | 0.333116 / 0.275898 (0.057218) | 0.371272 / 0.323480 (0.047792) | 0.006430 / 0.007986 (-0.001555) | 0.003689 / 0.004328 (-0.000639) | 0.068666 / 0.004250 (0.064416) | 0.057562 / 0.037052 (0.020510) | 0.347208 / 0.258489 (0.088719) | 0.390514 / 0.293841 (0.096673) | 0.050560 / 0.128546 (-0.077987) | 0.013372 / 0.075646 (-0.062275) | 0.311345 / 0.419271 (-0.107927) | 0.068990 / 0.043533 (0.025457) | 0.363026 / 0.255139 (0.107887) | 0.379793 / 0.283200 (0.096593) | 0.036891 / 0.141683 (-0.104792) | 1.583481 / 1.452155 (0.131327) | 1.688727 / 1.492716 (0.196011) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.209777 / 0.018006 (0.191771) | 0.507267 / 0.000490 (0.506777) | 0.003637 / 0.000200 (0.003438) | 0.000105 / 0.000054 (0.000051) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.029309 / 0.037411 (-0.008102) | 0.088386 / 0.014526 (0.073861) | 0.104974 / 0.176557 (-0.071582) | 0.171999 / 0.737135 (-0.565137) | 0.110797 / 0.296338 (-0.185542) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.543465 / 0.215209 (0.328256) | 5.361491 / 2.077655 (3.283836) | 2.348712 / 1.504120 (0.844592) | 2.012527 / 1.541195 (0.471332) | 2.069776 / 1.468490 (0.601286) | 0.874262 / 4.584777 (-3.710515) | 4.877317 / 3.745712 (1.131605) | 5.327459 / 5.269862 (0.057597) | 3.336823 / 4.565676 (-1.228854) | 0.100456 / 0.424275 (-0.323819) | 0.008503 / 0.007607 (0.000895) | 0.692009 / 0.226044 (0.465965) | 6.912731 / 2.268929 (4.643802) | 3.110548 / 55.444624 (-52.334076) | 2.443665 / 6.876477 (-4.432811) | 2.528713 / 2.142072 (0.386641) | 1.076358 / 4.805227 (-3.728869) | 0.220352 / 6.500664 (-6.280312) | 0.080293 / 0.075469 (0.004824) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.538444 / 1.841788 (-0.303344) | 21.121221 / 8.074308 (13.046913) | 19.810609 / 10.191392 (9.619216) | 0.225406 / 0.680424 (-0.455018) | 0.026652 / 0.534201 (-0.507549) | 0.430372 / 0.579283 (-0.148911) | 0.510722 / 0.434364 (0.076358) | 0.514347 / 0.540337 (-0.025991) | 0.686050 / 1.386936 (-0.700886) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007675 / 0.011353 (-0.003678) | 0.004542 / 0.011008 (-0.006466) | 0.069655 / 0.038508 (0.031147) | 0.069338 / 0.023109 (0.046229) | 0.436505 / 0.275898 (0.160607) | 0.481806 / 0.323480 (0.158326) | 0.005315 / 0.007986 (-0.002670) | 0.004455 / 0.004328 (0.000127) | 0.072674 / 0.004250 (0.068424) | 0.058088 / 0.037052 (0.021035) | 0.445825 / 0.258489 (0.187336) | 0.501706 / 0.293841 (0.207865) | 0.047123 / 0.128546 (-0.081424) | 0.012943 / 0.075646 (-0.062703) | 0.093491 / 0.419271 (-0.325780) | 0.060169 / 0.043533 (0.016637) | 0.436530 / 0.255139 (0.181391) | 0.466873 / 0.283200 (0.183674) | 0.040453 / 0.141683 (-0.101230) | 1.586438 / 1.452155 (0.134283) | 1.671081 / 1.492716 (0.178365) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.180607 / 0.018006 (0.162601) | 0.520145 / 0.000490 (0.519655) | 0.004824 / 0.000200 (0.004624) | 0.000116 / 0.000054 (0.000061) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.029308 / 0.037411 (-0.008103) | 0.093652 / 0.014526 (0.079126) | 0.102332 / 0.176557 (-0.074224) | 0.162414 / 0.737135 (-0.574721) | 0.098017 / 0.296338 (-0.198321) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.583949 / 0.215209 (0.368740) | 6.035191 / 2.077655 (3.957536) | 2.801274 / 1.504120 (1.297155) | 2.566150 / 1.541195 (1.024955) | 2.437122 / 1.468490 (0.968632) | 0.865038 / 4.584777 (-3.719739) | 4.841727 / 3.745712 (1.096015) | 4.683919 / 5.269862 (-0.585943) | 2.941240 / 4.565676 (-1.624437) | 0.104888 / 0.424275 (-0.319387) | 0.007747 / 0.007607 (0.000140) | 0.780041 / 0.226044 (0.553997) | 7.771314 / 2.268929 (5.502385) | 3.680814 / 55.444624 (-51.763811) | 2.938472 / 6.876477 (-3.938004) | 2.981740 / 2.142072 (0.839668) | 1.065411 / 4.805227 (-3.739816) | 0.222265 / 6.500664 (-6.278399) | 0.082428 / 0.075469 (0.006959) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.626774 / 1.841788 (-0.215014) | 21.618284 / 8.074308 (13.543976) | 20.596743 / 10.191392 (10.405351) | 0.240969 / 0.680424 (-0.439454) | 0.025630 / 0.534201 (-0.508570) | 0.481981 / 0.579283 (-0.097302) | 0.547914 / 0.434364 (0.113550) | 0.522296 / 0.540337 (-0.018041) | 0.729174 / 1.386936 (-0.657762) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#b8067c0262073891180869f700ebef5ac3dc5cce \"CML watermark\")\n" ]

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[ "Hi ! The huggingface/dataset-viewer code was not maintained anymore because we switched to a new dataset viewer that is deployed available for each dataset the Hugging Face website.\r\n\r\nWhat are you using this old repository for ?", "I think these parts are outdated:\r\n\r\n* https://github.com/huggingface/datasets-viewer/blob/8efad8eae313a891f713469983bf4c744786f26e/run.py#L126-L131\r\n* https://github.com/huggingface/datasets-viewer/blob/8efad8eae313a891f713469983bf4c744786f26e/run.py#L145-L150\r\n\r\nTo make the viewer work, the first one should be replaced with the following:\r\n```python\r\ndataset_module = datasets.load.dataset_module_factory(path)\r\nbuilder_cls = datasets.load.import_main_class(dataset_module.module_path)\r\nconfs = builder_cls.BUILDER_CONFIGS\r\n```\r\nAnd the second one:\r\n```python\r\ndataset_module = datasets.load.dataset_module_factory(path)\r\nbuilder_cls = datasets.load.import_main_class(dataset_module.module_path)\r\nif conf:\r\n builder_instance = builder_cls(name=conf, cache_dir=path if path_to_datasets is not None else None)\r\nelse:\r\n builder_instance = builder_cls(cache_dir=path if path_to_datasets is not None else None)\r\n```\r\n\r\nBut as @lhoestq suggested, it's better to use the `datasets-server` API nowadays to [fetch the rows](https://huggingface.co/docs/datasets-server/rows).", "> The dataset viewer on the Hugging Face website is incredibly useful\r\n\r\n@mariosasko i think @lilyorlilypad wants to run the new dataset-viewer, not the old one", "> wants to run the new dataset-viewer, not the old one\r\n\r\nThanks for the clarification for me. I do want to run the new dataset-viewer. ", "It should be possible to run it locally using the HF datasets-server API (docs [here](https://huggingface.co/docs/datasets-server)) but the front end part is not open source (yet ?)\r\n\r\nThe back-end is open source though if you're interested: https://github.com/huggingface/datasets-server\r\nIt automatically converts datasets on HF to Parquet, which is the format we use to power the viewer.", "the new frontend would probably be hard to open source, as is, as it's quite intertwined with the Hub's code.\r\n\r\nHowever, at some point it would be amazing to have a community-driven open source implementation of a frontend to datasets-server! ", "For the frontend viewer, see https://github.com/huggingface/datasets/issues/6139.\r\n\r\nAlso mentioned in https://github.com/huggingface/datasets-server/issues/213 and https://github.com/huggingface/datasets-server/issues/441\r\n\r\nClosing as a duplicate of https://github.com/huggingface/datasets/issues/6139" ]

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[ "You can use the `remove_columns` parameter in `map` to avoid duplicating the columns (and save disk space) and then concatenate the original dataset with the map result:\r\n```python\r\nfrom datasets import concatenate_datasets\r\n# dummy example\r\nds_new = ds.map(lambda x: {\"new_col\": x[\"col\"] + 2}, remove_columns=ds.column_names)\r\nds_combined = concatenate_datasets([ds, ds_new], axis=1)\r\n```\r\n\r\nDoing this automatically is hard to implement efficiently unless we know ahead of time which existing columns will be modified by a `map` transform. We have this info when `input_columns` are specified, so I think this is the only case we can optimize." ]

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[ "You can use `with_transform` to get a new dataset object.\r\n\r\nSupport for lazy `map` has already been discussed [here](https://github.com/huggingface/datasets/issues/3385) a little bit. Personally, I'm not a fan, as this would make `map` even more complex. ", "> You can use `with_transform` to get a new dataset object.\r\n> \r\n> Support for lazy `map` has already been discussed [here](https://github.com/huggingface/datasets/issues/3385) a little bit. Personally, I'm not a fan, as this would make `map` even more complex.\r\n\r\nI read about IterableDataset, and it seems to have lazy mapping. But I can't figure out how to convert an IterableDataset into a normal one when needed.\r\n\r\n`with_transform` still does not chain AFAIU.", "> I read about IterableDataset, and it seems to have lazy mapping. But I can't figure out how to convert an IterableDataset into a normal one when needed.\r\n\r\nYou must cache an `IterableDataset` to disk to load it as a `Dataset`. One way to do this is with `Dataset.from_generator`:\r\n```python\r\nfrom functools import partial\r\nfrom datasets import Dataset\r\n\r\ndef gen_from_iterable_dataset(iterable_ds)\r\n yield from iterable_ds\r\n\r\nds = Dataset.from_generator(partial(gen_from_iterable_dataset, iterable_ds), features=iterable_ds.features})\r\n```\r\n\r\n> with_transform still does not chain AFAIU.\r\n\r\nYes, not supported yet - the solution is to combine the transforms into a single one.", "I wonder if it would be beneficial to have a dedicated method to do that ? Maybe a `.save_to_disk()` so that the user can reload the resulting dataset later ?", "> ```python\r\n> from functools import partial\r\n> from datasets import Dataset\r\n> \r\n> def gen_from_iterable_dataset(iterable_ds)\r\n> yield from iterable_ds\r\n> \r\n> ds = Dataset.from_generator(partial(gen_from_iterable_dataset, iterable_ds), features=iterable_ds.features})\r\n> ```\r\n\r\n@mariosasko With these complex mapping functions, what hash will be used to cache this dataset?\r\n", "The params passed to `Dataset.from_generator` will be used to compute the hash (`partial` encapsulates the `iterable_ds` value, so changing it will also change the hash)", "Hi, I think this feature would be very useful. I want to concatenate large datasets with heterogeneous columns. I dislike `map` since I don't want multiple copy of that datasets locally. I tried to use \"set_transform\" on each dataset to convert it to a standard features format, but `datasets.concatenate_datasets` ignores the updated format of the datasets.  A work around is to use `torch.utils.data.ConcatDataset`. Is there a neat way to do it using HF datasets?" ]

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[ "Hi! You can do `ds.get_index(\"embeddings\").faiss_index.metric_type` to get the metric type and then match the result with the FAISS metric [enum](https://github.com/facebookresearch/faiss/blob/43d86e30736ede853c384b24667fc3ab897d6ba9/faiss/MetricType.h#L22-L36) (should be L2).", "Ah! Thank you for pointing this out. FYI: the enum indicates it's using the inner product. Using `torch.inner` or `torch.dot` still produces a discrepancy compared to the built-in score. I think this is because of the compression/quantization that occurs with the FAISS index." ]

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[ "I want to take a shot at this if possible ", "Yes, feel free to work on this.\r\n\r\nYou can check the PyArrow Table `__repr__` and Polars DataFrame `__repr__`/`_repr_html_` implementations for some pointers/ideas.", "@mariosasko are there any other similar issues that I could work on? I see this has been already solved. " ]

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[ "_The documentation is not available anymore as the PR was closed or merged._", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006961 / 0.011353 (-0.004392) | 0.004390 / 0.011008 (-0.006618) | 0.103249 / 0.038508 (0.064741) | 0.048084 / 0.023109 (0.024975) | 0.351213 / 0.275898 (0.075315) | 0.416918 / 0.323480 (0.093439) | 0.005539 / 0.007986 (-0.002446) | 0.003555 / 0.004328 (-0.000774) | 0.079306 / 0.004250 (0.075055) | 0.066937 / 0.037052 (0.029884) | 0.382601 / 0.258489 (0.124112) | 0.406125 / 0.293841 (0.112284) | 0.032269 / 0.128546 (-0.096277) | 0.009133 / 0.075646 (-0.066514) | 0.354449 / 0.419271 (-0.064822) | 0.068978 / 0.043533 (0.025445) | 0.352314 / 0.255139 (0.097175) | 0.390398 / 0.283200 (0.107199) | 0.025640 / 0.141683 (-0.116043) | 1.553865 / 1.452155 (0.101710) | 1.601292 / 1.492716 (0.108576) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.208310 / 0.018006 (0.190303) | 0.440076 / 0.000490 (0.439586) | 0.000363 / 0.000200 (0.000163) | 0.000059 / 0.000054 (0.000004) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.029173 / 0.037411 (-0.008238) | 0.111323 / 0.014526 (0.096797) | 0.123001 / 0.176557 (-0.053556) | 0.180180 / 0.737135 (-0.556955) | 0.125804 / 0.296338 (-0.170534) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.419919 / 0.215209 (0.204710) | 4.194515 / 2.077655 (2.116860) | 1.881234 / 1.504120 (0.377114) | 1.672914 / 1.541195 (0.131720) | 1.723102 / 1.468490 (0.254612) | 0.543584 / 4.584777 (-4.041193) | 3.822477 / 3.745712 (0.076765) | 1.837946 / 5.269862 (-3.431915) | 1.094975 / 4.565676 (-3.470701) | 0.066788 / 0.424275 (-0.357487) | 0.011689 / 0.007607 (0.004082) | 0.520983 / 0.226044 (0.294938) | 5.209245 / 2.268929 (2.940316) | 2.392916 / 55.444624 (-53.051708) | 2.060042 / 6.876477 (-4.816434) | 2.162291 / 2.142072 (0.020219) | 0.668472 / 4.805227 (-4.136755) | 0.144373 / 6.500664 (-6.356291) | 0.066152 / 0.075469 (-0.009318) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.251256 / 1.841788 (-0.590532) | 15.161338 / 8.074308 (7.087030) | 14.416133 / 10.191392 (4.224741) | 0.166145 / 0.680424 (-0.514279) | 0.018168 / 0.534201 (-0.516033) | 0.433364 / 0.579283 (-0.145919) | 0.417484 / 0.434364 (-0.016880) | 0.502543 / 0.540337 (-0.037794) | 0.602904 / 1.386936 (-0.784032) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006946 / 0.011353 (-0.004407) | 0.004248 / 0.011008 (-0.006761) | 0.079707 / 0.038508 (0.041199) | 0.046226 / 0.023109 (0.023117) | 0.375864 / 0.275898 (0.099966) | 0.430740 / 0.323480 (0.107260) | 0.006222 / 0.007986 (-0.001764) | 0.003474 / 0.004328 (-0.000854) | 0.079622 / 0.004250 (0.075372) | 0.066666 / 0.037052 (0.029613) | 0.379487 / 0.258489 (0.120998) | 0.423002 / 0.293841 (0.129161) | 0.032836 / 0.128546 (-0.095710) | 0.008976 / 0.075646 (-0.066670) | 0.086578 / 0.419271 (-0.332693) | 0.055651 / 0.043533 (0.012118) | 0.360787 / 0.255139 (0.105648) | 0.384265 / 0.283200 (0.101065) | 0.025350 / 0.141683 (-0.116333) | 1.547880 / 1.452155 (0.095725) | 1.605850 / 1.492716 (0.113134) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.184227 / 0.018006 (0.166220) | 0.442071 / 0.000490 (0.441582) | 0.002887 / 0.000200 (0.002687) | 0.000088 / 0.000054 (0.000034) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.031923 / 0.037411 (-0.005488) | 0.119093 / 0.014526 (0.104568) | 0.128704 / 0.176557 (-0.047853) | 0.187065 / 0.737135 (-0.550070) | 0.134135 / 0.296338 (-0.162204) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.455731 / 0.215209 (0.240522) | 4.562911 / 2.077655 (2.485256) | 2.247431 / 1.504120 (0.743311) | 2.053346 / 1.541195 (0.512151) | 2.049611 / 1.468490 (0.581121) | 0.546069 / 4.584777 (-4.038708) | 3.821852 / 3.745712 (0.076140) | 3.358497 / 5.269862 (-1.911364) | 1.667697 / 4.565676 (-2.897979) | 0.067968 / 0.424275 (-0.356307) | 0.012344 / 0.007607 (0.004737) | 0.550864 / 0.226044 (0.324820) | 5.496867 / 2.268929 (3.227939) | 2.680031 / 55.444624 (-52.764594) | 2.328673 / 6.876477 (-4.547804) | 2.436754 / 2.142072 (0.294682) | 0.681195 / 4.805227 (-4.124033) | 0.148761 / 6.500664 (-6.351904) | 0.067716 / 0.075469 (-0.007753) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.353798 / 1.841788 (-0.487990) | 15.992965 / 8.074308 (7.918657) | 14.051539 / 10.191392 (3.860147) | 0.181087 / 0.680424 (-0.499337) | 0.018653 / 0.534201 (-0.515548) | 0.433499 / 0.579283 (-0.145784) | 0.428845 / 0.434364 (-0.005519) | 0.501100 / 0.540337 (-0.039238) | 0.603666 / 1.386936 (-0.783270) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#10cfa871a2f387fe9c6360e1873ea74c6d69ff67 \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.010983 / 0.011353 (-0.000370) | 0.005630 / 0.011008 (-0.005378) | 0.109967 / 0.038508 (0.071458) | 0.101580 / 0.023109 (0.078471) | 0.490205 / 0.275898 (0.214307) | 0.534653 / 0.323480 (0.211173) | 0.008365 / 0.007986 (0.000379) | 0.004317 / 0.004328 (-0.000012) | 0.082429 / 0.004250 (0.078179) | 0.080556 / 0.037052 (0.043504) | 0.494627 / 0.258489 (0.236138) | 0.544189 / 0.293841 (0.250348) | 0.049419 / 0.128546 (-0.079127) | 0.014033 / 0.075646 (-0.061613) | 0.370406 / 0.419271 (-0.048866) | 0.083468 / 0.043533 (0.039935) | 0.463829 / 0.255139 (0.208690) | 0.507516 / 0.283200 (0.224316) | 0.053266 / 0.141683 (-0.088417) | 1.778680 / 1.452155 (0.326525) | 1.916616 / 1.492716 (0.423900) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.267646 / 0.018006 (0.249640) | 0.617824 / 0.000490 (0.617334) | 0.007720 / 0.000200 (0.007520) | 0.000139 / 0.000054 (0.000085) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.034464 / 0.037411 (-0.002948) | 0.113626 / 0.014526 (0.099100) | 0.118911 / 0.176557 (-0.057646) | 0.194701 / 0.737135 (-0.542434) | 0.123431 / 0.296338 (-0.172907) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.606073 / 0.215209 (0.390863) | 6.086393 / 2.077655 (4.008738) | 2.568712 / 1.504120 (1.064593) | 2.260801 / 1.541195 (0.719606) | 2.411798 / 1.468490 (0.943307) | 0.876433 / 4.584777 (-3.708344) | 5.521280 / 3.745712 (1.775568) | 5.969722 / 5.269862 (0.699861) | 3.671028 / 4.565676 (-0.894649) | 0.097082 / 0.424275 (-0.327193) | 0.011354 / 0.007607 (0.003747) | 0.713842 / 0.226044 (0.487798) | 7.291172 / 2.268929 (5.022244) | 3.315272 / 55.444624 (-52.129352) | 2.777487 / 6.876477 (-4.098990) | 3.025449 / 2.142072 (0.883377) | 1.014115 / 4.805227 (-3.791112) | 0.217928 / 6.500664 (-6.282736) | 0.083097 / 0.075469 (0.007627) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.640060 / 1.841788 (-0.201728) | 25.342172 / 8.074308 (17.267864) | 22.776510 / 10.191392 (12.585118) | 0.227300 / 0.680424 (-0.453124) | 0.032233 / 0.534201 (-0.501968) | 0.507547 / 0.579283 (-0.071736) | 0.647044 / 0.434364 (0.212680) | 0.607019 / 0.540337 (0.066682) | 0.823548 / 1.386936 (-0.563388) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.009576 / 0.011353 (-0.001777) | 0.009322 / 0.011008 (-0.001687) | 0.087184 / 0.038508 (0.048676) | 0.100795 / 0.023109 (0.077685) | 0.492138 / 0.275898 (0.216240) | 0.528386 / 0.323480 (0.204906) | 0.006689 / 0.007986 (-0.001296) | 0.004735 / 0.004328 (0.000406) | 0.085519 / 0.004250 (0.081269) | 0.072648 / 0.037052 (0.035595) | 0.496068 / 0.258489 (0.237579) | 0.549634 / 0.293841 (0.255793) | 0.049709 / 0.128546 (-0.078837) | 0.015077 / 0.075646 (-0.060569) | 0.099445 / 0.419271 (-0.319826) | 0.068080 / 0.043533 (0.024547) | 0.500426 / 0.255139 (0.245287) | 0.531437 / 0.283200 (0.248238) | 0.053176 / 0.141683 (-0.088507) | 1.827942 / 1.452155 (0.375787) | 1.914286 / 1.492716 (0.421570) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.247658 / 0.018006 (0.229652) | 0.590805 / 0.000490 (0.590315) | 0.005319 / 0.000200 (0.005119) | 0.000165 / 0.000054 (0.000110) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.036993 / 0.037411 (-0.000418) | 0.112944 / 0.014526 (0.098419) | 0.118964 / 0.176557 (-0.057593) | 0.194867 / 0.737135 (-0.542269) | 0.120816 / 0.296338 (-0.175523) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.638062 / 0.215209 (0.422853) | 6.246785 / 2.077655 (4.169130) | 2.957779 / 1.504120 (1.453659) | 2.739118 / 1.541195 (1.197924) | 2.795362 / 1.468490 (1.326872) | 0.890532 / 4.584777 (-3.694245) | 5.508198 / 3.745712 (1.762486) | 5.222315 / 5.269862 (-0.047547) | 3.152731 / 4.565676 (-1.412946) | 0.098344 / 0.424275 (-0.325931) | 0.008800 / 0.007607 (0.001193) | 0.757889 / 0.226044 (0.531845) | 7.545715 / 2.268929 (5.276787) | 3.694536 / 55.444624 (-51.750088) | 3.112872 / 6.876477 (-3.763605) | 3.182358 / 2.142072 (1.040285) | 1.028171 / 4.805227 (-3.777056) | 0.215223 / 6.500664 (-6.285441) | 0.085856 / 0.075469 (0.010387) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.853138 / 1.841788 (0.011350) | 25.939672 / 8.074308 (17.865364) | 23.118029 / 10.191392 (12.926637) | 0.250599 / 0.680424 (-0.429825) | 0.029942 / 0.534201 (-0.504259) | 0.508748 / 0.579283 (-0.070535) | 0.593966 / 0.434364 (0.159602) | 0.605499 / 0.540337 (0.065162) | 0.863827 / 1.386936 (-0.523109) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#5d15950d99677e9473cdcd31cfd83aa17e313e28 \"CML watermark\")\n" ]

