Parameter missing from state_dict of optimizer when loading from checkpoint

Environment info

• transformers version: '4.2.0dev0'
• Platform: Debian
• Python version: Python 3.6.10 |Anaconda, Inc.| (default, May 8 2020, 02:54:21)
• PyTorch version (GPU?): torch-xla-1.6
• Tensorflow version (GPU?):
• Using GPU in script?: No
• Using distributed or parallel set-up in script?: Yes
• Using TPUs

Who can help

@sgugger

Information

Model I am using (Bert, XLNet …):

The problem arises when using:

• [ X] the official example scripts: (give details below)
• [ X] my own modified scripts: (give details below)

The tasks I am working on is:

• MLM

To reproduce

You need to load a model from a checkpoint saved on the TPU.

Steps to reproduce the behavior:

1. Run run_mlm.py on any dataset and store a checkpoint. Then load from that checkpoint using the following command.
2. python transformers/examples/language-modeling/run_mlm.py --warmup_steps 10000 --learning_rate 1e-4 --save_steps 100000 --max_seq_length 512 --logging_steps 50 --overwrite_output_dir --model_name_or_path ../../bucket/model_outputs/en/inverted_order_500K/mlm/checkpoint-10000 --do_train --do_eval --max_steps 500000 --per_device_train_batch_size 16 --per_device_eval_batch_size 16 --train_file ../../bucket/pretrain_data/en/valid.txt --validation_file ../../bucket/pretrain_data/en/valid.txt --output_dir ../../bucket/model_outputs/en/inverted_order_500K/mlm
3. OR, use this nohup python transformers/examples/xla_spawn.py --num_cores 8 transformers/examples/language-modeling/run_mlm.py --warmup_steps 10000 --learning_rate 1e-4 --save_steps 100000 --max_seq_length 512 --logging_steps 50 --overwrite_output_dir --model_name_or_path ../../bucket/model_outputs/en/inverted_order_500K/mlm/checkpoint-10000 --do_train --do_eval --max_steps 500000 --per_device_train_batch_size 16 --per_device_eval_batch_size 16 --train_file ../../bucket/pretrain_data/en/valid.txt --validation_file ../../bucket/pretrain_data/en/valid.txt --output_dir ../../bucket/model_outputs/en/inverted_order_500K/mlm

Error trace

This error trace uses a modified Trainer, but the issue occurs with the original Trainer as well.

Traceback (most recent call last): File “transformers/examples/xla_spawn.py”, line 85, in <module> main() File “transformers/examples/xla_spawn.py”, line 81, in main xmp.spawn(mod._mp_fn, args=(), nprocs=args.num_cores) File “/anaconda3/envs/torch-xla-1.6/lib/python3.6/site-packages/torch_xla/distributed/xla_multiprocessing.py”, line 292, in spawn _start_fn(0, pf_cfg, fn, args) File “/anaconda3/envs/torch-xla-1.6/lib/python3.6/site-packages/torch_xla/distributed/xla_multiprocessing.py”, line 229, in _start_fn fn(gindex, *args) File “/home/asd/source_code/Multilingual/transformers/examples/language-modeling/run_mlm_synthetic.py”, line 486, in _mp_fn main() File “/home/asd/source_code/Multilingual/transformers/examples/language-modeling/run_mlm_synthetic.py”, line 460, in main trainer.train(model_path=model_path) File “/home/asd/source_code/Multilingual/transformers/src/transformers/trainer_word_modifications.py”, line 666, in train self._load_optimizer_and_scheduler(model_path) File “/home/asd/source_code/Multilingual/transformers/src/transformers/trainer_word_modifications.py”, line 1003, in _load_optimizer_and_scheduler self.optimizer.load_state_dict(optimizer_state) File “/anaconda3/envs/torch-xla-1.6/lib/python3.6/site-packages/torch/optim/optimizer.py”, line 123, in load_state_dict raise ValueError("loaded state dict contains a parameter group " ValueError: loaded state dict contains a parameter group that doesn’t match the size of optimizer’s group

Where is the issue?

I’ve isolated the issue to be a missing parameter in optimizer_state['state']. For some reason, index 136 is missing from optimizer_state['state'].keys()

The following is the debugger output in function _load_optimizer_and_scheduler and just before line self.optimizer.load_state_dict(optimizer_state) in block if is_torch_tpu_available().

>>> optimizer_state['param_groups']
[{'weight_decay': 0.0, 'lr': 0.0001, 'betas': [0.9, 0.999], 'eps': 1e-08, 'correct_bias': True, 'initial_lr': 0.0001, 'params': [0, 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]}, {'weight_decay': 0.0, 'lr': 0.0001, 'betas': [0.9, 0.999], 'eps': 1e-08, 'correct_bias': True, 'initial_lr': 0.0001, 'params': [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]}]
>>> optimizer_state['state'].keys()
dict_keys([0, 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, 137, 138, 139])

Expected behavior

Load the checkpoint correctly.

[ameet-1997]

Looks like you already found the solution, thanks for that! I wasn’t able to fix it earlier.

[finiteautomata]

I’m facing the same problem with 4.10.0.dev0. @ameet-1997 could you find a solution for this?