File size: 107,549 Bytes
6bc22e0 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 |
========================
START TIME: Tue Jul 2 18:31:59 UTC 2024
python3 version = Python 3.10.14
========================
The token has not been saved to the git credentials helper. Pass `add_to_git_credential=True` in this function directly or `--add-to-git-credential` if using via `huggingface-cli` if you want to set the git credential as well.
Token is valid (permission: write).
Your token has been saved to /admin/home/ferdinand_mom/.cache/huggingface/token
Login successful
Already on 'bench_cluster'
M examples/config_tiny_llama.py
M examples/config_tiny_llama.yaml
M examples/train_tiny_llama.sh
M src/nanotron/models/llama.py
M src/nanotron/trainer.py
Your branch is up to date with 'origin/bench_cluster'.
Job status: RUNNING
W0702 18:32:07.594000 139743167231808 torch/distributed/run.py:757]
W0702 18:32:07.594000 139743167231808 torch/distributed/run.py:757] *****************************************
W0702 18:32:07.594000 139743167231808 torch/distributed/run.py:757] Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed.
W0702 18:32:07.594000 139743167231808 torch/distributed/run.py:757] *****************************************
W0702 18:32:07.761000 139682410350400 torch/distributed/run.py:757]
W0702 18:32:07.761000 139682410350400 torch/distributed/run.py:757] *****************************************
W0702 18:32:07.761000 139682410350400 torch/distributed/run.py:757] Setting OMP_NUM_THREADS environment variable for each process to be 1 in default, to avoid your system being overloaded, please further tune the variable for optimal performance in your application as needed.
W0702 18:32:07.761000 139682410350400 torch/distributed/run.py:757] *****************************************
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: Config:
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: Config(general=GeneralArgs(project='bench_cluster',
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: run='%date_%jobid',
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: seed=42,
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: step=None,
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: consumed_train_samples=None,
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: benchmark_csv_path=None,
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: ignore_sanity_checks=True),
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: parallelism=ParallelismArgs(dp=1,
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: pp=16,
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: tp=1,
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: pp_engine=<nanotron.parallel.pipeline_parallel.engine.OneForwardOneBackwardPipelineEngine object at 0x7f7301914910>,
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: tp_mode=<TensorParallelLinearMode.REDUCE_SCATTER: 2>,
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: tp_linear_async_communication=False,
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: expert_parallel_size=1),
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: model=ModelArgs(model_config=LlamaConfig(bos_token_id=1,
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: eos_token_id=2,
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: hidden_act='silu',
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: hidden_size=2048,
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: initializer_range=0.02,
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: intermediate_size=4096,
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: is_llama_config=True,
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: max_position_embeddings=4096,
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: num_attention_heads=32,
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: num_hidden_layers=24,
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: num_key_value_heads=32,
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: pad_token_id=None,
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: pretraining_tp=1,
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: rms_norm_eps=1e-05,
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: rope_scaling=None,
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: rope_theta=10000.0,
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: tie_word_embeddings=True,
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: use_cache=True,
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: vocab_size=50257),
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: init_method=RandomInit(std=0.025),
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: dtype=torch.bfloat16,
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: make_vocab_size_divisible_by=1,
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: ddp_bucket_cap_mb=25),
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: tokenizer=TokenizerArgs(tokenizer_name_or_path='openai-community/gpt2',
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: tokenizer_revision=None,
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: tokenizer_max_length=None),
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: checkpoints=CheckpointsArgs(checkpoints_path=Path('/dev/null'),
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: checkpoint_interval=100000,
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: save_initial_state=False,
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: resume_checkpoint_path=None,
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: checkpoints_path_is_shared_file_system=False),
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: logging=LoggingArgs(log_level='info',
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: log_level_replica='info',
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: iteration_step_info_interval=1),
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: tokens=TokensArgs(sequence_length=4096,
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: train_steps=20,
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: micro_batch_size=2,
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: batch_accumulation_per_replica=512,
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: val_check_interval=-1,
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: limit_val_batches=0,
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: limit_test_batches=0),
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: optimizer=OptimizerArgs(optimizer_factory=AdamWOptimizerArgs(adam_eps=1e-08,
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: adam_beta1=0.9,
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: adam_beta2=0.95,
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: torch_adam_is_fused=True,
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: name='adamW'),
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: zero_stage=1,
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: weight_decay=0.01,
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: clip_grad=1.0,
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: accumulate_grad_in_fp32=True,
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: learning_rate_scheduler=LRSchedulerArgs(learning_rate=0.0001,
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: lr_warmup_steps=1,
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: lr_warmup_style='linear',
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: lr_decay_style='linear',
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: lr_decay_steps=19,
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: lr_decay_starting_step=None,
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: min_decay_lr=1e-05)),
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: data_stages=[DatasetStageArgs(name='Training Stage',
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: start_training_step=1,
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: data=DataArgs(dataset=PretrainDatasetsArgs(hf_dataset_or_datasets='roneneldan/TinyStories',
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: hf_dataset_splits='train',
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: hf_dataset_config_name=None,
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: dataset_processing_num_proc_per_process=64,
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: dataset_overwrite_cache=False,
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: text_column_name='text'),
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: seed=42,
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: num_loading_workers=32))],
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: profiler=ProfilerArgs(profiler_export_path=Path('/fsx/ferdinandmom/ferdinand-hf/bench_cluster/results/llama-1B/16_GPUS/dp-1_tp-1_pp-16_mbz-2')),
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: lighteval=None)
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: Model Config:
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: LlamaConfig(bos_token_id=1,
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: eos_token_id=2,
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: hidden_act='silu',
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: hidden_size=2048,
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: initializer_range=0.02,
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: intermediate_size=4096,
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: is_llama_config=True,
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: max_position_embeddings=4096,
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: num_attention_heads=32,
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: num_hidden_layers=24,
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: num_key_value_heads=32,
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: pad_token_id=None,
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: pretraining_tp=1,
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: rms_norm_eps=1e-05,
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: rope_scaling=None,
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: rope_theta=10000.0,
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: tie_word_embeddings=True,
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: use_cache=True,
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: vocab_size=50257)
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: Building model..
[default0]:07/02/2024 18:32:30 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: Setting PP block ranks...
[default0]:07/02/2024 18:32:48 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: Total number of parameters: 1.21G (2312.82MiB)
[default0]:07/02/2024 18:32:48 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: Local number of parameters: 187M (356.33MiB)
[default0]:07/02/2024 18:32:48 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: [After model building] Memory usage: 358.34MiB. Peak allocated: 360.37MiB Peak reserved: 368.00MiB
[default0]:07/02/2024 18:32:48 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: No checkpoint path provided.
[default0]:07/02/2024 18:32:48 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: Parametrizing model parameters using StandardParametrizator
[default4]:07/02/2024 18:32:48 [INFO|DP=0|PP=4|TP=0|ip-26-0-160-192]: Local number of parameters: 83.9M (160.02MiB)
[default4]:07/02/2024 18:32:48 [INFO|DP=0|PP=4|TP=0|ip-26-0-160-192]: [After model building] Memory usage: 162.03MiB. Peak allocated: 164.06MiB Peak reserved: 170.00MiB
[default4]:07/02/2024 18:32:48 [INFO|DP=0|PP=4|TP=0|ip-26-0-160-192]: No checkpoint path provided.
[default1]:07/02/2024 18:32:48 [INFO|DP=0|PP=1|TP=0|ip-26-0-160-192]: Local number of parameters: 83.9M (160.02MiB)
[default1]:07/02/2024 18:32:48 [INFO|DP=0|PP=1|TP=0|ip-26-0-160-192]: [After model building] Memory usage: 162.03MiB. Peak allocated: 164.06MiB Peak reserved: 170.00MiB
[default1]:07/02/2024 18:32:48 [INFO|DP=0|PP=1|TP=0|ip-26-0-160-192]: No checkpoint path provided.
[default7]:07/02/2024 18:32:48 [INFO|DP=0|PP=7|TP=0|ip-26-0-160-192]: Local number of parameters: 83.9M (160.02MiB)
[default7]:07/02/2024 18:32:48 [INFO|DP=0|PP=7|TP=0|ip-26-0-160-192]: [After model building] Memory usage: 162.03MiB. Peak allocated: 164.06MiB Peak reserved: 170.00MiB
[default7]:07/02/2024 18:32:48 [INFO|DP=0|PP=7|TP=0|ip-26-0-160-192]: No checkpoint path provided.
[default5]:07/02/2024 18:32:48 [INFO|DP=0|PP=5|TP=0|ip-26-0-160-192]: Local number of parameters: 41.9M (80.01MiB)
[default5]:07/02/2024 18:32:48 [INFO|DP=0|PP=5|TP=0|ip-26-0-160-192]: [After model building] Memory usage: 81.02MiB. Peak allocated: 83.05MiB Peak reserved: 96.00MiB
[default5]:07/02/2024 18:32:48 [INFO|DP=0|PP=5|TP=0|ip-26-0-160-192]: No checkpoint path provided.
[default6]:07/02/2024 18:32:48 [INFO|DP=0|PP=14|TP=0|ip-26-0-162-233]: Local number of parameters: 103M (196.32MiB)
[default6]:07/02/2024 18:32:48 [INFO|DP=0|PP=14|TP=0|ip-26-0-162-233]: [After model building] Memory usage: 196.33MiB. Peak allocated: 196.34MiB Peak reserved: 200.00MiB
[default6]:07/02/2024 18:32:48 [INFO|DP=0|PP=14|TP=0|ip-26-0-162-233]: No checkpoint path provided.
[default0]:07/02/2024 18:32:48 [INFO|DP=0|PP=8|TP=0|ip-26-0-162-233]: Local number of parameters: 41.9M (80.01MiB)
[default0]:07/02/2024 18:32:48 [INFO|DP=0|PP=8|TP=0|ip-26-0-162-233]: [After model building] Memory usage: 81.02MiB. Peak allocated: 83.05MiB Peak reserved: 96.00MiB
[default0]:07/02/2024 18:32:48 [INFO|DP=0|PP=8|TP=0|ip-26-0-162-233]: No checkpoint path provided.
[default2]:07/02/2024 18:32:48 [INFO|DP=0|PP=2|TP=0|ip-26-0-160-192]: Local number of parameters: 41.9M (80.01MiB)
[default2]:07/02/2024 18:32:48 [INFO|DP=0|PP=2|TP=0|ip-26-0-160-192]: [After model building] Memory usage: 81.02MiB. Peak allocated: 83.05MiB Peak reserved: 96.00MiB
[default2]:07/02/2024 18:32:48 [INFO|DP=0|PP=2|TP=0|ip-26-0-160-192]: No checkpoint path provided.
[default3]:07/02/2024 18:32:48 [INFO|DP=0|PP=3|TP=0|ip-26-0-160-192]: Local number of parameters: 83.9M (160.02MiB)
[default3]:07/02/2024 18:32:48 [INFO|DP=0|PP=3|TP=0|ip-26-0-160-192]: [After model building] Memory usage: 162.03MiB. Peak allocated: 164.06MiB Peak reserved: 170.00MiB
[default3]:07/02/2024 18:32:48 [INFO|DP=0|PP=3|TP=0|ip-26-0-160-192]: No checkpoint path provided.
[default7]:07/02/2024 18:32:48 [INFO|DP=0|PP=15|TP=0|ip-26-0-162-233]: Local number of parameters: 0 (0.00MiB)
[default7]:07/02/2024 18:32:48 [INFO|DP=0|PP=15|TP=0|ip-26-0-162-233]: [After model building] Memory usage: 0.01MiB. Peak allocated: 0.02MiB Peak reserved: 2.00MiB
[default7]:07/02/2024 18:32:48 [INFO|DP=0|PP=15|TP=0|ip-26-0-162-233]: No checkpoint path provided.
[default1]:07/02/2024 18:32:48 [INFO|DP=0|PP=9|TP=0|ip-26-0-162-233]: Local number of parameters: 83.9M (160.02MiB)
[default1]:07/02/2024 18:32:48 [INFO|DP=0|PP=9|TP=0|ip-26-0-162-233]: [After model building] Memory usage: 162.03MiB. Peak allocated: 164.06MiB Peak reserved: 170.00MiB
[default2]:07/02/2024 18:32:48 [INFO|DP=0|PP=10|TP=0|ip-26-0-162-233]: Local number of parameters: 83.9M (160.02MiB)
[default2]:07/02/2024 18:32:48 [INFO|DP=0|PP=10|TP=0|ip-26-0-162-233]: [After model building] Memory usage: 162.03MiB. Peak allocated: 164.06MiB Peak reserved: 170.00MiB
[default2]:07/02/2024 18:32:48 [INFO|DP=0|PP=10|TP=0|ip-26-0-162-233]: No checkpoint path provided.
[default4]:07/02/2024 18:32:48 [INFO|DP=0|PP=12|TP=0|ip-26-0-162-233]: Local number of parameters: 83.9M (160.02MiB)
[default5]:07/02/2024 18:32:48 [INFO|DP=0|PP=13|TP=0|ip-26-0-162-233]: Local number of parameters: 83.9M (160.02MiB)
[default3]:07/02/2024 18:32:48 [INFO|DP=0|PP=11|TP=0|ip-26-0-162-233]: Local number of parameters: 41.9M (80.01MiB)
[default4]:07/02/2024 18:32:48 [INFO|DP=0|PP=12|TP=0|ip-26-0-162-233]: [After model building] Memory usage: 162.03MiB. Peak allocated: 164.06MiB Peak reserved: 170.00MiB
[default4]:07/02/2024 18:32:48 [INFO|DP=0|PP=12|TP=0|ip-26-0-162-233]: No checkpoint path provided.
[default5]:07/02/2024 18:32:48 [INFO|DP=0|PP=13|TP=0|ip-26-0-162-233]: [After model building] Memory usage: 162.03MiB. Peak allocated: 164.06MiB Peak reserved: 170.00MiB
[default5]:07/02/2024 18:32:48 [INFO|DP=0|PP=13|TP=0|ip-26-0-162-233]: No checkpoint path provided.
[default3]:07/02/2024 18:32:48 [INFO|DP=0|PP=11|TP=0|ip-26-0-162-233]: [After model building] Memory usage: 81.02MiB. Peak allocated: 83.05MiB Peak reserved: 96.00MiB
[default3]:07/02/2024 18:32:48 [INFO|DP=0|PP=11|TP=0|ip-26-0-162-233]: No checkpoint path provided.
[default1]:07/02/2024 18:32:48 [INFO|DP=0|PP=9|TP=0|ip-26-0-162-233]: No checkpoint path provided.
[default6]:07/02/2024 18:32:48 [INFO|DP=0|PP=6|TP=0|ip-26-0-160-192]: Local number of parameters: 83.9M (160.02MiB)
[default6]:07/02/2024 18:32:48 [INFO|DP=0|PP=6|TP=0|ip-26-0-160-192]: [After model building] Memory usage: 162.03MiB. Peak allocated: 164.06MiB Peak reserved: 170.00MiB
[default6]:07/02/2024 18:32:48 [INFO|DP=0|PP=6|TP=0|ip-26-0-160-192]: No checkpoint path provided.
[default0]:07/02/2024 18:32:48 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: [Optimizer Building] Using LearningRateForSP as learning rate
[default0]:07/02/2024 18:32:48 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: [ZeRO sharding] Size of optimizer params per rank:
[default0]:07/02/2024 18:32:48 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: [ZeRO sharding] DP Rank 0 has 187M out of 187M (100.00%) params' optimizer states
[default0]:07/02/2024 18:32:50 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: [Training Plan] Stage Training Stage has 19 remaining training steps and has consumed 0 samples
[default0]:07/02/2024 18:32:50 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: Using `datasets` library
[default0]:07/02/2024 18:32:50 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: Loading tokenizer from openai-community/gpt2 and transformers/hf_hub versions ('4.41.2', '0.23.4')
[default0]:07/02/2024 18:32:50 [WARNING|DP=0|PP=0|TP=0|ip-26-0-160-192]: Repo card metadata block was not found. Setting CardData to empty.
[default0]:Repo card metadata block was not found. Setting CardData to empty.
[default0]:07/02/2024 18:32:52 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: [Training Plan] There are 1 training stages
[default0]:07/02/2024 18:32:52 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: [Stage Training Stage] start from step 1
[default0]:07/02/2024 18:32:52 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]:
[default0]:07/02/2024 18:32:52 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: [Start training] datetime: 2024-07-02 18:32:52.233490 | mbs: 2 | grad_accum: 512 | global_batch_size: 1024 | sequence_length: 4096 | train_steps: 20 | start_iteration_step: 0 | consumed_train_samples: 0
[default0]:07/02/2024 18:32:52 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: Resuming training from stage Training Stage, it has trained for 0 samples and has 19 remaining train steps
[default0]:07/02/2024 18:32:52 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: Memory usage: 1783.67MiB. Peak allocated 1783.67MiB. Peak reserved: 1796.00MiB
[default4]:07/02/2024 18:32:52 [WARNING|DP=0|PP=4|TP=0|ip-26-0-160-192]: Repo card metadata block was not found. Setting CardData to empty.
[default1]:07/02/2024 18:32:52 [WARNING|DP=0|PP=1|TP=0|ip-26-0-160-192]: Repo card metadata block was not found. Setting CardData to empty.
[default5]:07/02/2024 18:32:52 [WARNING|DP=0|PP=5|TP=0|ip-26-0-160-192]: Repo card metadata block was not found. Setting CardData to empty.
[default6]:07/02/2024 18:32:52 [WARNING|DP=0|PP=14|TP=0|ip-26-0-162-233]: Repo card metadata block was not found. Setting CardData to empty.
[default0]:07/02/2024 18:32:52 [WARNING|DP=0|PP=8|TP=0|ip-26-0-162-233]: Repo card metadata block was not found. Setting CardData to empty.
[default2]:07/02/2024 18:32:52 [WARNING|DP=0|PP=2|TP=0|ip-26-0-160-192]: Repo card metadata block was not found. Setting CardData to empty.
[default3]:07/02/2024 18:32:52 [WARNING|DP=0|PP=3|TP=0|ip-26-0-160-192]: Repo card metadata block was not found. Setting CardData to empty.
[default6]:Repo card metadata block was not found. Setting CardData to empty.
[default1]:Repo card metadata block was not found. Setting CardData to empty.
[default2]:Repo card metadata block was not found. Setting CardData to empty.
[default4]:Repo card metadata block was not found. Setting CardData to empty.
[default7]:07/02/2024 18:32:52 [WARNING|DP=0|PP=15|TP=0|ip-26-0-162-233]: Repo card metadata block was not found. Setting CardData to empty.
[default2]:Repo card metadata block was not found. Setting CardData to empty.
[default0]:Repo card metadata block was not found. Setting CardData to empty.
[default4]:07/02/2024 18:32:52 [WARNING|DP=0|PP=12|TP=0|ip-26-0-162-233]: Repo card metadata block was not found. Setting CardData to empty.
[default7]:Repo card metadata block was not found. Setting CardData to empty.
[default6]:Repo card metadata block was not found. Setting CardData to empty.
[default2]:07/02/2024 18:32:52 [WARNING|DP=0|PP=10|TP=0|ip-26-0-162-233]: Repo card metadata block was not found. Setting CardData to empty.
[default3]:07/02/2024 18:32:52 [WARNING|DP=0|PP=11|TP=0|ip-26-0-162-233]: Repo card metadata block was not found. Setting CardData to empty.
[default1]:07/02/2024 18:32:52 [WARNING|DP=0|PP=9|TP=0|ip-26-0-162-233]: Repo card metadata block was not found. Setting CardData to empty.
[default5]:Repo card metadata block was not found. Setting CardData to empty.
[default6]:07/02/2024 18:32:52 [WARNING|DP=0|PP=6|TP=0|ip-26-0-160-192]: Repo card metadata block was not found. Setting CardData to empty.
[default5]:07/02/2024 18:32:52 [WARNING|DP=0|PP=13|TP=0|ip-26-0-162-233]: Repo card metadata block was not found. Setting CardData to empty.
[default3]:Repo card metadata block was not found. Setting CardData to empty.
[default3]:Repo card metadata block was not found. Setting CardData to empty.
[default7]:Repo card metadata block was not found. Setting CardData to empty.
[default1]:Repo card metadata block was not found. Setting CardData to empty.
[default5]:Repo card metadata block was not found. Setting CardData to empty.
[default4]:Repo card metadata block was not found. Setting CardData to empty.
[default7]:07/02/2024 18:32:52 [WARNING|DP=0|PP=7|TP=0|ip-26-0-160-192]: Repo card metadata block was not found. Setting CardData to empty.
[default6]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/autograd/graph.py:744: UserWarning: c10d::allreduce_: an autograd kernel was not registered to the Autograd key(s) but we are trying to backprop through it. This may lead to silently incorrect behavior. This behavior is deprecated and will be removed in a future version of PyTorch. If your operator is differentiable, please ensure you have registered an autograd kernel to the correct Autograd key (e.g. DispatchKey::Autograd, DispatchKey::CompositeImplicitAutograd). If your operator is not differentiable, or to squash this warning and use the previous behavior, please register torch::CppFunction::makeFallthrough() to DispatchKey::Autograd. (Triggered internally at ../torch/csrc/autograd/autograd_not_implemented_fallback.cpp:63.)
