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Pytorch 2.0 has been released, and promises backwards compatibility, and many performance enhancements.
As an example of the performance enhancements, an option to compile models is now available, resulting in a ~50% speed-up on huggingface models on an A100, and slightly less on non-server-class GPUs, with minimal code. The speed-ups are even large for AMP precision compared to float32.
Seems like simply doing:
compiled_model = torch.compile(model)
will lead to this speed-up.
The text was updated successfully, but these errors were encountered:
Pytorch 2.0 has been released, and promises backwards compatibility, and many performance enhancements.
As an example of the performance enhancements, an option to compile models is now available, resulting in a ~50% speed-up on huggingface models on an A100, and slightly less on non-server-class GPUs, with minimal code. The speed-ups are even large for AMP precision compared to float32.
Seems like simply doing:
will lead to this speed-up.
The text was updated successfully, but these errors were encountered: