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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6925). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.", "Do you think this is worth making a patch release for?\r\nCC: @huggingface/datasets" ]

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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6922). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.", "<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) | 0.005525 / 0.011353 (-0.005828) | 0.004013 / 0.011008 (-0.006996) | 0.063931 / 0.038508 (0.025423) | 0.033857 / 0.023109 (0.010748) | 0.250910 / 0.275898 (-0.024988) | 0.278289 / 0.323480 (-0.045191) | 0.004289 / 0.007986 (-0.003697) | 0.002800 / 0.004328 (-0.001529) | 0.050127 / 0.004250 (0.045877) | 0.048901 / 0.037052 (0.011848) | 0.260628 / 0.258489 (0.002139) | 0.293904 / 0.293841 (0.000063) | 0.028339 / 0.128546 (-0.100207) | 0.010879 / 0.075646 (-0.064767) | 0.203618 / 0.419271 (-0.215654) | 0.036241 / 0.043533 (-0.007292) | 0.250481 / 0.255139 (-0.004657) | 0.274274 / 0.283200 (-0.008926) | 0.018912 / 0.141683 (-0.122771) | 1.146785 / 1.452155 (-0.305370) | 1.199795 / 1.492716 (-0.292921) |\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) | 0.095571 / 0.018006 (0.077564) | 0.302961 / 0.000490 (0.302471) | 0.000217 / 0.000200 (0.000017) | 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) | 0.020121 / 0.037411 (-0.017290) | 0.063231 / 0.014526 (0.048705) | 0.075434 / 0.176557 (-0.101122) | 0.123994 / 0.737135 (-0.613141) | 0.076479 / 0.296338 (-0.219860) |\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) | 0.277816 / 0.215209 (0.062607) | 2.775481 / 2.077655 (0.697826) | 1.454881 / 1.504120 (-0.049239) | 1.339055 / 1.541195 (-0.202140) | 1.347810 / 1.468490 (-0.120681) | 0.572802 / 4.584777 (-4.011975) | 2.357490 / 3.745712 (-1.388222) | 2.822548 / 5.269862 (-2.447313) | 1.746538 / 4.565676 (-2.819138) | 0.066159 / 0.424275 (-0.358116) | 0.005037 / 0.007607 (-0.002570) | 0.329256 / 0.226044 (0.103212) | 3.277511 / 2.268929 (1.008582) | 1.807855 / 55.444624 (-53.636769) | 1.505507 / 6.876477 (-5.370970) | 1.634237 / 2.142072 (-0.507835) | 0.643999 / 4.805227 (-4.161229) | 0.117494 / 6.500664 (-6.383170) | 0.042634 / 0.075469 (-0.032835) |\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) | 0.977689 / 1.841788 (-0.864098) | 12.261836 / 8.074308 (4.187528) | 9.871541 / 10.191392 (-0.319851) | 0.147293 / 0.680424 (-0.533130) | 0.015134 / 0.534201 (-0.519067) | 0.287677 / 0.579283 (-0.291606) | 0.264622 / 0.434364 (-0.169742) | 0.330511 / 0.540337 (-0.209826) | 0.467618 / 1.386936 (-0.919318) |\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) | 0.005690 / 0.011353 (-0.005663) | 0.003801 / 0.011008 (-0.007207) | 0.051817 / 0.038508 (0.013309) | 0.033355 / 0.023109 (0.010246) | 0.264416 / 0.275898 (-0.011482) | 0.288494 / 0.323480 (-0.034986) | 0.004246 / 0.007986 (-0.003740) | 0.002814 / 0.004328 (-0.001515) | 0.050547 / 0.004250 (0.046297) | 0.042977 / 0.037052 (0.005925) | 0.276884 / 0.258489 (0.018395) | 0.303758 / 0.293841 (0.009917) | 0.029412 / 0.128546 (-0.099134) | 0.010697 / 0.075646 (-0.064949) | 0.059497 / 0.419271 (-0.359775) | 0.033670 / 0.043533 (-0.009862) | 0.261311 / 0.255139 (0.006172) | 0.286478 / 0.283200 (0.003278) | 0.019386 / 0.141683 (-0.122297) | 1.155943 / 1.452155 (-0.296211) | 1.198512 / 1.492716 (-0.294205) |\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) | 0.092954 / 0.018006 (0.074948) | 0.294144 / 0.000490 (0.293655) | 0.000213 / 0.000200 (0.000013) | 0.000043 / 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) | 0.023013 / 0.037411 (-0.014398) | 0.077161 / 0.014526 (0.062635) | 0.089957 / 0.176557 (-0.086600) | 0.129305 / 0.737135 (-0.607831) | 0.091006 / 0.296338 (-0.205333) |\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) | 0.294091 / 0.215209 (0.078882) | 2.885395 / 2.077655 (0.807741) | 1.555658 / 1.504120 (0.051538) | 1.423276 / 1.541195 (-0.117919) | 1.476485 / 1.468490 (0.007995) | 0.569507 / 4.584777 (-4.015270) | 0.979221 / 3.745712 (-2.766491) | 2.818503 / 5.269862 (-2.451358) | 1.871938 / 4.565676 (-2.693739) | 0.064342 / 0.424275 (-0.359933) | 0.005495 / 0.007607 (-0.002112) | 0.351451 / 0.226044 (0.125407) | 3.516078 / 2.268929 (1.247149) | 1.928351 / 55.444624 (-53.516273) | 1.625362 / 6.876477 (-5.251115) | 1.813756 / 2.142072 (-0.328317) | 0.657642 / 4.805227 (-4.147585) | 0.117893 / 6.500664 (-6.382771) | 0.042009 / 0.075469 (-0.033460) |\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) | 1.032893 / 1.841788 (-0.808894) | 12.983400 / 8.074308 (4.909092) | 10.747204 / 10.191392 (0.555812) | 0.133163 / 0.680424 (-0.547261) | 0.015875 / 0.534201 (-0.518326) | 0.312592 / 0.579283 (-0.266691) | 0.124780 / 0.434364 (-0.309584) | 0.350735 / 0.540337 (-0.189603) | 0.447130 / 1.386936 (-0.939806) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#048c789607af0370c1f2337248897956f7a91617 \"CML watermark\")\n" ]

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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6921). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.", "<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) | 0.005252 / 0.011353 (-0.006100) | 0.003752 / 0.011008 (-0.007257) | 0.064034 / 0.038508 (0.025526) | 0.031205 / 0.023109 (0.008096) | 0.248903 / 0.275898 (-0.026995) | 0.275808 / 0.323480 (-0.047671) | 0.003135 / 0.007986 (-0.004851) | 0.002635 / 0.004328 (-0.001693) | 0.049869 / 0.004250 (0.045619) | 0.047602 / 0.037052 (0.010549) | 0.259738 / 0.258489 (0.001249) | 0.296131 / 0.293841 (0.002290) | 0.027467 / 0.128546 (-0.101080) | 0.010449 / 0.075646 (-0.065197) | 0.201369 / 0.419271 (-0.217903) | 0.036317 / 0.043533 (-0.007216) | 0.244347 / 0.255139 (-0.010792) | 0.267597 / 0.283200 (-0.015602) | 0.019930 / 0.141683 (-0.121753) | 1.149012 / 1.452155 (-0.303143) | 1.188083 / 1.492716 (-0.304633) |\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) | 0.095190 / 0.018006 (0.077184) | 0.300705 / 0.000490 (0.300215) | 0.000222 / 0.000200 (0.000022) | 0.000051 / 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) | 0.019297 / 0.037411 (-0.018115) | 0.063183 / 0.014526 (0.048657) | 0.075094 / 0.176557 (-0.101463) | 0.123556 / 0.737135 (-0.613579) | 0.076721 / 0.296338 (-0.219618) |\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) | 0.284136 / 0.215209 (0.068927) | 2.814041 / 2.077655 (0.736387) | 1.471038 / 1.504120 (-0.033082) | 1.344002 / 1.541195 (-0.197193) | 1.353875 / 1.468490 (-0.114615) | 0.599495 / 4.584777 (-3.985282) | 2.394491 / 3.745712 (-1.351221) | 2.781734 / 5.269862 (-2.488128) | 1.729829 / 4.565676 (-2.835848) | 0.064194 / 0.424275 (-0.360081) | 0.005022 / 0.007607 (-0.002585) | 0.343384 / 0.226044 (0.117340) | 3.357067 / 2.268929 (1.088139) | 1.816323 / 55.444624 (-53.628301) | 1.549405 / 6.876477 (-5.327072) | 1.594394 / 2.142072 (-0.547679) | 0.660650 / 4.805227 (-4.144578) | 0.120271 / 6.500664 (-6.380393) | 0.042422 / 0.075469 (-0.033047) |\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) | 0.975776 / 1.841788 (-0.866011) | 11.828093 / 8.074308 (3.753784) | 9.384164 / 10.191392 (-0.807228) | 0.140761 / 0.680424 (-0.539663) | 0.014038 / 0.534201 (-0.520163) | 0.284904 / 0.579283 (-0.294379) | 0.263430 / 0.434364 (-0.170934) | 0.320856 / 0.540337 (-0.219482) | 0.419199 / 1.386936 (-0.967737) |\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) | 0.005672 / 0.011353 (-0.005681) | 0.003667 / 0.011008 (-0.007341) | 0.049989 / 0.038508 (0.011481) | 0.033115 / 0.023109 (0.010006) | 0.269808 / 0.275898 (-0.006090) | 0.293286 / 0.323480 (-0.030193) | 0.004238 / 0.007986 (-0.003748) | 0.002722 / 0.004328 (-0.001606) | 0.049516 / 0.004250 (0.045265) | 0.042076 / 0.037052 (0.005024) | 0.282182 / 0.258489 (0.023693) | 0.310817 / 0.293841 (0.016976) | 0.029824 / 0.128546 (-0.098722) | 0.010516 / 0.075646 (-0.065130) | 0.058223 / 0.419271 (-0.361049) | 0.033263 / 0.043533 (-0.010270) | 0.268769 / 0.255139 (0.013630) | 0.288308 / 0.283200 (0.005108) | 0.018531 / 0.141683 (-0.123151) | 1.136806 / 1.452155 (-0.315349) | 1.192636 / 1.492716 (-0.300080) |\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) | 0.096583 / 0.018006 (0.078577) | 0.303678 / 0.000490 (0.303188) | 0.000211 / 0.000200 (0.000011) | 0.000044 / 0.000054 (-0.000010) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.022741 / 0.037411 (-0.014670) | 0.075799 / 0.014526 (0.061273) | 0.089930 / 0.176557 (-0.086626) | 0.129093 / 0.737135 (-0.608042) | 0.089672 / 0.296338 (-0.206666) |\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) | 0.292789 / 0.215209 (0.077580) | 2.860137 / 2.077655 (0.782483) | 1.566678 / 1.504120 (0.062558) | 1.437756 / 1.541195 (-0.103439) | 1.472347 / 1.468490 (0.003857) | 0.566814 / 4.584777 (-4.017963) | 0.963918 / 3.745712 (-2.781794) | 2.717199 / 5.269862 (-2.552663) | 1.763612 / 4.565676 (-2.802064) | 0.063601 / 0.424275 (-0.360674) | 0.005308 / 0.007607 (-0.002299) | 0.363111 / 0.226044 (0.137066) | 3.458222 / 2.268929 (1.189293) | 1.939185 / 55.444624 (-53.505440) | 1.659552 / 6.876477 (-5.216925) | 1.801006 / 2.142072 (-0.341067) | 0.648884 / 4.805227 (-4.156343) | 0.116259 / 6.500664 (-6.384405) | 0.041384 / 0.075469 (-0.034085) |\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) | 1.001594 / 1.841788 (-0.840194) | 12.371125 / 8.074308 (4.296817) | 10.489763 / 10.191392 (0.298371) | 0.132500 / 0.680424 (-0.547924) | 0.014742 / 0.534201 (-0.519459) | 0.282258 / 0.579283 (-0.297026) | 0.122755 / 0.434364 (-0.311608) | 0.346068 / 0.540337 (-0.194269) | 0.424943 / 1.386936 (-0.961994) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#df445c20346a34c08e7e039e4ec1a302eef3a69c \"CML watermark\")\n" ]

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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6920). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.", "<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) | 0.005643 / 0.011353 (-0.005710) | 0.003810 / 0.011008 (-0.007198) | 0.065896 / 0.038508 (0.027388) | 0.031692 / 0.023109 (0.008583) | 0.258297 / 0.275898 (-0.017601) | 0.294555 / 0.323480 (-0.028925) | 0.004403 / 0.007986 (-0.003583) | 0.002857 / 0.004328 (-0.001472) | 0.049848 / 0.004250 (0.045597) | 0.049719 / 0.037052 (0.012666) | 0.266393 / 0.258489 (0.007904) | 0.306214 / 0.293841 (0.012373) | 0.028283 / 0.128546 (-0.100264) | 0.010450 / 0.075646 (-0.065196) | 0.203064 / 0.419271 (-0.216208) | 0.036535 / 0.043533 (-0.006998) | 0.247839 / 0.255139 (-0.007300) | 0.270538 / 0.283200 (-0.012661) | 0.018748 / 0.141683 (-0.122935) | 1.117478 / 1.452155 (-0.334677) | 1.162575 / 1.492716 (-0.330141) |\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) | 0.101074 / 0.018006 (0.083068) | 0.304321 / 0.000490 (0.303831) | 0.000270 / 0.000200 (0.000070) | 0.000045 / 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) | 0.019036 / 0.037411 (-0.018376) | 0.064496 / 0.014526 (0.049970) | 0.076848 / 0.176557 (-0.099709) | 0.122979 / 0.737135 (-0.614156) | 0.078008 / 0.296338 (-0.218330) |\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) | 0.287009 / 0.215209 (0.071800) | 2.839084 / 2.077655 (0.761429) | 1.495977 / 1.504120 (-0.008143) | 1.379147 / 1.541195 (-0.162047) | 1.413170 / 1.468490 (-0.055320) | 0.616408 / 4.584777 (-3.968369) | 2.419183 / 3.745712 (-1.326529) | 2.905720 / 5.269862 (-2.364142) | 1.801634 / 4.565676 (-2.764043) | 0.064034 / 0.424275 (-0.360241) | 0.005098 / 0.007607 (-0.002509) | 0.341732 / 0.226044 (0.115688) | 3.365262 / 2.268929 (1.096334) | 1.844335 / 55.444624 (-53.600289) | 1.561450 / 6.876477 (-5.315027) | 1.646254 / 2.142072 (-0.495819) | 0.654993 / 4.805227 (-4.150234) | 0.119837 / 6.500664 (-6.380827) | 0.043375 / 0.075469 (-0.032094) |\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) | 1.000352 / 1.841788 (-0.841435) | 12.765122 / 8.074308 (4.690813) | 9.818879 / 10.191392 (-0.372513) | 0.133986 / 0.680424 (-0.546438) | 0.014065 / 0.534201 (-0.520136) | 0.295859 / 0.579283 (-0.283424) | 0.268497 / 0.434364 (-0.165867) | 0.330909 / 0.540337 (-0.209429) | 0.449218 / 1.386936 (-0.937718) |\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) | 0.005646 / 0.011353 (-0.005707) | 0.003926 / 0.011008 (-0.007082) | 0.050437 / 0.038508 (0.011929) | 0.031828 / 0.023109 (0.008719) | 0.268218 / 0.275898 (-0.007680) | 0.292987 / 0.323480 (-0.030493) | 0.004353 / 0.007986 (-0.003633) | 0.002933 / 0.004328 (-0.001395) | 0.050357 / 0.004250 (0.046107) | 0.042988 / 0.037052 (0.005935) | 0.281627 / 0.258489 (0.023138) | 0.305664 / 0.293841 (0.011824) | 0.030162 / 0.128546 (-0.098385) | 0.010856 / 0.075646 (-0.064790) | 0.059528 / 0.419271 (-0.359744) | 0.033800 / 0.043533 (-0.009733) | 0.268200 / 0.255139 (0.013061) | 0.284982 / 0.283200 (0.001782) | 0.019105 / 0.141683 (-0.122578) | 1.171714 / 1.452155 (-0.280441) | 1.205690 / 1.492716 (-0.287026) |\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) | 0.100979 / 0.018006 (0.082973) | 0.314691 / 0.000490 (0.314201) | 0.000217 / 0.000200 (0.000017) | 0.000050 / 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) | 0.023816 / 0.037411 (-0.013596) | 0.081749 / 0.014526 (0.067223) | 0.090118 / 0.176557 (-0.086438) | 0.131615 / 0.737135 (-0.605520) | 0.091821 / 0.296338 (-0.204517) |\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) | 0.301222 / 0.215209 (0.086013) | 2.835310 / 2.077655 (0.757655) | 1.562396 / 1.504120 (0.058276) | 1.432365 / 1.541195 (-0.108830) | 1.468358 / 1.468490 (-0.000132) | 0.561300 / 4.584777 (-4.023477) | 0.962294 / 3.745712 (-2.783419) | 2.799705 / 5.269862 (-2.470157) | 1.803035 / 4.565676 (-2.762642) | 0.064104 / 0.424275 (-0.360171) | 0.005480 / 0.007607 (-0.002127) | 0.342519 / 0.226044 (0.116475) | 3.406286 / 2.268929 (1.137357) | 1.966962 / 55.444624 (-53.477663) | 1.654664 / 6.876477 (-5.221813) | 1.829303 / 2.142072 (-0.312769) | 0.650932 / 4.805227 (-4.154295) | 0.119211 / 6.500664 (-6.381453) | 0.043739 / 0.075469 (-0.031730) |\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) | 1.006657 / 1.841788 (-0.835130) | 12.915348 / 8.074308 (4.841040) | 10.808156 / 10.191392 (0.616764) | 0.132664 / 0.680424 (-0.547760) | 0.015574 / 0.534201 (-0.518627) | 0.284525 / 0.579283 (-0.294758) | 0.122322 / 0.434364 (-0.312042) | 0.326826 / 0.540337 (-0.213511) | 0.416593 / 1.386936 (-0.970343) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#15ffefe5be194790a50af88ae1236a51b0ac95e6 \"CML watermark\")\n" ]

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[ "Thanks for reporting, @srehaag.\r\n\r\nWe are investigating this issue.", "I confirm there is a bug for data-based Hub datasets when the user passes `data_dir`, which was introduced by PR:\r\n- #6714" ]

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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6915). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update." ]

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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6914). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update." ]

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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6911). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.", "<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) | 0.005136 / 0.011353 (-0.006217) | 0.003136 / 0.011008 (-0.007872) | 0.063752 / 0.038508 (0.025244) | 0.031060 / 0.023109 (0.007950) | 0.249848 / 0.275898 (-0.026050) | 0.275918 / 0.323480 (-0.047561) | 0.004047 / 0.007986 (-0.003938) | 0.002696 / 0.004328 (-0.001632) | 0.049884 / 0.004250 (0.045634) | 0.044646 / 0.037052 (0.007593) | 0.264769 / 0.258489 (0.006280) | 0.299874 / 0.293841 (0.006033) | 0.027530 / 0.128546 (-0.101016) | 0.010026 / 0.075646 (-0.065620) | 0.204007 / 0.419271 (-0.215265) | 0.035982 / 0.043533 (-0.007550) | 0.253560 / 0.255139 (-0.001579) | 0.276206 / 0.283200 (-0.006993) | 0.017770 / 0.141683 (-0.123913) | 1.156008 / 1.452155 (-0.296146) | 1.197265 / 1.492716 (-0.295451) |\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) | 0.092960 / 0.018006 (0.074954) | 0.302876 / 0.000490 (0.302386) | 0.000214 / 0.000200 (0.000014) | 0.000044 / 0.000054 (-0.000010) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.019060 / 0.037411 (-0.018351) | 0.062262 / 0.014526 (0.047737) | 0.073836 / 0.176557 (-0.102721) | 0.122327 / 0.737135 (-0.614809) | 0.076050 / 0.296338 (-0.220289) |\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) | 0.282489 / 0.215209 (0.067280) | 2.745084 / 2.077655 (0.667429) | 1.453044 / 1.504120 (-0.051076) | 1.339065 / 1.541195 (-0.202130) | 1.341395 / 1.468490 (-0.127095) | 0.586497 / 4.584777 (-3.998280) | 2.342198 / 3.745712 (-1.403514) | 2.684984 / 5.269862 (-2.584878) | 1.703738 / 4.565676 (-2.861939) | 0.062489 / 0.424275 (-0.361786) | 0.004906 / 0.007607 (-0.002701) | 0.332325 / 0.226044 (0.106280) | 3.255381 / 2.268929 (0.986452) | 1.797045 / 55.444624 (-53.647579) | 1.515197 / 6.876477 (-5.361280) | 1.508317 / 2.142072 (-0.633756) | 0.635973 / 4.805227 (-4.169254) | 0.117292 / 6.500664 (-6.383372) | 0.041456 / 0.075469 (-0.034013) |\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) | 0.973934 / 1.841788 (-0.867853) | 11.288665 / 8.074308 (3.214356) | 9.269404 / 10.191392 (-0.921988) | 0.143190 / 0.680424 (-0.537234) | 0.014366 / 0.534201 (-0.519835) | 0.285936 / 0.579283 (-0.293347) | 0.261632 / 0.434364 (-0.172732) | 0.327191 / 0.540337 (-0.213146) | 0.418900 / 1.386936 (-0.968036) |\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) | 0.005131 / 0.011353 (-0.006222) | 0.003181 / 0.011008 (-0.007827) | 0.049697 / 0.038508 (0.011189) | 0.032754 / 0.023109 (0.009645) | 0.263954 / 0.275898 (-0.011944) | 0.285110 / 0.323480 (-0.038370) | 0.004133 / 0.007986 (-0.003852) | 0.002713 / 0.004328 (-0.001615) | 0.051684 / 0.004250 (0.047433) | 0.040607 / 0.037052 (0.003554) | 0.277919 / 0.258489 (0.019429) | 0.304773 / 0.293841 (0.010932) | 0.029530 / 0.128546 (-0.099016) | 0.010176 / 0.075646 (-0.065470) | 0.058501 / 0.419271 (-0.360771) | 0.033436 / 0.043533 (-0.010097) | 0.269899 / 0.255139 (0.014760) | 0.284490 / 0.283200 (0.001290) | 0.017092 / 0.141683 (-0.124591) | 1.132399 / 1.452155 (-0.319756) | 1.167290 / 1.492716 (-0.325427) |\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) | 0.094460 / 0.018006 (0.076454) | 0.301462 / 0.000490 (0.300972) | 0.000202 / 0.000200 (0.000002) | 0.000052 / 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) | 0.022767 / 0.037411 (-0.014645) | 0.075993 / 0.014526 (0.061467) | 0.087729 / 0.176557 (-0.088827) | 0.127599 / 0.737135 (-0.609536) | 0.088873 / 0.296338 (-0.207465) |\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) | 0.286420 / 0.215209 (0.071211) | 2.811376 / 2.077655 (0.733722) | 1.558645 / 1.504120 (0.054525) | 1.426371 / 1.541195 (-0.114824) | 1.422347 / 1.468490 (-0.046143) | 0.567181 / 4.584777 (-4.017596) | 0.936731 / 3.745712 (-2.808982) | 2.643566 / 5.269862 (-2.626296) | 1.727843 / 4.565676 (-2.837834) | 0.062748 / 0.424275 (-0.361527) | 0.005033 / 0.007607 (-0.002574) | 0.339708 / 0.226044 (0.113663) | 3.354119 / 2.268929 (1.085190) | 1.877594 / 55.444624 (-53.567030) | 1.589202 / 6.876477 (-5.287274) | 1.707780 / 2.142072 (-0.434292) | 0.644520 / 4.805227 (-4.160708) | 0.115226 / 6.500664 (-6.385438) | 0.040004 / 0.075469 (-0.035465) |\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) | 1.002774 / 1.841788 (-0.839014) | 11.812647 / 8.074308 (3.738339) | 10.384198 / 10.191392 (0.192806) | 0.131120 / 0.680424 (-0.549304) | 0.014862 / 0.534201 (-0.519339) | 0.282873 / 0.579283 (-0.296410) | 0.120415 / 0.434364 (-0.313949) | 0.321995 / 0.540337 (-0.218343) | 0.441987 / 1.386936 (-0.944949) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#b12a2c5016499cc1d110798c6815f0245f61010e \"CML watermark\")\n" ]

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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6910). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.", "<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) | 0.005135 / 0.011353 (-0.006218) | 0.003757 / 0.011008 (-0.007251) | 0.063122 / 0.038508 (0.024614) | 0.029837 / 0.023109 (0.006727) | 0.246120 / 0.275898 (-0.029778) | 0.268529 / 0.323480 (-0.054951) | 0.004136 / 0.007986 (-0.003849) | 0.002650 / 0.004328 (-0.001678) | 0.048749 / 0.004250 (0.044499) | 0.045279 / 0.037052 (0.008226) | 0.257970 / 0.258489 (-0.000519) | 0.285993 / 0.293841 (-0.007848) | 0.027612 / 0.128546 (-0.100935) | 0.010175 / 0.075646 (-0.065471) | 0.207373 / 0.419271 (-0.211899) | 0.037672 / 0.043533 (-0.005861) | 0.249603 / 0.255139 (-0.005536) | 0.271081 / 0.283200 (-0.012119) | 0.018174 / 0.141683 (-0.123509) | 1.116703 / 1.452155 (-0.335452) | 1.169261 / 1.492716 (-0.323455) |\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) | 0.095161 / 0.018006 (0.077155) | 0.301112 / 0.000490 (0.300623) | 0.000221 / 0.000200 (0.000021) | 0.000042 / 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) | 0.023218 / 0.037411 (-0.014193) | 0.063125 / 0.014526 (0.048599) | 0.075857 / 0.176557 (-0.100699) | 0.137922 / 0.737135 (-0.599213) | 0.076989 / 0.296338 (-0.219349) |\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) | 0.279272 / 0.215209 (0.064063) | 2.776463 / 2.077655 (0.698809) | 1.472220 / 1.504120 (-0.031900) | 1.347105 / 1.541195 (-0.194090) | 1.361014 / 1.468490 (-0.107476) | 0.589233 / 4.584777 (-3.995544) | 2.395212 / 3.745712 (-1.350500) | 2.794855 / 5.269862 (-2.475007) | 1.698350 / 4.565676 (-2.867327) | 0.063328 / 0.424275 (-0.360947) | 0.005020 / 0.007607 (-0.002588) | 0.335872 / 0.226044 (0.109828) | 3.293486 / 2.268929 (1.024558) | 1.837270 / 55.444624 (-53.607354) | 1.535694 / 6.876477 (-5.340782) | 1.559696 / 2.142072 (-0.582376) | 0.639302 / 4.805227 (-4.165925) | 0.116554 / 6.500664 (-6.384110) | 0.042305 / 0.075469 (-0.033164) |\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) | 0.971562 / 1.841788 (-0.870226) | 11.710500 / 8.074308 (3.636192) | 9.505935 / 10.191392 (-0.685457) | 0.139161 / 0.680424 (-0.541263) | 0.014351 / 0.534201 (-0.519850) | 0.285790 / 0.579283 (-0.293493) | 0.265718 / 0.434364 (-0.168646) | 0.323558 / 0.540337 (-0.216780) | 0.412635 / 1.386936 (-0.974301) |\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) | 0.005987 / 0.011353 (-0.005366) | 0.003787 / 0.011008 (-0.007221) | 0.049839 / 0.038508 (0.011331) | 0.032817 / 0.023109 (0.009708) | 0.268304 / 0.275898 (-0.007594) | 0.303409 / 0.323480 (-0.020071) | 0.004924 / 0.007986 (-0.003061) | 0.002740 / 0.004328 (-0.001589) | 0.048906 / 0.004250 (0.044655) | 0.044266 / 0.037052 (0.007213) | 0.290506 / 0.258489 (0.032017) | 0.314124 / 0.293841 (0.020283) | 0.030242 / 0.128546 (-0.098304) | 0.010555 / 0.075646 (-0.065091) | 0.058849 / 0.419271 (-0.360423) | 0.033540 / 0.043533 (-0.009993) | 0.267833 / 0.255139 (0.012694) | 0.291056 / 0.283200 (0.007857) | 0.018611 / 0.141683 (-0.123072) | 1.137620 / 1.452155 (-0.314534) | 1.199554 / 1.492716 (-0.293162) |\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) | 0.096716 / 0.018006 (0.078709) | 0.302033 / 0.000490 (0.301543) | 0.000217 / 0.000200 (0.000017) | 0.000044 / 0.000054 (-0.000010) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.023208 / 0.037411 (-0.014203) | 0.076231 / 0.014526 (0.061705) | 0.088672 / 0.176557 (-0.087884) | 0.129033 / 0.737135 (-0.608103) | 0.090709 / 0.296338 (-0.205630) |\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) | 0.297033 / 0.215209 (0.081824) | 2.951181 / 2.077655 (0.873526) | 1.567690 / 1.504120 (0.063570) | 1.436809 / 1.541195 (-0.104385) | 1.469696 / 1.468490 (0.001206) | 0.567963 / 4.584777 (-4.016813) | 0.954168 / 3.745712 (-2.791544) | 2.700473 / 5.269862 (-2.569389) | 1.742144 / 4.565676 (-2.823532) | 0.065027 / 0.424275 (-0.359248) | 0.005319 / 0.007607 (-0.002288) | 0.346459 / 0.226044 (0.120415) | 3.446117 / 2.268929 (1.177189) | 1.953142 / 55.444624 (-53.491483) | 1.639131 / 6.876477 (-5.237346) | 1.830664 / 2.142072 (-0.311409) | 0.657807 / 4.805227 (-4.147420) | 0.117987 / 6.500664 (-6.382678) | 0.040726 / 0.075469 (-0.034744) |\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) | 0.992666 / 1.841788 (-0.849122) | 12.305377 / 8.074308 (4.231069) | 10.274829 / 10.191392 (0.083437) | 0.141731 / 0.680424 (-0.538692) | 0.015100 / 0.534201 (-0.519101) | 0.282298 / 0.579283 (-0.296985) | 0.124301 / 0.434364 (-0.310063) | 0.320914 / 0.540337 (-0.219424) | 0.445855 / 1.386936 (-0.941081) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#3b66daa02b3307079a90fbfd13856e9bec0fc1ab \"CML watermark\")\n" ]

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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6909). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.", "<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) | 0.005375 / 0.011353 (-0.005978) | 0.004005 / 0.011008 (-0.007003) | 0.062407 / 0.038508 (0.023899) | 0.032241 / 0.023109 (0.009131) | 0.256092 / 0.275898 (-0.019806) | 0.285740 / 0.323480 (-0.037740) | 0.004146 / 0.007986 (-0.003839) | 0.002831 / 0.004328 (-0.001497) | 0.049179 / 0.004250 (0.044928) | 0.048303 / 0.037052 (0.011251) | 0.270841 / 0.258489 (0.012352) | 0.303209 / 0.293841 (0.009368) | 0.027642 / 0.128546 (-0.100905) | 0.010661 / 0.075646 (-0.064985) | 0.201999 / 0.419271 (-0.217272) | 0.036532 / 0.043533 (-0.007001) | 0.262441 / 0.255139 (0.007302) | 0.280944 / 0.283200 (-0.002256) | 0.018369 / 0.141683 (-0.123314) | 1.122249 / 1.452155 (-0.329906) | 1.171352 / 1.492716 (-0.321364) |\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) | 0.096433 / 0.018006 (0.078427) | 0.297272 / 0.000490 (0.296782) | 0.000222 / 0.000200 (0.000023) | 0.000043 / 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) | 0.019645 / 0.037411 (-0.017766) | 0.062744 / 0.014526 (0.048219) | 0.076096 / 0.176557 (-0.100460) | 0.121882 / 0.737135 (-0.615253) | 0.076267 / 0.296338 (-0.220072) |\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) | 0.274159 / 0.215209 (0.058950) | 2.729371 / 2.077655 (0.651716) | 1.454328 / 1.504120 (-0.049792) | 1.330517 / 1.541195 (-0.210678) | 1.338832 / 1.468490 (-0.129658) | 0.600252 / 4.584777 (-3.984525) | 2.388658 / 3.745712 (-1.357054) | 2.837717 / 5.269862 (-2.432145) | 1.747329 / 4.565676 (-2.818347) | 0.064620 / 0.424275 (-0.359655) | 0.004955 / 0.007607 (-0.002653) | 0.340253 / 0.226044 (0.114209) | 3.351559 / 2.268929 (1.082630) | 1.822718 / 55.444624 (-53.621907) | 1.518663 / 6.876477 (-5.357814) | 1.548066 / 2.142072 (-0.594006) | 0.663525 / 4.805227 (-4.141702) | 0.118334 / 6.500664 (-6.382331) | 0.042060 / 0.075469 (-0.033410) |\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) | 0.976509 / 1.841788 (-0.865278) | 11.703321 / 8.074308 (3.629013) | 9.305605 / 10.191392 (-0.885787) | 0.131016 / 0.680424 (-0.549408) | 0.014299 / 0.534201 (-0.519902) | 0.293963 / 0.579283 (-0.285320) | 0.264018 / 0.434364 (-0.170345) | 0.330265 / 0.540337 (-0.210073) | 0.427239 / 1.386936 (-0.959697) |\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) | 0.005437 / 0.011353 (-0.005916) | 0.003774 / 0.011008 (-0.007234) | 0.049927 / 0.038508 (0.011419) | 0.032246 / 0.023109 (0.009137) | 0.271808 / 0.275898 (-0.004090) | 0.295652 / 0.323480 (-0.027828) | 0.004220 / 0.007986 (-0.003766) | 0.002803 / 0.004328 (-0.001525) | 0.049656 / 0.004250 (0.045406) | 0.041938 / 0.037052 (0.004885) | 0.282199 / 0.258489 (0.023710) | 0.310206 / 0.293841 (0.016365) | 0.030389 / 0.128546 (-0.098157) | 0.010593 / 0.075646 (-0.065054) | 0.057862 / 0.419271 (-0.361409) | 0.033937 / 0.043533 (-0.009596) | 0.268920 / 0.255139 (0.013781) | 0.286000 / 0.283200 (0.002800) | 0.018766 / 0.141683 (-0.122917) | 1.118556 / 1.452155 (-0.333599) | 1.175083 / 1.492716 (-0.317633) |\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) | 0.095135 / 0.018006 (0.077129) | 0.304735 / 0.000490 (0.304245) | 0.000210 / 0.000200 (0.000010) | 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) | 0.022971 / 0.037411 (-0.014441) | 0.076204 / 0.014526 (0.061678) | 0.090801 / 0.176557 (-0.085756) | 0.130149 / 0.737135 (-0.606987) | 0.090986 / 0.296338 (-0.205352) |\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) | 0.298535 / 0.215209 (0.083326) | 2.882959 / 2.077655 (0.805304) | 1.574018 / 1.504120 (0.069899) | 1.445251 / 1.541195 (-0.095944) | 1.483651 / 1.468490 (0.015160) | 0.572012 / 4.584777 (-4.012765) | 0.972223 / 3.745712 (-2.773489) | 2.745776 / 5.269862 (-2.524085) | 1.783980 / 4.565676 (-2.781697) | 0.063910 / 0.424275 (-0.360365) | 0.005397 / 0.007607 (-0.002210) | 0.349104 / 0.226044 (0.123059) | 3.433303 / 2.268929 (1.164374) | 1.961506 / 55.444624 (-53.483119) | 1.665905 / 6.876477 (-5.210571) | 1.800977 / 2.142072 (-0.341095) | 0.655843 / 4.805227 (-4.149384) | 0.118320 / 6.500664 (-6.382345) | 0.041748 / 0.075469 (-0.033722) |\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) | 1.006835 / 1.841788 (-0.834952) | 12.506123 / 8.074308 (4.431815) | 10.564310 / 10.191392 (0.372918) | 0.143121 / 0.680424 (-0.537303) | 0.016340 / 0.534201 (-0.517861) | 0.284181 / 0.579283 (-0.295102) | 0.125975 / 0.434364 (-0.308389) | 0.324369 / 0.540337 (-0.215969) | 0.443713 / 1.386936 (-0.943223) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#60d21efbc01e15d0b596ac1072750cbecd91548a \"CML watermark\")\n" ]

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[ "I am not able to reproduce the error with datasets 2.19.1:\r\n```python\r\nIn [1]: from datasets import load_dataset; ds = load_dataset(\"stas/c4-en-10k\", streaming=True); item = next(iter(ds[\"train\"])); item\r\nOut[1]: {'text': 'Beginners BBQ Class Taking Place in Missoula!\\nDo you want to get better at making delicious BBQ? You will have the opportunity, put this on your calendar now. Thursday, September 22nd join World Class BBQ Champion, Tony Balay from Lonestar Smoke Rangers. He will be teaching a beginner level class for everyone who wants to get better with their culinary skills.\\nHe will teach you everything you need to know to compete in a KCBS BBQ competition, including techniques, recipes, timelines, meat selection and trimming, plus smoker and fire information.\\nThe cost to be in the class is $35 per person, and for spectators it is free. Included in the cost will be either a t-shirt or apron and you will be tasting samples of each meat that is prepared.'}\r\n\r\nIn [2]: from datasets import load_dataset; ds = load_dataset(\"stas/c4-en-10k\", download_mode=\"force_redownload\"); ds\r\nDownloading data: 100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 13.3M/13.3M [00:00<00:00, 18.7MB/s]\r\nGenerating train split: 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 10000/10000 [00:00<00:00, 78548.55 examples/s]\r\nOut[2]: \r\nDatasetDict({\r\n train: Dataset({\r\n features: ['text'],\r\n num_rows: 10000\r\n })\r\n})\r\n```\r\n\r\nLooking at your error traceback, I notice that the code line numbers do not correspond to the ones of datasets 2.19.1.\r\n\r\nAdditionally, I can't reproduce the issue with `HfFileSystem`:\r\n```python\r\nIn [1]: from huggingface_hub import HfFileSystem\r\n\r\nIn [2]: fs = HfFileSystem()\r\n\r\nIn [3]: with fs.open(\"datasets/stas/c4-en-10k/c4-en-10k.py\", \"rb\") as f:\r\n ...: data = f.read()\r\n ...: \r\n\r\nIn [4]: data[:20]\r\nOut[4]: b'# coding=utf-8\\n# Cop'\r\n```\r\n\r\nCould you please verify the `datasets` and `huggingface_hub` versions you are indeed using?\r\n```python\r\nimport datasets; print(datasets.__version__)\r\n\r\nimport huggingface_hub; print(huggingface_hub.__version__)\r\n```", "Thanks for your reply! After I update the datasets version from 2.15.0 back to 2.19.1 again, it seems everything work well. Sorry for bordering you!" ]

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[ "Update: I ended up deciding to go back to use lines of dictionaries instead of arrays, not because of this issue as my users would be capable of downloading my corpus without `datasets`, but the speed and storage savings are not currently worth breaking my API and harming the backwards compatibility of each new revision.\r\n\r\nWith that said, for a static dataset that is not regularly updated like mine, and particularly for extremely large datasets with millions or billions of rows, using arrays could have a meaningful impact, and so there is probably still value in supporting this structure, provided the effort is not too much." ]

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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6904). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.", "takign the liberty to merge this for the viewer and a new dataset being released", "<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) | 0.005004 / 0.011353 (-0.006349) | 0.003352 / 0.011008 (-0.007657) | 0.063035 / 0.038508 (0.024527) | 0.032031 / 0.023109 (0.008922) | 0.244801 / 0.275898 (-0.031097) | 0.270622 / 0.323480 (-0.052857) | 0.003110 / 0.007986 (-0.004876) | 0.002629 / 0.004328 (-0.001700) | 0.048784 / 0.004250 (0.044534) | 0.045779 / 0.037052 (0.008726) | 0.258642 / 0.258489 (0.000153) | 0.291606 / 0.293841 (-0.002235) | 0.028237 / 0.128546 (-0.100310) | 0.010184 / 0.075646 (-0.065463) | 0.202455 / 0.419271 (-0.216816) | 0.036012 / 0.043533 (-0.007521) | 0.248209 / 0.255139 (-0.006930) | 0.267315 / 0.283200 (-0.015884) | 0.019249 / 0.141683 (-0.122434) | 1.120420 / 1.452155 (-0.331735) | 1.169515 / 1.492716 (-0.323201) |\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) | 0.095193 / 0.018006 (0.077187) | 0.300544 / 0.000490 (0.300055) | 0.000214 / 0.000200 (0.000014) | 0.000050 / 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) | 0.019001 / 0.037411 (-0.018411) | 0.061857 / 0.014526 (0.047331) | 0.073379 / 0.176557 (-0.103178) | 0.121293 / 0.737135 (-0.615843) | 0.075665 / 0.296338 (-0.220673) |\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) | 0.285153 / 0.215209 (0.069944) | 2.875527 / 2.077655 (0.797873) | 1.479851 / 1.504120 (-0.024269) | 1.360691 / 1.541195 (-0.180504) | 1.385581 / 1.468490 (-0.082909) | 0.566312 / 4.584777 (-4.018465) | 2.400202 / 3.745712 (-1.345510) | 2.719241 / 5.269862 (-2.550620) | 1.706469 / 4.565676 (-2.859208) | 0.062129 / 0.424275 (-0.362146) | 0.005291 / 0.007607 (-0.002316) | 0.334585 / 0.226044 (0.108540) | 3.293347 / 2.268929 (1.024419) | 1.790490 / 55.444624 (-53.654134) | 1.505519 / 6.876477 (-5.370958) | 1.527730 / 2.142072 (-0.614343) | 0.644554 / 4.805227 (-4.160673) | 0.119775 / 6.500664 (-6.380889) | 0.056912 / 0.075469 (-0.018557) |\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) | 0.977512 / 1.841788 (-0.864275) | 11.293883 / 8.074308 (3.219575) | 9.669439 / 10.191392 (-0.521953) | 0.129910 / 0.680424 (-0.550514) | 0.014322 / 0.534201 (-0.519879) | 0.284967 / 0.579283 (-0.294316) | 0.265355 / 0.434364 (-0.169008) | 0.321965 / 0.540337 (-0.218372) | 0.415254 / 1.386936 (-0.971682) |\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) | 0.005138 / 0.011353 (-0.006215) | 0.003321 / 0.011008 (-0.007687) | 0.049731 / 0.038508 (0.011223) | 0.032307 / 0.023109 (0.009198) | 0.266331 / 0.275898 (-0.009567) | 0.290863 / 0.323480 (-0.032617) | 0.004151 / 0.007986 (-0.003835) | 0.002684 / 0.004328 (-0.001644) | 0.048760 / 0.004250 (0.044510) | 0.042251 / 0.037052 (0.005199) | 0.280414 / 0.258489 (0.021925) | 0.305089 / 0.293841 (0.011248) | 0.029118 / 0.128546 (-0.099428) | 0.010276 / 0.075646 (-0.065370) | 0.057790 / 0.419271 (-0.361482) | 0.033290 / 0.043533 (-0.010243) | 0.267250 / 0.255139 (0.012111) | 0.285233 / 0.283200 (0.002034) | 0.018587 / 0.141683 (-0.123096) | 1.136198 / 1.452155 (-0.315957) | 1.185274 / 1.492716 (-0.307442) |\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) | 0.096355 / 0.018006 (0.078349) | 0.301827 / 0.000490 (0.301337) | 0.000216 / 0.000200 (0.000016) | 0.000052 / 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) | 0.022607 / 0.037411 (-0.014805) | 0.075724 / 0.014526 (0.061198) | 0.088197 / 0.176557 (-0.088359) | 0.127864 / 0.737135 (-0.609271) | 0.089294 / 0.296338 (-0.207044) |\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) | 0.289321 / 0.215209 (0.074112) | 2.832456 / 2.077655 (0.754802) | 1.559208 / 1.504120 (0.055088) | 1.426229 / 1.541195 (-0.114966) | 1.424564 / 1.468490 (-0.043926) | 0.557754 / 4.584777 (-4.027023) | 0.940179 / 3.745712 (-2.805533) | 2.713640 / 5.269862 (-2.556222) | 1.697583 / 4.565676 (-2.868093) | 0.062024 / 0.424275 (-0.362251) | 0.005270 / 0.007607 (-0.002337) | 0.339450 / 0.226044 (0.113406) | 3.333024 / 2.268929 (1.064096) | 1.946087 / 55.444624 (-53.498537) | 1.601057 / 6.876477 (-5.275420) | 1.599862 / 2.142072 (-0.542210) | 0.642838 / 4.805227 (-4.162390) | 0.120470 / 6.500664 (-6.380194) | 0.040815 / 0.075469 (-0.034654) |\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) | 1.012904 / 1.841788 (-0.828884) | 11.917035 / 8.074308 (3.842727) | 9.717822 / 10.191392 (-0.473570) | 0.141730 / 0.680424 (-0.538694) | 0.015750 / 0.534201 (-0.518451) | 0.284470 / 0.579283 (-0.294813) | 0.125662 / 0.434364 (-0.308702) | 0.380740 / 0.540337 (-0.159598) | 0.418119 / 1.386936 (-0.968817) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#b3f772468b2bbf77a7510e265f9d41e9eb77d53f \"CML watermark\")\n" ]

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[]

[ "I think [`Dataset.to_parquet`](https://huggingface.co/docs/datasets/v1.10.2/package_reference/main_classes.html#datasets.Dataset.to_parquet) is what you're looking for.\r\n\r\nLet me know if I'm wrong ", "No, it does not save the metadata json.\r\n\r\nWe have to recode all meta json load/save\r\nwith another custome functions.\r\n\r\nsave_to_disk\r\nand load should have option with\r\n“Parquet” instead of “arrow”\r\n\r\nsince “arrow” is never user for production \r\n(only parquet).\r\n\r\nThanks !\r\n\r\n> On May 17, 2024, at 5:38, Frédéric Branchaud-Charron ***@***.***> wrote:\r\n> \r\n> \r\n> I think Dataset.to_parquet is what you're looking for.\r\n> \r\n> Let me know if I'm wrong\r\n> \r\n> —\r\n> Reply to this email directly, view it on GitHub, or unsubscribe.\r\n> You are receiving this because you authored the thread.\r\n" ]

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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6902). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.", "<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) | 0.005026 / 0.011353 (-0.006327) | 0.003672 / 0.011008 (-0.007336) | 0.062776 / 0.038508 (0.024268) | 0.032056 / 0.023109 (0.008947) | 0.245359 / 0.275898 (-0.030540) | 0.269371 / 0.323480 (-0.054109) | 0.004205 / 0.007986 (-0.003780) | 0.002774 / 0.004328 (-0.001555) | 0.048958 / 0.004250 (0.044708) | 0.046442 / 0.037052 (0.009390) | 0.263924 / 0.258489 (0.005434) | 0.291854 / 0.293841 (-0.001987) | 0.027299 / 0.128546 (-0.101248) | 0.010332 / 0.075646 (-0.065315) | 0.202677 / 0.419271 (-0.216595) | 0.037732 / 0.043533 (-0.005801) | 0.246028 / 0.255139 (-0.009111) | 0.272100 / 0.283200 (-0.011099) | 0.018497 / 0.141683 (-0.123186) | 1.101192 / 1.452155 (-0.350962) | 1.149683 / 1.492716 (-0.343033) |\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) | 0.097838 / 0.018006 (0.079832) | 0.305598 / 0.000490 (0.305108) | 0.000230 / 0.000200 (0.000030) | 0.000045 / 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) | 0.019489 / 0.037411 (-0.017922) | 0.061902 / 0.014526 (0.047376) | 0.074825 / 0.176557 (-0.101732) | 0.121664 / 0.737135 (-0.615472) | 0.076440 / 0.296338 (-0.219898) |\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) | 0.279194 / 0.215209 (0.063985) | 2.756777 / 2.077655 (0.679123) | 1.429298 / 1.504120 (-0.074822) | 1.313423 / 1.541195 (-0.227771) | 1.340466 / 1.468490 (-0.128024) | 0.556349 / 4.584777 (-4.028428) | 2.355910 / 3.745712 (-1.389802) | 2.806733 / 5.269862 (-2.463128) | 1.741903 / 4.565676 (-2.823773) | 0.061556 / 0.424275 (-0.362719) | 0.005477 / 0.007607 (-0.002130) | 0.327856 / 0.226044 (0.101812) | 3.283092 / 2.268929 (1.014164) | 1.797776 / 55.444624 (-53.646848) | 1.498683 / 6.876477 (-5.377794) | 1.518501 / 2.142072 (-0.623572) | 0.632267 / 4.805227 (-4.172960) | 0.116505 / 6.500664 (-6.384159) | 0.042446 / 0.075469 (-0.033023) |\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) | 0.982841 / 1.841788 (-0.858947) | 11.709436 / 8.074308 (3.635128) | 9.570519 / 10.191392 (-0.620873) | 0.141968 / 0.680424 (-0.538456) | 0.014299 / 0.534201 (-0.519902) | 0.285101 / 0.579283 (-0.294182) | 0.267118 / 0.434364 (-0.167246) | 0.324720 / 0.540337 (-0.215617) | 0.423626 / 1.386936 (-0.963310) |\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) | 0.005567 / 0.011353 (-0.005786) | 0.003703 / 0.011008 (-0.007306) | 0.050516 / 0.038508 (0.012008) | 0.032617 / 0.023109 (0.009508) | 0.276546 / 0.275898 (0.000648) | 0.299798 / 0.323480 (-0.023682) | 0.004282 / 0.007986 (-0.003704) | 0.002719 / 0.004328 (-0.001609) | 0.049424 / 0.004250 (0.045173) | 0.042924 / 0.037052 (0.005871) | 0.287785 / 0.258489 (0.029296) | 0.315490 / 0.293841 (0.021649) | 0.029533 / 0.128546 (-0.099013) | 0.010575 / 0.075646 (-0.065071) | 0.058210 / 0.419271 (-0.361061) | 0.033269 / 0.043533 (-0.010263) | 0.273325 / 0.255139 (0.018186) | 0.291762 / 0.283200 (0.008563) | 0.018922 / 0.141683 (-0.122761) | 1.118913 / 1.452155 (-0.333242) | 1.175554 / 1.492716 (-0.317162) |\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) | 0.099920 / 0.018006 (0.081914) | 0.317188 / 0.000490 (0.316698) | 0.000211 / 0.000200 (0.000011) | 0.000045 / 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) | 0.022297 / 0.037411 (-0.015114) | 0.077775 / 0.014526 (0.063249) | 0.090239 / 0.176557 (-0.086317) | 0.130498 / 0.737135 (-0.606638) | 0.092010 / 0.296338 (-0.204328) |\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) | 0.293534 / 0.215209 (0.078325) | 2.866070 / 2.077655 (0.788415) | 1.547147 / 1.504120 (0.043027) | 1.419684 / 1.541195 (-0.121510) | 1.432128 / 1.468490 (-0.036362) | 0.571365 / 4.584777 (-4.013412) | 0.968879 / 3.745712 (-2.776833) | 2.797415 / 5.269862 (-2.472446) | 1.767821 / 4.565676 (-2.797856) | 0.063281 / 0.424275 (-0.360994) | 0.005072 / 0.007607 (-0.002535) | 0.344547 / 0.226044 (0.118502) | 3.383888 / 2.268929 (1.114959) | 1.879537 / 55.444624 (-53.565087) | 1.598392 / 6.876477 (-5.278085) | 1.627788 / 2.142072 (-0.514284) | 0.641199 / 4.805227 (-4.164028) | 0.116349 / 6.500664 (-6.384315) | 0.041940 / 0.075469 (-0.033529) |\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) | 1.002494 / 1.841788 (-0.839294) | 12.310056 / 8.074308 (4.235748) | 9.819718 / 10.191392 (-0.371674) | 0.134745 / 0.680424 (-0.545679) | 0.016223 / 0.534201 (-0.517978) | 0.284791 / 0.579283 (-0.294492) | 0.124665 / 0.434364 (-0.309699) | 0.381601 / 0.540337 (-0.158737) | 0.413007 / 1.386936 (-0.973929) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#6255b36be14ae22890c78749575f1f0793901f14 \"CML watermark\")\n" ]