[default6]: return Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass
[default5]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/autograd/graph.py:744: UserWarning: c10d::allreduce_: an autograd kernel was not registered to the Autograd key(s) but we are trying to backprop through it. This may lead to silently incorrect behavior. This behavior is deprecated and will be removed in a future version of PyTorch. If your operator is differentiable, please ensure you have registered an autograd kernel to the correct Autograd key (e.g. DispatchKey::Autograd, DispatchKey::CompositeImplicitAutograd). If your operator is not differentiable, or to squash this warning and use the previous behavior, please register torch::CppFunction::makeFallthrough() to DispatchKey::Autograd. (Triggered internally at ../torch/csrc/autograd/autograd_not_implemented_fallback.cpp:63.)
[default5]: return Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass
[default4]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/autograd/graph.py:744: UserWarning: c10d::allreduce_: an autograd kernel was not registered to the Autograd key(s) but we are trying to backprop through it. This may lead to silently incorrect behavior. This behavior is deprecated and will be removed in a future version of PyTorch. If your operator is differentiable, please ensure you have registered an autograd kernel to the correct Autograd key (e.g. DispatchKey::Autograd, DispatchKey::CompositeImplicitAutograd). If your operator is not differentiable, or to squash this warning and use the previous behavior, please register torch::CppFunction::makeFallthrough() to DispatchKey::Autograd. (Triggered internally at ../torch/csrc/autograd/autograd_not_implemented_fallback.cpp:63.)
[default4]: return Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass
[default3]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/autograd/graph.py:744: UserWarning: c10d::allreduce_: an autograd kernel was not registered to the Autograd key(s) but we are trying to backprop through it. This may lead to silently incorrect behavior. This behavior is deprecated and will be removed in a future version of PyTorch. If your operator is differentiable, please ensure you have registered an autograd kernel to the correct Autograd key (e.g. DispatchKey::Autograd, DispatchKey::CompositeImplicitAutograd). If your operator is not differentiable, or to squash this warning and use the previous behavior, please register torch::CppFunction::makeFallthrough() to DispatchKey::Autograd. (Triggered internally at ../torch/csrc/autograd/autograd_not_implemented_fallback.cpp:63.)
[default3]: return Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass
[default2]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/autograd/graph.py:744: UserWarning: c10d::allreduce_: an autograd kernel was not registered to the Autograd key(s) but we are trying to backprop through it. This may lead to silently incorrect behavior. This behavior is deprecated and will be removed in a future version of PyTorch. If your operator is differentiable, please ensure you have registered an autograd kernel to the correct Autograd key (e.g. DispatchKey::Autograd, DispatchKey::CompositeImplicitAutograd). If your operator is not differentiable, or to squash this warning and use the previous behavior, please register torch::CppFunction::makeFallthrough() to DispatchKey::Autograd. (Triggered internally at ../torch/csrc/autograd/autograd_not_implemented_fallback.cpp:63.)
[default2]: return Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass
[default1]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/autograd/graph.py:744: UserWarning: c10d::allreduce_: an autograd kernel was not registered to the Autograd key(s) but we are trying to backprop through it. This may lead to silently incorrect behavior. This behavior is deprecated and will be removed in a future version of PyTorch. If your operator is differentiable, please ensure you have registered an autograd kernel to the correct Autograd key (e.g. DispatchKey::Autograd, DispatchKey::CompositeImplicitAutograd). If your operator is not differentiable, or to squash this warning and use the previous behavior, please register torch::CppFunction::makeFallthrough() to DispatchKey::Autograd. (Triggered internally at ../torch/csrc/autograd/autograd_not_implemented_fallback.cpp:63.)
[default1]: return Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass
[default0]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/autograd/graph.py:744: UserWarning: Attempting to run cuBLAS, but there was no current CUDA context! Attempting to set the primary context... (Triggered internally at ../aten/src/ATen/cuda/CublasHandlePool.cpp:135.)
[default0]: return Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass
[default0]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/autograd/graph.py:744: UserWarning: c10d::allreduce_: an autograd kernel was not registered to the Autograd key(s) but we are trying to backprop through it. This may lead to silently incorrect behavior. This behavior is deprecated and will be removed in a future version of PyTorch. If your operator is differentiable, please ensure you have registered an autograd kernel to the correct Autograd key (e.g. DispatchKey::Autograd, DispatchKey::CompositeImplicitAutograd). If your operator is not differentiable, or to squash this warning and use the previous behavior, please register torch::CppFunction::makeFallthrough() to DispatchKey::Autograd. (Triggered internally at ../torch/csrc/autograd/autograd_not_implemented_fallback.cpp:63.)
[default0]: return Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass
[default7]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/autograd/graph.py:744: UserWarning: c10d::allreduce_: an autograd kernel was not registered to the Autograd key(s) but we are trying to backprop through it. This may lead to silently incorrect behavior. This behavior is deprecated and will be removed in a future version of PyTorch. If your operator is differentiable, please ensure you have registered an autograd kernel to the correct Autograd key (e.g. DispatchKey::Autograd, DispatchKey::CompositeImplicitAutograd). If your operator is not differentiable, or to squash this warning and use the previous behavior, please register torch::CppFunction::makeFallthrough() to DispatchKey::Autograd. (Triggered internally at ../torch/csrc/autograd/autograd_not_implemented_fallback.cpp:63.)
[default7]: return Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass
[default6]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/autograd/graph.py:744: UserWarning: c10d::allreduce_: an autograd kernel was not registered to the Autograd key(s) but we are trying to backprop through it. This may lead to silently incorrect behavior. This behavior is deprecated and will be removed in a future version of PyTorch. If your operator is differentiable, please ensure you have registered an autograd kernel to the correct Autograd key (e.g. DispatchKey::Autograd, DispatchKey::CompositeImplicitAutograd). If your operator is not differentiable, or to squash this warning and use the previous behavior, please register torch::CppFunction::makeFallthrough() to DispatchKey::Autograd. (Triggered internally at ../torch/csrc/autograd/autograd_not_implemented_fallback.cpp:63.)
[default6]: return Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass
[default5]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/autograd/graph.py:744: UserWarning: c10d::allreduce_: an autograd kernel was not registered to the Autograd key(s) but we are trying to backprop through it. This may lead to silently incorrect behavior. This behavior is deprecated and will be removed in a future version of PyTorch. If your operator is differentiable, please ensure you have registered an autograd kernel to the correct Autograd key (e.g. DispatchKey::Autograd, DispatchKey::CompositeImplicitAutograd). If your operator is not differentiable, or to squash this warning and use the previous behavior, please register torch::CppFunction::makeFallthrough() to DispatchKey::Autograd. (Triggered internally at ../torch/csrc/autograd/autograd_not_implemented_fallback.cpp:63.)
[default5]: return Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass
[default4]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/autograd/graph.py:744: UserWarning: c10d::allreduce_: an autograd kernel was not registered to the Autograd key(s) but we are trying to backprop through it. This may lead to silently incorrect behavior. This behavior is deprecated and will be removed in a future version of PyTorch. If your operator is differentiable, please ensure you have registered an autograd kernel to the correct Autograd key (e.g. DispatchKey::Autograd, DispatchKey::CompositeImplicitAutograd). If your operator is not differentiable, or to squash this warning and use the previous behavior, please register torch::CppFunction::makeFallthrough() to DispatchKey::Autograd. (Triggered internally at ../torch/csrc/autograd/autograd_not_implemented_fallback.cpp:63.)
[default4]: return Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass
[default3]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/autograd/graph.py:744: UserWarning: c10d::allreduce_: an autograd kernel was not registered to the Autograd key(s) but we are trying to backprop through it. This may lead to silently incorrect behavior. This behavior is deprecated and will be removed in a future version of PyTorch. If your operator is differentiable, please ensure you have registered an autograd kernel to the correct Autograd key (e.g. DispatchKey::Autograd, DispatchKey::CompositeImplicitAutograd). If your operator is not differentiable, or to squash this warning and use the previous behavior, please register torch::CppFunction::makeFallthrough() to DispatchKey::Autograd. (Triggered internally at ../torch/csrc/autograd/autograd_not_implemented_fallback.cpp:63.)
[default3]: return Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass
[default2]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/autograd/graph.py:744: UserWarning: c10d::allreduce_: an autograd kernel was not registered to the Autograd key(s) but we are trying to backprop through it. This may lead to silently incorrect behavior. This behavior is deprecated and will be removed in a future version of PyTorch. If your operator is differentiable, please ensure you have registered an autograd kernel to the correct Autograd key (e.g. DispatchKey::Autograd, DispatchKey::CompositeImplicitAutograd). If your operator is not differentiable, or to squash this warning and use the previous behavior, please register torch::CppFunction::makeFallthrough() to DispatchKey::Autograd. (Triggered internally at ../torch/csrc/autograd/autograd_not_implemented_fallback.cpp:63.)
[default2]: return Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass
[default1]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/autograd/graph.py:744: UserWarning: c10d::allreduce_: an autograd kernel was not registered to the Autograd key(s) but we are trying to backprop through it. This may lead to silently incorrect behavior. This behavior is deprecated and will be removed in a future version of PyTorch. If your operator is differentiable, please ensure you have registered an autograd kernel to the correct Autograd key (e.g. DispatchKey::Autograd, DispatchKey::CompositeImplicitAutograd). If your operator is not differentiable, or to squash this warning and use the previous behavior, please register torch::CppFunction::makeFallthrough() to DispatchKey::Autograd. (Triggered internally at ../torch/csrc/autograd/autograd_not_implemented_fallback.cpp:63.)
[default1]: return Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass
[default0]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/autograd/graph.py:744: UserWarning: Attempting to run cuBLAS, but there was no current CUDA context! Attempting to set the primary context... (Triggered internally at ../aten/src/ATen/cuda/CublasHandlePool.cpp:135.)
[default0]: return Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass
[default0]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/autograd/graph.py:744: UserWarning: c10d::allreduce_: an autograd kernel was not registered to the Autograd key(s) but we are trying to backprop through it. This may lead to silently incorrect behavior. This behavior is deprecated and will be removed in a future version of PyTorch. If your operator is differentiable, please ensure you have registered an autograd kernel to the correct Autograd key (e.g. DispatchKey::Autograd, DispatchKey::CompositeImplicitAutograd). If your operator is not differentiable, or to squash this warning and use the previous behavior, please register torch::CppFunction::makeFallthrough() to DispatchKey::Autograd. (Triggered internally at ../torch/csrc/autograd/autograd_not_implemented_fallback.cpp:63.)