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[ "By default, we write data to disk (so it can be memory-mapped) every 1000 rows/samples. You can control this with the `writer_batch_size` parameter. Also, when working with fixed-size arrays, the `ArrayXD` feature types yield better performance (e.g., in your case, `features=datasets.Features({\"i\": datasets.Array3D(shape=(512,512,3), dtype=\"float32\")})` should be faster).\r\n\r\nOur support for multi-dim arrays could be better, and we plan to improve it as part of https://github.com/huggingface/datasets/issues/5272.", "> By default, we write data to disk (so it can be memory-mapped) every 1000 rows/samples. You can control this with the `writer_batch_size` parameter. Also, when working with fixed-size arrays, the `ArrayXD` feature types yield better performance (e.g., in your case, `features=datasets.Features({\"i\": datasets.Array3D(shape=(512,512,3), dtype=\"float32\")})` should be faster).\r\n> \r\n> Our support for multi-dim arrays could be better, and we plan to improve it as part of #5272.\r\n\r\nThanks for the explanation! The Image array was just for demonstration, I use PIL Images in practice. Does that make a difference? What's the best approach for a dataset with PIL Images as rows?", "It's best to use the `datasets.Image()` feature type for PIL images (to save space) :)" ]

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[]

[ "This error means that one of the int32 (`Value(\"int32\")`) columns in the dataset has a value that is out of the valid (int32) range.\r\n\r\nI'll open a PR to print the name of a problematic column to make debugging such errors easier.", "I am afraid int32 is not the reason for this error.\r\n\r\nI have submitted a commit to use int64 for all ints in the dataset:\r\nhttps://huggingface.co/datasets/liwu/MNBVC/commit/857ac00d9eab96a6708ad6a82bd9001686042a9e\r\n\r\nand I have updated my env to the latest datasets release:\r\nCopy-and-paste the text below in your GitHub issue.\r\n\r\n- `datasets` version: 2.13.1\r\n- Platform: macOS-13.2.1-arm64-arm-64bit\r\n- Python version: 3.11.2\r\n- Huggingface_hub version: 0.13.4\r\n- PyArrow version: 11.0.0\r\n- Pandas version: 1.5.3\r\n\r\nBut the error still exist\r\n\r\n```\r\nDownloading and preparing dataset mnbvc/news_peoples_daily to /Users/silver/.cache/huggingface/datasets/liwu___mnbvc/news_peoples_daily/0.0.1/ee380f6309fe9b8b0d1fb14d77118f132444f22c8c4b28bf5c1645312688e051...\r\nDownloading data files: 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 12/12 [00:00<00:00, 9070.40it/s]\r\nExtracting data files: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 12/12 [00:00<00:00, 2697.16it/s]\r\n---------------------------------------------------------------------------\r\nOverflowError Traceback (most recent call last)\r\nFile ~/git/venv/lib/python3.11/site-packages/datasets/builder.py:1647, in GeneratorBasedBuilder._prepare_split_single(self, gen_kwargs, fpath, file_format, max_shard_size, split_info, check_duplicate_keys, job_id)\r\n 1646 example = self.info.features.encode_example(record) if self.info.features is not None else record\r\n-> 1647 writer.write(example, key)\r\n 1648 num_examples_progress_update += 1\r\n\r\nFile ~/git/venv/lib/python3.11/site-packages/datasets/arrow_writer.py:490, in ArrowWriter.write(self, example, key, writer_batch_size)\r\n 488 self.hkey_record = []\r\n--> 490 self.write_examples_on_file()\r\n\r\nFile ~/git/venv/lib/python3.11/site-packages/datasets/arrow_writer.py:448, in ArrowWriter.write_examples_on_file(self)\r\n 444 batch_examples[col] = [\r\n 445 row[0][col].to_pylist()[0] if isinstance(row[0][col], (pa.Array, pa.ChunkedArray)) else row[0][col]\r\n 446 for row in self.current_examples\r\n 447 ]\r\n--> 448 self.write_batch(batch_examples=batch_examples)\r\n 449 self.current_examples = []\r\n\r\nFile ~/git/venv/lib/python3.11/site-packages/datasets/arrow_writer.py:553, in ArrowWriter.write_batch(self, batch_examples, writer_batch_size)\r\n 552 typed_sequence = OptimizedTypedSequence(col_values, type=col_type, try_type=col_try_type, col=col)\r\n--> 553 arrays.append(pa.array(typed_sequence))\r\n 554 inferred_features[col] = typed_sequence.get_inferred_type()\r\n\r\nFile ~/git/venv/lib/python3.11/site-packages/pyarrow/array.pxi:236, in pyarrow.lib.array()\r\n\r\nFile ~/git/venv/lib/python3.11/site-packages/pyarrow/array.pxi:110, in pyarrow.lib._handle_arrow_array_protocol()\r\n\r\nFile ~/git/venv/lib/python3.11/site-packages/datasets/arrow_writer.py:189, in TypedSequence.__arrow_array__(self, type)\r\n 188 trying_cast_to_python_objects = True\r\n--> 189 out = pa.array(cast_to_python_objects(data, only_1d_for_numpy=True))\r\n 190 # use smaller integer precisions if possible\r\n\r\nFile ~/git/venv/lib/python3.11/site-packages/pyarrow/array.pxi:320, in pyarrow.lib.array()\r\n\r\nFile ~/git/venv/lib/python3.11/site-packages/pyarrow/array.pxi:39, in pyarrow.lib._sequence_to_array()\r\n\r\nFile ~/git/venv/lib/python3.11/site-packages/pyarrow/error.pxi:144, in pyarrow.lib.pyarrow_internal_check_status()\r\n\r\nOverflowError: Python int too large to convert to C long\r\n\r\nDuring handling of the above exception, another exception occurred:\r\n\r\nOverflowError Traceback (most recent call last)\r\nFile ~/git/venv/lib/python3.11/site-packages/datasets/builder.py:1656, in GeneratorBasedBuilder._prepare_split_single(self, gen_kwargs, fpath, file_format, max_shard_size, split_info, check_duplicate_keys, job_id)\r\n 1655 num_shards = shard_id + 1\r\n-> 1656 num_examples, num_bytes = writer.finalize()\r\n 1657 writer.close()\r\n\r\nFile ~/git/venv/lib/python3.11/site-packages/datasets/arrow_writer.py:584, in ArrowWriter.finalize(self, close_stream)\r\n 583 self.hkey_record = []\r\n--> 584 self.write_examples_on_file()\r\n 585 # If schema is known, infer features even if no examples were written\r\n\r\nFile ~/git/venv/lib/python3.11/site-packages/datasets/arrow_writer.py:448, in ArrowWriter.write_examples_on_file(self)\r\n 444 batch_examples[col] = [\r\n 445 row[0][col].to_pylist()[0] if isinstance(row[0][col], (pa.Array, pa.ChunkedArray)) else row[0][col]\r\n 446 for row in self.current_examples\r\n 447 ]\r\n--> 448 self.write_batch(batch_examples=batch_examples)\r\n 449 self.current_examples = []\r\n\r\nFile ~/git/venv/lib/python3.11/site-packages/datasets/arrow_writer.py:553, in ArrowWriter.write_batch(self, batch_examples, writer_batch_size)\r\n 552 typed_sequence = OptimizedTypedSequence(col_values, type=col_type, try_type=col_try_type, col=col)\r\n--> 553 arrays.append(pa.array(typed_sequence))\r\n 554 inferred_features[col] = typed_sequence.get_inferred_type()\r\n\r\nFile ~/git/venv/lib/python3.11/site-packages/pyarrow/array.pxi:236, in pyarrow.lib.array()\r\n\r\nFile ~/git/venv/lib/python3.11/site-packages/pyarrow/array.pxi:110, in pyarrow.lib._handle_arrow_array_protocol()\r\n\r\nFile ~/git/venv/lib/python3.11/site-packages/datasets/arrow_writer.py:189, in TypedSequence.__arrow_array__(self, type)\r\n 188 trying_cast_to_python_objects = True\r\n--> 189 out = pa.array(cast_to_python_objects(data, only_1d_for_numpy=True))\r\n 190 # use smaller integer precisions if possible\r\n\r\nFile ~/git/venv/lib/python3.11/site-packages/pyarrow/array.pxi:320, in pyarrow.lib.array()\r\n\r\nFile ~/git/venv/lib/python3.11/site-packages/pyarrow/array.pxi:39, in pyarrow.lib._sequence_to_array()\r\n\r\nFile ~/git/venv/lib/python3.11/site-packages/pyarrow/error.pxi:144, in pyarrow.lib.pyarrow_internal_check_status()\r\n\r\nOverflowError: Python int too large to convert to C long\r\n\r\nThe above exception was the direct cause of the following exception:\r\n\r\nDatasetGenerationError Traceback (most recent call last)\r\nCell In[2], line 1\r\n----> 1 dataset = load_dataset(\"liwu/MNBVC\", 'news_peoples_daily', split='train')\r\n\r\nFile ~/git/venv/lib/python3.11/site-packages/datasets/load.py:1809, in load_dataset(path, name, data_dir, data_files, split, cache_dir, features, download_config, download_mode, verification_mode, ignore_verifications, keep_in_memory, save_infos, revision, use_auth_token, task, streaming, num_proc, storage_options, **config_kwargs)\r\n 1806 try_from_hf_gcs = path not in _PACKAGED_DATASETS_MODULES\r\n 1808 # Download and prepare data\r\n-> 1809 builder_instance.download_and_prepare(\r\n 1810 download_config=download_config,\r\n 1811 download_mode=download_mode,\r\n 1812 verification_mode=verification_mode,\r\n 1813 try_from_hf_gcs=try_from_hf_gcs,\r\n 1814 num_proc=num_proc,\r\n 1815 storage_options=storage_options,\r\n 1816 )\r\n 1818 # Build dataset for splits\r\n 1819 keep_in_memory = (\r\n 1820 keep_in_memory if keep_in_memory is not None else is_small_dataset(builder_instance.info.dataset_size)\r\n 1821 )\r\n\r\nFile ~/git/venv/lib/python3.11/site-packages/datasets/builder.py:909, in DatasetBuilder.download_and_prepare(self, output_dir, download_config, download_mode, verification_mode, ignore_verifications, try_from_hf_gcs, dl_manager, base_path, use_auth_token, file_format, max_shard_size, num_proc, storage_options, **download_and_prepare_kwargs)\r\n 907 if num_proc is not None:\r\n 908 prepare_split_kwargs[\"num_proc\"] = num_proc\r\n--> 909 self._download_and_prepare(\r\n 910 dl_manager=dl_manager,\r\n 911 verification_mode=verification_mode,\r\n 912 **prepare_split_kwargs,\r\n 913 **download_and_prepare_kwargs,\r\n 914 )\r\n 915 # Sync info\r\n 916 self.info.dataset_size = sum(split.num_bytes for split in self.info.splits.values())\r\n\r\nFile ~/git/venv/lib/python3.11/site-packages/datasets/builder.py:1670, in GeneratorBasedBuilder._download_and_prepare(self, dl_manager, verification_mode, **prepare_splits_kwargs)\r\n 1669 def _download_and_prepare(self, dl_manager, verification_mode, **prepare_splits_kwargs):\r\n-> 1670 super()._download_and_prepare(\r\n 1671 dl_manager,\r\n 1672 verification_mode,\r\n 1673 check_duplicate_keys=verification_mode == VerificationMode.BASIC_CHECKS\r\n 1674 or verification_mode == VerificationMode.ALL_CHECKS,\r\n 1675 **prepare_splits_kwargs,\r\n 1676 )\r\n\r\nFile ~/git/venv/lib/python3.11/site-packages/datasets/builder.py:1004, in DatasetBuilder._download_and_prepare(self, dl_manager, verification_mode, **prepare_split_kwargs)\r\n 1000 split_dict.add(split_generator.split_info)\r\n 1002 try:\r\n 1003 # Prepare split will record examples associated to the split\r\n-> 1004 self._prepare_split(split_generator, **prepare_split_kwargs)\r\n 1005 except OSError as e:\r\n 1006 raise OSError(\r\n 1007 \"Cannot find data file. \"\r\n 1008 + (self.manual_download_instructions or \"\")\r\n 1009 + \"\\nOriginal error:\\n\"\r\n 1010 + str(e)\r\n 1011 ) from None\r\n\r\nFile ~/git/venv/lib/python3.11/site-packages/datasets/builder.py:1508, in GeneratorBasedBuilder._prepare_split(self, split_generator, check_duplicate_keys, file_format, num_proc, max_shard_size)\r\n 1506 job_id = 0\r\n 1507 with pbar:\r\n-> 1508 for job_id, done, content in self._prepare_split_single(\r\n 1509 gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args\r\n 1510 ):\r\n 1511 if done:\r\n 1512 result = content\r\n\r\nFile ~/git/venv/lib/python3.11/site-packages/datasets/builder.py:1665, in GeneratorBasedBuilder._prepare_split_single(self, gen_kwargs, fpath, file_format, max_shard_size, split_info, check_duplicate_keys, job_id)\r\n 1663 if isinstance(e, SchemaInferenceError) and e.__context__ is not None:\r\n 1664 e = e.__context__\r\n-> 1665 raise DatasetGenerationError(\"An error occurred while generating the dataset\") from e\r\n 1667 yield job_id, True, (total_num_examples, total_num_bytes, writer._features, num_shards, shard_lengths)\r\n\r\nDatasetGenerationError: An error occurred while generating the dataset\r\n```\r\n\r\nBesides, it works fine when I am using streamed dataset.", "`simhash` is the problematic column - it has values such as `18329103420363166823` that are out of the int64 range. You can fix this by setting the feature type to `Value(\"string\")` (it's advised to use this type for hash values in general)\r\n\r\n> Besides, it works fine when I am using streamed dataset.\r\n\r\nStreaming yields Python dictionaries from the script without converting them to the Arrow representation, as this conversion step is not that cheap performance-wise.", "i am using uint64 for simhash\r\n\r\nuint64 ranges up to about 3.69E19.\r\n\r\n18329103420363166823 is less than this value.\r\n\r\nmoreover, our simhash algorithm use 64 bits. it should fit in uint64.\r\n\r\n\r\n\r\n", "You are right. I overlooked the feature type.\r\n\r\nThis is a reproducer:\r\n```python\r\nimport pyarrow as pa\r\nfrom datasets.arrow_writer import TypedSequence\r\n\r\npa.array(TypedSequence([18329103420363166823], type=Value(\"uint64\")))\r\n```\r\n\r\n`pa.array([18329103420363166823])` also fails with the same error, so it seems PyArrow does not always infer the correct type as NumPy does (`uint64` in this case).\r\n\r\nI'll report this issue in the Arrow repo.\r\n\r\n`pa.array([18329103420363166823], pa.uint64)` works, so maybe we can implement a temporary fix (supporting complex input such as `[{\"image\": pil_image, \"num\": uint64_value}]` would be hard though).\r\n\r\nIn the meantime, you should be able to bypass this error by returning the `simhash` values as NumPy scalars in the script:\r\n```python\r\ndef _generate_examples(self, ...):\r\n ...\r\n yield {..., \"simhash\": np.uint64(simhash), ...}\r\n```", "Thank you for checking this issue in detail.\r\n\r\nHowever, it seems that using `np.uint64(simhash)` does not work. The same issue still exists.\r\n\r\nhttps://huggingface.co/datasets/liwu/MNBVC/commit/1e44f1e400b7e61052647d44c99cdae3bae9c830\r\n\r\nAnyway, we decide to use string type for these simhash values. Hope pyarrow can fix their bug soon.", "Arrow issue: https://github.com/apache/arrow/issues/36520", "May be something read your training data line by line.\r\nThen your training data just only one line. \r\nIt is so large.\r\nI guess.\r\n" ]

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[ "issue due to corrupted download files. resolved after cleaning download cache. sorry for any inconvinence." ]