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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6898). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.", "After this PR, the README file looks like:\r\n\r\n\r\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) | 0.004936 / 0.011353 (-0.006417) | 0.003591 / 0.011008 (-0.007418) | 0.062967 / 0.038508 (0.024459) | 0.031314 / 0.023109 (0.008205) | 0.248040 / 0.275898 (-0.027858) | 0.271630 / 0.323480 (-0.051850) | 0.003085 / 0.007986 (-0.004901) | 0.002605 / 0.004328 (-0.001724) | 0.049452 / 0.004250 (0.045202) | 0.044929 / 0.037052 (0.007876) | 0.264254 / 0.258489 (0.005765) | 0.287531 / 0.293841 (-0.006310) | 0.027197 / 0.128546 (-0.101349) | 0.009925 / 0.075646 (-0.065721) | 0.203165 / 0.419271 (-0.216107) | 0.035658 / 0.043533 (-0.007875) | 0.250207 / 0.255139 (-0.004932) | 0.269258 / 0.283200 (-0.013941) | 0.019975 / 0.141683 (-0.121708) | 1.093703 / 1.452155 (-0.358452) | 1.134031 / 1.492716 (-0.358685) |\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) | 0.095089 / 0.018006 (0.077082) | 0.301410 / 0.000490 (0.300920) | 0.000251 / 0.000200 (0.000051) | 0.000047 / 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) | 0.018453 / 0.037411 (-0.018958) | 0.061674 / 0.014526 (0.047148) | 0.073442 / 0.176557 (-0.103114) | 0.119743 / 0.737135 (-0.617392) | 0.074518 / 0.296338 (-0.221820) |\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) | 0.276351 / 0.215209 (0.061142) | 2.757670 / 2.077655 (0.680015) | 1.471199 / 1.504120 (-0.032921) | 1.363620 / 1.541195 (-0.177575) | 1.374175 / 1.468490 (-0.094315) | 0.556444 / 4.584777 (-4.028333) | 2.340637 / 3.745712 (-1.405075) | 2.728341 / 5.269862 (-2.541521) | 1.701214 / 4.565676 (-2.864463) | 0.061832 / 0.424275 (-0.362443) | 0.005287 / 0.007607 (-0.002320) | 0.331848 / 0.226044 (0.105804) | 3.334204 / 2.268929 (1.065276) | 1.791203 / 55.444624 (-53.653421) | 1.512246 / 6.876477 (-5.364231) | 1.529570 / 2.142072 (-0.612503) | 0.632193 / 4.805227 (-4.173034) | 0.116512 / 6.500664 (-6.384153) | 0.041271 / 0.075469 (-0.034198) |\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) | 0.981813 / 1.841788 (-0.859974) | 11.271398 / 8.074308 (3.197090) | 9.654613 / 10.191392 (-0.536780) | 0.140235 / 0.680424 (-0.540188) | 0.014336 / 0.534201 (-0.519865) | 0.284286 / 0.579283 (-0.294997) | 0.260265 / 0.434364 (-0.174099) | 0.321064 / 0.540337 (-0.219274) | 0.417554 / 1.386936 (-0.969382) |\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) | 0.005265 / 0.011353 (-0.006088) | 0.003237 / 0.011008 (-0.007772) | 0.049723 / 0.038508 (0.011215) | 0.031705 / 0.023109 (0.008596) | 0.255548 / 0.275898 (-0.020350) | 0.281651 / 0.323480 (-0.041829) | 0.004099 / 0.007986 (-0.003886) | 0.002739 / 0.004328 (-0.001589) | 0.049713 / 0.004250 (0.045463) | 0.041563 / 0.037052 (0.004511) | 0.269500 / 0.258489 (0.011011) | 0.293948 / 0.293841 (0.000107) | 0.029259 / 0.128546 (-0.099287) | 0.010391 / 0.075646 (-0.065255) | 0.057772 / 0.419271 (-0.361500) | 0.033125 / 0.043533 (-0.010408) | 0.258838 / 0.255139 (0.003699) | 0.278616 / 0.283200 (-0.004584) | 0.017543 / 0.141683 (-0.124139) | 1.130319 / 1.452155 (-0.321835) | 1.185976 / 1.492716 (-0.306740) |\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) | 0.094827 / 0.018006 (0.076821) | 0.296820 / 0.000490 (0.296331) | 0.000212 / 0.000200 (0.000012) | 0.000046 / 0.000054 (-0.000008) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.022583 / 0.037411 (-0.014828) | 0.076318 / 0.014526 (0.061792) | 0.087435 / 0.176557 (-0.089121) | 0.127351 / 0.737135 (-0.609784) | 0.089051 / 0.296338 (-0.207287) |\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) | 0.289476 / 0.215209 (0.074267) | 2.842065 / 2.077655 (0.764410) | 1.536857 / 1.504120 (0.032737) | 1.393914 / 1.541195 (-0.147281) | 1.392636 / 1.468490 (-0.075854) | 0.570299 / 4.584777 (-4.014478) | 0.982246 / 3.745712 (-2.763466) | 2.758773 / 5.269862 (-2.511088) | 1.728615 / 4.565676 (-2.837062) | 0.063944 / 0.424275 (-0.360331) | 0.005014 / 0.007607 (-0.002593) | 0.347474 / 0.226044 (0.121430) | 3.398092 / 2.268929 (1.129164) | 1.855134 / 55.444624 (-53.589491) | 1.568705 / 6.876477 (-5.307772) | 1.574201 / 2.142072 (-0.567871) | 0.649466 / 4.805227 (-4.155761) | 0.116330 / 6.500664 (-6.384334) | 0.040730 / 0.075469 (-0.034739) |\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) | 1.000675 / 1.841788 (-0.841113) | 11.899660 / 8.074308 (3.825352) | 9.913335 / 10.191392 (-0.278058) | 0.132517 / 0.680424 (-0.547907) | 0.016467 / 0.534201 (-0.517734) | 0.282221 / 0.579283 (-0.297062) | 0.125205 / 0.434364 (-0.309159) | 0.374986 / 0.540337 (-0.165351) | 0.418666 / 1.386936 (-0.968270) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#e2f989d01b49e3d6f98b2014d9ece3307e885b7a \"CML watermark\")\n" ]

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[ "Hello, @bghira.\r\n\r\nThanks for reporting. Please note that the text originating the error is not supposed to be valid YAML: it contains the instructions to generate the actual YAML content, that should replace the instructions comment.\r\n\r\nOn the other hand, I agree that it is not nice to have that YAML error message at the top of the page: \r\n\r\n\r\nI am proposing a change to make the YAML error disappear.", "thanks albert! i looked at it for a while to figure it out. i think the `raw` view option is the correct way to look at it?" ]

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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6895). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.", "<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) | 0.004914 / 0.011353 (-0.006439) | 0.003621 / 0.011008 (-0.007387) | 0.062841 / 0.038508 (0.024333) | 0.031630 / 0.023109 (0.008520) | 0.247666 / 0.275898 (-0.028232) | 0.288192 / 0.323480 (-0.035288) | 0.003145 / 0.007986 (-0.004841) | 0.002655 / 0.004328 (-0.001674) | 0.049484 / 0.004250 (0.045233) | 0.046593 / 0.037052 (0.009540) | 0.271550 / 0.258489 (0.013061) | 0.293228 / 0.293841 (-0.000613) | 0.026941 / 0.128546 (-0.101606) | 0.009936 / 0.075646 (-0.065710) | 0.201741 / 0.419271 (-0.217530) | 0.035435 / 0.043533 (-0.008098) | 0.251868 / 0.255139 (-0.003271) | 0.272082 / 0.283200 (-0.011118) | 0.019731 / 0.141683 (-0.121952) | 1.125752 / 1.452155 (-0.326403) | 1.152058 / 1.492716 (-0.340659) |\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) | 0.099695 / 0.018006 (0.081689) | 0.308306 / 0.000490 (0.307816) | 0.000223 / 0.000200 (0.000023) | 0.000044 / 0.000054 (-0.000010) |\n\n### Benchmark: benchmark_indices_mapping.json\n\n| metric | select | shard | shuffle | sort | train_test_split |\n|--------|---|---|---|---|---|\n| new / old (diff) | 0.018616 / 0.037411 (-0.018795) | 0.061886 / 0.014526 (0.047360) | 0.074059 / 0.176557 (-0.102498) | 0.124902 / 0.737135 (-0.612234) | 0.075108 / 0.296338 (-0.221230) |\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) | 0.336707 / 0.215209 (0.121498) | 2.805197 / 2.077655 (0.727542) | 1.565826 / 1.504120 (0.061706) | 1.443708 / 1.541195 (-0.097486) | 1.341167 / 1.468490 (-0.127323) | 0.566814 / 4.584777 (-4.017963) | 2.374536 / 3.745712 (-1.371176) | 2.804921 / 5.269862 (-2.464941) | 1.739848 / 4.565676 (-2.825829) | 0.062779 / 0.424275 (-0.361496) | 0.005341 / 0.007607 (-0.002266) | 0.326482 / 0.226044 (0.100438) | 3.273460 / 2.268929 (1.004531) | 1.803656 / 55.444624 (-53.640968) | 1.502518 / 6.876477 (-5.373958) | 1.523665 / 2.142072 (-0.618407) | 0.642443 / 4.805227 (-4.162784) | 0.117820 / 6.500664 (-6.382844) | 0.042540 / 0.075469 (-0.032929) |\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) | 0.963399 / 1.841788 (-0.878388) | 11.503648 / 8.074308 (3.429340) | 9.483957 / 10.191392 (-0.707435) | 0.129118 / 0.680424 (-0.551306) | 0.014136 / 0.534201 (-0.520065) | 0.286766 / 0.579283 (-0.292517) | 0.273328 / 0.434364 (-0.161036) | 0.324075 / 0.540337 (-0.216262) | 0.420408 / 1.386936 (-0.966528) |\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) | 0.005099 / 0.011353 (-0.006254) | 0.003721 / 0.011008 (-0.007288) | 0.050614 / 0.038508 (0.012106) | 0.031882 / 0.023109 (0.008773) | 0.267619 / 0.275898 (-0.008279) | 0.291874 / 0.323480 (-0.031606) | 0.004254 / 0.007986 (-0.003731) | 0.002766 / 0.004328 (-0.001563) | 0.049291 / 0.004250 (0.045041) | 0.043302 / 0.037052 (0.006249) | 0.274891 / 0.258489 (0.016402) | 0.304977 / 0.293841 (0.011136) | 0.029088 / 0.128546 (-0.099459) | 0.010425 / 0.075646 (-0.065221) | 0.057781 / 0.419271 (-0.361491) | 0.033589 / 0.043533 (-0.009943) | 0.264293 / 0.255139 (0.009154) | 0.284861 / 0.283200 (0.001661) | 0.018025 / 0.141683 (-0.123658) | 1.124954 / 1.452155 (-0.327200) | 1.161957 / 1.492716 (-0.330759) |\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) | 0.103622 / 0.018006 (0.085615) | 0.310915 / 0.000490 (0.310425) | 0.000241 / 0.000200 (0.000041) | 0.000051 / 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) | 0.022550 / 0.037411 (-0.014862) | 0.076466 / 0.014526 (0.061940) | 0.088297 / 0.176557 (-0.088260) | 0.128659 / 0.737135 (-0.608477) | 0.091823 / 0.296338 (-0.204516) |\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) | 0.293431 / 0.215209 (0.078222) | 2.888105 / 2.077655 (0.810450) | 1.559581 / 1.504120 (0.055461) | 1.421424 / 1.541195 (-0.119771) | 1.437941 / 1.468490 (-0.030549) | 0.577544 / 4.584777 (-4.007233) | 0.968840 / 3.745712 (-2.776872) | 2.799796 / 5.269862 (-2.470066) | 1.744791 / 4.565676 (-2.820885) | 0.064159 / 0.424275 (-0.360116) | 0.005043 / 0.007607 (-0.002564) | 0.341039 / 0.226044 (0.114995) | 3.354402 / 2.268929 (1.085474) | 1.904093 / 55.444624 (-53.540532) | 1.604046 / 6.876477 (-5.272431) | 1.610384 / 2.142072 (-0.531688) | 0.658129 / 4.805227 (-4.147098) | 0.119297 / 6.500664 (-6.381367) | 0.041396 / 0.075469 (-0.034073) |\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) | 1.001109 / 1.841788 (-0.840678) | 12.081856 / 8.074308 (4.007548) | 10.090943 / 10.191392 (-0.100449) | 0.150433 / 0.680424 (-0.529991) | 0.015850 / 0.534201 (-0.518351) | 0.286590 / 0.579283 (-0.292693) | 0.131137 / 0.434364 (-0.303227) | 0.389033 / 0.540337 (-0.151304) | 0.421382 / 1.386936 (-0.965554) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#22b7baed53f9f295a5dda2fe3eb0b7434bf57e89 \"CML watermark\")\n" ]

