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abhishekkrthakur avatar abhishekkrthakur commented on July 1, 2024

did you use data parallel to train the model?

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vijender412 avatar vijender412 commented on July 1, 2024

@abhishekkrthakur Yes used data parallel while training

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abhishekkrthakur avatar abhishekkrthakur commented on July 1, 2024

does your bert_base_path has bert base uncased model files?

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vijender412 avatar vijender412 commented on July 1, 2024

@abhishekkrthakur Fixed the issue was with data parallel. I local i was not making use of "MODEL = nn.DataParallel(MODEL)". Now working with this. Can you help me understand the use of DataParallel and if it does require after training also?
Thanks for quick replying. Good to close the issue

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abhishekkrthakur avatar abhishekkrthakur commented on July 1, 2024

DataParallel is used only when you have multiple GPUs during training.
If you used it in training, you have to use in inference but there are other ways too.

Closing this issue for now. :)

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nipunsadvilkar avatar nipunsadvilkar commented on July 1, 2024

@abhishekkrthakur : Can you give any leads on how to load DataParallel GPU model on CPU?
As per pytorch docs tried following but still raises above RuntimeError

device = torch.device('cpu')
model = TheModelClass(*args, **kwargs)
model.load_state_dict(torch.load(PATH, map_location=device))

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