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[ "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006152 / 0.011353 (-0.005200) | 0.003916 / 0.011008 (-0.007092) | 0.097355 / 0.038508 (0.058847) | 0.037228 / 0.023109 (0.014119) | 0.315753 / 0.275898 (0.039855) | 0.387949 / 0.323480 (0.064470) | 0.004804 / 0.007986 (-0.003181) | 0.002975 / 0.004328 (-0.001353) | 0.076932 / 0.004250 (0.072682) | 0.053497 / 0.037052 (0.016445) | 0.331143 / 0.258489 (0.072654) | 0.388347 / 0.293841 (0.094506) | 0.027535 / 0.128546 (-0.101011) | 0.008509 / 0.075646 (-0.067137) | 0.312639 / 0.419271 (-0.106632) | 0.047212 / 0.043533 (0.003679) | 0.316875 / 0.255139 (0.061736) | 0.352191 / 0.283200 (0.068992) | 0.021380 / 0.141683 (-0.120303) | 1.541401 / 1.452155 (0.089247) | 1.519420 / 1.492716 (0.026704) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.206332 / 0.018006 (0.188326) | 0.412252 / 0.000490 (0.411762) | 0.005119 / 0.000200 (0.004919) | 0.000077 / 0.000054 (0.000022) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.023856 / 0.037411 (-0.013556) | 0.098216 / 0.014526 (0.083691) | 0.106553 / 0.176557 (-0.070003) | 0.168767 / 0.737135 (-0.568369) | 0.109244 / 0.296338 (-0.187094) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.457580 / 0.215209 (0.242371) | 4.583246 / 2.077655 (2.505591) | 2.296356 / 1.504120 (0.792236) | 2.096216 / 1.541195 (0.555021) | 2.159086 / 1.468490 (0.690596) | 0.557905 / 4.584777 (-4.026872) | 3.345910 / 3.745712 (-0.399802) | 1.767436 / 5.269862 (-3.502426) | 1.021583 / 4.565676 (-3.544094) | 0.067265 / 0.424275 (-0.357011) | 0.011411 / 0.007607 (0.003804) | 0.559841 / 0.226044 (0.333797) | 5.586892 / 2.268929 (3.317963) | 2.735520 / 55.444624 (-52.709104) | 2.429393 / 6.876477 (-4.447084) | 2.544901 / 2.142072 (0.402829) | 0.667603 / 4.805227 (-4.137625) | 0.136244 / 6.500664 (-6.364421) | 0.066961 / 0.075469 (-0.008508) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.206529 / 1.841788 (-0.635259) | 13.988306 / 8.074308 (5.913998) | 13.481813 / 10.191392 (3.290421) | 0.161901 / 0.680424 (-0.518523) | 0.016850 / 0.534201 (-0.517351) | 0.367657 / 0.579283 (-0.211626) | 0.393343 / 0.434364 (-0.041021) | 0.465288 / 0.540337 (-0.075050) | 0.559888 / 1.386936 (-0.827048) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.005956 / 0.011353 (-0.005397) | 0.003734 / 0.011008 (-0.007274) | 0.077841 / 0.038508 (0.039333) | 0.036532 / 0.023109 (0.013422) | 0.438923 / 0.275898 (0.163025) | 0.490133 / 0.323480 (0.166653) | 0.004651 / 0.007986 (-0.003335) | 0.002881 / 0.004328 (-0.001448) | 0.077868 / 0.004250 (0.073618) | 0.051700 / 0.037052 (0.014647) | 0.448018 / 0.258489 (0.189529) | 0.500304 / 0.293841 (0.206464) | 0.029051 / 0.128546 (-0.099496) | 0.008498 / 0.075646 (-0.067148) | 0.082932 / 0.419271 (-0.336339) | 0.043665 / 0.043533 (0.000132) | 0.431613 / 0.255139 (0.176474) | 0.458749 / 0.283200 (0.175549) | 0.021951 / 0.141683 (-0.119731) | 1.556043 / 1.452155 (0.103888) | 1.588391 / 1.492716 (0.095675) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.220674 / 0.018006 (0.202667) | 0.415408 / 0.000490 (0.414918) | 0.002613 / 0.000200 (0.002413) | 0.000075 / 0.000054 (0.000020) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.025548 / 0.037411 (-0.011863) | 0.103633 / 0.014526 (0.089107) | 0.115193 / 0.176557 (-0.061364) | 0.163971 / 0.737135 (-0.573164) | 0.114754 / 0.296338 (-0.181585) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.456823 / 0.215209 (0.241614) | 4.569950 / 2.077655 (2.492296) | 2.196339 / 1.504120 (0.692219) | 1.985822 / 1.541195 (0.444628) | 2.044083 / 1.468490 (0.575593) | 0.567919 / 4.584777 (-4.016858) | 3.397515 / 3.745712 (-0.348197) | 1.741087 / 5.269862 (-3.528775) | 1.041237 / 4.565676 (-3.524440) | 0.068963 / 0.424275 (-0.355313) | 0.011677 / 0.007607 (0.004070) | 0.565010 / 0.226044 (0.338966) | 5.625886 / 2.268929 (3.356957) | 2.670658 / 55.444624 (-52.773967) | 2.300279 / 6.876477 (-4.576198) | 2.392178 / 2.142072 (0.250106) | 0.680226 / 4.805227 (-4.125001) | 0.139119 / 6.500664 (-6.361545) | 0.067953 / 0.075469 (-0.007516) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.303280 / 1.841788 (-0.538507) | 14.458686 / 8.074308 (6.384378) | 14.409369 / 10.191392 (4.217977) | 0.144581 / 0.680424 (-0.535843) | 0.016634 / 0.534201 (-0.517567) | 0.364607 / 0.579283 (-0.214676) | 0.394521 / 0.434364 (-0.039843) | 0.433417 / 0.540337 (-0.106921) | 0.527127 / 1.386936 (-0.859809) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#04a36f9546484dceadb84a133c1a460281d018f8 \"CML watermark\")\n", "_The documentation is not available anymore as the PR was closed or merged._", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006245 / 0.011353 (-0.005108) | 0.003871 / 0.011008 (-0.007138) | 0.098823 / 0.038508 (0.060315) | 0.039853 / 0.023109 (0.016744) | 0.314989 / 0.275898 (0.039091) | 0.376733 / 0.323480 (0.053254) | 0.004754 / 0.007986 (-0.003232) | 0.002971 / 0.004328 (-0.001357) | 0.078451 / 0.004250 (0.074201) | 0.053160 / 0.037052 (0.016107) | 0.324443 / 0.258489 (0.065954) | 0.361488 / 0.293841 (0.067647) | 0.027942 / 0.128546 (-0.100604) | 0.008535 / 0.075646 (-0.067111) | 0.315526 / 0.419271 (-0.103745) | 0.045706 / 0.043533 (0.002174) | 0.329614 / 0.255139 (0.074475) | 0.336339 / 0.283200 (0.053139) | 0.021278 / 0.141683 (-0.120405) | 1.529710 / 1.452155 (0.077555) | 1.566833 / 1.492716 (0.074116) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.215263 / 0.018006 (0.197257) | 0.440320 / 0.000490 (0.439830) | 0.002627 / 0.000200 (0.002427) | 0.000075 / 0.000054 (0.000021) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.023971 / 0.037411 (-0.013441) | 0.100549 / 0.014526 (0.086023) | 0.106995 / 0.176557 (-0.069561) | 0.169630 / 0.737135 (-0.567505) | 0.111614 / 0.296338 (-0.184724) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.424911 / 0.215209 (0.209702) | 4.246920 / 2.077655 (2.169266) | 1.923321 / 1.504120 (0.419202) | 1.714795 / 1.541195 (0.173600) | 1.772906 / 1.468490 (0.304416) | 0.554676 / 4.584777 (-4.030101) | 3.478896 / 3.745712 (-0.266816) | 2.800494 / 5.269862 (-2.469368) | 1.382630 / 4.565676 (-3.183047) | 0.067271 / 0.424275 (-0.357004) | 0.010967 / 0.007607 (0.003360) | 0.526769 / 0.226044 (0.300725) | 5.288564 / 2.268929 (3.019636) | 2.337459 / 55.444624 (-53.107165) | 1.999975 / 6.876477 (-4.876502) | 2.102680 / 2.142072 (-0.039392) | 0.672181 / 4.805227 (-4.133046) | 0.135097 / 6.500664 (-6.365567) | 0.066950 / 0.075469 (-0.008519) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.264365 / 1.841788 (-0.577423) | 14.282440 / 8.074308 (6.208132) | 14.220200 / 10.191392 (4.028808) | 0.139055 / 0.680424 (-0.541369) | 0.016681 / 0.534201 (-0.517520) | 0.367936 / 0.579283 (-0.211348) | 0.393959 / 0.434364 (-0.040404) | 0.424438 / 0.540337 (-0.115900) | 0.508065 / 1.386936 (-0.878872) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006514 / 0.011353 (-0.004839) | 0.003890 / 0.011008 (-0.007118) | 0.078871 / 0.038508 (0.040363) | 0.038080 / 0.023109 (0.014971) | 0.358282 / 0.275898 (0.082384) | 0.430654 / 0.323480 (0.107174) | 0.005712 / 0.007986 (-0.002273) | 0.003030 / 0.004328 (-0.001299) | 0.078636 / 0.004250 (0.074386) | 0.057771 / 0.037052 (0.020719) | 0.368814 / 0.258489 (0.110325) | 0.437047 / 0.293841 (0.143206) | 0.029470 / 0.128546 (-0.099076) | 0.008523 / 0.075646 (-0.067124) | 0.083334 / 0.419271 (-0.335938) | 0.044505 / 0.043533 (0.000972) | 0.357484 / 0.255139 (0.102345) | 0.393839 / 0.283200 (0.110639) | 0.023340 / 0.141683 (-0.118343) | 1.561033 / 1.452155 (0.108878) | 1.595560 / 1.492716 (0.102844) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.204149 / 0.018006 (0.186143) | 0.442747 / 0.000490 (0.442257) | 0.003105 / 0.000200 (0.002905) | 0.000085 / 0.000054 (0.000030) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.027002 / 0.037411 (-0.010409) | 0.105595 / 0.014526 (0.091070) | 0.108695 / 0.176557 (-0.067861) | 0.163182 / 0.737135 (-0.573953) | 0.114999 / 0.296338 (-0.181339) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.483713 / 0.215209 (0.268504) | 4.836063 / 2.077655 (2.758409) | 2.488072 / 1.504120 (0.983952) | 2.289556 / 1.541195 (0.748361) | 2.342912 / 1.468490 (0.874422) | 0.565937 / 4.584777 (-4.018840) | 3.479085 / 3.745712 (-0.266627) | 1.770922 / 5.269862 (-3.498940) | 1.046084 / 4.565676 (-3.519592) | 0.067857 / 0.424275 (-0.356418) | 0.011283 / 0.007607 (0.003676) | 0.592966 / 0.226044 (0.366921) | 5.932842 / 2.268929 (3.663914) | 2.956252 / 55.444624 (-52.488372) | 2.602704 / 6.876477 (-4.273772) | 2.715625 / 2.142072 (0.573552) | 0.674299 / 4.805227 (-4.130929) | 0.136039 / 6.500664 (-6.364625) | 0.067629 / 0.075469 (-0.007840) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.333734 / 1.841788 (-0.508054) | 14.561943 / 8.074308 (6.487634) | 14.455385 / 10.191392 (4.263993) | 0.132020 / 0.680424 (-0.548404) | 0.016893 / 0.534201 (-0.517308) | 0.367146 / 0.579283 (-0.212137) | 0.399623 / 0.434364 (-0.034741) | 0.432658 / 0.540337 (-0.107680) | 0.530475 / 1.386936 (-0.856461) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#18da5adb22b2b403b8d8ae673192746d2ed7e9f9 \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006045 / 0.011353 (-0.005308) | 0.003906 / 0.011008 (-0.007103) | 0.097558 / 0.038508 (0.059050) | 0.038827 / 0.023109 (0.015718) | 0.393564 / 0.275898 (0.117666) | 0.442459 / 0.323480 (0.118980) | 0.004792 / 0.007986 (-0.003194) | 0.002984 / 0.004328 (-0.001345) | 0.076419 / 0.004250 (0.072169) | 0.053606 / 0.037052 (0.016554) | 0.409743 / 0.258489 (0.151254) | 0.445753 / 0.293841 (0.151912) | 0.027753 / 0.128546 (-0.100793) | 0.008428 / 0.075646 (-0.067219) | 0.310267 / 0.419271 (-0.109004) | 0.057582 / 0.043533 (0.014049) | 0.396624 / 0.255139 (0.141485) | 0.416288 / 0.283200 (0.133089) | 0.029048 / 0.141683 (-0.112635) | 1.495362 / 1.452155 (0.043207) | 1.546331 / 1.492716 (0.053615) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.203832 / 0.018006 (0.185826) | 0.423649 / 0.000490 (0.423160) | 0.004533 / 0.000200 (0.004333) | 0.000076 / 0.000054 (0.000022) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.023084 / 0.037411 (-0.014328) | 0.100503 / 0.014526 (0.085977) | 0.105058 / 0.176557 (-0.071499) | 0.168506 / 0.737135 (-0.568629) | 0.112019 / 0.296338 (-0.184320) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.425877 / 0.215209 (0.210668) | 4.251278 / 2.077655 (2.173624) | 1.931339 / 1.504120 (0.427219) | 1.730578 / 1.541195 (0.189383) | 1.750637 / 1.468490 (0.282147) | 0.559307 / 4.584777 (-4.025470) | 3.461665 / 3.745712 (-0.284047) | 2.826959 / 5.269862 (-2.442903) | 1.418448 / 4.565676 (-3.147229) | 0.067881 / 0.424275 (-0.356394) | 0.011394 / 0.007607 (0.003787) | 0.533226 / 0.226044 (0.307181) | 5.341849 / 2.268929 (3.072921) | 2.367832 / 55.444624 (-53.076792) | 2.027240 / 6.876477 (-4.849236) | 2.095852 / 2.142072 (-0.046220) | 0.673790 / 4.805227 (-4.131437) | 0.136044 / 6.500664 (-6.364620) | 0.066350 / 0.075469 (-0.009119) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.203740 / 1.841788 (-0.638048) | 13.720879 / 8.074308 (5.646571) | 13.405939 / 10.191392 (3.214547) | 0.146792 / 0.680424 (-0.533632) | 0.016844 / 0.534201 (-0.517357) | 0.373455 / 0.579283 (-0.205828) | 0.394596 / 0.434364 (-0.039768) | 0.464715 / 0.540337 (-0.075623) | 0.558931 / 1.386936 (-0.828005) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006118 / 0.011353 (-0.005235) | 0.003817 / 0.011008 (-0.007191) | 0.077494 / 0.038508 (0.038985) | 0.037507 / 0.023109 (0.014398) | 0.387030 / 0.275898 (0.111132) | 0.437352 / 0.323480 (0.113872) | 0.004810 / 0.007986 (-0.003176) | 0.002935 / 0.004328 (-0.001394) | 0.077143 / 0.004250 (0.072892) | 0.053986 / 0.037052 (0.016933) | 0.393164 / 0.258489 (0.134675) | 0.449603 / 0.293841 (0.155762) | 0.029303 / 0.128546 (-0.099244) | 0.008481 / 0.075646 (-0.067165) | 0.083363 / 0.419271 (-0.335908) | 0.043877 / 0.043533 (0.000344) | 0.378175 / 0.255139 (0.123036) | 0.403996 / 0.283200 (0.120797) | 0.021688 / 0.141683 (-0.119995) | 1.541606 / 1.452155 (0.089452) | 1.552996 / 1.492716 (0.060280) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.236759 / 0.018006 (0.218752) | 0.416221 / 0.000490 (0.415732) | 0.000862 / 0.000200 (0.000662) | 0.000070 / 0.000054 (0.000016) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.025543 / 0.037411 (-0.011868) | 0.101731 / 0.014526 (0.087206) | 0.108482 / 0.176557 (-0.068075) | 0.160290 / 0.737135 (-0.576845) | 0.111392 / 0.296338 (-0.184946) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.457767 / 0.215209 (0.242558) | 4.565976 / 2.077655 (2.488321) | 2.245413 / 1.504120 (0.741294) | 2.031458 / 1.541195 (0.490264) | 2.073193 / 1.468490 (0.604702) | 0.560461 / 4.584777 (-4.024316) | 3.422536 / 3.745712 (-0.323176) | 2.977017 / 5.269862 (-2.292845) | 1.377021 / 4.565676 (-3.188655) | 0.068444 / 0.424275 (-0.355831) | 0.011036 / 0.007607 (0.003429) | 0.571501 / 0.226044 (0.345456) | 5.702652 / 2.268929 (3.433723) | 2.727132 / 55.444624 (-52.717492) | 2.399269 / 6.876477 (-4.477208) | 2.574281 / 2.142072 (0.432208) | 0.682600 / 4.805227 (-4.122627) | 0.136943 / 6.500664 (-6.363722) | 0.067126 / 0.075469 (-0.008343) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.322196 / 1.841788 (-0.519592) | 14.239509 / 8.074308 (6.165201) | 14.235779 / 10.191392 (4.044387) | 0.148262 / 0.680424 (-0.532162) | 0.016566 / 0.534201 (-0.517635) | 0.364034 / 0.579283 (-0.215249) | 0.399157 / 0.434364 (-0.035207) | 0.426348 / 0.540337 (-0.113990) | 0.520804 / 1.386936 (-0.866132) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#8f57aae06bd325d76cb70cb774450f3a66f169cf \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007808 / 0.011353 (-0.003545) | 0.004706 / 0.011008 (-0.006303) | 0.100530 / 0.038508 (0.062022) | 0.052052 / 0.023109 (0.028943) | 0.419300 / 0.275898 (0.143402) | 0.488451 / 0.323480 (0.164971) | 0.006350 / 0.007986 (-0.001636) | 0.003875 / 0.004328 (-0.000453) | 0.076489 / 0.004250 (0.072238) | 0.077554 / 0.037052 (0.040502) | 0.435863 / 0.258489 (0.177373) | 0.483241 / 0.293841 (0.189400) | 0.037518 / 0.128546 (-0.091028) | 0.009857 / 0.075646 (-0.065789) | 0.340933 / 0.419271 (-0.078339) | 0.087046 / 0.043533 (0.043514) | 0.410721 / 0.255139 (0.155582) | 0.428995 / 0.283200 (0.145795) | 0.041701 / 0.141683 (-0.099982) | 1.821017 / 1.452155 (0.368862) | 1.837021 / 1.492716 (0.344305) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.228444 / 0.018006 (0.210438) | 0.480446 / 0.000490 (0.479956) | 0.004963 / 0.000200 (0.004763) | 0.000101 / 0.000054 (0.000046) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.032485 / 0.037411 (-0.004926) | 0.096500 / 0.014526 (0.081974) | 0.111547 / 0.176557 (-0.065010) | 0.178842 / 0.737135 (-0.558294) | 0.111099 / 0.296338 (-0.185240) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.467159 / 0.215209 (0.251950) | 4.701676 / 2.077655 (2.624021) | 2.390560 / 1.504120 (0.886440) | 2.197722 / 1.541195 (0.656528) | 2.264705 / 1.468490 (0.796215) | 0.568667 / 4.584777 (-4.016110) | 4.200724 / 3.745712 (0.455012) | 3.777625 / 5.269862 (-1.492236) | 2.372451 / 4.565676 (-2.193225) | 0.067562 / 0.424275 (-0.356714) | 0.008947 / 0.007607 (0.001340) | 0.556910 / 0.226044 (0.330865) | 5.528927 / 2.268929 (3.259998) | 2.902780 / 55.444624 (-52.541844) | 2.507933 / 6.876477 (-4.368544) | 2.734627 / 2.142072 (0.592554) | 0.683305 / 4.805227 (-4.121922) | 0.158288 / 6.500664 (-6.342376) | 0.071252 / 0.075469 (-0.004217) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.487502 / 1.841788 (-0.354286) | 22.193341 / 8.074308 (14.119033) | 15.922607 / 10.191392 (5.731215) | 0.172189 / 0.680424 (-0.508235) | 0.021502 / 0.534201 (-0.512699) | 0.471198 / 0.579283 (-0.108085) | 0.475979 / 0.434364 (0.041615) | 0.544675 / 0.540337 (0.004338) | 0.756102 / 1.386936 (-0.630834) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007635 / 0.011353 (-0.003717) | 0.004614 / 0.011008 (-0.006394) | 0.075852 / 0.038508 (0.037344) | 0.049700 / 0.023109 (0.026591) | 0.425957 / 0.275898 (0.150059) | 0.512590 / 0.323480 (0.189110) | 0.006921 / 0.007986 (-0.001065) | 0.003714 / 0.004328 (-0.000615) | 0.075536 / 0.004250 (0.071286) | 0.070206 / 0.037052 (0.033153) | 0.455706 / 0.258489 (0.197217) | 0.512231 / 0.293841 (0.218390) | 0.036685 / 0.128546 (-0.091861) | 0.009793 / 0.075646 (-0.065853) | 0.084208 / 0.419271 (-0.335064) | 0.065262 / 0.043533 (0.021729) | 0.423761 / 0.255139 (0.168622) | 0.456791 / 0.283200 (0.173591) | 0.044539 / 0.141683 (-0.097144) | 1.797029 / 1.452155 (0.344874) | 1.864124 / 1.492716 (0.371408) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.366840 / 0.018006 (0.348834) | 0.479254 / 0.000490 (0.478765) | 0.070383 / 0.000200 (0.070183) | 0.000762 / 0.000054 (0.000707) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.034233 / 0.037411 (-0.003178) | 0.103140 / 0.014526 (0.088614) | 0.117099 / 0.176557 (-0.059457) | 0.178532 / 0.737135 (-0.558603) | 0.120092 / 0.296338 (-0.176247) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.492993 / 0.215209 (0.277784) | 4.878776 / 2.077655 (2.801121) | 2.566666 / 1.504120 (1.062547) | 2.356383 / 1.541195 (0.815188) | 2.454723 / 1.468490 (0.986233) | 0.571432 / 4.584777 (-4.013345) | 4.240554 / 3.745712 (0.494842) | 7.509259 / 5.269862 (2.239398) | 4.040294 / 4.565676 (-0.525382) | 0.067409 / 0.424275 (-0.356866) | 0.008657 / 0.007607 (0.001050) | 0.585751 / 0.226044 (0.359707) | 5.967668 / 2.268929 (3.698739) | 3.195573 / 55.444624 (-52.249052) | 2.839772 / 6.876477 (-4.036704) | 2.806319 / 2.142072 (0.664246) | 0.681502 / 4.805227 (-4.123725) | 0.158673 / 6.500664 (-6.341991) | 0.073224 / 0.075469 (-0.002245) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.623335 / 1.841788 (-0.218453) | 22.490806 / 8.074308 (14.416498) | 16.762435 / 10.191392 (6.571043) | 0.180961 / 0.680424 (-0.499463) | 0.022716 / 0.534201 (-0.511485) | 0.472910 / 0.579283 (-0.106373) | 0.471616 / 0.434364 (0.037252) | 0.548192 / 0.540337 (0.007854) | 0.734357 / 1.386936 (-0.652579) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#c0498b47a00153d4730352b6595fc51ab054fb95 \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.005858 / 0.011353 (-0.005495) | 0.003512 / 0.011008 (-0.007497) | 0.079739 / 0.038508 (0.041231) | 0.057736 / 0.023109 (0.034627) | 0.317640 / 0.275898 (0.041742) | 0.354157 / 0.323480 (0.030677) | 0.004772 / 0.007986 (-0.003214) | 0.002824 / 0.004328 (-0.001504) | 0.063288 / 0.004250 (0.059037) | 0.049542 / 0.037052 (0.012489) | 0.323974 / 0.258489 (0.065485) | 0.372149 / 0.293841 (0.078308) | 0.026841 / 0.128546 (-0.101705) | 0.007846 / 0.075646 (-0.067800) | 0.262546 / 0.419271 (-0.156725) | 0.051952 / 0.043533 (0.008420) | 0.319439 / 0.255139 (0.064300) | 0.343862 / 0.283200 (0.060663) | 0.027021 / 0.141683 (-0.114662) | 1.445211 / 1.452155 (-0.006944) | 1.485006 / 1.492716 (-0.007711) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.183174 / 0.018006 (0.165167) | 0.422794 / 0.000490 (0.422304) | 0.004148 / 0.000200 (0.003948) | 0.000067 / 0.000054 (0.000012) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.023037 / 0.037411 (-0.014374) | 0.071300 / 0.014526 (0.056775) | 0.083022 / 0.176557 (-0.093535) | 0.146215 / 0.737135 (-0.590920) | 0.082549 / 0.296338 (-0.213789) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.422846 / 0.215209 (0.207637) | 4.215280 / 2.077655 (2.137626) | 2.256802 / 1.504120 (0.752682) | 2.056867 / 1.541195 (0.515673) | 2.102478 / 1.468490 (0.633988) | 0.497552 / 4.584777 (-4.087225) | 3.049716 / 3.745712 (-0.695996) | 4.209227 / 5.269862 (-1.060635) | 2.599947 / 4.565676 (-1.965730) | 0.059131 / 0.424275 (-0.365144) | 0.006459 / 0.007607 (-0.001148) | 0.495047 / 0.226044 (0.269003) | 4.952332 / 2.268929 (2.683404) | 2.675260 / 55.444624 (-52.769365) | 2.333223 / 6.876477 (-4.543254) | 2.449573 / 2.142072 (0.307500) | 0.583420 / 4.805227 (-4.221807) | 0.125140 / 6.500664 (-6.375524) | 0.060209 / 0.075469 (-0.015260) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.215033 / 1.841788 (-0.626755) | 18.101107 / 8.074308 (10.026799) | 13.489222 / 10.191392 (3.297830) | 0.147122 / 0.680424 (-0.533302) | 0.016567 / 0.534201 (-0.517634) | 0.329909 / 0.579283 (-0.249374) | 0.340952 / 0.434364 (-0.093412) | 0.379166 / 0.540337 (-0.161172) | 0.510767 / 1.386936 (-0.876169) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.005942 / 0.011353 (-0.005411) | 0.003628 / 0.011008 (-0.007380) | 0.061975 / 0.038508 (0.023467) | 0.058331 / 0.023109 (0.035221) | 0.393277 / 0.275898 (0.117379) | 0.410740 / 0.323480 (0.087261) | 0.004546 / 0.007986 (-0.003440) | 0.002826 / 0.004328 (-0.001503) | 0.062216 / 0.004250 (0.057966) | 0.049801 / 0.037052 (0.012748) | 0.394070 / 0.258489 (0.135581) | 0.414407 / 0.293841 (0.120566) | 0.027161 / 0.128546 (-0.101385) | 0.007901 / 0.075646 (-0.067746) | 0.066778 / 0.419271 (-0.352493) | 0.041354 / 0.043533 (-0.002179) | 0.379432 / 0.255139 (0.124293) | 0.402966 / 0.283200 (0.119766) | 0.020279 / 0.141683 (-0.121404) | 1.416986 / 1.452155 (-0.035169) | 1.474335 / 1.492716 (-0.018382) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.226147 / 0.018006 (0.208140) | 0.404361 / 0.000490 (0.403871) | 0.000358 / 0.000200 (0.000158) | 0.000054 / 0.000054 (-0.000000) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.025105 / 0.037411 (-0.012306) | 0.075849 / 0.014526 (0.061323) | 0.084781 / 0.176557 (-0.091775) | 0.137415 / 0.737135 (-0.599720) | 0.086288 / 0.296338 (-0.210051) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.445925 / 0.215209 (0.230716) | 4.453478 / 2.077655 (2.375823) | 2.419048 / 1.504120 (0.914928) | 2.246363 / 1.541195 (0.705168) | 2.304022 / 1.468490 (0.835532) | 0.499132 / 4.584777 (-4.085645) | 3.001336 / 3.745712 (-0.744376) | 2.902593 / 5.269862 (-2.367269) | 1.819843 / 4.565676 (-2.745834) | 0.057210 / 0.424275 (-0.367065) | 0.006338 / 0.007607 (-0.001269) | 0.523280 / 0.226044 (0.297236) | 5.235969 / 2.268929 (2.967040) | 2.897585 / 55.444624 (-52.547039) | 2.541586 / 6.876477 (-4.334891) | 2.564233 / 2.142072 (0.422160) | 0.584714 / 4.805227 (-4.220513) | 0.124611 / 6.500664 (-6.376053) | 0.061774 / 0.075469 (-0.013695) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.349799 / 1.841788 (-0.491988) | 18.225076 / 8.074308 (10.150768) | 13.781518 / 10.191392 (3.590126) | 0.130562 / 0.680424 (-0.549862) | 0.016434 / 0.534201 (-0.517767) | 0.331607 / 0.579283 (-0.247676) | 0.343456 / 0.434364 (-0.090908) | 0.380437 / 0.540337 (-0.159900) | 0.522793 / 1.386936 (-0.864143) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#f0a3dbbd2e7ace162346d95ec27db674e80c1e23 \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.013721 / 0.011353 (0.002368) | 0.005715 / 0.011008 (-0.005293) | 0.090116 / 0.038508 (0.051608) | 0.087185 / 0.023109 (0.064075) | 0.427813 / 0.275898 (0.151915) | 0.390614 / 0.323480 (0.067135) | 0.006976 / 0.007986 (-0.001009) | 0.004231 / 0.004328 (-0.000098) | 0.078320 / 0.004250 (0.074070) | 0.066235 / 0.037052 (0.029183) | 0.439904 / 0.258489 (0.181415) | 0.424119 / 0.293841 (0.130278) | 0.050362 / 0.128546 (-0.078184) | 0.014992 / 0.075646 (-0.060654) | 0.293519 / 0.419271 (-0.125753) | 0.066906 / 0.043533 (0.023373) | 0.449657 / 0.255139 (0.194518) | 0.393800 / 0.283200 (0.110600) | 0.032258 / 0.141683 (-0.109425) | 1.539534 / 1.452155 (0.087379) | 1.675292 / 1.492716 (0.182576) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.210515 / 0.018006 (0.192508) | 0.506817 / 0.000490 (0.506327) | 0.001938 / 0.000200 (0.001738) | 0.000118 / 0.000054 (0.000064) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.026019 / 0.037411 (-0.011393) | 0.080635 / 0.014526 (0.066109) | 0.103050 / 0.176557 (-0.073507) | 0.160597 / 0.737135 (-0.576538) | 0.095844 / 0.296338 (-0.200495) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.506359 / 0.215209 (0.291150) | 5.041586 / 2.077655 (2.963931) | 2.198288 / 1.504120 (0.694168) | 1.987544 / 1.541195 (0.446349) | 1.866790 / 1.468490 (0.398300) | 0.681642 / 4.584777 (-3.903135) | 4.719306 / 3.745712 (0.973593) | 7.669869 / 5.269862 (2.400008) | 4.466082 / 4.565676 (-0.099595) | 0.092974 / 0.424275 (-0.331301) | 0.008196 / 0.007607 (0.000589) | 0.707656 / 0.226044 (0.481612) | 6.974507 / 2.268929 (4.705579) | 3.254206 / 55.444624 (-52.190418) | 2.499019 / 6.876477 (-4.377457) | 2.509089 / 2.142072 (0.367017) | 0.915952 / 4.805227 (-3.889276) | 0.192119 / 6.500664 (-6.308545) | 0.065473 / 0.075469 (-0.009996) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.309078 / 1.841788 (-0.532710) | 19.660348 / 8.074308 (11.586040) | 16.659582 / 10.191392 (6.468190) | 0.194315 / 0.680424 (-0.486109) | 0.027773 / 0.534201 (-0.506428) | 0.401241 / 0.579283 (-0.178042) | 0.515799 / 0.434364 (0.081435) | 0.488772 / 0.540337 (-0.051566) | 0.604790 / 1.386936 (-0.782146) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006823 / 0.011353 (-0.004530) | 0.003940 / 0.011008 (-0.007068) | 0.061533 / 0.038508 (0.023025) | 0.065241 / 0.023109 (0.042132) | 0.411790 / 0.275898 (0.135892) | 0.475720 / 0.323480 (0.152241) | 0.005376 / 0.007986 (-0.002609) | 0.003433 / 0.004328 (-0.000895) | 0.065703 / 0.004250 (0.061452) | 0.050736 / 0.037052 (0.013683) | 0.435890 / 0.258489 (0.177401) | 0.436698 / 0.293841 (0.142857) | 0.040357 / 0.128546 (-0.088189) | 0.011578 / 0.075646 (-0.064069) | 0.072831 / 0.419271 (-0.346440) | 0.055698 / 0.043533 (0.012165) | 0.408225 / 0.255139 (0.153086) | 0.439551 / 0.283200 (0.156352) | 0.030469 / 0.141683 (-0.111214) | 1.443866 / 1.452155 (-0.008289) | 1.502022 / 1.492716 (0.009306) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.290338 / 0.018006 (0.272332) | 0.540726 / 0.000490 (0.540236) | 0.003244 / 0.000200 (0.003044) | 0.000170 / 0.000054 (0.000116) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.030865 / 0.037411 (-0.006547) | 0.090866 / 0.014526 (0.076340) | 0.106224 / 0.176557 (-0.070332) | 0.166583 / 0.737135 (-0.570553) | 0.104448 / 0.296338 (-0.191891) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.518025 / 0.215209 (0.302816) | 6.027065 / 2.077655 (3.949410) | 2.671840 / 1.504120 (1.167720) | 2.273949 / 1.541195 (0.732754) | 2.414892 / 1.468490 (0.946402) | 0.774318 / 4.584777 (-3.810459) | 5.020364 / 3.745712 (1.274652) | 4.146927 / 5.269862 (-1.122934) | 2.584598 / 4.565676 (-1.981078) | 0.089519 / 0.424275 (-0.334756) | 0.009181 / 0.007607 (0.001574) | 0.654467 / 0.226044 (0.428423) | 6.421595 / 2.268929 (4.152666) | 3.091589 / 55.444624 (-52.353036) | 2.554798 / 6.876477 (-4.321679) | 2.441354 / 2.142072 (0.299282) | 0.943386 / 4.805227 (-3.861841) | 0.173641 / 6.500664 (-6.327023) | 0.072209 / 0.075469 (-0.003260) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.557147 / 1.841788 (-0.284641) | 19.980747 / 8.074308 (11.906439) | 17.816813 / 10.191392 (7.625421) | 0.212078 / 0.680424 (-0.468346) | 0.025435 / 0.534201 (-0.508766) | 0.396200 / 0.579283 (-0.183084) | 0.546249 / 0.434364 (0.111885) | 0.459632 / 0.540337 (-0.080705) | 0.616548 / 1.386936 (-0.770388) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#535e972a70a3d4f8490a7e1a77ac43d5a4ab2655 \"CML watermark\")\n" ]