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[ "The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/datasets/pr_6893). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.", "<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) | 0.005388 / 0.011353 (-0.005965) | 0.003822 / 0.011008 (-0.007187) | 0.063285 / 0.038508 (0.024777) | 0.033780 / 0.023109 (0.010671) | 0.239580 / 0.275898 (-0.036318) | 0.264203 / 0.323480 (-0.059277) | 0.004207 / 0.007986 (-0.003778) | 0.002716 / 0.004328 (-0.001612) | 0.049569 / 0.004250 (0.045319) | 0.048591 / 0.037052 (0.011538) | 0.252606 / 0.258489 (-0.005884) | 0.285998 / 0.293841 (-0.007843) | 0.028650 / 0.128546 (-0.099896) | 0.010652 / 0.075646 (-0.064994) | 0.203962 / 0.419271 (-0.215310) | 0.036207 / 0.043533 (-0.007326) | 0.240374 / 0.255139 (-0.014765) | 0.263564 / 0.283200 (-0.019636) | 0.017722 / 0.141683 (-0.123961) | 1.143741 / 1.452155 (-0.308414) | 1.192452 / 1.492716 (-0.300264) |\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) | 0.141329 / 0.018006 (0.123323) | 0.320169 / 0.000490 (0.319679) | 0.000240 / 0.000200 (0.000041) | 0.000045 / 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) | 0.019885 / 0.037411 (-0.017526) | 0.063322 / 0.014526 (0.048796) | 0.075446 / 0.176557 (-0.101110) | 0.122619 / 0.737135 (-0.614517) | 0.077175 / 0.296338 (-0.219163) |\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) | 0.281292 / 0.215209 (0.066083) | 2.796220 / 2.077655 (0.718565) | 1.456035 / 1.504120 (-0.048085) | 1.334445 / 1.541195 (-0.206750) | 1.380223 / 1.468490 (-0.088267) | 0.575895 / 4.584777 (-4.008882) | 2.375791 / 3.745712 (-1.369921) | 2.926273 / 5.269862 (-2.343589) | 1.832586 / 4.565676 (-2.733090) | 0.064323 / 0.424275 (-0.359952) | 0.005403 / 0.007607 (-0.002204) | 0.334088 / 0.226044 (0.108043) | 3.321174 / 2.268929 (1.052246) | 1.821432 / 55.444624 (-53.623193) | 1.520181 / 6.876477 (-5.356296) | 1.582487 / 2.142072 (-0.559585) | 0.645641 / 4.805227 (-4.159586) | 0.119596 / 6.500664 (-6.381068) | 0.043144 / 0.075469 (-0.032325) |\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) | 0.985104 / 1.841788 (-0.856684) | 12.518240 / 8.074308 (4.443932) | 10.017118 / 10.191392 (-0.174274) | 0.133900 / 0.680424 (-0.546524) | 0.014591 / 0.534201 (-0.519610) | 0.288326 / 0.579283 (-0.290957) | 0.262292 / 0.434364 (-0.172072) | 0.327601 / 0.540337 (-0.212736) | 0.421525 / 1.386936 (-0.965411) |\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) | 0.005546 / 0.011353 (-0.005807) | 0.003961 / 0.011008 (-0.007047) | 0.051745 / 0.038508 (0.013237) | 0.032587 / 0.023109 (0.009478) | 0.266886 / 0.275898 (-0.009012) | 0.301327 / 0.323480 (-0.022153) | 0.004273 / 0.007986 (-0.003713) | 0.002851 / 0.004328 (-0.001477) | 0.049333 / 0.004250 (0.045082) | 0.044530 / 0.037052 (0.007478) | 0.286829 / 0.258489 (0.028340) | 0.310732 / 0.293841 (0.016892) | 0.029925 / 0.128546 (-0.098621) | 0.011270 / 0.075646 (-0.064377) | 0.059071 / 0.419271 (-0.360200) | 0.033899 / 0.043533 (-0.009633) | 0.270448 / 0.255139 (0.015309) | 0.286935 / 0.283200 (0.003735) | 0.019516 / 0.141683 (-0.122167) | 1.125815 / 1.452155 (-0.326339) | 1.179893 / 1.492716 (-0.312823) |\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) | 0.096476 / 0.018006 (0.078470) | 0.305149 / 0.000490 (0.304660) | 0.000207 / 0.000200 (0.000008) | 0.000046 / 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) | 0.023648 / 0.037411 (-0.013763) | 0.082847 / 0.014526 (0.068322) | 0.089210 / 0.176557 (-0.087347) | 0.130194 / 0.737135 (-0.606941) | 0.091700 / 0.296338 (-0.204639) |\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) | 0.290995 / 0.215209 (0.075786) | 2.870335 / 2.077655 (0.792680) | 1.595661 / 1.504120 (0.091541) | 1.452319 / 1.541195 (-0.088876) | 1.505647 / 1.468490 (0.037157) | 0.575856 / 4.584777 (-4.008921) | 1.005527 / 3.745712 (-2.740185) | 2.927824 / 5.269862 (-2.342038) | 1.791702 / 4.565676 (-2.773975) | 0.064804 / 0.424275 (-0.359471) | 0.005203 / 0.007607 (-0.002404) | 0.348615 / 0.226044 (0.122570) | 3.463989 / 2.268929 (1.195060) | 1.947758 / 55.444624 (-53.496866) | 1.669974 / 6.876477 (-5.206502) | 1.721663 / 2.142072 (-0.420410) | 0.650999 / 4.805227 (-4.154228) | 0.117769 / 6.500664 (-6.382895) | 0.041738 / 0.075469 (-0.033731) |\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) | 1.004140 / 1.841788 (-0.837648) | 13.035487 / 8.074308 (4.961179) | 10.318152 / 10.191392 (0.126760) | 0.143776 / 0.680424 (-0.536648) | 0.016272 / 0.534201 (-0.517929) | 0.286564 / 0.579283 (-0.292719) | 0.126579 / 0.434364 (-0.307785) | 0.397253 / 0.540337 (-0.143085) | 0.424968 / 1.386936 (-0.961968) |\n\n</details>\n</details>\n\n![](https://cml.dev/watermark.png#ddb6a283d7dfccc81a9fb12e761b819fed86c7a0 \"CML watermark\")\n", "Supersede and close: #6889" ]

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