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https://github.com/pytorch/pytorch.git
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9a883007a2
This reverts commit c7515da7b00de40942c83dc5856b6daec727e280. Reverted https://github.com/pytorch/pytorch/pull/140979 on behalf of https://github.com/huydhn due to This change has been reported to break internal code ([comment](https://github.com/pytorch/pytorch/pull/140979#issuecomment-2657361940))
126 lines
3.3 KiB
C++
126 lines
3.3 KiB
C++
#include <cuda.h>
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#include <cuda_runtime.h>
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#include <torch/csrc/utils/pybind.h>
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#if !defined(USE_ROCM)
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#include <cuda_profiler_api.h>
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#else
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#include <hip/hip_runtime_api.h>
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#endif
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#include <c10/cuda/CUDAException.h>
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#include <c10/cuda/CUDAGuard.h>
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namespace torch::cuda::shared {
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#ifdef USE_ROCM
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namespace {
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hipError_t hipReturnSuccess() {
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return hipSuccess;
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}
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} // namespace
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#endif
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void initCudartBindings(PyObject* module) {
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auto m = py::handle(module).cast<py::module>();
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auto cudart = m.def_submodule("_cudart", "libcudart.so bindings");
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// By splitting the names of these objects into two literals we prevent the
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// HIP rewrite rules from changing these names when building with HIP.
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#if !defined(USE_ROCM) && defined(CUDA_VERSION) && CUDA_VERSION < 12000
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// cudaOutputMode_t is used in cudaProfilerInitialize only. The latter is gone
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// in CUDA 12.
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py::enum_<cudaOutputMode_t>(
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cudart,
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"cuda"
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"OutputMode")
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.value("KeyValuePair", cudaKeyValuePair)
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.value("CSV", cudaCSV);
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#endif
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py::enum_<cudaError_t>(
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cudart,
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"cuda"
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"Error")
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.value("success", cudaSuccess);
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cudart.def(
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"cuda"
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"GetErrorString",
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cudaGetErrorString);
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cudart.def(
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"cuda"
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"ProfilerStart",
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#ifdef USE_ROCM
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hipReturnSuccess
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#else
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cudaProfilerStart
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#endif
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);
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cudart.def(
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"cuda"
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"ProfilerStop",
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#ifdef USE_ROCM
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hipReturnSuccess
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#else
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cudaProfilerStop
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#endif
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);
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cudart.def(
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"cuda"
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"HostRegister",
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[](uintptr_t ptr, size_t size, unsigned int flags) -> cudaError_t {
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py::gil_scoped_release no_gil;
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return C10_CUDA_ERROR_HANDLED(
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// NOLINTNEXTLINE(performance-no-int-to-ptr)
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cudaHostRegister((void*)ptr, size, flags));
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});
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cudart.def(
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"cuda"
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"HostUnregister",
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[](uintptr_t ptr) -> cudaError_t {
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py::gil_scoped_release no_gil;
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// NOLINTNEXTLINE(performance-no-int-to-ptr)
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return C10_CUDA_ERROR_HANDLED(cudaHostUnregister((void*)ptr));
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});
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cudart.def(
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"cuda"
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"StreamCreate",
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[](uintptr_t ptr) -> cudaError_t {
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py::gil_scoped_release no_gil;
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// NOLINTNEXTLINE(performance-no-int-to-ptr)
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return C10_CUDA_ERROR_HANDLED(cudaStreamCreate((cudaStream_t*)ptr));
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});
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cudart.def(
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"cuda"
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"StreamDestroy",
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[](uintptr_t ptr) -> cudaError_t {
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py::gil_scoped_release no_gil;
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// NOLINTNEXTLINE(performance-no-int-to-ptr)
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return C10_CUDA_ERROR_HANDLED(cudaStreamDestroy((cudaStream_t)ptr));
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});
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#if !defined(USE_ROCM) && defined(CUDA_VERSION) && CUDA_VERSION < 12000
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// cudaProfilerInitialize is no longer needed after CUDA 12:
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// https://forums.developer.nvidia.com/t/cudaprofilerinitialize-is-deprecated-alternative/200776/3
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cudart.def(
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"cuda"
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"ProfilerInitialize",
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cudaProfilerInitialize,
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py::call_guard<py::gil_scoped_release>());
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#endif
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cudart.def(
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"cuda"
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"MemGetInfo",
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[](c10::DeviceIndex device) -> std::pair<size_t, size_t> {
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c10::cuda::CUDAGuard guard(device);
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size_t device_free = 0;
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size_t device_total = 0;
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py::gil_scoped_release no_gil;
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C10_CUDA_CHECK(cudaMemGetInfo(&device_free, &device_total));
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return {device_free, device_total};
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});
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}
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} // namespace torch::cuda::shared
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