[default0]: return Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass
[default6]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py:2261: UserWarning: torch.distributed.all_reduce_coalesced will be deprecated. If you must use it, please revisit our documentation later at https://pytorch.org/docs/master/distributed.html#collective-functions
[default6]: warnings.warn(
[default0]:07/02/2024 18:34:28 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: Memory usage: 1848.74MiB. Peak allocated 21515.73MiB. Peak reserved: 21810.00MiB
[default0]:/fsx/ferdinandmom/miniforge3/envs/env-bench-cluster/lib/python3.10/site-packages/torch/distributed/distributed_c10d.py:2261: UserWarning: torch.distributed.all_reduce_coalesced will be deprecated. If you must use it, please revisit our documentation later at https://pytorch.org/docs/master/distributed.html#collective-functions
[default0]: warnings.warn(
[default0]:07/02/2024 18:34:28 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: Memory usage: 3274.08MiB. Peak allocated 3274.08MiB. Peak reserved: 22598.00MiB
[default7]:07/02/2024 18:34:28 [INFO|DP=0|PP=15|TP=0|ip-26-0-162-233]: iteration: 1 / 20 | consumed_tokens: 4.19M | elapsed_time_per_iteration_ms: 90.8K | tokens_per_sec: 46.2K | tokens_per_sec_per_gpu: 2.89K | global_batch_size: 1.02K | lm_loss: 11.1 | lr: 0.0001 | model_tflops_per_gpu: 26.2 | hardware_tflops_per_gpu: 26.2 | grad_norm: 25.6 | cuda_memory_allocated: 346K | cuda_max_memory_reserved: 5.77G | hd_total_memory_tb: 312G | hd_used_memory_tb: 66.1G | hd_free_memory_tb: 246G
[default0]:07/02/2024 18:35:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: Memory usage: 3274.08MiB. Peak allocated 22941.07MiB. Peak reserved: 23444.00MiB
[default0]:07/02/2024 18:35:00 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: Memory usage: 3274.08MiB. Peak allocated 3274.08MiB. Peak reserved: 23444.00MiB
[default7]:07/02/2024 18:35:00 [INFO|DP=0|PP=15|TP=0|ip-26-0-162-233]: iteration: 2 / 20 | consumed_tokens: 8.39M | elapsed_time_per_iteration_ms: 31.7K | tokens_per_sec: 132K | tokens_per_sec_per_gpu: 8.27K | global_batch_size: 1.02K | lm_loss: 11.1 | lr: 9.53e-05 | model_tflops_per_gpu: 75.1 | hardware_tflops_per_gpu: 75.1 | grad_norm: 25.9 | cuda_memory_allocated: 346K | cuda_max_memory_reserved: 5.77G | hd_total_memory_tb: 312G | hd_used_memory_tb: 66.1G | hd_free_memory_tb: 246G
[default0]:07/02/2024 18:35:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: Memory usage: 3274.08MiB. Peak allocated 22941.07MiB. Peak reserved: 23444.00MiB
[default7]:07/02/2024 18:35:32 [INFO|DP=0|PP=15|TP=0|ip-26-0-162-233]: iteration: 3 / 20 | consumed_tokens: 12.6M | elapsed_time_per_iteration_ms: 31.9K | tokens_per_sec: 131K | tokens_per_sec_per_gpu: 8.21K | global_batch_size: 1.02K | lm_loss: 9.9 | lr: 9.05e-05 | model_tflops_per_gpu: 74.5 | hardware_tflops_per_gpu: 74.5 | grad_norm: 40.4 | cuda_memory_allocated: 346K | cuda_max_memory_reserved: 5.77G | hd_total_memory_tb: 312G | hd_used_memory_tb: 66.1G | hd_free_memory_tb: 246G
[default0]:07/02/2024 18:35:32 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: Memory usage: 3274.08MiB. Peak allocated 3274.08MiB. Peak reserved: 23444.00MiB
[default0]:STAGE:2024-07-02 18:35:32 925006:925006 ActivityProfilerController.cpp:314] Completed Stage: Warm Up
[default0]:07/02/2024 18:36:02 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: Memory usage: 3274.08MiB. Peak allocated 22941.07MiB. Peak reserved: 23444.00MiB
[default7]:07/02/2024 18:36:02 [INFO|DP=0|PP=15|TP=0|ip-26-0-162-233]: iteration: 4 / 20 | consumed_tokens: 16.8M | elapsed_time_per_iteration_ms: 30.4K | tokens_per_sec: 138K | tokens_per_sec_per_gpu: 8.63K | global_batch_size: 1.02K | lm_loss: 11.9 | lr: 8.58e-05 | model_tflops_per_gpu: 78.3 | hardware_tflops_per_gpu: 78.3 | grad_norm: 61.2 | cuda_memory_allocated: 346K | cuda_max_memory_reserved: 5.77G | hd_total_memory_tb: 312G | hd_used_memory_tb: 66.1G | hd_free_memory_tb: 246G
[default0]:07/02/2024 18:36:02 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: Memory usage: 3274.08MiB. Peak allocated 3274.08MiB. Peak reserved: 23444.00MiB
[default7]:07/02/2024 18:36:33 [INFO|DP=0|PP=15|TP=0|ip-26-0-162-233]: iteration: 5 / 20 | consumed_tokens: 21M | elapsed_time_per_iteration_ms: 30.1K | tokens_per_sec: 139K | tokens_per_sec_per_gpu: 8.7K | global_batch_size: 1.02K | lm_loss: 9.05 | lr: 8.11e-05 | model_tflops_per_gpu: 78.9 | hardware_tflops_per_gpu: 78.9 | grad_norm: 8.32
[default0]:07/02/2024 18:36:33 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: Memory usage: 3274.08MiB. Peak allocated 22941.07MiB. Peak reserved: 23444.00MiB
[default7]:07/02/2024 18:37:05 [INFO|DP=0|PP=15|TP=0|ip-26-0-162-233]: iteration: 6 / 20 | consumed_tokens: 25.2M | elapsed_time_per_iteration_ms: 32.9K | tokens_per_sec: 128K | tokens_per_sec_per_gpu: 7.97K | global_batch_size: 1.02K | lm_loss: 8.86 | lr: 7.63e-05 | model_tflops_per_gpu: 72.3 | hardware_tflops_per_gpu: 72.3 | grad_norm: 6.61
[default0]:STAGE:2024-07-02 18:37:34 925006:925006 ActivityProfilerController.cpp:320] Completed Stage: Collection
[default0]:STAGE:2024-07-02 18:37:37 925006:925006 ActivityProfilerController.cpp:324] Completed Stage: Post Processing
[default0]:07/02/2024 18:41:04 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: Memory usage: 3274.08MiB. Peak allocated 22941.07MiB. Peak reserved: 23444.00MiB
[default7]:07/02/2024 18:41:37 [INFO|DP=0|PP=15|TP=0|ip-26-0-162-233]: iteration: 7 / 20 | consumed_tokens: 29.4M | elapsed_time_per_iteration_ms: 272K | tokens_per_sec: 15.4K | tokens_per_sec_per_gpu: 965 | global_batch_size: 1.02K | lm_loss: 8.37 | lr: 7.16e-05 | model_tflops_per_gpu: 8.75 | hardware_tflops_per_gpu: 8.75 | grad_norm: 4.93
[default0]:07/02/2024 18:41:37 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: Memory usage: 3274.08MiB. Peak allocated 22941.07MiB. Peak reserved: 23444.00MiB
[default0]:07/02/2024 18:42:09 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: Memory usage: 3274.08MiB. Peak allocated 22941.07MiB. Peak reserved: 23444.00MiB
[default7]:07/02/2024 18:42:09 [INFO|DP=0|PP=15|TP=0|ip-26-0-162-233]: iteration: 8 / 20 | consumed_tokens: 33.6M | elapsed_time_per_iteration_ms: 32K | tokens_per_sec: 131K | tokens_per_sec_per_gpu: 8.19K | global_batch_size: 1.02K | lm_loss: 7.97 | lr: 6.68e-05 | model_tflops_per_gpu: 74.3 | hardware_tflops_per_gpu: 74.3 | grad_norm: 3.12
[default0]:07/02/2024 18:42:42 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: Memory usage: 3274.08MiB. Peak allocated 22941.07MiB. Peak reserved: 23444.00MiB
[default7]:07/02/2024 18:42:42 [INFO|DP=0|PP=15|TP=0|ip-26-0-162-233]: iteration: 9 / 20 | consumed_tokens: 37.7M | elapsed_time_per_iteration_ms: 32.6K | tokens_per_sec: 129K | tokens_per_sec_per_gpu: 8.04K | global_batch_size: 1.02K | lm_loss: 7.83 | lr: 6.21e-05 | model_tflops_per_gpu: 73 | hardware_tflops_per_gpu: 73 | grad_norm: 9.04
[default0]:07/02/2024 18:43:13 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: Memory usage: 3274.08MiB. Peak allocated 22941.07MiB. Peak reserved: 23444.00MiB
[default7]:07/02/2024 18:43:13 [INFO|DP=0|PP=15|TP=0|ip-26-0-162-233]: iteration: 10 / 20 | consumed_tokens: 41.9M | elapsed_time_per_iteration_ms: 31.1K | tokens_per_sec: 135K | tokens_per_sec_per_gpu: 8.43K | global_batch_size: 1.02K | lm_loss: 7.62 | lr: 5.74e-05 | model_tflops_per_gpu: 76.5 | hardware_tflops_per_gpu: 76.5 | grad_norm: 5.08
[default7]:07/02/2024 18:43:44 [INFO|DP=0|PP=15|TP=0|ip-26-0-162-233]: iteration: 11 / 20 | consumed_tokens: 46.1M | elapsed_time_per_iteration_ms: 31.1K | tokens_per_sec: 135K | tokens_per_sec_per_gpu: 8.44K | global_batch_size: 1.02K | lm_loss: 7.47 | lr: 5.26e-05 | model_tflops_per_gpu: 76.5 | hardware_tflops_per_gpu: 76.5 | grad_norm: 4.05
[default0]:07/02/2024 18:43:44 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: Memory usage: 3274.08MiB. Peak allocated 22941.07MiB. Peak reserved: 23444.00MiB
[default0]:07/02/2024 18:44:16 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: Memory usage: 3274.08MiB. Peak allocated 22941.07MiB. Peak reserved: 23444.00MiB
[default7]:07/02/2024 18:44:16 [INFO|DP=0|PP=15|TP=0|ip-26-0-162-233]: iteration: 12 / 20 | consumed_tokens: 50.3M | elapsed_time_per_iteration_ms: 32.4K | tokens_per_sec: 130K | tokens_per_sec_per_gpu: 8.09K | global_batch_size: 1.02K | lm_loss: 7.34 | lr: 4.79e-05 | model_tflops_per_gpu: 73.4 | hardware_tflops_per_gpu: 73.4 | grad_norm: 3.13
[default0]:07/02/2024 18:44:48 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: Memory usage: 3274.08MiB. Peak allocated 22941.07MiB. Peak reserved: 23444.00MiB
[default7]:07/02/2024 18:44:48 [INFO|DP=0|PP=15|TP=0|ip-26-0-162-233]: iteration: 13 / 20 | consumed_tokens: 54.5M | elapsed_time_per_iteration_ms: 32K | tokens_per_sec: 131K | tokens_per_sec_per_gpu: 8.18K | global_batch_size: 1.02K | lm_loss: 7.23 | lr: 4.32e-05 | model_tflops_per_gpu: 74.2 | hardware_tflops_per_gpu: 74.2 | grad_norm: 2.74
[default7]:07/02/2024 18:45:21 [INFO|DP=0|PP=15|TP=0|ip-26-0-162-233]: iteration: 14 / 20 | consumed_tokens: 58.7M | elapsed_time_per_iteration_ms: 32.1K | tokens_per_sec: 131K | tokens_per_sec_per_gpu: 8.16K | global_batch_size: 1.02K | lm_loss: 7.14 | lr: 3.84e-05 | model_tflops_per_gpu: 74 | hardware_tflops_per_gpu: 74 | grad_norm: 2.32
[default0]:07/02/2024 18:45:21 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: Memory usage: 3274.08MiB. Peak allocated 22941.07MiB. Peak reserved: 23444.00MiB
[default7]:07/02/2024 18:45:51 [INFO|DP=0|PP=15|TP=0|ip-26-0-162-233]: iteration: 15 / 20 | consumed_tokens: 62.9M | elapsed_time_per_iteration_ms: 30K | tokens_per_sec: 140K | tokens_per_sec_per_gpu: 8.74K | global_batch_size: 1.02K | lm_loss: 7.06 | lr: 3.37e-05 | model_tflops_per_gpu: 79.3 | hardware_tflops_per_gpu: 79.3 | grad_norm: 2.47
[default0]:07/02/2024 18:45:51 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: Memory usage: 3274.08MiB. Peak allocated 22941.07MiB. Peak reserved: 23444.00MiB
[default0]:07/02/2024 18:46:25 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: Memory usage: 3274.08MiB. Peak allocated 22941.07MiB. Peak reserved: 23444.00MiB
[default7]:07/02/2024 18:46:25 [INFO|DP=0|PP=15|TP=0|ip-26-0-162-233]: iteration: 16 / 20 | consumed_tokens: 67.1M | elapsed_time_per_iteration_ms: 34K | tokens_per_sec: 123K | tokens_per_sec_per_gpu: 7.7K | global_batch_size: 1.02K | lm_loss: 6.98 | lr: 2.89e-05 | model_tflops_per_gpu: 69.9 | hardware_tflops_per_gpu: 69.9 | grad_norm: 2.66
[default7]:07/02/2024 18:46:57 [INFO|DP=0|PP=15|TP=0|ip-26-0-162-233]: iteration: 17 / 20 | consumed_tokens: 71.3M | elapsed_time_per_iteration_ms: 32.9K | tokens_per_sec: 128K | tokens_per_sec_per_gpu: 7.97K | global_batch_size: 1.02K | lm_loss: 6.9 | lr: 2.42e-05 | model_tflops_per_gpu: 72.4 | hardware_tflops_per_gpu: 72.4 | grad_norm: 1.88
[default0]:07/02/2024 18:46:57 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: Memory usage: 3274.08MiB. Peak allocated 22941.07MiB. Peak reserved: 23444.00MiB
