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Fixing GPU for token-classification in a better way. #13856
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LysandreJik
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huggingface:master
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Narsil:fix_gpu_token_classification
Oct 6, 2021
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I'm not as familiar as you with the pipeline but will the
model_outputs["outputs"]
can still be on GPU ?Maybe all preprocessing is firstly casted to CPU but I would rather double check.
Else should we use
model_outputs["outputs"].cpu().numpy()
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Hi @ierezell,
Just like this file does not ever mention
.to(device)
it shouldn't mention.cpu()
as it's not the task of the pipeline to encapsulate that logic. Before it was done this way meaning many pipelines wouldn't actually support some features.The logic is now in the
Pipeline.forward
method.Rougly:
preprocess
: (generic python objects) -> Tensors_forward
: Tensors -> Tensorspostprocess
: Tensors -> Generic python objectsforward
encapsulate classic logic for inference (inference mode, GPU tensor moving and other if needed, like batching)There was a problem hiding this comment.
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Ok, then everything will be at the good place at the good moment so that's perfect! Thanks for the clarification.