Hi there,
am just starting with pytorch, but have you tried using the flag: torch.backends.cudnn.benchmark=True. It should help (if you have a static architecture).
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Hi there,
am just starting with pytorch, but have you tried using the flag: torch.backends.cudnn.benchmark=True. It should help (if you have a static architecture).