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soumith avatar soumith commented on July 30, 2024

checking with @gchanan and @yf225 , is this fine to do?

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yf225 avatar yf225 commented on July 30, 2024

Yes we should use torch:: in the cpp and cuda modules as we are deprecating the at:: namespace in the public API. @ClementPinard We would love to have PR contribution on it. Thanks!

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gchanan avatar gchanan commented on July 30, 2024

which cpu and cuda modules are you talking about?

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ClementPinard avatar ClementPinard commented on July 30, 2024

https://github.com/pytorch/extension-cpp/tree/master/cpp
https://github.com/pytorch/extension-cpp/tree/master/cuda

Also, I would like to make this example more up to date in general to help people develop cuda modules easily.
More specificly, I'd like to solve the fmax issue that seems to bother many people since the beginning, and seems to be solvable by a scalar_t cast. (see #27 , this does not seem to be an environment error).

Besides, as suggested #12 , I'd like to add usage of .packed_accessor in the cuda kernel.

Finally, I'd like to update the tutorial code here to reflect those changes, along maybe a mention to packed_accessor in the tensor basics doc here

How does that sound to you ? Unfortunately, i'm stuck at the moment because of #27 but hopefully I'll find a solution or a working setup where the code compiles.

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