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[ "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006897 / 0.011353 (-0.004456) | 0.004207 / 0.011008 (-0.006802) | 0.104828 / 0.038508 (0.066320) | 0.048054 / 0.023109 (0.024945) | 0.373991 / 0.275898 (0.098093) | 0.426740 / 0.323480 (0.103260) | 0.005540 / 0.007986 (-0.002446) | 0.003531 / 0.004328 (-0.000797) | 0.079304 / 0.004250 (0.075053) | 0.066996 / 0.037052 (0.029944) | 0.370675 / 0.258489 (0.112186) | 0.414154 / 0.293841 (0.120313) | 0.031567 / 0.128546 (-0.096979) | 0.008843 / 0.075646 (-0.066803) | 0.357426 / 0.419271 (-0.061845) | 0.067040 / 0.043533 (0.023508) | 0.362384 / 0.255139 (0.107245) | 0.376056 / 0.283200 (0.092856) | 0.032985 / 0.141683 (-0.108697) | 1.560603 / 1.452155 (0.108448) | 1.619024 / 1.492716 (0.126308) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.229059 / 0.018006 (0.211053) | 0.440513 / 0.000490 (0.440023) | 0.004647 / 0.000200 (0.004447) | 0.000085 / 0.000054 (0.000030) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.029517 / 0.037411 (-0.007894) | 0.120974 / 0.014526 (0.106448) | 0.125070 / 0.176557 (-0.051486) | 0.184695 / 0.737135 (-0.552441) | 0.130244 / 0.296338 (-0.166095) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.436930 / 0.215209 (0.221721) | 4.356118 / 2.077655 (2.278463) | 2.049169 / 1.504120 (0.545049) | 1.842898 / 1.541195 (0.301703) | 1.918948 / 1.468490 (0.450458) | 0.553573 / 4.584777 (-4.031204) | 3.883195 / 3.745712 (0.137483) | 3.209780 / 5.269862 (-2.060081) | 1.551707 / 4.565676 (-3.013970) | 0.068181 / 0.424275 (-0.356094) | 0.012370 / 0.007607 (0.004762) | 0.539899 / 0.226044 (0.313854) | 5.380008 / 2.268929 (3.111079) | 2.518178 / 55.444624 (-52.926446) | 2.174190 / 6.876477 (-4.702286) | 2.317812 / 2.142072 (0.175740) | 0.674154 / 4.805227 (-4.131073) | 0.149313 / 6.500664 (-6.351351) | 0.068297 / 0.075469 (-0.007172) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.261426 / 1.841788 (-0.580362) | 15.316378 / 8.074308 (7.242070) | 13.573512 / 10.191392 (3.382120) | 0.190022 / 0.680424 (-0.490401) | 0.018697 / 0.534201 (-0.515504) | 0.448122 / 0.579283 (-0.131161) | 0.435044 / 0.434364 (0.000681) | 0.550065 / 0.540337 (0.009728) | 0.653547 / 1.386936 (-0.733389) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007116 / 0.011353 (-0.004237) | 0.004375 / 0.011008 (-0.006633) | 0.081793 / 0.038508 (0.043285) | 0.047980 / 0.023109 (0.024871) | 0.392185 / 0.275898 (0.116287) | 0.462263 / 0.323480 (0.138783) | 0.005574 / 0.007986 (-0.002412) | 0.003552 / 0.004328 (-0.000776) | 0.080413 / 0.004250 (0.076162) | 0.065539 / 0.037052 (0.028487) | 0.413137 / 0.258489 (0.154648) | 0.467377 / 0.293841 (0.173536) | 0.034386 / 0.128546 (-0.094160) | 0.009183 / 0.075646 (-0.066464) | 0.087542 / 0.419271 (-0.331730) | 0.053954 / 0.043533 (0.010421) | 0.385096 / 0.255139 (0.129957) | 0.404900 / 0.283200 (0.121701) | 0.025908 / 0.141683 (-0.115775) | 1.550159 / 1.452155 (0.098005) | 1.598794 / 1.492716 (0.106078) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.246222 / 0.018006 (0.228216) | 0.441095 / 0.000490 (0.440605) | 0.006863 / 0.000200 (0.006663) | 0.000109 / 0.000054 (0.000055) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.032179 / 0.037411 (-0.005233) | 0.120112 / 0.014526 (0.105586) | 0.129326 / 0.176557 (-0.047230) | 0.184542 / 0.737135 (-0.552593) | 0.135038 / 0.296338 (-0.161300) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.459002 / 0.215209 (0.243793) | 4.580258 / 2.077655 (2.502604) | 2.296689 / 1.504120 (0.792569) | 2.104338 / 1.541195 (0.563143) | 2.182896 / 1.468490 (0.714406) | 0.546447 / 4.584777 (-4.038330) | 3.854047 / 3.745712 (0.108335) | 1.873829 / 5.269862 (-3.396032) | 1.116484 / 4.565676 (-3.449193) | 0.067158 / 0.424275 (-0.357117) | 0.012035 / 0.007607 (0.004428) | 0.556642 / 0.226044 (0.330597) | 5.574436 / 2.268929 (3.305508) | 2.828223 / 55.444624 (-52.616402) | 2.519851 / 6.876477 (-4.356626) | 2.668594 / 2.142072 (0.526521) | 0.675989 / 4.805227 (-4.129238) | 0.146075 / 6.500664 (-6.354589) | 0.067788 / 0.075469 (-0.007681) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.345958 / 1.841788 (-0.495830) | 15.672748 / 8.074308 (7.598440) | 14.937583 / 10.191392 (4.746191) | 0.163479 / 0.680424 (-0.516945) | 0.018364 / 0.534201 (-0.515837) | 0.433296 / 0.579283 (-0.145987) | 0.432463 / 0.434364 (-0.001901) | 0.512000 / 0.540337 (-0.028338) | 0.619397 / 1.386936 (-0.767539) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#0832d48a07ed00b406271f4b4439e6d54ae38ebf \"CML watermark\")\n", "_The documentation is not available anymore as the PR was closed or merged._", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.010097 / 0.011353 (-0.001256) | 0.005070 / 0.011008 (-0.005939) | 0.118638 / 0.038508 (0.080130) | 0.043651 / 0.023109 (0.020542) | 0.356074 / 0.275898 (0.080176) | 0.414578 / 0.323480 (0.091098) | 0.005939 / 0.007986 (-0.002046) | 0.004927 / 0.004328 (0.000598) | 0.089545 / 0.004250 (0.085294) | 0.067533 / 0.037052 (0.030481) | 0.371550 / 0.258489 (0.113061) | 0.417808 / 0.293841 (0.123967) | 0.045186 / 0.128546 (-0.083361) | 0.015763 / 0.075646 (-0.059883) | 0.393304 / 0.419271 (-0.025967) | 0.065123 / 0.043533 (0.021591) | 0.345057 / 0.255139 (0.089918) | 0.378809 / 0.283200 (0.095610) | 0.033243 / 0.141683 (-0.108440) | 1.679956 / 1.452155 (0.227802) | 1.775456 / 1.492716 (0.282739) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.229723 / 0.018006 (0.211717) | 0.554630 / 0.000490 (0.554140) | 0.008729 / 0.000200 (0.008529) | 0.000183 / 0.000054 (0.000129) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.027284 / 0.037411 (-0.010128) | 0.114741 / 0.014526 (0.100215) | 0.129188 / 0.176557 (-0.047369) | 0.189270 / 0.737135 (-0.547866) | 0.126000 / 0.296338 (-0.170339) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.580417 / 0.215209 (0.365208) | 5.829337 / 2.077655 (3.751683) | 2.421191 / 1.504120 (0.917071) | 2.063673 / 1.541195 (0.522479) | 2.133427 / 1.468490 (0.664937) | 0.830964 / 4.584777 (-3.753813) | 5.107139 / 3.745712 (1.361427) | 4.599451 / 5.269862 (-0.670410) | 2.406502 / 4.565676 (-2.159175) | 0.100422 / 0.424275 (-0.323853) | 0.011850 / 0.007607 (0.004243) | 0.741881 / 0.226044 (0.515836) | 7.425689 / 2.268929 (5.156760) | 3.068948 / 55.444624 (-52.375676) | 2.496292 / 6.876477 (-4.380184) | 2.566420 / 2.142072 (0.424348) | 1.093084 / 4.805227 (-3.712144) | 0.224106 / 6.500664 (-6.276558) | 0.084549 / 0.075469 (0.009080) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.416315 / 1.841788 (-0.425473) | 16.306901 / 8.074308 (8.232593) | 19.792419 / 10.191392 (9.601027) | 0.224223 / 0.680424 (-0.456201) | 0.026385 / 0.534201 (-0.507816) | 0.463460 / 0.579283 (-0.115823) | 0.598385 / 0.434364 (0.164021) | 0.543981 / 0.540337 (0.003644) | 0.647454 / 1.386936 (-0.739482) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.009470 / 0.011353 (-0.001883) | 0.004800 / 0.011008 (-0.006208) | 0.094276 / 0.038508 (0.055768) | 0.045157 / 0.023109 (0.022048) | 0.397302 / 0.275898 (0.121404) | 0.474213 / 0.323480 (0.150733) | 0.005826 / 0.007986 (-0.002160) | 0.003724 / 0.004328 (-0.000605) | 0.090060 / 0.004250 (0.085809) | 0.066671 / 0.037052 (0.029618) | 0.439560 / 0.258489 (0.181071) | 0.468598 / 0.293841 (0.174757) | 0.044549 / 0.128546 (-0.083997) | 0.014000 / 0.075646 (-0.061646) | 0.110457 / 0.419271 (-0.308815) | 0.065898 / 0.043533 (0.022365) | 0.408101 / 0.255139 (0.152962) | 0.433473 / 0.283200 (0.150273) | 0.038438 / 0.141683 (-0.103245) | 1.767781 / 1.452155 (0.315626) | 1.791575 / 1.492716 (0.298859) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.230257 / 0.018006 (0.212251) | 0.492280 / 0.000490 (0.491790) | 0.005110 / 0.000200 (0.004910) | 0.000119 / 0.000054 (0.000065) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.028854 / 0.037411 (-0.008557) | 0.111702 / 0.014526 (0.097176) | 0.122040 / 0.176557 (-0.054517) | 0.179103 / 0.737135 (-0.558032) | 0.128869 / 0.296338 (-0.167470) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.634795 / 0.215209 (0.419586) | 6.204760 / 2.077655 (4.127105) | 2.692479 / 1.504120 (1.188359) | 2.324260 / 1.541195 (0.783066) | 2.380640 / 1.468490 (0.912149) | 0.887827 / 4.584777 (-3.696950) | 5.251648 / 3.745712 (1.505935) | 2.632767 / 5.269862 (-2.637095) | 1.745721 / 4.565676 (-2.819955) | 0.108364 / 0.424275 (-0.315911) | 0.013409 / 0.007607 (0.005802) | 0.783427 / 0.226044 (0.557383) | 7.765144 / 2.268929 (5.496216) | 3.340686 / 55.444624 (-52.103938) | 2.715340 / 6.876477 (-4.161137) | 2.768604 / 2.142072 (0.626531) | 1.119746 / 4.805227 (-3.685481) | 0.210804 / 6.500664 (-6.289860) | 0.072600 / 0.075469 (-0.002869) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.517334 / 1.841788 (-0.324454) | 17.046837 / 8.074308 (8.972529) | 19.371090 / 10.191392 (9.179698) | 0.194275 / 0.680424 (-0.486148) | 0.026712 / 0.534201 (-0.507488) | 0.462731 / 0.579283 (-0.116552) | 0.568958 / 0.434364 (0.134595) | 0.555707 / 0.540337 (0.015370) | 0.663654 / 1.386936 (-0.723283) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#5d20476b1d4c8e11e0ffafc1570cbf4bd19011cf \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006423 / 0.011353 (-0.004930) | 0.003882 / 0.011008 (-0.007126) | 0.082976 / 0.038508 (0.044468) | 0.071281 / 0.023109 (0.048171) | 0.311367 / 0.275898 (0.035469) | 0.348228 / 0.323480 (0.024748) | 0.005315 / 0.007986 (-0.002671) | 0.003326 / 0.004328 (-0.001003) | 0.064641 / 0.004250 (0.060391) | 0.056134 / 0.037052 (0.019081) | 0.314071 / 0.258489 (0.055582) | 0.360534 / 0.293841 (0.066693) | 0.030642 / 0.128546 (-0.097904) | 0.008301 / 0.075646 (-0.067345) | 0.285820 / 0.419271 (-0.133451) | 0.069241 / 0.043533 (0.025708) | 0.313995 / 0.255139 (0.058856) | 0.336656 / 0.283200 (0.053457) | 0.031686 / 0.141683 (-0.109997) | 1.467627 / 1.452155 (0.015472) | 1.536493 / 1.492716 (0.043777) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.196518 / 0.018006 (0.178512) | 0.458235 / 0.000490 (0.457745) | 0.005599 / 0.000200 (0.005399) | 0.000088 / 0.000054 (0.000034) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.027371 / 0.037411 (-0.010040) | 0.080986 / 0.014526 (0.066460) | 0.093296 / 0.176557 (-0.083260) | 0.150592 / 0.737135 (-0.586543) | 0.094150 / 0.296338 (-0.202188) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.379412 / 0.215209 (0.164202) | 3.797927 / 2.077655 (1.720272) | 1.830654 / 1.504120 (0.326534) | 1.669569 / 1.541195 (0.128374) | 1.746738 / 1.468490 (0.278248) | 0.479536 / 4.584777 (-4.105241) | 3.592867 / 3.745712 (-0.152845) | 5.468098 / 5.269862 (0.198237) | 3.268013 / 4.565676 (-1.297663) | 0.056635 / 0.424275 (-0.367640) | 0.007224 / 0.007607 (-0.000383) | 0.456681 / 0.226044 (0.230636) | 4.566736 / 2.268929 (2.297807) | 2.362831 / 55.444624 (-53.081793) | 1.965141 / 6.876477 (-4.911336) | 2.156905 / 2.142072 (0.014833) | 0.572543 / 4.805227 (-4.232684) | 0.132203 / 6.500664 (-6.368461) | 0.059254 / 0.075469 (-0.016215) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.256134 / 1.841788 (-0.585654) | 19.905438 / 8.074308 (11.831130) | 14.179556 / 10.191392 (3.988164) | 0.168043 / 0.680424 (-0.512381) | 0.018215 / 0.534201 (-0.515986) | 0.392740 / 0.579283 (-0.186543) | 0.398397 / 0.434364 (-0.035967) | 0.463806 / 0.540337 (-0.076531) | 0.616248 / 1.386936 (-0.770688) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006564 / 0.011353 (-0.004789) | 0.003923 / 0.011008 (-0.007085) | 0.063929 / 0.038508 (0.025421) | 0.073780 / 0.023109 (0.050671) | 0.360242 / 0.275898 (0.084344) | 0.395078 / 0.323480 (0.071598) | 0.005265 / 0.007986 (-0.002720) | 0.003229 / 0.004328 (-0.001100) | 0.064094 / 0.004250 (0.059843) | 0.057468 / 0.037052 (0.020416) | 0.369530 / 0.258489 (0.111041) | 0.411159 / 0.293841 (0.117318) | 0.031278 / 0.128546 (-0.097268) | 0.008424 / 0.075646 (-0.067222) | 0.070411 / 0.419271 (-0.348860) | 0.048714 / 0.043533 (0.005181) | 0.361280 / 0.255139 (0.106141) | 0.382468 / 0.283200 (0.099269) | 0.023059 / 0.141683 (-0.118624) | 1.452369 / 1.452155 (0.000215) | 1.519192 / 1.492716 (0.026475) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.223745 / 0.018006 (0.205739) | 0.442086 / 0.000490 (0.441596) | 0.000379 / 0.000200 (0.000179) | 0.000055 / 0.000054 (0.000001) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.030919 / 0.037411 (-0.006493) | 0.088483 / 0.014526 (0.073958) | 0.101165 / 0.176557 (-0.075391) | 0.154332 / 0.737135 (-0.582804) | 0.103030 / 0.296338 (-0.193309) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.414520 / 0.215209 (0.199311) | 4.126754 / 2.077655 (2.049099) | 2.142677 / 1.504120 (0.638557) | 1.995300 / 1.541195 (0.454106) | 2.101678 / 1.468490 (0.633188) | 0.481099 / 4.584777 (-4.103678) | 3.562813 / 3.745712 (-0.182900) | 3.392463 / 5.269862 (-1.877399) | 1.983943 / 4.565676 (-2.581734) | 0.056594 / 0.424275 (-0.367681) | 0.007216 / 0.007607 (-0.000391) | 0.495085 / 0.226044 (0.269041) | 4.955640 / 2.268929 (2.686712) | 2.629434 / 55.444624 (-52.815191) | 2.269577 / 6.876477 (-4.606900) | 2.357708 / 2.142072 (0.215635) | 0.612370 / 4.805227 (-4.192857) | 0.131169 / 6.500664 (-6.369495) | 0.061029 / 0.075469 (-0.014440) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.339438 / 1.841788 (-0.502350) | 19.757611 / 8.074308 (11.683303) | 14.246254 / 10.191392 (4.054862) | 0.170750 / 0.680424 (-0.509674) | 0.018192 / 0.534201 (-0.516009) | 0.395693 / 0.579283 (-0.183590) | 0.411003 / 0.434364 (-0.023361) | 0.478531 / 0.540337 (-0.061806) | 0.650291 / 1.386936 (-0.736645) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#3e34d06d746688dd5d26e4c85517b7e1a2f361ca \"CML watermark\")\n" ]

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[ "The metrics API in `datasets` is deprecated as of version 2.0, and `evaulate` is our new library for metrics. You can add a new metric to it by following [these steps](https://huggingface.co/docs/evaluate/creating_and_sharing)." ]

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[ "_The documentation is not available anymore as the PR was closed or merged._", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006038 / 0.011353 (-0.005315) | 0.003797 / 0.011008 (-0.007211) | 0.097686 / 0.038508 (0.059178) | 0.035235 / 0.023109 (0.012126) | 0.317294 / 0.275898 (0.041396) | 0.377682 / 0.323480 (0.054202) | 0.003485 / 0.007986 (-0.004501) | 0.003603 / 0.004328 (-0.000725) | 0.077268 / 0.004250 (0.073017) | 0.054649 / 0.037052 (0.017597) | 0.322293 / 0.258489 (0.063804) | 0.372277 / 0.293841 (0.078436) | 0.027927 / 0.128546 (-0.100619) | 0.008495 / 0.075646 (-0.067151) | 0.313078 / 0.419271 (-0.106193) | 0.046974 / 0.043533 (0.003441) | 0.313848 / 0.255139 (0.058709) | 0.338454 / 0.283200 (0.055255) | 0.020462 / 0.141683 (-0.121221) | 1.473027 / 1.452155 (0.020873) | 1.539468 / 1.492716 (0.046752) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.221429 / 0.018006 (0.203423) | 0.412044 / 0.000490 (0.411555) | 0.005866 / 0.000200 (0.005666) | 0.000075 / 0.000054 (0.000021) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.022870 / 0.037411 (-0.014541) | 0.099129 / 0.014526 (0.084603) | 0.103463 / 0.176557 (-0.073094) | 0.164969 / 0.737135 (-0.572166) | 0.110000 / 0.296338 (-0.186339) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.431311 / 0.215209 (0.216102) | 4.293562 / 2.077655 (2.215907) | 1.961209 / 1.504120 (0.457089) | 1.733680 / 1.541195 (0.192485) | 1.793171 / 1.468490 (0.324681) | 0.568566 / 4.584777 (-4.016211) | 3.401794 / 3.745712 (-0.343918) | 1.827949 / 5.269862 (-3.441913) | 1.055963 / 4.565676 (-3.509714) | 0.068459 / 0.424275 (-0.355816) | 0.011586 / 0.007607 (0.003979) | 0.533936 / 0.226044 (0.307891) | 5.347637 / 2.268929 (3.078708) | 2.378056 / 55.444624 (-53.066569) | 2.032159 / 6.876477 (-4.844318) | 2.159064 / 2.142072 (0.016991) | 0.674528 / 4.805227 (-4.130699) | 0.136859 / 6.500664 (-6.363805) | 0.066629 / 0.075469 (-0.008840) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.218084 / 1.841788 (-0.623704) | 14.141710 / 8.074308 (6.067402) | 13.588415 / 10.191392 (3.397023) | 0.155104 / 0.680424 (-0.525320) | 0.017160 / 0.534201 (-0.517041) | 0.375558 / 0.579283 (-0.203725) | 0.386293 / 0.434364 (-0.048071) | 0.459476 / 0.540337 (-0.080862) | 0.548561 / 1.386936 (-0.838375) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.005878 / 0.011353 (-0.005475) | 0.003750 / 0.011008 (-0.007259) | 0.077720 / 0.038508 (0.039212) | 0.034955 / 0.023109 (0.011846) | 0.357480 / 0.275898 (0.081582) | 0.418210 / 0.323480 (0.094730) | 0.004566 / 0.007986 (-0.003419) | 0.002918 / 0.004328 (-0.001410) | 0.076517 / 0.004250 (0.072266) | 0.050202 / 0.037052 (0.013150) | 0.368166 / 0.258489 (0.109677) | 0.415681 / 0.293841 (0.121840) | 0.029496 / 0.128546 (-0.099050) | 0.008547 / 0.075646 (-0.067099) | 0.083037 / 0.419271 (-0.336234) | 0.045001 / 0.043533 (0.001468) | 0.356503 / 0.255139 (0.101364) | 0.383747 / 0.283200 (0.100547) | 0.025071 / 0.141683 (-0.116612) | 1.541985 / 1.452155 (0.089830) | 1.594710 / 1.492716 (0.101994) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.204491 / 0.018006 (0.186484) | 0.408686 / 0.000490 (0.408196) | 0.002505 / 0.000200 (0.002305) | 0.000082 / 0.000054 (0.000027) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.024446 / 0.037411 (-0.012965) | 0.101432 / 0.014526 (0.086906) | 0.108105 / 0.176557 (-0.068452) | 0.161195 / 0.737135 (-0.575940) | 0.112671 / 0.296338 (-0.183667) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.459697 / 0.215209 (0.244488) | 4.570071 / 2.077655 (2.492416) | 2.211547 / 1.504120 (0.707427) | 1.996651 / 1.541195 (0.455457) | 2.015621 / 1.468490 (0.547131) | 0.567423 / 4.584777 (-4.017354) | 3.408027 / 3.745712 (-0.337685) | 2.913824 / 5.269862 (-2.356038) | 1.423223 / 4.565676 (-3.142453) | 0.068740 / 0.424275 (-0.355535) | 0.010997 / 0.007607 (0.003390) | 0.567340 / 0.226044 (0.341296) | 5.666280 / 2.268929 (3.397351) | 2.804934 / 55.444624 (-52.639690) | 2.430761 / 6.876477 (-4.445716) | 2.451820 / 2.142072 (0.309748) | 0.681926 / 4.805227 (-4.123301) | 0.137761 / 6.500664 (-6.362903) | 0.067173 / 0.075469 (-0.008296) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.329853 / 1.841788 (-0.511934) | 14.436232 / 8.074308 (6.361924) | 14.398645 / 10.191392 (4.207253) | 0.147421 / 0.680424 (-0.533002) | 0.016743 / 0.534201 (-0.517458) | 0.364964 / 0.579283 (-0.214319) | 0.387072 / 0.434364 (-0.047292) | 0.423892 / 0.540337 (-0.116445) | 0.521304 / 1.386936 (-0.865632) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#a62b6ce65f718e9ff4189da86d160ae4bb197fc2 \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006463 / 0.011353 (-0.004889) | 0.003923 / 0.011008 (-0.007086) | 0.102096 / 0.038508 (0.063588) | 0.040230 / 0.023109 (0.017121) | 0.384688 / 0.275898 (0.108789) | 0.445574 / 0.323480 (0.122094) | 0.003590 / 0.007986 (-0.004395) | 0.004023 / 0.004328 (-0.000306) | 0.080125 / 0.004250 (0.075875) | 0.057406 / 0.037052 (0.020354) | 0.395049 / 0.258489 (0.136560) | 0.438065 / 0.293841 (0.144224) | 0.028963 / 0.128546 (-0.099583) | 0.008693 / 0.075646 (-0.066954) | 0.317158 / 0.419271 (-0.102114) | 0.047930 / 0.043533 (0.004397) | 0.382442 / 0.255139 (0.127303) | 0.410665 / 0.283200 (0.127466) | 0.020127 / 0.141683 (-0.121555) | 1.558554 / 1.452155 (0.106400) | 1.590959 / 1.492716 (0.098242) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.208826 / 0.018006 (0.190820) | 0.432037 / 0.000490 (0.431547) | 0.006509 / 0.000200 (0.006309) | 0.000285 / 0.000054 (0.000230) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.023460 / 0.037411 (-0.013951) | 0.099070 / 0.014526 (0.084545) | 0.105771 / 0.176557 (-0.070785) | 0.166683 / 0.737135 (-0.570452) | 0.108755 / 0.296338 (-0.187583) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.424324 / 0.215209 (0.209115) | 4.225696 / 2.077655 (2.148042) | 1.910955 / 1.504120 (0.406835) | 1.704493 / 1.541195 (0.163298) | 1.782784 / 1.468490 (0.314293) | 0.562927 / 4.584777 (-4.021850) | 3.380163 / 3.745712 (-0.365550) | 1.779641 / 5.269862 (-3.490221) | 1.029134 / 4.565676 (-3.536543) | 0.068325 / 0.424275 (-0.355950) | 0.011528 / 0.007607 (0.003921) | 0.530141 / 0.226044 (0.304097) | 5.323443 / 2.268929 (3.054514) | 2.346956 / 55.444624 (-53.097668) | 2.013335 / 6.876477 (-4.863142) | 2.118531 / 2.142072 (-0.023541) | 0.675206 / 4.805227 (-4.130021) | 0.135473 / 6.500664 (-6.365191) | 0.064804 / 0.075469 (-0.010665) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.240179 / 1.841788 (-0.601608) | 14.692449 / 8.074308 (6.618141) | 13.672223 / 10.191392 (3.480831) | 0.147748 / 0.680424 (-0.532676) | 0.017119 / 0.534201 (-0.517082) | 0.369481 / 0.579283 (-0.209802) | 0.390133 / 0.434364 (-0.044231) | 0.458768 / 0.540337 (-0.081569) | 0.548989 / 1.386936 (-0.837947) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006319 / 0.011353 (-0.005034) | 0.003975 / 0.011008 (-0.007033) | 0.077886 / 0.038508 (0.039378) | 0.038322 / 0.023109 (0.015213) | 0.379851 / 0.275898 (0.103953) | 0.456749 / 0.323480 (0.133269) | 0.005320 / 0.007986 (-0.002665) | 0.003135 / 0.004328 (-0.001194) | 0.078272 / 0.004250 (0.074022) | 0.059919 / 0.037052 (0.022866) | 0.430062 / 0.258489 (0.171573) | 0.477432 / 0.293841 (0.183591) | 0.029713 / 0.128546 (-0.098833) | 0.008704 / 0.075646 (-0.066942) | 0.082488 / 0.419271 (-0.336784) | 0.044667 / 0.043533 (0.001134) | 0.354910 / 0.255139 (0.099771) | 0.434637 / 0.283200 (0.151438) | 0.026402 / 0.141683 (-0.115281) | 1.528825 / 1.452155 (0.076671) | 1.548209 / 1.492716 (0.055493) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.237988 / 0.018006 (0.219982) | 0.420402 / 0.000490 (0.419913) | 0.003098 / 0.000200 (0.002898) | 0.000077 / 0.000054 (0.000023) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.026253 / 0.037411 (-0.011159) | 0.106137 / 0.014526 (0.091611) | 0.110273 / 0.176557 (-0.066284) | 0.165316 / 0.737135 (-0.571819) | 0.115720 / 0.296338 (-0.180619) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.454244 / 0.215209 (0.239035) | 4.526018 / 2.077655 (2.448364) | 2.395985 / 1.504120 (0.891865) | 2.234822 / 1.541195 (0.693627) | 2.370235 / 1.468490 (0.901745) | 0.567607 / 4.584777 (-4.017169) | 3.650156 / 3.745712 (-0.095556) | 3.360094 / 5.269862 (-1.909768) | 1.415252 / 4.565676 (-3.150424) | 0.068012 / 0.424275 (-0.356263) | 0.011135 / 0.007607 (0.003528) | 0.561967 / 0.226044 (0.335923) | 5.621819 / 2.268929 (3.352890) | 2.676912 / 55.444624 (-52.767712) | 2.338306 / 6.876477 (-4.538171) | 2.430888 / 2.142072 (0.288815) | 0.684576 / 4.805227 (-4.120651) | 0.138923 / 6.500664 (-6.361741) | 0.069933 / 0.075469 (-0.005536) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.313383 / 1.841788 (-0.528405) | 15.125088 / 8.074308 (7.050780) | 14.801501 / 10.191392 (4.610109) | 0.134235 / 0.680424 (-0.546189) | 0.017058 / 0.534201 (-0.517143) | 0.365166 / 0.579283 (-0.214117) | 0.395415 / 0.434364 (-0.038949) | 0.419355 / 0.540337 (-0.120983) | 0.513411 / 1.386936 (-0.873525) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#8b9649b3cfb49342e44873ce7e29e0c75eaf3efa \"CML watermark\")\n" ]

