Environment info
transformers version: 4.0.0-rc-1- Platform: Linux-4.9.0-14-amd64-x86_64-with-debian-9.13
- Python version: 3.6.10
- PyTorch version (GPU?): 1.8.0a0+4ed7f36 (False)
- Tensorflow version (GPU?): not installed (NA)
- Using GPU in script?: No
- Using distributed or parallel set-up in script?: 8-core TPU training
- Using TPU
Who can help
albert, bert, GPT2, XLM: @LysandreJik
Information
Model I am using (Bert, XLNet ...): bert and roberta
The problem arises when using:
The tasks I am working on is:
To reproduce
Steps to reproduce the behavior:
2 examples of failing commands:
E 2020-11-18T17:38:08.657584093Z python examples/xla_spawn.py \
E 2020-11-18T17:38:08.657588780Z --num_cores 8 \
E 2020-11-18T17:38:08.657593609Z examples/contrib/legacy/run_language_modeling.py \
E 2020-11-18T17:38:08.657598646Z --logging_dir ./tensorboard-metrics \
E 2020-11-18T17:38:08.657604088Z --cache_dir ./cache_dir \
E 2020-11-18T17:38:08.657609492Z --train_data_file /datasets/wikitext-103-raw/wiki.train.raw \
E 2020-11-18T17:38:08.657614614Z --do_train \
E 2020-11-18T17:38:08.657619772Z --do_eval \
E 2020-11-18T17:38:08.657624531Z --eval_data_file /datasets/wikitext-103-raw/wiki.valid.raw \
E 2020-11-18T17:38:08.657629731Z --overwrite_output_dir \
E 2020-11-18T17:38:08.657641827Z --output_dir language-modeling \
E 2020-11-18T17:38:08.657647203Z --logging_steps 100 \
E 2020-11-18T17:38:08.657651823Z --save_steps 3000 \
E 2020-11-18T17:38:08.657656739Z --overwrite_cache \
E 2020-11-18T17:38:08.657661282Z --tpu_metrics_debug \
E 2020-11-18T17:38:08.657667598Z --mlm --model_type=bert \
E 2020-11-18T17:38:08.657672545Z --model_name_or_path bert-base-cased \
E 2020-11-18T17:38:08.657677441Z --num_train_epochs 3 \
E 2020-11-18T17:38:08.657682320Z --per_device_train_batch_size 16 \
E 2020-11-18T17:38:08.657687053Z --per_device_eval_batch_size 16
2020-11-18T17:51:49.357234955Z Traceback (most recent call last):
E
2020-11-18T17:51:49.357239554Z File "/root/anaconda3/envs/pytorch/lib/python3.6/site-packages/torch_xla/distributed/xla_multiprocessing.py", line 329, in _mp_start_fn
E
2020-11-18T17:51:49.357245350Z _start_fn(index, pf_cfg, fn, args)
E
2020-11-18T17:51:49.357249851Z File "/root/anaconda3/envs/pytorch/lib/python3.6/site-packages/torch_xla/distributed/xla_multiprocessing.py", line 323, in _start_fn
E
2020-11-18T17:51:49.357254654Z fn(gindex, *args)
E
2020-11-18T17:51:49.357272443Z File "/transformers/examples/contrib/legacy/run_language_modeling.py", line 359, in _mp_fn
E
2020-11-18T17:51:49.357277658Z main()
E
2020-11-18T17:51:49.357281928Z File "/transformers/examples/contrib/legacy/run_language_modeling.py", line 279, in main
E
2020-11-18T17:51:49.357287863Z data_args.block_size = tokenizer.max_len
E
2020-11-18T17:51:49.357292355Z AttributeError: 'BertTokenizerFast' object has no attribute 'max_len'
E
E 2020-11-18T06:47:53.910306819Z python examples/xla_spawn.py \
E 2020-11-18T06:47:53.910310176Z --num_cores 8 \
E 2020-11-18T06:47:53.910314263Z examples/contrib/legacy/run_language_modeling.py \
E 2020-11-18T06:47:53.910319173Z --logging_dir ./tensorboard-metrics \
E 2020-11-18T06:47:53.910322683Z --cache_dir ./cache_dir \
E 2020-11-18T06:47:53.910325895Z --train_data_file /datasets/wikitext-103-raw/wiki.train.raw \
E 2020-11-18T06:47:53.910329170Z --do_train \
E 2020-11-18T06:47:53.910332491Z --do_eval \
E 2020-11-18T06:47:53.910335626Z --eval_data_file /datasets/wikitext-103-raw/wiki.valid.raw \
E 2020-11-18T06:47:53.910340314Z --overwrite_output_dir \
E 2020-11-18T06:47:53.910343710Z --output_dir language-modeling \
E 2020-11-18T06:47:53.910347004Z --logging_steps 100 \
E 2020-11-18T06:47:53.910350089Z --save_steps 3000 \
E 2020-11-18T06:47:53.910353259Z --overwrite_cache \
E 2020-11-18T06:47:53.910356297Z --tpu_metrics_debug \
E 2020-11-18T06:47:53.910359351Z --mlm --model_type=roberta \
E 2020-11-18T06:47:53.910362484Z --tokenizer=roberta-base \
E 2020-11-18T06:47:53.910365650Z --num_train_epochs 5 \
E 2020-11-18T06:47:53.910368797Z --per_device_train_batch_size 8 \
E 2020-11-18T06:47:53.910371843Z --per_device_eval_batch_size 8
2020-11-18T06:48:27.357394365Z Traceback (most recent call last):
E
2020-11-18T06:48:27.357399685Z File "/root/anaconda3/envs/pytorch/lib/python3.6/site-packages/torch_xla/distributed/xla_multiprocessing.py", line 329, in _mp_start_fn
E
2020-11-18T06:48:27.357405353Z _start_fn(index, pf_cfg, fn, args)
E
2020-11-18T06:48:27.357426600Z File "/root/anaconda3/envs/pytorch/lib/python3.6/site-packages/torch_xla/distributed/xla_multiprocessing.py", line 323, in _start_fn
E
2020-11-18T06:48:27.357448514Z fn(gindex, *args)
E
2020-11-18T06:48:27.357454250Z File "/transformers/examples/contrib/legacy/run_language_modeling.py", line 359, in _mp_fn
E
2020-11-18T06:48:27.357460262Z main()
E
2020-11-18T06:48:27.357465843Z File "/transformers/examples/contrib/legacy/run_language_modeling.py", line 279, in main
E
2020-11-18T06:48:27.357471227Z data_args.block_size = tokenizer.max_len
E
2020-11-18T06:48:27.357477576Z AttributeError: 'RobertaTokenizerFast' object has no attribute 'max_len'
E
The timing of this issue lines up with #8586
Tests started failing on the evening of Nov 17, a few hours after that PR was submitted
Environment info
transformersversion: 4.0.0-rc-1Who can help
albert, bert, GPT2, XLM: @LysandreJik
Information
Model I am using (Bert, XLNet ...): bert and roberta
The problem arises when using:
The tasks I am working on is:
To reproduce
Steps to reproduce the behavior:
2 examples of failing commands:
The timing of this issue lines up with #8586
Tests started failing on the evening of Nov 17, a few hours after that PR was submitted