[default7]:07/02/2024 18:47:29 [INFO|DP=0|PP=15|TP=0|ip-26-0-162-233]: iteration: 18 / 20 | consumed_tokens: 75.5M | elapsed_time_per_iteration_ms: 31.5K | tokens_per_sec: 133K | tokens_per_sec_per_gpu: 8.34K | global_batch_size: 1.02K | lm_loss: 6.84 | lr: 1.95e-05 | model_tflops_per_gpu: 75.6 | hardware_tflops_per_gpu: 75.6 | grad_norm: 1.61
[default0]:07/02/2024 18:47:29 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: Memory usage: 3274.08MiB. Peak allocated 22941.07MiB. Peak reserved: 23444.00MiB
[default7]:07/02/2024 18:48:01 [INFO|DP=0|PP=15|TP=0|ip-26-0-162-233]: iteration: 19 / 20 | consumed_tokens: 79.7M | elapsed_time_per_iteration_ms: 31.9K | tokens_per_sec: 132K | tokens_per_sec_per_gpu: 8.23K | global_batch_size: 1.02K | lm_loss: 6.8 | lr: 1.47e-05 | model_tflops_per_gpu: 74.7 | hardware_tflops_per_gpu: 74.7 | grad_norm: 1.83
[default0]:07/02/2024 18:48:01 [INFO|DP=0|PP=0|TP=0|ip-26-0-160-192]: Memory usage: 3274.08MiB. Peak allocated 22941.07MiB. Peak reserved: 23444.00MiB
[default7]:07/02/2024 18:48:32 [INFO|DP=0|PP=15|TP=0|ip-26-0-162-233]: iteration: 20 / 20 | consumed_tokens: 83.9M | elapsed_time_per_iteration_ms: 31.6K | tokens_per_sec: 133K | tokens_per_sec_per_gpu: 8.29K | global_batch_size: 1.02K | lm_loss: 6.77 | lr: 1e-05 | model_tflops_per_gpu: 75.2 | hardware_tflops_per_gpu: 75.2 | grad_norm: 1.82
W0702 18:49:14.895000 139682410350400 torch/distributed/elastic/rendezvous/dynamic_rendezvous.py:1203] The node 'ip-26-0-162-233.ec2.internal_1273047_0' has failed to shutdown the rendezvous 'none' due to an error of type RendezvousConnectionError.
W0702 18:49:14.899000 139682410350400 torch/distributed/elastic/rendezvous/dynamic_rendezvous.py:1203] The node 'ip-26-0-162-233.ec2.internal_1273047_0' has failed to shutdown the rendezvous 'none' due to an error of type RendezvousConnectionError.
Traceback (most recent call last):
File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/main.py", line 4, in <module>
from bench_cluster.submit_jobs import submit_jobs, check_status
ImportError: cannot import name 'check_status' from 'bench_cluster.submit_jobs' (/fsx/ferdinandmom/ferdinand-hf/bench_cluster/bench_cluster/submit_jobs.py)
Traceback (most recent call last):
File "/fsx/ferdinandmom/ferdinand-hf/bench_cluster/main.py", line 4, in <module>
from bench_cluster.submit_jobs import submit_jobs, check_status
ImportError: cannot import name 'check_status' from 'bench_cluster.submit_jobs' (/fsx/ferdinandmom/ferdinand-hf/bench_cluster/bench_cluster/submit_jobs.py)
Consider using `hf_transfer` for faster uploads. This solution comes with some limitations. See https://huggingface.co/docs/huggingface_hub/hf_transfer for more details.
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 0%| | 0.00/6.72G [00:00<?, ?B/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 0%| | 5.55M/6.72G [00:00<02:02, 55.0MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 0%| | 16.0M/6.72G [00:00<03:07, 35.7MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 0%| | 32.0M/6.72G [00:00<02:21, 47.2MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 1%| | 48.0M/6.72G [00:00<01:56, 57.2MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 1%| | 64.0M/6.72G [00:01<02:03, 53.9MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 1%| | 80.0M/6.72G [00:01<01:44, 63.5MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 1%|▏ | 96.0M/6.72G [00:02<03:03, 36.1MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 2%|▏ | 112M/6.72G [00:02<02:44, 40.3MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 2%|▏ | 128M/6.72G [00:02<02:23, 46.1MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 2%|▏ | 144M/6.72G [00:03<02:34, 42.6MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 2%|▏ | 160M/6.72G [00:03<02:13, 49.3MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 3%|▎ | 176M/6.72G [00:03<01:59, 54.7MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 3%|▎ | 192M/6.72G [00:04<03:35, 30.3MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 3%|▎ | 208M/6.72G [00:04<02:59, 36.3MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 3%|▎ | 224M/6.72G [00:05<02:35, 41.7MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 4%|▎ | 240M/6.72G [00:05<02:32, 42.5MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 4%|▍ | 256M/6.72G [00:05<02:21, 45.8MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 4%|▍ | 272M/6.72G [00:06<02:07, 50.8MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 4%|▍ | 288M/6.72G [00:06<01:53, 56.5MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 5%|▍ | 304M/6.72G [00:06<01:52, 56.8MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 5%|▍ | 320M/6.72G [00:06<01:33, 68.6MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 5%|▍ | 328M/6.72G [00:06<01:45, 60.6MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 5%|▍ | 336M/6.72G [00:07<01:52, 56.9MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 5%|▌ | 352M/6.72G [00:07<01:58, 53.9MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 5%|▌ | 368M/6.72G [00:07<01:44, 60.6MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 6%|▌ | 384M/6.72G [00:07<01:45, 60.1MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 6%|▌ | 400M/6.72G [00:08<01:46, 59.2MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 6%|▌ | 416M/6.72G [00:08<01:52, 56.2MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 6%|▋ | 432M/6.72G [00:08<02:02, 51.3MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 7%|▋ | 448M/6.72G [00:09<02:00, 52.2MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 7%|▋ | 464M/6.72G [00:09<02:13, 47.0MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 7%|▋ | 480M/6.72G [00:09<02:02, 50.8MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 7%|▋ | 496M/6.72G [00:10<01:52, 55.3MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 8%|▊ | 512M/6.72G [00:10<01:49, 56.9MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 8%|▊ | 528M/6.72G [00:10<01:50, 56.1MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 8%|▊ | 544M/6.72G [00:10<01:50, 56.1MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 8%|▊ | 560M/6.72G [00:11<01:49, 56.2MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 9%|▊ | 576M/6.72G [00:11<01:42, 60.0MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 9%|▉ | 592M/6.72G [00:11<01:57, 52.3MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 9%|▉ | 608M/6.72G [00:12<01:56, 52.6MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 9%|▉ | 624M/6.72G [00:12<01:59, 51.0MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 10%|▉ | 640M/6.72G [00:12<01:47, 56.7MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 10%|▉ | 656M/6.72G [00:12<01:45, 57.5MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 10%|▉ | 672M/6.72G [00:13<01:40, 60.1MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 10%|█ | 688M/6.72G [00:13<01:46, 56.6MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 10%|█ | 704M/6.72G [00:13<01:35, 63.0MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 11%|█ | 720M/6.72G [00:13<01:38, 61.2MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 11%|█ | 736M/6.72G [00:14<01:31, 65.7MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 11%|█ | 752M/6.72G [00:14<01:31, 64.9MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 11%|█▏ | 768M/6.72G [00:14<01:30, 66.0MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 12%|█▏ | 784M/6.72G [00:14<01:39, 59.6MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 12%|█▏ | 800M/6.72G [00:15<01:37, 60.9MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 12%|█▏ | 816M/6.72G [00:20<10:43, 9.17MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 12%|█▏ | 832M/6.72G [00:20<07:59, 12.3MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 13%|█▎ | 848M/6.72G [00:20<05:54, 16.6MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 13%|█▎ | 864M/6.72G [00:21<04:54, 19.9MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 13%|█▎ | 880M/6.72G [00:21<03:47, 25.7MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 13%|█▎ | 896M/6.72G [00:21<03:00, 32.3MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 14%|█▎ | 912M/6.72G [00:21<02:26, 39.8MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 14%|█▍ | 928M/6.72G [00:22<03:24, 28.4MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 14%|█▍ | 944M/6.72G [00:23<02:54, 33.2MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 14%|█▍ | 960M/6.72G [00:23<02:32, 37.8MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 15%|█▍ | 976M/6.72G [00:24<02:57, 32.4MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 15%|█▍ | 992M/6.72G [00:24<02:29, 38.4MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 15%|█▍ | 1.01G/6.72G [00:24<02:23, 39.7MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 15%|█▌ | 1.02G/6.72G [00:24<02:06, 45.0MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 15%|█▌ | 1.04G/6.72G [00:25<02:02, 46.4MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 16%|█▌ | 1.06G/6.72G [00:26<03:55, 24.1MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 16%|█▌ | 1.07G/6.72G [00:26<03:16, 28.8MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 16%|█▌ | 1.09G/6.72G [00:27<02:50, 33.1MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 16%|█▋ | 1.10G/6.72G [00:27<02:28, 37.9MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 17%|█▋ | 1.12G/6.72G [00:27<02:04, 45.0MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 17%|█▋ | 1.14G/6.72G [00:27<01:54, 48.8MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 17%|█▋ | 1.15G/6.72G [00:28<01:48, 51.1MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 17%|█▋ | 1.17G/6.72G [00:28<02:05, 44.3MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 18%|█▊ | 1.18G/6.72G [00:28<01:57, 47.2MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 18%|█▊ | 1.20G/6.72G [00:29<02:06, 43.5MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 18%|█▊ | 1.22G/6.72G [00:29<02:03, 44.4MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 18%|█▊ | 1.23G/6.72G [00:30<02:57, 30.9MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 19%|█▊ | 1.25G/6.72G [00:30<02:30, 36.3MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 19%|█▉ | 1.26G/6.72G [00:31<02:10, 41.9MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 19%|█▉ | 1.28G/6.72G [00:31<01:56, 46.6MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 19%|█▉ | 1.30G/6.72G [00:31<01:46, 50.9MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 20%|█▉ | 1.31G/6.72G [00:31<01:44, 51.5MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 20%|█▉ | 1.33G/6.72G [00:32<01:41, 53.4MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 20%|█▉ | 1.34G/6.72G [00:32<01:31, 58.7MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 20%|██ | 1.36G/6.72G [00:32<01:30, 59.4MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 20%|██ | 1.38G/6.72G [00:33<01:52, 47.7MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 21%|██ | 1.39G/6.72G [00:33<01:35, 56.1MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 21%|██ | 1.41G/6.72G [00:33<01:30, 58.5MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 21%|██ | 1.42G/6.72G [00:33<01:24, 62.6MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 21%|██▏ | 1.44G/6.72G [00:34<01:41, 52.0MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 22%|██▏ | 1.46G/6.72G [00:34<01:29, 58.6MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 22%|██▏ | 1.47G/6.72G [00:35<01:58, 44.3MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 22%|██▏ | 1.49G/6.72G [00:35<01:45, 49.8MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 22%|██▏ | 1.50G/6.72G [00:35<01:39, 52.4MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 23%|██▎ | 1.52G/6.72G [00:35<01:28, 58.7MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 23%|██▎ | 1.54G/6.72G [00:36<01:34, 55.1MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 23%|██▎ | 1.55G/6.72G [00:36<02:11, 39.4MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 23%|██▎ | 1.57G/6.72G [00:37<02:44, 31.2MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 24%|██▎ | 1.58G/6.72G [00:37<02:19, 36.7MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 24%|██▍ | 1.60G/6.72G [00:37<02:00, 42.6MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 24%|██▍ | 1.62G/6.72G [00:38<01:56, 43.9MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 24%|██▍ | 1.63G/6.72G [00:38<01:42, 49.4MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 25%|██▍ | 1.65G/6.72G [00:39<02:02, 41.4MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 25%|██▍ | 1.66G/6.72G [00:39<01:43, 48.8MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 25%|██▍ | 1.68G/6.72G [00:40<02:56, 28.6MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 25%|██▌ | 1.70G/6.72G [00:40<02:27, 34.0MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 25%|██▌ | 1.71G/6.72G [00:40<02:02, 40.9MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 26%|██▌ | 1.73G/6.72G [00:41<01:46, 46.8MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 26%|██▌ | 1.74G/6.72G [00:41<01:37, 51.0MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 26%|██▌ | 1.76G/6.72G [00:41<01:21, 60.8MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 26%|██▋ | 1.78G/6.72G [00:41<01:19, 62.4MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 27%|██▋ | 1.79G/6.72G [00:41<01:15, 65.5MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 27%|██▋ | 1.81G/6.72G [00:42<01:10, 69.7MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 27%|██▋ | 1.82G/6.72G [00:42<01:14, 66.0MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 27%|██▋ | 1.84G/6.72G [00:42<01:21, 60.0MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 28%|██▊ | 1.86G/6.72G [00:42<01:22, 59.1MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 28%|██▊ | 1.87G/6.72G [00:43<01:18, 61.5MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 28%|██▊ | 1.89G/6.72G [00:43<01:23, 57.6MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 28%|██▊ | 1.90G/6.72G [00:43<01:25, 56.4MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 29%|██▊ | 1.92G/6.72G [00:44<01:24, 56.7MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 29%|██▉ | 1.94G/6.72G [00:44<01:27, 54.8MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 29%|██▉ | 1.95G/6.72G [00:44<01:22, 57.6MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 29%|██▉ | 1.97G/6.72G [00:45<01:34, 50.2MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 30%|██▉ | 1.98G/6.72G [00:45<01:42, 46.2MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 30%|██▉ | 2.00G/6.72G [00:45<01:41, 46.7MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 30%|██▉ | 2.02G/6.72G [00:46<01:31, 51.2MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 30%|███ | 2.03G/6.72G [00:46<01:32, 50.6MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 30%|███ | 2.05G/6.72G [00:47<03:12, 24.3MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 31%|███ | 2.06G/6.72G [00:48<02:29, 31.1MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 31%|███ | 2.08G/6.72G [00:48<02:07, 36.5MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 31%|███ | 2.10G/6.72G [00:48<01:48, 42.5MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 31%|███▏ | 2.11G/6.72G [00:48<01:37, 47.2MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 32%|███▏ | 2.13G/6.72G [00:49<02:31, 30.2MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 32%|███▏ | 2.14G/6.72G [00:50<02:09, 35.2MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 32%|███▏ | 2.16G/6.72G [00:50<01:58, 38.6MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 32%|███▏ | 2.18G/6.72G [00:50<01:42, 44.3MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 33%|███▎ | 2.19G/6.72G [00:50<01:33, 48.3MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 33%|███▎ | 2.21G/6.72G [00:51<01:25, 52.9MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 33%|███▎ | 2.22G/6.72G [00:51<01:21, 55.2MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 33%|███▎ | 2.24G/6.72G [00:51<01:20, 55.9MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 34%|███▎ | 2.26G/6.72G [00:51<01:16, 58.6MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 34%|███▍ | 2.27G/6.72G [00:52<01:27, 50.9MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 34%|███▍ | 2.29G/6.72G [00:52<01:24, 52.5MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 34%|███▍ | 2.30G/6.72G [00:52<01:16, 58.0MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 35%|███▍ | 2.32G/6.72G [00:53<01:35, 46.2MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 35%|███▍ | 2.34G/6.72G [00:53<01:42, 42.6MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 35%|███▍ | 2.35G/6.72G [00:53<01:33, 46.6MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 35%|███▌ | 2.37G/6.72G [00:54<01:38, 44.4MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 35%|███▌ | 2.38G/6.72G [00:54<01:43, 41.7MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 36%|███▌ | 2.40G/6.72G [00:55<01:38, 43.9MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 36%|███▌ | 2.42G/6.72G [00:55<01:40, 42.8MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 36%|███▌ | 2.43G/6.72G [00:55<01:27, 49.1MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 36%|███▋ | 2.45G/6.72G [00:56<01:22, 51.6MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 37%|███▋ | 2.46G/6.72G [00:56<01:23, 51.3MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 37%|███▋ | 2.48G/6.72G [00:56<01:18, 53.8MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 37%|███▋ | 2.50G/6.72G [00:57<01:28, 47.8MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 37%|███▋ | 2.51G/6.72G [00:57<01:21, 51.4MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 38%|███▊ | 2.53G/6.72G [00:57<01:20, 52.4MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 38%|███▊ | 2.54G/6.72G [00:57<01:13, 56.5MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 38%|███▊ | 2.56G/6.72G [00:58<01:12, 57.2MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 38%|███▊ | 2.58G/6.72G [00:58<01:05, 63.0MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 39%|███▊ | 2.59G/6.72G [00:58<01:03, 65.3MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 39%|███▉ | 2.61G/6.72G [00:58<00:59, 69.0MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 39%|███▉ | 2.62G/6.72G [00:58<01:00, 67.5MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 39%|███▉ | 2.64G/6.72G [00:59<01:02, 65.4MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 40%|███▉ | 2.66G/6.72G [00:59<01:03, 63.8MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 40%|███▉ | 2.67G/6.72G [00:59<01:06, 60.9MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 40%|███▉ | 2.69G/6.72G [00:59<01:02, 64.5MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 40%|████ | 2.70G/6.72G [01:00<01:27, 46.2MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 40%|████ | 2.72G/6.72G [01:00<01:26, 46.2MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 41%|████ | 2.74G/6.72G [01:01<01:17, 51.2MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 41%|████ | 2.75G/6.72G [01:01<01:11, 55.9MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 41%|████ | 2.77G/6.72G [01:01<01:05, 60.2MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 41%|████▏ | 2.78G/6.72G [01:01<01:06, 58.9MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 42%|████▏ | 2.80G/6.72G [01:02<01:06, 58.7MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 42%|████▏ | 2.82G/6.72G [01:02<01:07, 58.2MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 42%|████▏ | 2.83G/6.72G [01:02<01:05, 59.8MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 42%|████▏ | 2.85G/6.72G [01:02<01:02, 62.2MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 43%|████▎ | 2.86G/6.72G [01:03<00:54, 71.3MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 43%|████▎ | 2.88G/6.72G [01:03<00:57, 67.2MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 43%|████▎ | 2.90G/6.72G [01:03<00:59, 64.8MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 43%|████▎ | 2.91G/6.72G [01:04<01:14, 51.3MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 44%|████▎ | 2.93G/6.72G [01:04<01:22, 46.3MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 44%|████▍ | 2.94G/6.72G [01:04<01:17, 48.9MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 44%|████▍ | 2.96G/6.72G [01:05<01:13, 51.0MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 44%|████▍ | 2.98G/6.72G [01:05<01:07, 55.5MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 45%|████▍ | 2.99G/6.72G [01:05<01:06, 55.7MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 45%|████▍ | 3.01G/6.72G [01:05<01:01, 60.1MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 45%|████▍ | 3.02G/6.72G [01:06<01:10, 52.8MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 45%|████▌ | 3.04G/6.72G [01:06<01:10, 52.4MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 45%|████▌ | 3.06G/6.72G [01:06<01:03, 57.4MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 46%|████▌ | 3.07G/6.72G [01:06<01:04, 56.6MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 46%|████▌ | 3.09G/6.72G [01:07<01:01, 59.0MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 46%|████▌ | 3.10G/6.72G [01:07<01:00, 60.2MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 46%|████▋ | 3.12G/6.72G [01:07<01:14, 48.5MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 47%|████▋ | 3.14G/6.72G [01:08<01:06, 53.9MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 47%|████▋ | 3.15G/6.72G [01:08<01:01, 58.2MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 47%|████▋ | 3.17G/6.72G [01:08<01:03, 56.4MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 47%|████▋ | 3.18G/6.72G [01:09<01:04, 54.9MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 48%|████▊ | 3.20G/6.72G [01:09<01:02, 56.4MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 48%|████▊ | 3.22G/6.72G [01:09<01:03, 55.4MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 48%|████▊ | 3.23G/6.72G [01:09<00:59, 58.2MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 48%|████▊ | 3.25G/6.72G [01:10<00:59, 58.4MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 49%|████▊ | 3.26G/6.72G [01:10<00:54, 63.6MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 49%|████▉ | 3.28G/6.72G [01:10<00:58, 58.9MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 49%|████▉ | 3.30G/6.72G [01:10<00:56, 60.4MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 49%|████▉ | 3.31G/6.72G [01:11<00:59, 57.3MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 50%|████▉ | 3.33G/6.72G [01:11<00:54, 62.3MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 50%|████▉ | 3.34G/6.72G [01:11<00:52, 64.3MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 50%|████▉ | 3.36G/6.72G [01:12<01:02, 53.5MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 50%|█████ | 3.38G/6.72G [01:12<01:42, 32.7MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 50%|█████ | 3.39G/6.72G [01:13<01:33, 35.8MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 51%|█████ | 3.41G/6.72G [01:13<01:20, 41.3MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 51%|█████ | 3.42G/6.72G [01:13<01:11, 46.2MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 51%|█████ | 3.44G/6.72G [01:14<01:03, 51.4MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 51%|█████▏ | 3.46G/6.72G [01:14<01:01, 53.2MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 52%|█████▏ | 3.47G/6.72G [01:14<00:55, 58.8MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 52%|█████▏ | 3.49G/6.72G [01:14<00:53, 60.5MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 52%|█████▏ | 3.50G/6.72G [01:15<00:51, 62.3MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 52%|█████▏ | 3.52G/6.72G [01:15<00:51, 62.0MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 53%|█████▎ | 3.54G/6.72G [01:15<00:50, 62.5MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 53%|█████▎ | 3.55G/6.72G [01:15<00:51, 62.0MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 53%|█████▎ | 3.57G/6.72G [01:16<00:56, 56.3MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 53%|█████▎ | 3.58G/6.72G [01:16<00:57, 54.2MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 54%|█████▎ | 3.60G/6.72G [01:16<00:52, 59.7MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 54%|█████▍ | 3.62G/6.72G [01:16<00:50, 61.3MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 54%|█████▍ | 3.63G/6.72G [01:17<00:54, 57.1MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 54%|█████▍ | 3.65G/6.72G [01:17<00:48, 63.8MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 55%|█████▍ | 3.66G/6.72G [01:17<00:44, 69.4MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 55%|█████▍ | 3.68G/6.72G [01:17<00:49, 61.3MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 55%|█████▍ | 3.70G/6.72G [01:18<00:46, 64.6MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 55%|█████▌ | 3.71G/6.72G [01:18<00:45, 65.6MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 55%|█████▌ | 3.73G/6.72G [01:18<00:49, 60.0MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 56%|█████▌ | 3.74G/6.72G [01:18<00:50, 59.1MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 56%|█████▌ | 3.76G/6.72G [01:19<00:51, 57.9MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 56%|█████▌ | 3.78G/6.72G [01:19<00:53, 55.4MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 56%|█████▋ | 3.79G/6.72G [01:19<00:55, 53.1MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 57%|█████▋ | 3.81G/6.72G [01:20<00:49, 58.6MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 57%|█████▋ | 3.82G/6.72G [01:20<00:49, 59.1MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 57%|█████▋ | 3.84G/6.72G [01:20<00:49, 58.4MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 57%|█████▋ | 3.86G/6.72G [01:20<00:48, 58.7MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 58%|█████▊ | 3.87G/6.72G [01:21<00:48, 58.5MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 58%|█████▊ | 3.89G/6.72G [01:21<00:51, 55.6MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 58%|█████▊ | 3.90G/6.72G [01:22<01:01, 45.9MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 58%|█████▊ | 3.92G/6.72G [01:22<01:04, 43.7MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 59%|█████▊ | 3.94G/6.72G [01:22<01:01, 45.6MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 59%|█████▉ | 3.95G/6.72G [01:22<00:52, 53.2MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 59%|█████▉ | 3.97G/6.72G [01:23<00:49, 55.6MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 59%|█████▉ | 3.98G/6.72G [01:23<00:47, 58.3MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 60%|█████▉ | 4.00G/6.72G [01:23<00:46, 58.4MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 60%|█████▉ | 4.02G/6.72G [01:24<00:59, 45.1MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 60%|█████▉ | 4.03G/6.72G [01:24<00:58, 45.9MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 60%|██████ | 4.05G/6.72G [01:24<00:53, 50.1MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 60%|██████ | 4.06G/6.72G [01:25<00:56, 47.4MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 61%|██████ | 4.08G/6.72G [01:25<00:54, 48.3MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 61%|██████ | 4.10G/6.72G [01:25<00:51, 51.5MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 61%|██████ | 4.11G/6.72G [01:26<00:48, 53.4MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 61%|██████▏ | 4.13G/6.72G [01:26<00:45, 56.6MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 62%|██████▏ | 4.14G/6.72G [01:26<00:44, 57.6MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 62%|██████▏ | 4.16G/6.72G [01:26<00:44, 57.4MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 62%|██████▏ | 4.18G/6.72G [01:27<00:42, 60.2MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 62%|██████▏ | 4.19G/6.72G [01:27<00:44, 57.2MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 63%|██████▎ | 4.21G/6.72G [01:27<00:45, 55.5MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 63%|██████▎ | 4.22G/6.72G [01:28<01:31, 27.4MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 63%|██████▎ | 4.24G/6.72G [01:29<01:13, 33.9MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 63%|██████▎ | 4.26G/6.72G [01:29<01:05, 37.5MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 64%|██████▎ | 4.27G/6.72G [01:29<00:59, 41.2MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 64%|██████▍ | 4.29G/6.72G [01:30<00:54, 44.3MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 64%|██████▍ | 4.30G/6.72G [01:30<00:50, 47.7MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 64%|██████▍ | 4.32G/6.72G [01:30<00:46, 51.5MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 64%|██████▍ | 4.34G/6.72G [01:30<00:45, 52.6MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 65%|██████▍ | 4.35G/6.72G [01:31<00:43, 54.8MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 65%|██████▍ | 4.37G/6.72G [01:31<00:39, 59.0MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 65%|██████▌ | 4.38G/6.72G [01:31<00:38, 61.1MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 65%|██████▌ | 4.40G/6.72G [01:32<00:42, 54.5MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 66%|██████▌ | 4.42G/6.72G [01:32<00:42, 54.3MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 66%|██████▌ | 4.43G/6.72G [01:32<00:43, 53.2MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 66%|██████▌ | 4.45G/6.72G [01:33<00:55, 40.7MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 66%|██████▋ | 4.46G/6.72G [01:33<00:50, 44.5MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 67%|██████▋ | 4.48G/6.72G [01:33<00:49, 45.3MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 67%|██████▋ | 4.50G/6.72G [01:34<00:42, 52.5MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 67%|██████▋ | 4.51G/6.72G [01:34<00:39, 56.0MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 67%|██████▋ | 4.53G/6.72G [01:34<00:35, 61.5MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 68%|██████▊ | 4.54G/6.72G [01:34<00:35, 62.2MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 68%|██████▊ | 4.56G/6.72G [01:35<00:35, 60.8MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 68%|██████▊ | 4.58G/6.72G [01:35<00:38, 56.3MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 68%|██████▊ | 4.59G/6.72G [01:35<00:36, 58.6MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 69%|██████▊ | 4.61G/6.72G [01:35<00:37, 55.9MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 69%|██████▉ | 4.62G/6.72G [01:36<00:34, 60.0MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 69%|██████▉ | 4.64G/6.72G [01:36<00:39, 53.3MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 69%|██████▉ | 4.66G/6.72G [01:37<01:00, 34.2MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 69%|██████▉ | 4.67G/6.72G [01:37<01:00, 34.1MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 70%|██████▉ | 4.69G/6.72G [01:38<00:51, 39.3MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 70%|██████▉ | 4.70G/6.72G [01:38<00:45, 44.4MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 70%|███████ | 4.72G/6.72G [01:38<00:41, 48.2MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 70%|███████ | 4.74G/6.72G [01:38<00:38, 51.4MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 71%|███████ | 4.75G/6.72G [01:39<00:33, 58.3MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 71%|███████ | 4.77G/6.72G [01:39<00:32, 59.9MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 71%|███████ | 4.78G/6.72G [01:39<00:31, 60.6MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 71%|███████▏ | 4.80G/6.72G [01:39<00:31, 60.7MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 72%|███████▏ | 4.82G/6.72G [01:40<00:29, 63.8MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 72%|███████▏ | 4.83G/6.72G [01:40<00:33, 56.0MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 72%|███████▏ | 4.85G/6.72G [01:40<00:31, 59.7MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 72%|███████▏ | 4.86G/6.72G [01:40<00:30, 60.6MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 73%|███████▎ | 4.88G/6.72G [01:41<00:31, 57.9MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 73%|███████▎ | 4.90G/6.72G [01:41<00:33, 54.7MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 73%|███████▎ | 4.91G/6.72G [01:41<00:31, 58.4MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 73%|███████▎ | 4.93G/6.72G [01:41<00:28, 62.5MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 74%|███████▎ | 4.94G/6.72G [01:42<00:28, 61.7MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 74%|███████▍ | 4.96G/6.72G [01:42<00:27, 63.0MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 74%|███████▍ | 4.98G/6.72G [01:42<00:27, 63.4MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 74%|███████▍ | 4.99G/6.72G [01:42<00:26, 65.2MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 74%|███████▍ | 5.01G/6.72G [01:43<00:26, 64.5MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 75%|███████▍ | 5.02G/6.72G [01:43<00:24, 68.0MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 75%|███████▍ | 5.04G/6.72G [01:43<00:28, 59.7MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 75%|███████▌ | 5.06G/6.72G [01:44<00:30, 53.8MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 75%|███████▌ | 5.07G/6.72G [01:44<00:29, 55.1MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 76%|███████▌ | 5.09G/6.72G [01:44<00:30, 54.0MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 76%|███████▌ | 5.10G/6.72G [01:44<00:27, 58.3MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 76%|███████▌ | 5.12G/6.72G [01:45<00:27, 57.8MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 76%|███████▋ | 5.14G/6.72G [01:45<00:29, 54.3MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 77%|███████▋ | 5.15G/6.72G [01:45<00:27, 57.5MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 77%|███████▋ | 5.17G/6.72G [01:46<00:27, 56.2MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 77%|███████▋ | 5.18G/6.72G [01:46<00:30, 50.5MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 77%|███████▋ | 5.20G/6.72G [01:46<00:28, 52.8MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 78%|███████▊ | 5.22G/6.72G [01:46<00:25, 59.0MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 78%|███████▊ | 5.23G/6.72G [01:47<00:25, 58.9MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 78%|███████▊ | 5.25G/6.72G [01:47<00:25, 57.6MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 78%|███████▊ | 5.26G/6.72G [01:47<00:24, 60.7MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 79%|███████▊ | 5.28G/6.72G [01:48<00:23, 60.4MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 79%|███████▉ | 5.30G/6.72G [01:48<00:27, 51.2MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 79%|███████▉ | 5.31G/6.72G [01:48<00:25, 54.8MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 79%|███████▉ | 5.33G/6.72G [01:49<00:25, 54.2MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 79%|███████▉ | 5.34G/6.72G [01:49<00:24, 57.2MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 80%|███████▉ | 5.36G/6.72G [01:49<00:23, 57.9MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 80%|███████▉ | 5.38G/6.72G [01:49<00:21, 61.5MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 80%|████████ | 5.39G/6.72G [01:50<00:21, 61.9MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 80%|████████ | 5.41G/6.72G [01:50<00:21, 62.6MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 81%|████████ | 5.42G/6.72G [01:50<00:17, 73.1MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 81%|████████ | 5.43G/6.72G [01:50<00:18, 68.3MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 81%|████████ | 5.44G/6.72G [01:50<00:22, 57.1MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 81%|████████ | 5.46G/6.72G [01:51<00:21, 58.6MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 81%|████████▏ | 5.47G/6.72G [01:51<00:22, 55.7MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 82%|████████▏ | 5.49G/6.72G [01:51<00:24, 50.9MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 82%|████████▏ | 5.50G/6.72G [01:51<00:22, 53.5MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 82%|████████▏ | 5.52G/6.72G [01:52<00:20, 58.0MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 82%|████████▏ | 5.54G/6.72G [01:52<00:20, 58.0MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 83%|████████▎ | 5.55G/6.72G [01:52<00:22, 51.8MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 83%|████████▎ | 5.57G/6.72G [01:53<00:20, 55.5MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 83%|████████▎ | 5.58G/6.72G [01:53<00:20, 54.9MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 83%|████████▎ | 5.60G/6.72G [01:53<00:18, 59.6MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 84%|████████▎ | 5.62G/6.72G [01:54<00:22, 50.1MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 84%|████████▍ | 5.63G/6.72G [01:54<00:20, 52.7MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 84%|████████▍ | 5.65G/6.72G [01:54<00:21, 51.1MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 84%|████████▍ | 5.66G/6.72G [01:54<00:21, 50.4MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 84%|████████▍ | 5.68G/6.72G [01:55<00:19, 54.7MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 85%|████████▍ | 5.70G/6.72G [01:55<00:19, 53.8MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 85%|████████▍ | 5.71G/6.72G [01:55<00:17, 58.1MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 85%|████████▌ | 5.73G/6.72G [01:55<00:15, 62.3MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 85%|████████▌ | 5.74G/6.72G [01:56<00:17, 56.9MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 86%|████████▌ | 5.76G/6.72G [01:56<00:16, 57.0MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 86%|████████▌ | 5.78G/6.72G [01:56<00:15, 59.6MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 86%|████████▌ | 5.79G/6.72G [01:57<00:17, 52.3MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 86%|████████▋ | 5.81G/6.72G [01:57<00:16, 55.0MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 87%|████████▋ | 5.82G/6.72G [01:57<00:17, 52.1MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 87%|████████▋ | 5.84G/6.72G [01:58<00:23, 37.7MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 87%|████████▋ | 5.86G/6.72G [01:59<00:24, 35.5MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 87%|████████▋ | 5.87G/6.72G [01:59<00:20, 40.7MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 88%|████████▊ | 5.89G/6.72G [01:59<00:17, 46.5MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 88%|████████▊ | 5.90G/6.72G [01:59<00:16, 50.6MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 88%|████████▊ | 5.92G/6.72G [02:00<00:15, 53.2MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 88%|████████▊ | 5.94G/6.72G [02:00<00:14, 54.2MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 89%|████████▊ | 5.95G/6.72G [02:00<00:13, 56.1MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 89%|████████▉ | 5.97G/6.72G [02:00<00:13, 54.5MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 89%|████████▉ | 5.98G/6.72G [02:01<00:14, 52.6MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 89%|████████▉ | 6.00G/6.72G [02:01<00:13, 55.2MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 89%|████████▉ | 6.02G/6.72G [02:01<00:11, 59.9MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 90%|████████▉ | 6.03G/6.72G [02:01<00:11, 59.9MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 90%|████████▉ | 6.05G/6.72G [02:02<00:11, 60.9MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 90%|█████████ | 6.06G/6.72G [02:02<00:11, 55.6MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 90%|█████████ | 6.08G/6.72G [02:02<00:11, 55.6MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 91%|█████████ | 6.10G/6.72G [02:03<00:10, 58.9MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 91%|█████████ | 6.11G/6.72G [02:03<00:11, 52.1MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 91%|█████████ | 6.13G/6.72G [02:03<00:11, 53.7MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 91%|█████████▏| 6.14G/6.72G [02:04<00:10, 55.0MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 92%|█████████▏| 6.16G/6.72G [02:04<00:09, 59.0MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 92%|█████████▏| 6.18G/6.72G [02:04<00:09, 59.3MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 92%|█████████▏| 6.19G/6.72G [02:04<00:08, 61.8MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 92%|█████████▏| 6.21G/6.72G [02:05<00:08, 60.3MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 93%|█████████▎| 6.22G/6.72G [02:05<00:08, 59.2MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 93%|█████████▎| 6.24G/6.72G [02:05<00:08, 57.9MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 93%|█████████▎| 6.26G/6.72G [02:05<00:08, 57.0MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 93%|█████████▎| 6.27G/6.72G [02:06<00:07, 58.7MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 94%|█████████▎| 6.29G/6.72G [02:06<00:08, 49.8MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 94%|█████████▍| 6.30G/6.72G [02:06<00:07, 54.5MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 94%|█████████▍| 6.32G/6.72G [02:07<00:07, 56.6MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 94%|█████████▍| 6.34G/6.72G [02:07<00:07, 48.7MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 94%|█████████▍| 6.35G/6.72G [02:07<00:07, 52.2MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 95%|█████████▍| 6.37G/6.72G [02:08<00:06, 52.2MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 95%|█████████▍| 6.38G/6.72G [02:08<00:05, 56.9MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 95%|█████████▌| 6.40G/6.72G [02:08<00:05, 55.4MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 95%|█████████▌| 6.42G/6.72G [02:08<00:05, 53.6MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 96%|█████████▌| 6.43G/6.72G [02:09<00:05, 56.4MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 96%|█████████▌| 6.45G/6.72G [02:09<00:07, 37.9MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 96%|█████████▌| 6.46G/6.72G [02:10<00:08, 31.0MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 96%|█████████▋| 6.48G/6.72G [02:10<00:06, 36.9MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 97%|█████████▋| 6.50G/6.72G [02:11<00:05, 42.7MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 97%|█████████▋| 6.51G/6.72G [02:11<00:04, 48.9MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 97%|█████████▋| 6.53G/6.72G [02:11<00:03, 49.3MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 97%|█████████▋| 6.54G/6.72G [02:12<00:03, 47.8MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 98%|█████████▊| 6.56G/6.72G [02:12<00:02, 54.8MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 98%|█████████▊| 6.58G/6.72G [02:12<00:02, 57.1MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 98%|█████████▊| 6.59G/6.72G [02:12<00:02, 57.2MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 98%|█████████▊| 6.61G/6.72G [02:13<00:02, 51.8MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 99%|█████████▊| 6.62G/6.72G [02:13<00:01, 54.4MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 99%|█████████▉| 6.64G/6.72G [02:13<00:01, 47.9MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 99%|█████████▉| 6.66G/6.72G [02:14<00:01, 45.2MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 99%|█████████▉| 6.67G/6.72G [02:14<00:01, 49.4MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 99%|█████████▉| 6.69G/6.72G [02:14<00:00, 50.0MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 100%|█████████▉| 6.70G/6.72G [02:15<00:00, 50.5MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 100%|█████████▉| 6.72G/6.72G [02:15<00:00, 53.9MB/s]
ip-26-0-160-192_925006.1719945618152196843.pt.trace.json: 100%|██████████| 6.72G/6.72G [02:15<00:00, 49.6MB/s]
|