Looks like one of the first failures seen is `test_causal_variants_compile_causal_variant_CausalVariant_LOWER_RIGHT_shape0_cuda` when `test_causal_variants_causal_variant_CausalVariant_LOWER_RIGHT_shape0_cuda` passes.
What seems interesting here is that the `torch.compile` version fails while the eager version passes. Not sure what the difference would be here...
Nevertheless, is there a recommended mechanism to skip cuDNN SDPA as a backend for this test? CC @drisspg
Pull Request resolved: https://github.com/pytorch/pytorch/pull/125343
Approved by: https://github.com/Skylion007
Looks like one of the first failures seen is `test_causal_variants_compile_causal_variant_CausalVariant_LOWER_RIGHT_shape0_cuda` when `test_causal_variants_causal_variant_CausalVariant_LOWER_RIGHT_shape0_cuda` passes.
What seems interesting here is that the `torch.compile` version fails while the eager version passes. Not sure what the difference would be here...
Nevertheless, is there a recommended mechanism to skip cuDNN SDPA as a backend for this test? CC @drisspg
Pull Request resolved: https://github.com/pytorch/pytorch/pull/125343
Approved by: https://github.com/Skylion007
Summary: When looking up for what backend call to use for a fallback op (see get_backend_index_for_aoti), sometimes we need to search for a NativeFunction's structured delegate. Previous str:NativeFunctionsGroup dict missed some cases, such as aten.index.Tensor, and that's why aten.index.Tensor was specified in the fallback_ops list but no C shim entry was generated for it. This PR uses a more robust OperatorName:NativeFunctionsGroup mapping.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/125962
Approved by: https://github.com/chenyang78
Summary: The current C shim layer manually implements a C interface for a handful of ops. Obviously that's not scalable if we want to extend it to cover all aten ops. This new torchgen script automatically generates C shim interfaces for CPU and CUDA backends. The interface follows the same parameter passing rules as the current C shim layer, such as
* Use plain C data types to pass parameters
* Use AtenTensorHandle to pass at::Tensor
* Use pointer type to pass optional parameter
* Use pointer+length to pass list
* Use device_type+device_index to pass device
* When a parameter is a pointer of pointer, e.g. AtenTensorHandle**, the script generates either a list of optional values or an optional list of values
https://gist.github.com/desertfire/83701532b126c6d34dae6ba68a1b074a is an example of the generated torch/csrc/inductor/aoti_torch/generated/c_shim_cuda.cpp file. The current version doesn't generate C shim wrappers for all aten ops, and probably generates more wrappers than needed on the other hand, but it should serve as a good basis.
This PR by itself won't change AOTI codegen and thus won't introduce any FC breakage. The actual wrapper codegen changes will come in another PR with some version control flag to avoid FC breakage.
Differential Revision: [D54258087](https://our.internmc.facebook.com/intern/diff/D54258087)
Pull Request resolved: https://github.com/pytorch/pytorch/pull/120513
Approved by: https://github.com/jansel