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[ "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006722 / 0.011353 (-0.004631) | 0.004425 / 0.011008 (-0.006583) | 0.100850 / 0.038508 (0.062341) | 0.040816 / 0.023109 (0.017707) | 0.348823 / 0.275898 (0.072925) | 0.446285 / 0.323480 (0.122805) | 0.005738 / 0.007986 (-0.002247) | 0.003517 / 0.004328 (-0.000811) | 0.078824 / 0.004250 (0.074574) | 0.064695 / 0.037052 (0.027643) | 0.389894 / 0.258489 (0.131405) | 0.416107 / 0.293841 (0.122266) | 0.028850 / 0.128546 (-0.099696) | 0.009011 / 0.075646 (-0.066635) | 0.323117 / 0.419271 (-0.096154) | 0.049162 / 0.043533 (0.005629) | 0.340144 / 0.255139 (0.085005) | 0.382072 / 0.283200 (0.098872) | 0.023160 / 0.141683 (-0.118523) | 1.549218 / 1.452155 (0.097063) | 1.581266 / 1.492716 (0.088550) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.293360 / 0.018006 (0.275353) | 0.602189 / 0.000490 (0.601700) | 0.004608 / 0.000200 (0.004408) | 0.000082 / 0.000054 (0.000028) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.028144 / 0.037411 (-0.009267) | 0.107088 / 0.014526 (0.092562) | 0.112188 / 0.176557 (-0.064369) | 0.174669 / 0.737135 (-0.562466) | 0.116359 / 0.296338 (-0.179980) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.422911 / 0.215209 (0.207702) | 4.231524 / 2.077655 (2.153869) | 1.906711 / 1.504120 (0.402591) | 1.706841 / 1.541195 (0.165646) | 1.792066 / 1.468490 (0.323576) | 0.559221 / 4.584777 (-4.025556) | 3.434280 / 3.745712 (-0.311433) | 1.918714 / 5.269862 (-3.351148) | 1.073070 / 4.565676 (-3.492606) | 0.067891 / 0.424275 (-0.356384) | 0.011927 / 0.007607 (0.004320) | 0.530843 / 0.226044 (0.304799) | 5.309213 / 2.268929 (3.040285) | 2.439246 / 55.444624 (-53.005378) | 2.101245 / 6.876477 (-4.775231) | 2.177436 / 2.142072 (0.035363) | 0.672150 / 4.805227 (-4.133077) | 0.137571 / 6.500664 (-6.363093) | 0.068343 / 0.075469 (-0.007126) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.265262 / 1.841788 (-0.576525) | 14.988021 / 8.074308 (6.913713) | 13.611677 / 10.191392 (3.420285) | 0.171389 / 0.680424 (-0.509035) | 0.017681 / 0.534201 (-0.516520) | 0.377542 / 0.579283 (-0.201741) | 0.399475 / 0.434364 (-0.034889) | 0.469553 / 0.540337 (-0.070785) | 0.561888 / 1.386936 (-0.825048) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006782 / 0.011353 (-0.004571) | 0.004412 / 0.011008 (-0.006597) | 0.078594 / 0.038508 (0.040086) | 0.039930 / 0.023109 (0.016820) | 0.371879 / 0.275898 (0.095981) | 0.444910 / 0.323480 (0.121430) | 0.005707 / 0.007986 (-0.002279) | 0.003901 / 0.004328 (-0.000427) | 0.080125 / 0.004250 (0.075875) | 0.063977 / 0.037052 (0.026925) | 0.382781 / 0.258489 (0.124292) | 0.441791 / 0.293841 (0.147950) | 0.030428 / 0.128546 (-0.098118) | 0.009008 / 0.075646 (-0.066638) | 0.084447 / 0.419271 (-0.334824) | 0.044432 / 0.043533 (0.000899) | 0.365686 / 0.255139 (0.110547) | 0.394312 / 0.283200 (0.111113) | 0.024508 / 0.141683 (-0.117175) | 1.577020 / 1.452155 (0.124865) | 1.630259 / 1.492716 (0.137543) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.307960 / 0.018006 (0.289953) | 0.591473 / 0.000490 (0.590983) | 0.008098 / 0.000200 (0.007898) | 0.000110 / 0.000054 (0.000056) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.029567 / 0.037411 (-0.007845) | 0.112773 / 0.014526 (0.098247) | 0.117362 / 0.176557 (-0.059194) | 0.174293 / 0.737135 (-0.562843) | 0.123156 / 0.296338 (-0.173182) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.457475 / 0.215209 (0.242266) | 4.599067 / 2.077655 (2.521412) | 2.262638 / 1.504120 (0.758518) | 2.124943 / 1.541195 (0.583748) | 2.339912 / 1.468490 (0.871422) | 0.566264 / 4.584777 (-4.018513) | 3.489261 / 3.745712 (-0.256451) | 1.925151 / 5.269862 (-3.344711) | 1.099389 / 4.565676 (-3.466287) | 0.068232 / 0.424275 (-0.356043) | 0.011660 / 0.007607 (0.004052) | 0.571227 / 0.226044 (0.345183) | 5.702059 / 2.268929 (3.433130) | 2.837701 / 55.444624 (-52.606924) | 2.605468 / 6.876477 (-4.271008) | 2.818396 / 2.142072 (0.676323) | 0.681856 / 4.805227 (-4.123371) | 0.141401 / 6.500664 (-6.359263) | 0.069728 / 0.075469 (-0.005741) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.354935 / 1.841788 (-0.486853) | 15.437404 / 8.074308 (7.363095) | 15.415193 / 10.191392 (5.223801) | 0.153459 / 0.680424 (-0.526964) | 0.017190 / 0.534201 (-0.517011) | 0.367256 / 0.579283 (-0.212027) | 0.392709 / 0.434364 (-0.041655) | 0.426125 / 0.540337 (-0.114213) | 0.522612 / 1.386936 (-0.864324) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#25ac13d8ab23e7d99252ce083a45e8333b6bbcdc \"CML watermark\")\n", "_The documentation is not available anymore as the PR was closed or merged._", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.009183 / 0.011353 (-0.002170) | 0.005232 / 0.011008 (-0.005776) | 0.120349 / 0.038508 (0.081841) | 0.044715 / 0.023109 (0.021606) | 0.361519 / 0.275898 (0.085621) | 0.463702 / 0.323480 (0.140223) | 0.005842 / 0.007986 (-0.002144) | 0.004041 / 0.004328 (-0.000288) | 0.096953 / 0.004250 (0.092703) | 0.070593 / 0.037052 (0.033540) | 0.409790 / 0.258489 (0.151301) | 0.477452 / 0.293841 (0.183611) | 0.045827 / 0.128546 (-0.082719) | 0.014038 / 0.075646 (-0.061608) | 0.421317 / 0.419271 (0.002045) | 0.065276 / 0.043533 (0.021743) | 0.360074 / 0.255139 (0.104935) | 0.409147 / 0.283200 (0.125947) | 0.032444 / 0.141683 (-0.109238) | 1.739257 / 1.452155 (0.287102) | 1.831408 / 1.492716 (0.338692) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.274852 / 0.018006 (0.256846) | 0.596320 / 0.000490 (0.595830) | 0.006399 / 0.000200 (0.006199) | 0.000133 / 0.000054 (0.000079) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.031400 / 0.037411 (-0.006012) | 0.127052 / 0.014526 (0.112526) | 0.134269 / 0.176557 (-0.042288) | 0.225998 / 0.737135 (-0.511137) | 0.150019 / 0.296338 (-0.146319) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.654202 / 0.215209 (0.438993) | 6.216735 / 2.077655 (4.139081) | 2.440214 / 1.504120 (0.936094) | 2.150575 / 1.541195 (0.609380) | 2.124790 / 1.468490 (0.656300) | 0.923514 / 4.584777 (-3.661263) | 5.556924 / 3.745712 (1.811212) | 2.843886 / 5.269862 (-2.425975) | 1.834232 / 4.565676 (-2.731444) | 0.111735 / 0.424275 (-0.312540) | 0.014823 / 0.007607 (0.007216) | 0.820503 / 0.226044 (0.594459) | 7.887737 / 2.268929 (5.618809) | 3.120307 / 55.444624 (-52.324317) | 2.405856 / 6.876477 (-4.470621) | 2.411239 / 2.142072 (0.269167) | 1.071283 / 4.805227 (-3.733944) | 0.227738 / 6.500664 (-6.272926) | 0.073516 / 0.075469 (-0.001953) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.531806 / 1.841788 (-0.309982) | 18.547661 / 8.074308 (10.473353) | 21.083922 / 10.191392 (10.892530) | 0.241706 / 0.680424 (-0.438718) | 0.034169 / 0.534201 (-0.500032) | 0.497514 / 0.579283 (-0.081769) | 0.599801 / 0.434364 (0.165437) | 0.576465 / 0.540337 (0.036127) | 0.673509 / 1.386936 (-0.713427) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007558 / 0.011353 (-0.003795) | 0.005001 / 0.011008 (-0.006008) | 0.093809 / 0.038508 (0.055301) | 0.039792 / 0.023109 (0.016683) | 0.456869 / 0.275898 (0.180971) | 0.493370 / 0.323480 (0.169891) | 0.005561 / 0.007986 (-0.002424) | 0.003982 / 0.004328 (-0.000346) | 0.085421 / 0.004250 (0.081170) | 0.059817 / 0.037052 (0.022765) | 0.468040 / 0.258489 (0.209550) | 0.514853 / 0.293841 (0.221012) | 0.044267 / 0.128546 (-0.084279) | 0.012674 / 0.075646 (-0.062972) | 0.098324 / 0.419271 (-0.320948) | 0.056604 / 0.043533 (0.013071) | 0.432200 / 0.255139 (0.177061) | 0.459812 / 0.283200 (0.176612) | 0.033872 / 0.141683 (-0.107811) | 1.618576 / 1.452155 (0.166421) | 1.676562 / 1.492716 (0.183846) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.230625 / 0.018006 (0.212619) | 0.600558 / 0.000490 (0.600068) | 0.003419 / 0.000200 (0.003219) | 0.000113 / 0.000054 (0.000059) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.026916 / 0.037411 (-0.010496) | 0.103003 / 0.014526 (0.088478) | 0.117078 / 0.176557 (-0.059478) | 0.169359 / 0.737135 (-0.567776) | 0.120305 / 0.296338 (-0.176034) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.616877 / 0.215209 (0.401668) | 6.157232 / 2.077655 (4.079577) | 2.869219 / 1.504120 (1.365099) | 2.381410 / 1.541195 (0.840216) | 2.417357 / 1.468490 (0.948867) | 0.914947 / 4.584777 (-3.669830) | 5.718526 / 3.745712 (1.972814) | 2.757253 / 5.269862 (-2.512609) | 1.794122 / 4.565676 (-2.771554) | 0.108423 / 0.424275 (-0.315852) | 0.013378 / 0.007607 (0.005771) | 0.831067 / 0.226044 (0.605023) | 8.478946 / 2.268929 (6.210018) | 3.685937 / 55.444624 (-51.758687) | 2.867472 / 6.876477 (-4.009005) | 2.895975 / 2.142072 (0.753903) | 1.137547 / 4.805227 (-3.667681) | 0.213891 / 6.500664 (-6.286773) | 0.075825 / 0.075469 (0.000356) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.621193 / 1.841788 (-0.220594) | 17.322110 / 8.074308 (9.247802) | 21.804016 / 10.191392 (11.612624) | 0.243692 / 0.680424 (-0.436732) | 0.030331 / 0.534201 (-0.503870) | 0.492186 / 0.579283 (-0.087097) | 0.632583 / 0.434364 (0.198219) | 0.576265 / 0.540337 (0.035927) | 0.713165 / 1.386936 (-0.673771) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#a293ceb5aa41c4ae265c0e2aa9ada2d544466121 \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.008916 / 0.011353 (-0.002437) | 0.004737 / 0.011008 (-0.006271) | 0.134271 / 0.038508 (0.095763) | 0.054472 / 0.023109 (0.031363) | 0.380942 / 0.275898 (0.105044) | 0.474138 / 0.323480 (0.150658) | 0.007917 / 0.007986 (-0.000068) | 0.003748 / 0.004328 (-0.000580) | 0.092765 / 0.004250 (0.088515) | 0.077873 / 0.037052 (0.040821) | 0.397533 / 0.258489 (0.139043) | 0.454737 / 0.293841 (0.160896) | 0.039901 / 0.128546 (-0.088645) | 0.010188 / 0.075646 (-0.065458) | 0.447312 / 0.419271 (0.028040) | 0.068684 / 0.043533 (0.025151) | 0.371554 / 0.255139 (0.116415) | 0.459655 / 0.283200 (0.176455) | 0.027157 / 0.141683 (-0.114526) | 1.874643 / 1.452155 (0.422488) | 2.014800 / 1.492716 (0.522083) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.227079 / 0.018006 (0.209073) | 0.483241 / 0.000490 (0.482751) | 0.012404 / 0.000200 (0.012204) | 0.000409 / 0.000054 (0.000354) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.033135 / 0.037411 (-0.004277) | 0.137782 / 0.014526 (0.123257) | 0.142951 / 0.176557 (-0.033605) | 0.209825 / 0.737135 (-0.527311) | 0.152438 / 0.296338 (-0.143900) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.513066 / 0.215209 (0.297857) | 5.122776 / 2.077655 (3.045121) | 2.399270 / 1.504120 (0.895150) | 2.180143 / 1.541195 (0.638949) | 2.286395 / 1.468490 (0.817905) | 0.641866 / 4.584777 (-3.942911) | 4.694922 / 3.745712 (0.949210) | 2.543390 / 5.269862 (-2.726472) | 1.398592 / 4.565676 (-3.167084) | 0.088662 / 0.424275 (-0.335613) | 0.015854 / 0.007607 (0.008247) | 0.688891 / 0.226044 (0.462847) | 6.370148 / 2.268929 (4.101220) | 2.949974 / 55.444624 (-52.494650) | 2.538049 / 6.876477 (-4.338428) | 2.699380 / 2.142072 (0.557308) | 0.792670 / 4.805227 (-4.012557) | 0.169126 / 6.500664 (-6.331538) | 0.078511 / 0.075469 (0.003042) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.609119 / 1.841788 (-0.232669) | 18.785069 / 8.074308 (10.710761) | 16.670783 / 10.191392 (6.479391) | 0.213081 / 0.680424 (-0.467343) | 0.023904 / 0.534201 (-0.510296) | 0.567720 / 0.579283 (-0.011564) | 0.505806 / 0.434364 (0.071442) | 0.649466 / 0.540337 (0.109129) | 0.773174 / 1.386936 (-0.613762) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.008036 / 0.011353 (-0.003317) | 0.004808 / 0.011008 (-0.006201) | 0.094316 / 0.038508 (0.055808) | 0.056174 / 0.023109 (0.033065) | 0.481618 / 0.275898 (0.205720) | 0.565300 / 0.323480 (0.241820) | 0.006339 / 0.007986 (-0.001646) | 0.003950 / 0.004328 (-0.000379) | 0.093389 / 0.004250 (0.089139) | 0.076163 / 0.037052 (0.039111) | 0.489013 / 0.258489 (0.230524) | 0.565451 / 0.293841 (0.271611) | 0.039392 / 0.128546 (-0.089155) | 0.010553 / 0.075646 (-0.065093) | 0.101406 / 0.419271 (-0.317865) | 0.062355 / 0.043533 (0.018822) | 0.470461 / 0.255139 (0.215322) | 0.502574 / 0.283200 (0.219375) | 0.030196 / 0.141683 (-0.111486) | 1.893926 / 1.452155 (0.441771) | 1.958902 / 1.492716 (0.466185) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.198074 / 0.018006 (0.180068) | 0.476828 / 0.000490 (0.476338) | 0.003457 / 0.000200 (0.003257) | 0.000105 / 0.000054 (0.000051) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.037576 / 0.037411 (0.000165) | 0.146663 / 0.014526 (0.132138) | 0.152969 / 0.176557 (-0.023588) | 0.218683 / 0.737135 (-0.518452) | 0.161552 / 0.296338 (-0.134786) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.525988 / 0.215209 (0.310779) | 5.234673 / 2.077655 (3.157018) | 2.571668 / 1.504120 (1.067548) | 2.339760 / 1.541195 (0.798565) | 2.422886 / 1.468490 (0.954395) | 0.651537 / 4.584777 (-3.933240) | 4.811148 / 3.745712 (1.065436) | 4.451165 / 5.269862 (-0.818697) | 2.016283 / 4.565676 (-2.549394) | 0.096393 / 0.424275 (-0.327882) | 0.015222 / 0.007607 (0.007615) | 0.739132 / 0.226044 (0.513087) | 6.813327 / 2.268929 (4.544399) | 3.169018 / 55.444624 (-52.275606) | 2.783120 / 6.876477 (-4.093356) | 2.918979 / 2.142072 (0.776907) | 0.797476 / 4.805227 (-4.007751) | 0.171038 / 6.500664 (-6.329626) | 0.079878 / 0.075469 (0.004409) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.595082 / 1.841788 (-0.246705) | 19.685844 / 8.074308 (11.611536) | 17.518989 / 10.191392 (7.327597) | 0.220015 / 0.680424 (-0.460409) | 0.026351 / 0.534201 (-0.507850) | 0.578977 / 0.579283 (-0.000306) | 0.549564 / 0.434364 (0.115200) | 0.667564 / 0.540337 (0.127227) | 0.802121 / 1.386936 (-0.584815) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#e9aee64766aaddfda60a735cfc93345aed64bdcf \"CML watermark\")\n" ]

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[ "Thanks for reporting, @Praful932.\r\n\r\nLet's continue the conversation on the Hub: https://huggingface.co/datasets/xglue/discussions/5" ]

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[ "Thanks for reporting, @wangyuxinwhy. " ]

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[ "I just noticed the [docs](https://github.com/huggingface/datasets/blob/main/src/datasets/arrow_dataset.py#L2881C11-L2881C200) say:\r\n\r\n>If batched is `True` and `batch_size` is `n > 1`, then the function takes a batch of `n` examples as input and can return a batch with `n` examples, or with an arbitrary number of examples.\r\n\r\nso maybe this is a bug then.", "All the values in a batch must be of the same length. So one solution is dropping all the input columns:\r\n```python\r\ndata = data.map(lambda samples: tokenizer(samples[\"text\"], max_length=tokenizer.model_max_length, truncation=True, stride=4, return_overflowing_tokens=True), batched=True, remove_columns=data.column_names)\r\n```\r\n\r\nAnother is padding/transforming the input columns to the tokenizer output's length (447). " ]

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[ "_The documentation is not available anymore as the PR was closed or merged._", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006134 / 0.011353 (-0.005219) | 0.003816 / 0.011008 (-0.007193) | 0.098226 / 0.038508 (0.059718) | 0.036830 / 0.023109 (0.013721) | 0.314551 / 0.275898 (0.038653) | 0.372251 / 0.323480 (0.048771) | 0.004762 / 0.007986 (-0.003224) | 0.003041 / 0.004328 (-0.001287) | 0.077651 / 0.004250 (0.073401) | 0.052445 / 0.037052 (0.015393) | 0.324632 / 0.258489 (0.066143) | 0.365724 / 0.293841 (0.071883) | 0.028069 / 0.128546 (-0.100477) | 0.008444 / 0.075646 (-0.067203) | 0.312767 / 0.419271 (-0.106505) | 0.047773 / 0.043533 (0.004240) | 0.305317 / 0.255139 (0.050178) | 0.332007 / 0.283200 (0.048807) | 0.018985 / 0.141683 (-0.122698) | 1.538022 / 1.452155 (0.085868) | 1.575898 / 1.492716 (0.083182) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.204780 / 0.018006 (0.186774) | 0.428125 / 0.000490 (0.427635) | 0.003454 / 0.000200 (0.003254) | 0.000078 / 0.000054 (0.000024) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.025064 / 0.037411 (-0.012348) | 0.099419 / 0.014526 (0.084893) | 0.111068 / 0.176557 (-0.065489) | 0.169775 / 0.737135 (-0.567361) | 0.112067 / 0.296338 (-0.184271) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.429642 / 0.215209 (0.214433) | 4.275556 / 2.077655 (2.197901) | 1.914658 / 1.504120 (0.410539) | 1.706556 / 1.541195 (0.165361) | 1.754228 / 1.468490 (0.285738) | 0.563669 / 4.584777 (-4.021108) | 3.391501 / 3.745712 (-0.354211) | 1.791517 / 5.269862 (-3.478345) | 1.030704 / 4.565676 (-3.534973) | 0.070882 / 0.424275 (-0.353393) | 0.011351 / 0.007607 (0.003744) | 0.529438 / 0.226044 (0.303394) | 5.294316 / 2.268929 (3.025387) | 2.344653 / 55.444624 (-53.099972) | 1.997468 / 6.876477 (-4.879009) | 2.108932 / 2.142072 (-0.033140) | 0.676794 / 4.805227 (-4.128433) | 0.135058 / 6.500664 (-6.365607) | 0.065857 / 0.075469 (-0.009612) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.231864 / 1.841788 (-0.609924) | 13.986694 / 8.074308 (5.912386) | 13.306600 / 10.191392 (3.115208) | 0.145520 / 0.680424 (-0.534904) | 0.016717 / 0.534201 (-0.517484) | 0.366303 / 0.579283 (-0.212980) | 0.391637 / 0.434364 (-0.042727) | 0.425445 / 0.540337 (-0.114892) | 0.507719 / 1.386936 (-0.879217) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006236 / 0.011353 (-0.005116) | 0.003766 / 0.011008 (-0.007242) | 0.076794 / 0.038508 (0.038286) | 0.037210 / 0.023109 (0.014101) | 0.378387 / 0.275898 (0.102489) | 0.425456 / 0.323480 (0.101977) | 0.004694 / 0.007986 (-0.003291) | 0.002921 / 0.004328 (-0.001407) | 0.076985 / 0.004250 (0.072735) | 0.052188 / 0.037052 (0.015136) | 0.394385 / 0.258489 (0.135896) | 0.432527 / 0.293841 (0.138686) | 0.029091 / 0.128546 (-0.099455) | 0.008364 / 0.075646 (-0.067282) | 0.082583 / 0.419271 (-0.336689) | 0.042928 / 0.043533 (-0.000605) | 0.375321 / 0.255139 (0.120182) | 0.391719 / 0.283200 (0.108519) | 0.019388 / 0.141683 (-0.122295) | 1.550644 / 1.452155 (0.098489) | 1.604882 / 1.492716 (0.112166) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.236859 / 0.018006 (0.218853) | 0.418528 / 0.000490 (0.418039) | 0.000388 / 0.000200 (0.000188) | 0.000059 / 0.000054 (0.000004) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.025548 / 0.037411 (-0.011863) | 0.100644 / 0.014526 (0.086118) | 0.109102 / 0.176557 (-0.067455) | 0.161694 / 0.737135 (-0.575441) | 0.112088 / 0.296338 (-0.184250) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.484128 / 0.215209 (0.268919) | 4.849952 / 2.077655 (2.772297) | 2.512769 / 1.504120 (1.008649) | 2.303295 / 1.541195 (0.762100) | 2.356699 / 1.468490 (0.888209) | 0.564181 / 4.584777 (-4.020596) | 3.421393 / 3.745712 (-0.324319) | 2.570875 / 5.269862 (-2.698987) | 1.474307 / 4.565676 (-3.091370) | 0.068035 / 0.424275 (-0.356240) | 0.011300 / 0.007607 (0.003693) | 0.587867 / 0.226044 (0.361823) | 5.862447 / 2.268929 (3.593519) | 3.004017 / 55.444624 (-52.440607) | 2.664989 / 6.876477 (-4.211488) | 2.740020 / 2.142072 (0.597948) | 0.680840 / 4.805227 (-4.124387) | 0.137001 / 6.500664 (-6.363663) | 0.068098 / 0.075469 (-0.007371) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.297362 / 1.841788 (-0.544426) | 14.207891 / 8.074308 (6.133583) | 14.087562 / 10.191392 (3.896170) | 0.149514 / 0.680424 (-0.530910) | 0.016566 / 0.534201 (-0.517635) | 0.367602 / 0.579283 (-0.211681) | 0.400692 / 0.434364 (-0.033671) | 0.432907 / 0.540337 (-0.107431) | 0.525924 / 1.386936 (-0.861012) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#1ec069feaaf6c28d4e4df76d344693b591a74c3f \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006223 / 0.011353 (-0.005130) | 0.003672 / 0.011008 (-0.007336) | 0.097451 / 0.038508 (0.058943) | 0.036243 / 0.023109 (0.013133) | 0.375650 / 0.275898 (0.099752) | 0.431652 / 0.323480 (0.108172) | 0.004758 / 0.007986 (-0.003227) | 0.002941 / 0.004328 (-0.001387) | 0.077383 / 0.004250 (0.073132) | 0.055342 / 0.037052 (0.018289) | 0.390335 / 0.258489 (0.131846) | 0.427867 / 0.293841 (0.134026) | 0.027619 / 0.128546 (-0.100927) | 0.008244 / 0.075646 (-0.067402) | 0.313499 / 0.419271 (-0.105773) | 0.054987 / 0.043533 (0.011454) | 0.394044 / 0.255139 (0.138905) | 0.398784 / 0.283200 (0.115584) | 0.026499 / 0.141683 (-0.115184) | 1.496907 / 1.452155 (0.044753) | 1.554465 / 1.492716 (0.061749) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.241197 / 0.018006 (0.223190) | 0.427856 / 0.000490 (0.427366) | 0.006264 / 0.000200 (0.006065) | 0.000218 / 0.000054 (0.000164) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.025550 / 0.037411 (-0.011862) | 0.104426 / 0.014526 (0.089901) | 0.110310 / 0.176557 (-0.066246) | 0.173813 / 0.737135 (-0.563322) | 0.112129 / 0.296338 (-0.184209) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.458806 / 0.215209 (0.243597) | 4.576351 / 2.077655 (2.498697) | 2.265670 / 1.504120 (0.761550) | 2.073230 / 1.541195 (0.532035) | 2.135283 / 1.468490 (0.666793) | 0.562506 / 4.584777 (-4.022271) | 3.375101 / 3.745712 (-0.370611) | 1.734393 / 5.269862 (-3.535469) | 1.026622 / 4.565676 (-3.539054) | 0.068144 / 0.424275 (-0.356131) | 0.011092 / 0.007607 (0.003485) | 0.562779 / 0.226044 (0.336734) | 5.608256 / 2.268929 (3.339328) | 2.706468 / 55.444624 (-52.738157) | 2.381607 / 6.876477 (-4.494869) | 2.451027 / 2.142072 (0.308954) | 0.671590 / 4.805227 (-4.133637) | 0.135749 / 6.500664 (-6.364915) | 0.065389 / 0.075469 (-0.010080) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.244806 / 1.841788 (-0.596981) | 14.042150 / 8.074308 (5.967841) | 14.246612 / 10.191392 (4.055220) | 0.134309 / 0.680424 (-0.546114) | 0.017082 / 0.534201 (-0.517119) | 0.366043 / 0.579283 (-0.213240) | 0.400748 / 0.434364 (-0.033616) | 0.425695 / 0.540337 (-0.114643) | 0.509355 / 1.386936 (-0.877581) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006134 / 0.011353 (-0.005219) | 0.003980 / 0.011008 (-0.007028) | 0.078353 / 0.038508 (0.039845) | 0.038011 / 0.023109 (0.014902) | 0.375784 / 0.275898 (0.099886) | 0.433619 / 0.323480 (0.110139) | 0.004897 / 0.007986 (-0.003088) | 0.002981 / 0.004328 (-0.001347) | 0.077362 / 0.004250 (0.073112) | 0.056108 / 0.037052 (0.019056) | 0.395984 / 0.258489 (0.137495) | 0.427397 / 0.293841 (0.133556) | 0.029325 / 0.128546 (-0.099221) | 0.008498 / 0.075646 (-0.067148) | 0.082478 / 0.419271 (-0.336794) | 0.044085 / 0.043533 (0.000552) | 0.389923 / 0.255139 (0.134784) | 0.391180 / 0.283200 (0.107980) | 0.022452 / 0.141683 (-0.119231) | 1.507758 / 1.452155 (0.055603) | 1.530459 / 1.492716 (0.037743) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.230928 / 0.018006 (0.212922) | 0.408484 / 0.000490 (0.407995) | 0.000806 / 0.000200 (0.000606) | 0.000067 / 0.000054 (0.000012) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.025183 / 0.037411 (-0.012228) | 0.102292 / 0.014526 (0.087766) | 0.108142 / 0.176557 (-0.068415) | 0.161172 / 0.737135 (-0.575963) | 0.114476 / 0.296338 (-0.181862) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.482978 / 0.215209 (0.267769) | 4.816103 / 2.077655 (2.738448) | 2.505567 / 1.504120 (1.001447) | 2.302598 / 1.541195 (0.761404) | 2.371238 / 1.468490 (0.902748) | 0.567467 / 4.584777 (-4.017310) | 3.363407 / 3.745712 (-0.382306) | 1.746213 / 5.269862 (-3.523649) | 1.035468 / 4.565676 (-3.530208) | 0.068431 / 0.424275 (-0.355844) | 0.011069 / 0.007607 (0.003462) | 0.598241 / 0.226044 (0.372196) | 5.953927 / 2.268929 (3.684999) | 3.007493 / 55.444624 (-52.437132) | 2.629399 / 6.876477 (-4.247078) | 2.737201 / 2.142072 (0.595129) | 0.682456 / 4.805227 (-4.122771) | 0.137613 / 6.500664 (-6.363051) | 0.067941 / 0.075469 (-0.007528) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.306015 / 1.841788 (-0.535772) | 14.359240 / 8.074308 (6.284932) | 14.187601 / 10.191392 (3.996209) | 0.138612 / 0.680424 (-0.541812) | 0.016708 / 0.534201 (-0.517493) | 0.366365 / 0.579283 (-0.212918) | 0.396982 / 0.434364 (-0.037382) | 0.426939 / 0.540337 (-0.113398) | 0.520064 / 1.386936 (-0.866872) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#21d0fd041a5eca02d3ee787396216ac613c662ac \"CML watermark\")\n", "They use `token` and emit a deprecation warning if `use_auth_token` is passed instead (see https://github.com/huggingface/transformers/blob/78a2b19fc84ed55c65f4bf20a901edb7ceb73c5f/src/transformers/modeling_utils.py#L1933). \r\n\r\nI think we can update the `examples` scripts after merging this PR.", "> I think we can update the examples scripts after merging this PR.\r\n\r\nWe should do a release before updated in the examples scripts no ? That's why it's an option to not have a deprecation warning until transformers and co are updated with the `token` arg", "> We should do a release before updated in the examples scripts no ? That's why it's an option to not have a deprecation warning until transformers and co are updated with the token arg\r\n\r\nThis would avoid the warning only for the latest `datasets` release. TBH, I don't think this is worth the hassle, considering how simple it is to remove it.", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007644 / 0.011353 (-0.003709) | 0.004667 / 0.011008 (-0.006341) | 0.117347 / 0.038508 (0.078839) | 0.050620 / 0.023109 (0.027510) | 0.415402 / 0.275898 (0.139504) | 0.485898 / 0.323480 (0.162418) | 0.005848 / 0.007986 (-0.002138) | 0.003736 / 0.004328 (-0.000592) | 0.089798 / 0.004250 (0.085547) | 0.069344 / 0.037052 (0.032292) | 0.441684 / 0.258489 (0.183195) | 0.468972 / 0.293841 (0.175131) | 0.036637 / 0.128546 (-0.091909) | 0.010219 / 0.075646 (-0.065427) | 0.394293 / 0.419271 (-0.024978) | 0.061462 / 0.043533 (0.017929) | 0.409448 / 0.255139 (0.154309) | 0.431557 / 0.283200 (0.148358) | 0.027795 / 0.141683 (-0.113888) | 1.837844 / 1.452155 (0.385690) | 1.862683 / 1.492716 (0.369967) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.230500 / 0.018006 (0.212494) | 0.483139 / 0.000490 (0.482649) | 0.006517 / 0.000200 (0.006317) | 0.000143 / 0.000054 (0.000088) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.033152 / 0.037411 (-0.004259) | 0.133673 / 0.014526 (0.119147) | 0.143853 / 0.176557 (-0.032704) | 0.215254 / 0.737135 (-0.521882) | 0.150676 / 0.296338 (-0.145662) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.503796 / 0.215209 (0.288587) | 5.049981 / 2.077655 (2.972326) | 2.399427 / 1.504120 (0.895307) | 2.167635 / 1.541195 (0.626441) | 2.257448 / 1.468490 (0.788958) | 0.641298 / 4.584777 (-3.943479) | 4.828676 / 3.745712 (1.082964) | 4.346069 / 5.269862 (-0.923793) | 2.103890 / 4.565676 (-2.461786) | 0.079115 / 0.424275 (-0.345160) | 0.013377 / 0.007607 (0.005770) | 0.621207 / 0.226044 (0.395162) | 6.190939 / 2.268929 (3.922011) | 2.920129 / 55.444624 (-52.524495) | 2.549225 / 6.876477 (-4.327252) | 2.719221 / 2.142072 (0.577149) | 0.790949 / 4.805227 (-4.014278) | 0.172032 / 6.500664 (-6.328632) | 0.077779 / 0.075469 (0.002310) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.432572 / 1.841788 (-0.409216) | 21.000031 / 8.074308 (12.925723) | 17.555093 / 10.191392 (7.363701) | 0.166646 / 0.680424 (-0.513778) | 0.020451 / 0.534201 (-0.513750) | 0.488767 / 0.579283 (-0.090516) | 0.737036 / 0.434364 (0.302672) | 0.621694 / 0.540337 (0.081356) | 0.732074 / 1.386936 (-0.654862) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.008198 / 0.011353 (-0.003155) | 0.004987 / 0.011008 (-0.006021) | 0.090714 / 0.038508 (0.052206) | 0.053379 / 0.023109 (0.030270) | 0.425199 / 0.275898 (0.149301) | 0.514036 / 0.323480 (0.190556) | 0.006043 / 0.007986 (-0.001943) | 0.003888 / 0.004328 (-0.000441) | 0.088294 / 0.004250 (0.084043) | 0.073024 / 0.037052 (0.035971) | 0.435983 / 0.258489 (0.177494) | 0.514293 / 0.293841 (0.220452) | 0.039451 / 0.128546 (-0.089095) | 0.010439 / 0.075646 (-0.065207) | 0.096885 / 0.419271 (-0.322387) | 0.060165 / 0.043533 (0.016632) | 0.421053 / 0.255139 (0.165914) | 0.455545 / 0.283200 (0.172345) | 0.027234 / 0.141683 (-0.114449) | 1.768975 / 1.452155 (0.316820) | 1.842853 / 1.492716 (0.350137) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.278940 / 0.018006 (0.260933) | 0.480709 / 0.000490 (0.480219) | 0.000436 / 0.000200 (0.000236) | 0.000070 / 0.000054 (0.000016) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.034900 / 0.037411 (-0.002511) | 0.144893 / 0.014526 (0.130368) | 0.149567 / 0.176557 (-0.026989) | 0.213200 / 0.737135 (-0.523935) | 0.156735 / 0.296338 (-0.139604) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.535897 / 0.215209 (0.320687) | 5.336998 / 2.077655 (3.259343) | 2.685854 / 1.504120 (1.181734) | 2.470177 / 1.541195 (0.928983) | 2.547495 / 1.468490 (1.079004) | 0.642830 / 4.584777 (-3.941947) | 4.595866 / 3.745712 (0.850154) | 2.186696 / 5.269862 (-3.083165) | 1.317969 / 4.565676 (-3.247708) | 0.079268 / 0.424275 (-0.345007) | 0.013792 / 0.007607 (0.006185) | 0.662236 / 0.226044 (0.436192) | 6.604775 / 2.268929 (4.335847) | 3.355888 / 55.444624 (-52.088736) | 2.968911 / 6.876477 (-3.907565) | 3.121862 / 2.142072 (0.979790) | 0.794752 / 4.805227 (-4.010475) | 0.170800 / 6.500664 (-6.329864) | 0.078393 / 0.075469 (0.002924) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.601605 / 1.841788 (-0.240183) | 20.743553 / 8.074308 (12.669245) | 17.543968 / 10.191392 (7.352576) | 0.221884 / 0.680424 (-0.458540) | 0.020779 / 0.534201 (-0.513422) | 0.479677 / 0.579283 (-0.099606) | 0.516207 / 0.434364 (0.081843) | 0.564046 / 0.540337 (0.023709) | 0.711336 / 1.386936 (-0.675600) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#819bb4346434912eb405ce3f3e9f21dc25a2fe85 \"CML watermark\")\n", "Yes, sounds great! Thanks", "yup" ]

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[ "_The documentation is not available anymore as the PR was closed or merged._", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.009725 / 0.011353 (-0.001628) | 0.006014 / 0.011008 (-0.004994) | 0.136039 / 0.038508 (0.097531) | 0.049685 / 0.023109 (0.026576) | 0.492967 / 0.275898 (0.217068) | 0.553775 / 0.323480 (0.230295) | 0.007421 / 0.007986 (-0.000564) | 0.004686 / 0.004328 (0.000357) | 0.106639 / 0.004250 (0.102389) | 0.073483 / 0.037052 (0.036431) | 0.507194 / 0.258489 (0.248705) | 0.535760 / 0.293841 (0.241919) | 0.049666 / 0.128546 (-0.078880) | 0.014139 / 0.075646 (-0.061507) | 0.435459 / 0.419271 (0.016188) | 0.076026 / 0.043533 (0.032493) | 0.454542 / 0.255139 (0.199403) | 0.512724 / 0.283200 (0.229524) | 0.034969 / 0.141683 (-0.106713) | 1.881048 / 1.452155 (0.428893) | 1.959915 / 1.492716 (0.467199) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.265322 / 0.018006 (0.247316) | 0.573963 / 0.000490 (0.573474) | 0.017493 / 0.000200 (0.017293) | 0.000637 / 0.000054 (0.000582) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.028712 / 0.037411 (-0.008699) | 0.149554 / 0.014526 (0.135029) | 0.130013 / 0.176557 (-0.046544) | 0.203408 / 0.737135 (-0.533727) | 0.144778 / 0.296338 (-0.151561) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.664198 / 0.215209 (0.448989) | 6.418054 / 2.077655 (4.340399) | 2.602338 / 1.504120 (1.098219) | 2.212992 / 1.541195 (0.671797) | 2.214309 / 1.468490 (0.745819) | 0.914772 / 4.584777 (-3.670005) | 5.824831 / 3.745712 (2.079119) | 2.865381 / 5.269862 (-2.404481) | 1.906020 / 4.565676 (-2.659657) | 0.106947 / 0.424275 (-0.317328) | 0.013467 / 0.007607 (0.005860) | 0.834556 / 0.226044 (0.608512) | 8.237078 / 2.268929 (5.968150) | 3.380919 / 55.444624 (-52.063705) | 2.656713 / 6.876477 (-4.219764) | 2.834941 / 2.142072 (0.692869) | 1.151241 / 4.805227 (-3.653986) | 0.220860 / 6.500664 (-6.279804) | 0.080781 / 0.075469 (0.005312) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.655128 / 1.841788 (-0.186660) | 18.696108 / 8.074308 (10.621800) | 22.882108 / 10.191392 (12.690716) | 0.236041 / 0.680424 (-0.444383) | 0.031073 / 0.534201 (-0.503128) | 0.525263 / 0.579283 (-0.054021) | 0.632933 / 0.434364 (0.198569) | 0.707228 / 0.540337 (0.166890) | 0.753508 / 1.386936 (-0.633428) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.009875 / 0.011353 (-0.001478) | 0.005135 / 0.011008 (-0.005873) | 0.101307 / 0.038508 (0.062799) | 0.044895 / 0.023109 (0.021786) | 0.497824 / 0.275898 (0.221926) | 0.573098 / 0.323480 (0.249618) | 0.006669 / 0.007986 (-0.001317) | 0.004289 / 0.004328 (-0.000039) | 0.105824 / 0.004250 (0.101573) | 0.061002 / 0.037052 (0.023950) | 0.510127 / 0.258489 (0.251638) | 0.581387 / 0.293841 (0.287546) | 0.052843 / 0.128546 (-0.075703) | 0.015506 / 0.075646 (-0.060140) | 0.116057 / 0.419271 (-0.303215) | 0.063444 / 0.043533 (0.019912) | 0.479366 / 0.255139 (0.224227) | 0.518419 / 0.283200 (0.235220) | 0.034876 / 0.141683 (-0.106806) | 2.018446 / 1.452155 (0.566292) | 1.960755 / 1.492716 (0.468039) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.269077 / 0.018006 (0.251070) | 0.606059 / 0.000490 (0.605569) | 0.000488 / 0.000200 (0.000288) | 0.000093 / 0.000054 (0.000038) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.032465 / 0.037411 (-0.004946) | 0.136517 / 0.014526 (0.121991) | 0.147740 / 0.176557 (-0.028816) | 0.193802 / 0.737135 (-0.543334) | 0.151876 / 0.296338 (-0.144462) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.709866 / 0.215209 (0.494657) | 6.848193 / 2.077655 (4.770538) | 3.310853 / 1.504120 (1.806733) | 2.940813 / 1.541195 (1.399619) | 2.934934 / 1.468490 (1.466444) | 0.927104 / 4.584777 (-3.657673) | 5.921607 / 3.745712 (2.175895) | 4.926558 / 5.269862 (-0.343303) | 2.853269 / 4.565676 (-1.712407) | 0.120278 / 0.424275 (-0.303998) | 0.015468 / 0.007607 (0.007861) | 0.820509 / 0.226044 (0.594464) | 8.263136 / 2.268929 (5.994208) | 3.780214 / 55.444624 (-51.664410) | 3.108482 / 6.876477 (-3.767995) | 3.101544 / 2.142072 (0.959471) | 1.165539 / 4.805227 (-3.639688) | 0.229215 / 6.500664 (-6.271449) | 0.079862 / 0.075469 (0.004393) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.775071 / 1.841788 (-0.066717) | 19.327621 / 8.074308 (11.253313) | 23.057537 / 10.191392 (12.866145) | 0.250649 / 0.680424 (-0.429775) | 0.029767 / 0.534201 (-0.504434) | 0.554774 / 0.579283 (-0.024509) | 0.651919 / 0.434364 (0.217555) | 0.651641 / 0.540337 (0.111304) | 0.762386 / 1.386936 (-0.624550) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#fdc3ce7060366f480621e8640903c9ab476164e7 \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.005997 / 0.011353 (-0.005356) | 0.003892 / 0.011008 (-0.007116) | 0.098020 / 0.038508 (0.059512) | 0.042584 / 0.023109 (0.019475) | 0.317909 / 0.275898 (0.042011) | 0.395042 / 0.323480 (0.071563) | 0.005358 / 0.007986 (-0.002628) | 0.003266 / 0.004328 (-0.001062) | 0.076698 / 0.004250 (0.072447) | 0.062331 / 0.037052 (0.025279) | 0.334900 / 0.258489 (0.076411) | 0.379355 / 0.293841 (0.085514) | 0.030815 / 0.128546 (-0.097731) | 0.008596 / 0.075646 (-0.067050) | 0.327739 / 0.419271 (-0.091533) | 0.054061 / 0.043533 (0.010528) | 0.311044 / 0.255139 (0.055905) | 0.336705 / 0.283200 (0.053506) | 0.022785 / 0.141683 (-0.118898) | 1.516793 / 1.452155 (0.064639) | 1.590435 / 1.492716 (0.097719) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.289157 / 0.018006 (0.271151) | 0.531074 / 0.000490 (0.530585) | 0.004672 / 0.000200 (0.004472) | 0.000095 / 0.000054 (0.000040) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.026173 / 0.037411 (-0.011238) | 0.105723 / 0.014526 (0.091197) | 0.118010 / 0.176557 (-0.058547) | 0.178062 / 0.737135 (-0.559073) | 0.120059 / 0.296338 (-0.176279) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.410870 / 0.215209 (0.195661) | 4.042183 / 2.077655 (1.964528) | 1.830059 / 1.504120 (0.325939) | 1.638996 / 1.541195 (0.097802) | 1.701368 / 1.468490 (0.232878) | 0.529915 / 4.584777 (-4.054861) | 3.693308 / 3.745712 (-0.052404) | 1.827875 / 5.269862 (-3.441986) | 1.063237 / 4.565676 (-3.502440) | 0.065368 / 0.424275 (-0.358907) | 0.010986 / 0.007607 (0.003379) | 0.509399 / 0.226044 (0.283354) | 5.092739 / 2.268929 (2.823810) | 2.293490 / 55.444624 (-53.151135) | 1.958742 / 6.876477 (-4.917735) | 2.024985 / 2.142072 (-0.117088) | 0.646978 / 4.805227 (-4.158249) | 0.138616 / 6.500664 (-6.362048) | 0.062101 / 0.075469 (-0.013368) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.202016 / 1.841788 (-0.639772) | 14.493204 / 8.074308 (6.418896) | 12.992160 / 10.191392 (2.800768) | 0.188922 / 0.680424 (-0.491502) | 0.017594 / 0.534201 (-0.516606) | 0.399917 / 0.579283 (-0.179367) | 0.429760 / 0.434364 (-0.004604) | 0.497906 / 0.540337 (-0.042431) | 0.608745 / 1.386936 (-0.778191) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006164 / 0.011353 (-0.005189) | 0.003980 / 0.011008 (-0.007028) | 0.074676 / 0.038508 (0.036168) | 0.041337 / 0.023109 (0.018228) | 0.400981 / 0.275898 (0.125083) | 0.448791 / 0.323480 (0.125312) | 0.004063 / 0.007986 (-0.003923) | 0.004443 / 0.004328 (0.000114) | 0.075011 / 0.004250 (0.070760) | 0.056494 / 0.037052 (0.019441) | 0.402054 / 0.258489 (0.143565) | 0.446122 / 0.293841 (0.152281) | 0.031752 / 0.128546 (-0.096794) | 0.008835 / 0.075646 (-0.066811) | 0.081226 / 0.419271 (-0.338046) | 0.051501 / 0.043533 (0.007969) | 0.383674 / 0.255139 (0.128535) | 0.405524 / 0.283200 (0.122325) | 0.025929 / 0.141683 (-0.115754) | 1.492985 / 1.452155 (0.040830) | 1.541601 / 1.492716 (0.048885) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.305149 / 0.018006 (0.287142) | 0.497259 / 0.000490 (0.496770) | 0.000420 / 0.000200 (0.000220) | 0.000056 / 0.000054 (0.000002) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.027933 / 0.037411 (-0.009479) | 0.111900 / 0.014526 (0.097374) | 0.124879 / 0.176557 (-0.051678) | 0.178952 / 0.737135 (-0.558184) | 0.127698 / 0.296338 (-0.168640) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.448525 / 0.215209 (0.233316) | 4.486791 / 2.077655 (2.409137) | 2.256687 / 1.504120 (0.752567) | 2.061078 / 1.541195 (0.519884) | 2.078924 / 1.468490 (0.610434) | 0.534412 / 4.584777 (-4.050365) | 3.721098 / 3.745712 (-0.024614) | 1.818735 / 5.269862 (-3.451127) | 1.104198 / 4.565676 (-3.461479) | 0.066277 / 0.424275 (-0.357998) | 0.011441 / 0.007607 (0.003834) | 0.550140 / 0.226044 (0.324095) | 5.498079 / 2.268929 (3.229150) | 2.717398 / 55.444624 (-52.727227) | 2.410194 / 6.876477 (-4.466283) | 2.405304 / 2.142072 (0.263231) | 0.665432 / 4.805227 (-4.139796) | 0.141488 / 6.500664 (-6.359177) | 0.064051 / 0.075469 (-0.011419) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.272334 / 1.841788 (-0.569454) | 14.901608 / 8.074308 (6.827300) | 14.287857 / 10.191392 (4.096465) | 0.165337 / 0.680424 (-0.515086) | 0.017402 / 0.534201 (-0.516799) | 0.398120 / 0.579283 (-0.181163) | 0.416539 / 0.434364 (-0.017825) | 0.463890 / 0.540337 (-0.076447) | 0.567909 / 1.386936 (-0.819027) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#504ec0f2e00ee38e0993ed1e4f1e10f1eefaea0d \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.009434 / 0.011353 (-0.001919) | 0.005567 / 0.011008 (-0.005441) | 0.122652 / 0.038508 (0.084144) | 0.050177 / 0.023109 (0.027067) | 0.384292 / 0.275898 (0.108394) | 0.446608 / 0.323480 (0.123128) | 0.006502 / 0.007986 (-0.001484) | 0.004523 / 0.004328 (0.000194) | 0.100581 / 0.004250 (0.096331) | 0.073615 / 0.037052 (0.036563) | 0.420179 / 0.258489 (0.161690) | 0.474631 / 0.293841 (0.180790) | 0.047942 / 0.128546 (-0.080604) | 0.013864 / 0.075646 (-0.061783) | 0.419384 / 0.419271 (0.000112) | 0.088317 / 0.043533 (0.044784) | 0.379620 / 0.255139 (0.124481) | 0.412639 / 0.283200 (0.129440) | 0.048947 / 0.141683 (-0.092736) | 1.823498 / 1.452155 (0.371343) | 1.966629 / 1.492716 (0.473913) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.300669 / 0.018006 (0.282663) | 0.593499 / 0.000490 (0.593009) | 0.007247 / 0.000200 (0.007047) | 0.000114 / 0.000054 (0.000059) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.030556 / 0.037411 (-0.006856) | 0.119252 / 0.014526 (0.104726) | 0.131403 / 0.176557 (-0.045153) | 0.201845 / 0.737135 (-0.535291) | 0.139350 / 0.296338 (-0.156989) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.652400 / 0.215209 (0.437191) | 6.536540 / 2.077655 (4.458886) | 2.644565 / 1.504120 (1.140445) | 2.245181 / 1.541195 (0.703986) | 2.316030 / 1.468490 (0.847540) | 0.922535 / 4.584777 (-3.662242) | 5.469065 / 3.745712 (1.723353) | 2.800489 / 5.269862 (-2.469373) | 1.749042 / 4.565676 (-2.816635) | 0.108444 / 0.424275 (-0.315831) | 0.015651 / 0.007607 (0.008044) | 0.846085 / 0.226044 (0.620041) | 8.018460 / 2.268929 (5.749531) | 3.338710 / 55.444624 (-52.105914) | 2.675998 / 6.876477 (-4.200479) | 2.918550 / 2.142072 (0.776478) | 1.135145 / 4.805227 (-3.670082) | 0.215165 / 6.500664 (-6.285499) | 0.082066 / 0.075469 (0.006597) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.561661 / 1.841788 (-0.280127) | 18.519035 / 8.074308 (10.444727) | 19.046300 / 10.191392 (8.854908) | 0.236890 / 0.680424 (-0.443534) | 0.027681 / 0.534201 (-0.506520) | 0.511998 / 0.579283 (-0.067285) | 0.591627 / 0.434364 (0.157264) | 0.562021 / 0.540337 (0.021683) | 0.679354 / 1.386936 (-0.707582) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.009643 / 0.011353 (-0.001710) | 0.005768 / 0.011008 (-0.005241) | 0.104430 / 0.038508 (0.065922) | 0.050044 / 0.023109 (0.026935) | 0.464117 / 0.275898 (0.188219) | 0.518439 / 0.323480 (0.194959) | 0.006935 / 0.007986 (-0.001051) | 0.004316 / 0.004328 (-0.000013) | 0.094330 / 0.004250 (0.090080) | 0.071451 / 0.037052 (0.034399) | 0.492248 / 0.258489 (0.233759) | 0.555740 / 0.293841 (0.261899) | 0.047836 / 0.128546 (-0.080711) | 0.014788 / 0.075646 (-0.060859) | 0.107590 / 0.419271 (-0.311682) | 0.064396 / 0.043533 (0.020863) | 0.451529 / 0.255139 (0.196390) | 0.475025 / 0.283200 (0.191826) | 0.040006 / 0.141683 (-0.101677) | 1.797107 / 1.452155 (0.344953) | 1.879261 / 1.492716 (0.386545) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.298458 / 0.018006 (0.280451) | 0.613022 / 0.000490 (0.612532) | 0.003582 / 0.000200 (0.003382) | 0.000106 / 0.000054 (0.000052) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.030179 / 0.037411 (-0.007232) | 0.123286 / 0.014526 (0.108760) | 0.132070 / 0.176557 (-0.044486) | 0.190883 / 0.737135 (-0.546252) | 0.138526 / 0.296338 (-0.157812) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.666908 / 0.215209 (0.451699) | 6.489035 / 2.077655 (4.411381) | 2.897027 / 1.504120 (1.392907) | 2.565150 / 1.541195 (1.023956) | 2.504827 / 1.468490 (1.036336) | 0.916112 / 4.584777 (-3.668665) | 5.651751 / 3.745712 (1.906039) | 2.743382 / 5.269862 (-2.526479) | 1.773338 / 4.565676 (-2.792338) | 0.128764 / 0.424275 (-0.295511) | 0.013140 / 0.007607 (0.005533) | 0.803281 / 0.226044 (0.577236) | 8.258874 / 2.268929 (5.989945) | 3.633260 / 55.444624 (-51.811364) | 2.878827 / 6.876477 (-3.997649) | 2.977178 / 2.142072 (0.835106) | 1.130467 / 4.805227 (-3.674760) | 0.226381 / 6.500664 (-6.274283) | 0.081550 / 0.075469 (0.006081) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.842927 / 1.841788 (0.001139) | 18.411520 / 8.074308 (10.337212) | 21.118228 / 10.191392 (10.926836) | 0.231526 / 0.680424 (-0.448898) | 0.029300 / 0.534201 (-0.504901) | 0.527450 / 0.579283 (-0.051834) | 0.618873 / 0.434364 (0.184509) | 0.593314 / 0.540337 (0.052976) | 0.734430 / 1.386936 (-0.652506) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#0d2b8854c265b4dc202e480427890f472b34ea15 \"CML watermark\")\n" ]

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[ "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.005969 / 0.011353 (-0.005384) | 0.003687 / 0.011008 (-0.007321) | 0.100843 / 0.038508 (0.062335) | 0.036912 / 0.023109 (0.013803) | 0.312389 / 0.275898 (0.036491) | 0.370335 / 0.323480 (0.046855) | 0.003434 / 0.007986 (-0.004552) | 0.003710 / 0.004328 (-0.000619) | 0.076899 / 0.004250 (0.072648) | 0.053647 / 0.037052 (0.016594) | 0.324825 / 0.258489 (0.066336) | 0.367711 / 0.293841 (0.073870) | 0.028079 / 0.128546 (-0.100467) | 0.008326 / 0.075646 (-0.067320) | 0.312342 / 0.419271 (-0.106930) | 0.047423 / 0.043533 (0.003890) | 0.321063 / 0.255139 (0.065924) | 0.336508 / 0.283200 (0.053308) | 0.019973 / 0.141683 (-0.121710) | 1.529334 / 1.452155 (0.077179) | 1.573746 / 1.492716 (0.081030) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.210849 / 0.018006 (0.192843) | 0.418798 / 0.000490 (0.418309) | 0.007347 / 0.000200 (0.007147) | 0.000070 / 0.000054 (0.000016) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.022718 / 0.037411 (-0.014694) | 0.098400 / 0.014526 (0.083874) | 0.106590 / 0.176557 (-0.069967) | 0.168460 / 0.737135 (-0.568675) | 0.108401 / 0.296338 (-0.187938) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.443066 / 0.215209 (0.227857) | 4.416658 / 2.077655 (2.339003) | 2.088844 / 1.504120 (0.584724) | 1.879564 / 1.541195 (0.338369) | 1.933815 / 1.468490 (0.465325) | 0.565085 / 4.584777 (-4.019692) | 3.412440 / 3.745712 (-0.333273) | 1.754686 / 5.269862 (-3.515175) | 1.024576 / 4.565676 (-3.541100) | 0.067909 / 0.424275 (-0.356366) | 0.011054 / 0.007607 (0.003447) | 0.534748 / 0.226044 (0.308703) | 5.351457 / 2.268929 (3.082529) | 2.517368 / 55.444624 (-52.927256) | 2.182762 / 6.876477 (-4.693715) | 2.238205 / 2.142072 (0.096133) | 0.672962 / 4.805227 (-4.132265) | 0.136098 / 6.500664 (-6.364566) | 0.066534 / 0.075469 (-0.008935) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.281241 / 1.841788 (-0.560547) | 13.872881 / 8.074308 (5.798573) | 13.161023 / 10.191392 (2.969631) | 0.130011 / 0.680424 (-0.550412) | 0.016759 / 0.534201 (-0.517442) | 0.359802 / 0.579283 (-0.219481) | 0.392577 / 0.434364 (-0.041787) | 0.427742 / 0.540337 (-0.112595) | 0.522241 / 1.386936 (-0.864695) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.005985 / 0.011353 (-0.005368) | 0.003705 / 0.011008 (-0.007304) | 0.077699 / 0.038508 (0.039191) | 0.035686 / 0.023109 (0.012577) | 0.420356 / 0.275898 (0.144458) | 0.476753 / 0.323480 (0.153273) | 0.003510 / 0.007986 (-0.004475) | 0.002807 / 0.004328 (-0.001521) | 0.077151 / 0.004250 (0.072901) | 0.046420 / 0.037052 (0.009368) | 0.391781 / 0.258489 (0.133292) | 0.461128 / 0.293841 (0.167287) | 0.027847 / 0.128546 (-0.100699) | 0.008322 / 0.075646 (-0.067324) | 0.082768 / 0.419271 (-0.336503) | 0.042629 / 0.043533 (-0.000904) | 0.405745 / 0.255139 (0.150606) | 0.430797 / 0.283200 (0.147598) | 0.019832 / 0.141683 (-0.121851) | 1.556208 / 1.452155 (0.104054) | 1.612166 / 1.492716 (0.119450) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.230633 / 0.018006 (0.212626) | 0.401667 / 0.000490 (0.401178) | 0.000776 / 0.000200 (0.000576) | 0.000069 / 0.000054 (0.000014) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.024959 / 0.037411 (-0.012452) | 0.100560 / 0.014526 (0.086034) | 0.109175 / 0.176557 (-0.067382) | 0.159919 / 0.737135 (-0.577217) | 0.112810 / 0.296338 (-0.183528) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.460601 / 0.215209 (0.245392) | 4.620039 / 2.077655 (2.542385) | 2.257900 / 1.504120 (0.753780) | 2.039192 / 1.541195 (0.497997) | 2.064451 / 1.468490 (0.595961) | 0.557887 / 4.584777 (-4.026890) | 3.356100 / 3.745712 (-0.389612) | 1.703578 / 5.269862 (-3.566284) | 1.024984 / 4.565676 (-3.540693) | 0.067602 / 0.424275 (-0.356673) | 0.011450 / 0.007607 (0.003842) | 0.563230 / 0.226044 (0.337186) | 5.632150 / 2.268929 (3.363221) | 2.698701 / 55.444624 (-52.745924) | 2.363218 / 6.876477 (-4.513259) | 2.363997 / 2.142072 (0.221925) | 0.671260 / 4.805227 (-4.133967) | 0.136166 / 6.500664 (-6.364499) | 0.067094 / 0.075469 (-0.008375) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.303030 / 1.841788 (-0.538757) | 14.137277 / 8.074308 (6.062969) | 13.937631 / 10.191392 (3.746239) | 0.162626 / 0.680424 (-0.517798) | 0.016687 / 0.534201 (-0.517514) | 0.363657 / 0.579283 (-0.215626) | 0.392021 / 0.434364 (-0.042343) | 0.427275 / 0.540337 (-0.113062) | 0.512192 / 1.386936 (-0.874744) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#42603528d9bd8c3ab287ed0eadc7fa3d1ef4cfd8 \"CML watermark\")\n", "_The documentation is not available anymore as the PR was closed or merged._", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.005974 / 0.011353 (-0.005378) | 0.003947 / 0.011008 (-0.007061) | 0.098604 / 0.038508 (0.060096) | 0.036947 / 0.023109 (0.013838) | 0.311844 / 0.275898 (0.035946) | 0.375243 / 0.323480 (0.051763) | 0.003453 / 0.007986 (-0.004533) | 0.003834 / 0.004328 (-0.000495) | 0.077943 / 0.004250 (0.073692) | 0.052956 / 0.037052 (0.015904) | 0.320812 / 0.258489 (0.062323) | 0.373963 / 0.293841 (0.080122) | 0.028382 / 0.128546 (-0.100164) | 0.008525 / 0.075646 (-0.067121) | 0.311306 / 0.419271 (-0.107965) | 0.047029 / 0.043533 (0.003496) | 0.309933 / 0.255139 (0.054794) | 0.335114 / 0.283200 (0.051915) | 0.019629 / 0.141683 (-0.122054) | 1.569771 / 1.452155 (0.117617) | 1.585899 / 1.492716 (0.093182) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.216565 / 0.018006 (0.198559) | 0.426717 / 0.000490 (0.426228) | 0.003609 / 0.000200 (0.003409) | 0.000077 / 0.000054 (0.000023) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.023079 / 0.037411 (-0.014332) | 0.096954 / 0.014526 (0.082428) | 0.105398 / 0.176557 (-0.071158) | 0.165433 / 0.737135 (-0.571703) | 0.109703 / 0.296338 (-0.186636) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.456227 / 0.215209 (0.241018) | 4.529857 / 2.077655 (2.452202) | 2.214054 / 1.504120 (0.709934) | 2.029716 / 1.541195 (0.488521) | 2.081175 / 1.468490 (0.612685) | 0.563642 / 4.584777 (-4.021135) | 3.355393 / 3.745712 (-0.390320) | 1.765938 / 5.269862 (-3.503924) | 1.039062 / 4.565676 (-3.526615) | 0.067952 / 0.424275 (-0.356323) | 0.011044 / 0.007607 (0.003437) | 0.556935 / 0.226044 (0.330890) | 5.588167 / 2.268929 (3.319239) | 2.667217 / 55.444624 (-52.777407) | 2.337383 / 6.876477 (-4.539094) | 2.429590 / 2.142072 (0.287517) | 0.676972 / 4.805227 (-4.128256) | 0.135782 / 6.500664 (-6.364882) | 0.066323 / 0.075469 (-0.009146) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.237358 / 1.841788 (-0.604429) | 13.910492 / 8.074308 (5.836184) | 13.227275 / 10.191392 (3.035883) | 0.146857 / 0.680424 (-0.533567) | 0.016991 / 0.534201 (-0.517210) | 0.363637 / 0.579283 (-0.215646) | 0.392462 / 0.434364 (-0.041902) | 0.450009 / 0.540337 (-0.090329) | 0.536077 / 1.386936 (-0.850859) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.006067 / 0.011353 (-0.005286) | 0.003851 / 0.011008 (-0.007158) | 0.078462 / 0.038508 (0.039954) | 0.036221 / 0.023109 (0.013112) | 0.389195 / 0.275898 (0.113297) | 0.428710 / 0.323480 (0.105230) | 0.004645 / 0.007986 (-0.003341) | 0.002973 / 0.004328 (-0.001355) | 0.078299 / 0.004250 (0.074048) | 0.047076 / 0.037052 (0.010024) | 0.375673 / 0.258489 (0.117184) | 0.432352 / 0.293841 (0.138511) | 0.028212 / 0.128546 (-0.100334) | 0.008475 / 0.075646 (-0.067172) | 0.083902 / 0.419271 (-0.335369) | 0.046699 / 0.043533 (0.003166) | 0.364502 / 0.255139 (0.109363) | 0.389792 / 0.283200 (0.106592) | 0.025266 / 0.141683 (-0.116417) | 1.517458 / 1.452155 (0.065303) | 1.543634 / 1.492716 (0.050918) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.236479 / 0.018006 (0.218472) | 0.411528 / 0.000490 (0.411038) | 0.005213 / 0.000200 (0.005013) | 0.000091 / 0.000054 (0.000036) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.025764 / 0.037411 (-0.011647) | 0.103174 / 0.014526 (0.088648) | 0.110609 / 0.176557 (-0.065948) | 0.164630 / 0.737135 (-0.572506) | 0.114863 / 0.296338 (-0.181475) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.457155 / 0.215209 (0.241946) | 4.550675 / 2.077655 (2.473021) | 2.350473 / 1.504120 (0.846353) | 2.204919 / 1.541195 (0.663724) | 2.076724 / 1.468490 (0.608234) | 0.563107 / 4.584777 (-4.021670) | 3.390669 / 3.745712 (-0.355043) | 1.741111 / 5.269862 (-3.528751) | 1.033268 / 4.565676 (-3.532408) | 0.068400 / 0.424275 (-0.355875) | 0.011607 / 0.007607 (0.004000) | 0.561944 / 0.226044 (0.335900) | 5.620224 / 2.268929 (3.351296) | 2.705241 / 55.444624 (-52.739384) | 2.344520 / 6.876477 (-4.531957) | 2.386119 / 2.142072 (0.244046) | 0.681583 / 4.805227 (-4.123644) | 0.137272 / 6.500664 (-6.363392) | 0.069217 / 0.075469 (-0.006252) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.322690 / 1.841788 (-0.519098) | 14.464953 / 8.074308 (6.390645) | 14.269350 / 10.191392 (4.077958) | 0.158879 / 0.680424 (-0.521545) | 0.016722 / 0.534201 (-0.517479) | 0.360299 / 0.579283 (-0.218984) | 0.391609 / 0.434364 (-0.042755) | 0.420507 / 0.540337 (-0.119831) | 0.512822 / 1.386936 (-0.874114) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#ca68191900d97b29abb3c2c4ba0502fe30d137d1 \"CML watermark\")\n", "<details>\n<summary>Show benchmarks</summary>\n\nPyArrow==8.0.0\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007106 / 0.011353 (-0.004247) | 0.005224 / 0.011008 (-0.005784) | 0.127563 / 0.038508 (0.089055) | 0.055067 / 0.023109 (0.031958) | 0.418660 / 0.275898 (0.142761) | 0.487891 / 0.323480 (0.164411) | 0.005712 / 0.007986 (-0.002274) | 0.004585 / 0.004328 (0.000256) | 0.090994 / 0.004250 (0.086743) | 0.071837 / 0.037052 (0.034784) | 0.446957 / 0.258489 (0.188468) | 0.475966 / 0.293841 (0.182125) | 0.038062 / 0.128546 (-0.090484) | 0.010056 / 0.075646 (-0.065590) | 0.406796 / 0.419271 (-0.012475) | 0.066542 / 0.043533 (0.023009) | 0.413676 / 0.255139 (0.158537) | 0.448624 / 0.283200 (0.165424) | 0.030332 / 0.141683 (-0.111351) | 1.895307 / 1.452155 (0.443152) | 1.904411 / 1.492716 (0.411694) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.221246 / 0.018006 (0.203240) | 0.461288 / 0.000490 (0.460799) | 0.005957 / 0.000200 (0.005757) | 0.000112 / 0.000054 (0.000058) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.029255 / 0.037411 (-0.008156) | 0.131299 / 0.014526 (0.116773) | 0.135814 / 0.176557 (-0.040742) | 0.201342 / 0.737135 (-0.535793) | 0.141748 / 0.296338 (-0.154591) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.463936 / 0.215209 (0.248727) | 4.709621 / 2.077655 (2.631966) | 2.093844 / 1.504120 (0.589724) | 1.897963 / 1.541195 (0.356768) | 1.927865 / 1.468490 (0.459375) | 0.610879 / 4.584777 (-3.973898) | 4.481370 / 3.745712 (0.735658) | 2.112235 / 5.269862 (-3.157627) | 1.203349 / 4.565676 (-3.362327) | 0.074828 / 0.424275 (-0.349447) | 0.013121 / 0.007607 (0.005514) | 0.580894 / 0.226044 (0.354849) | 5.801872 / 2.268929 (3.532943) | 2.579950 / 55.444624 (-52.864674) | 2.251569 / 6.876477 (-4.624908) | 2.421305 / 2.142072 (0.279232) | 0.760938 / 4.805227 (-4.044289) | 0.169554 / 6.500664 (-6.331110) | 0.077499 / 0.075469 (0.002030) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.410419 / 1.841788 (-0.431368) | 17.442331 / 8.074308 (9.368023) | 15.782183 / 10.191392 (5.590791) | 0.180649 / 0.680424 (-0.499775) | 0.021790 / 0.534201 (-0.512411) | 0.511040 / 0.579283 (-0.068243) | 0.510472 / 0.434364 (0.076108) | 0.607141 / 0.540337 (0.066804) | 0.724794 / 1.386936 (-0.662142) |\n\n</details>\nPyArrow==latest\n\n<details>\n<summary>Show updated benchmarks!</summary>\n\n### Benchmark: benchmark_array_xd.json\n\n| metric | read_batch_formatted_as_numpy after write_array2d | read_batch_formatted_as_numpy after write_flattened_sequence | read_batch_formatted_as_numpy after write_nested_sequence | read_batch_unformated after write_array2d | read_batch_unformated after write_flattened_sequence | read_batch_unformated after write_nested_sequence | read_col_formatted_as_numpy after write_array2d | read_col_formatted_as_numpy after write_flattened_sequence | read_col_formatted_as_numpy after write_nested_sequence | read_col_unformated after write_array2d | read_col_unformated after write_flattened_sequence | read_col_unformated after write_nested_sequence | read_formatted_as_numpy after write_array2d | read_formatted_as_numpy after write_flattened_sequence | read_formatted_as_numpy after write_nested_sequence | read_unformated after write_array2d | read_unformated after write_flattened_sequence | read_unformated after write_nested_sequence | write_array2d | write_flattened_sequence | write_nested_sequence |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.007280 / 0.011353 (-0.004073) | 0.004712 / 0.011008 (-0.006296) | 0.089225 / 0.038508 (0.050717) | 0.053157 / 0.023109 (0.030048) | 0.431949 / 0.275898 (0.156051) | 0.478128 / 0.323480 (0.154648) | 0.006181 / 0.007986 (-0.001804) | 0.003387 / 0.004328 (-0.000941) | 0.083741 / 0.004250 (0.079490) | 0.071610 / 0.037052 (0.034557) | 0.414698 / 0.258489 (0.156209) | 0.484422 / 0.293841 (0.190581) | 0.034988 / 0.128546 (-0.093558) | 0.009831 / 0.075646 (-0.065816) | 0.089644 / 0.419271 (-0.329628) | 0.057053 / 0.043533 (0.013520) | 0.413144 / 0.255139 (0.158005) | 0.445464 / 0.283200 (0.162264) | 0.026109 / 0.141683 (-0.115574) | 1.842899 / 1.452155 (0.390745) | 1.923774 / 1.492716 (0.431057) |\n\n### Benchmark: benchmark_getitem\\_100B.json\n\n| metric | get_batch_of\\_1024\\_random_rows | get_batch_of\\_1024\\_rows | get_first_row | get_last_row |\n|--------|---|---|---|---|\n| new / old (diff) | 0.245051 / 0.018006 (0.227045) | 0.460444 / 0.000490 (0.459954) | 0.000444 / 0.000200 (0.000244) | 0.000067 / 0.000054 (0.000012) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.034835 / 0.037411 (-0.002577) | 0.130078 / 0.014526 (0.115553) | 0.147012 / 0.176557 (-0.029544) | 0.203097 / 0.737135 (-0.534038) | 0.149636 / 0.296338 (-0.146702) |\n\n### Benchmark: benchmark_iterating.json\n\n| metric | read 5000 | read 50000 | read_batch 50000 10 | read_batch 50000 100 | read_batch 50000 1000 | read_formatted numpy 5000 | read_formatted pandas 5000 | read_formatted tensorflow 5000 | read_formatted torch 5000 | read_formatted_batch numpy 5000 10 | read_formatted_batch numpy 5000 1000 | shuffled read 5000 | shuffled read 50000 | shuffled read_batch 50000 10 | shuffled read_batch 50000 100 | shuffled read_batch 50000 1000 | shuffled read_formatted numpy 5000 | shuffled read_formatted_batch numpy 5000 10 | shuffled read_formatted_batch numpy 5000 1000 |\n|--------|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 0.521664 / 0.215209 (0.306455) | 5.283865 / 2.077655 (3.206210) | 2.456701 / 1.504120 (0.952581) | 2.266059 / 1.541195 (0.724864) | 2.295387 / 1.468490 (0.826897) | 0.613200 / 4.584777 (-3.971577) | 4.526107 / 3.745712 (0.780394) | 2.047327 / 5.269862 (-3.222535) | 1.261063 / 4.565676 (-3.304614) | 0.070402 / 0.424275 (-0.353873) | 0.014128 / 0.007607 (0.006521) | 0.620929 / 0.226044 (0.394884) | 6.109127 / 2.268929 (3.840198) | 3.081406 / 55.444624 (-52.363218) | 2.658224 / 6.876477 (-4.218253) | 2.671974 / 2.142072 (0.529902) | 0.744081 / 4.805227 (-4.061146) | 0.161498 / 6.500664 (-6.339166) | 0.075148 / 0.075469 (-0.000321) |\n\n### Benchmark: benchmark_map_filter.json\n\n| metric | filter | map fast-tokenizer batched | map identity | map identity batched | map no-op batched | map no-op batched numpy | map no-op batched pandas | map no-op batched pytorch | map no-op batched tensorflow |\n|--------|---|---|---|---|---|---|---|---|---|\n| new / old (diff) | 1.585640 / 1.841788 (-0.256148) | 17.884321 / 8.074308 (9.810013) | 15.938937 / 10.191392 (5.747545) | 0.220818 / 0.680424 (-0.459605) | 0.021452 / 0.534201 (-0.512749) | 0.499747 / 0.579283 (-0.079536) | 0.512318 / 0.434364 (0.077954) | 0.562853 / 0.540337 (0.022515) | 0.678512 / 1.386936 (-0.708424) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#aa50937d82256827aee3dbd749c7a23555e05e38 \"CML watermark\")\n" ]

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[ "We'll do a new release of `datasets` soon to make the fix available :)\r\n\r\nIn the meantime you can use `datasets` from source (main)", "Thank you very much @lhoestq ! 🚀 " ]

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