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chore: import upstream snapshot with attribution
2026-07-13 12:55:37 +08:00

40 lines
1.5 KiB
C++

// Provides torch::Tensor for ops.h (previously included transitively via
// cache.h, which is no longer included here after cache ops moved to
// _C_stable_libtorch).
#include <torch/all.h>
#include "ops.h"
#include "core/registration.h"
#include <torch/library.h>
#include <torch/version.h>
// Note on op signatures:
// The X_meta signatures are for the meta functions corresponding to op X.
// They must be kept in sync with the signature for X. Generally, only
// functions that return Tensors require a meta function.
//
// See the following links for detailed docs on op registration and function
// schemas.
// https://docs.google.com/document/d/1_W62p8WJOQQUzPsJYa7s701JXt0qf2OfLub2sbkHOaU/edit#heading=h.ptttacy8y1u9
// https://github.com/pytorch/pytorch/blob/main/aten/src/ATen/native/README.md#annotations
#ifdef USE_ROCM
TORCH_LIBRARY_FRAGMENT(CONCAT(TORCH_EXTENSION_NAME, _custom_ar), custom_ar) {
// Quick Reduce all-reduce kernels (ROCm-only; stays on legacy _C).
custom_ar.def(
"qr_all_reduce(int fa, Tensor inp, Tensor out, int quant_level, bool "
"cast_bf2half) -> ()");
custom_ar.impl("qr_all_reduce", torch::kCUDA, &qr_all_reduce);
custom_ar.def("init_custom_qr", &init_custom_qr);
custom_ar.def("qr_destroy", &qr_destroy);
custom_ar.def("qr_get_handle", &qr_get_handle);
custom_ar.def("qr_open_handles(int _fa, Tensor[](b!) handles) -> ()");
custom_ar.impl("qr_open_handles", torch::kCPU, &qr_open_handles);
custom_ar.def("qr_max_size", &qr_max_size);
}
#endif
REGISTER_EXTENSION(TORCH_EXTENSION_NAME)