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When we try to fine-tune a model that doesn't fit in the memory as per the configured parameter, trainer currently tries to find appropriate batch size. If it is not able to find appropriate batch size it will error out with following error:
-- Process 0 terminated with the following error:
2023-10-24T19:16:50.309027 [torch:ERRR] Traceback (most recent call last):
2023-10-24T19:16:50.309027 [torch:ERRR] File "/u/joeolson/.conda/envs/tuning/lib/python3.9/site-packages/torch/multiprocessing/spawn.py", line 69, in _wrap
2023-10-24T19:16:50.309027 [torch:ERRR] fn(i, *args)
2023-10-24T19:16:50.309027 [torch:ERRR] File "/u/joeolson/.conda/envs/tuning/lib/python3.9/site-packages/torch/distributed/elastic/multiprocessing/api.py", line 370, in _wrap
2023-10-24T19:16:50.309027 [torch:ERRR] ret = record(fn)(*args_)
2023-10-24T19:16:50.309027 [torch:ERRR] File "/u/joeolson/.conda/envs/tuning/lib/python3.9/site-packages/torch/distributed/elastic/multiprocessing/errors/__init__.py", line 346, in wrapper
2023-10-24T19:16:50.309027 [torch:ERRR] return f(*args, **kwargs)
2023-10-24T19:16:50.309027 [torch:ERRR] File "/u/joeolson/git/caikit-nlp2/examples/../caikit_nlp/modules/text_generation/text_generation_local.py", line 617, in _launch_training
2023-10-24T19:16:50.309027 [torch:ERRR] trainer.train()
2023-10-24T19:16:50.309027 [torch:ERRR] File "/u/joeolson/.conda/envs/tuning/lib/python3.9/site-packages/transformers/trainer.py", line 1591, in train
2023-10-24T19:16:50.309027 [torch:ERRR] return inner_training_loop(
2023-10-24T19:16:50.309027 [torch:ERRR] File "/u/joeolson/.conda/envs/tuning/lib/python3.9/site-packages/accelerate/utils/memory.py", line 134, in decorator
2023-10-24T19:16:50.309027 [torch:ERRR] raise RuntimeError("No executable batch size found, reached zero.")
2023-10-24T19:16:50.309027 [torch:ERRR] RuntimeError: No executable batch size found, reached zero.
We can use this error to throw OOM to better let user know of the issue.
The text was updated successfully, but these errors were encountered:
Description
When we try to fine-tune a model that doesn't fit in the memory as per the configured parameter, trainer currently tries to find appropriate batch size. If it is not able to find appropriate batch size it will error out with following error:
We can use this error to throw OOM to better let user know of the issue.
The text was updated successfully, but these errors were encountered: