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0aeaeffb6c
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/18485 I don't know how (1) we landed the wrong version of the patch and (2) how this passed the push blocking test Reviewed By: pjh5 Differential Revision: D14621961 fbshipit-source-id: 0a3953d7adcdc79727a61c2acff65f436dcafe55
49 lines
1.5 KiB
C++
49 lines
1.5 KiB
C++
#pragma once
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// This header provides C++ wrappers around commonly used CUDA API functions.
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// The benefit of using C++ here is that we can raise an exception in the
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// event of an error, rather than explicitly pass around error codes. This
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// leads to more natural APIs.
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//
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// The naming convention used here matches the naming convention of torch.cuda
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#include <cuda_runtime_api.h>
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#include <c10/macros/Macros.h>
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#include <c10/core/Device.h>
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#include <c10/cuda/CUDAException.h>
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namespace c10 {
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namespace cuda {
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inline DeviceIndex device_count() noexcept {
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int count;
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// NB: In the past, we were inconsistent about whether or not this reported
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// an error if there were driver problems are not. Based on experience
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// interacting with users, it seems that people basically ~never want this
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// function to fail; it should just return zero if things are not working.
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// Oblige them.
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cudaError_t err = cudaGetDeviceCount(&count);
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if (err != cudaSuccess) {
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// Clear out the error state, so we don't spuriously trigger someone else.
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// (This shouldn't really matter, since we won't be running very much CUDA
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// code in this regime.)
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cudaError_t last_err = cudaGetLastError();
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(void)last_err;
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return 0;
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}
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return static_cast<DeviceIndex>(count);
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}
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inline DeviceIndex current_device() {
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int cur_device;
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C10_CUDA_CHECK(cudaGetDevice(&cur_device));
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return static_cast<DeviceIndex>(cur_device);
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}
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inline void set_device(DeviceIndex device) {
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C10_CUDA_CHECK(cudaSetDevice(static_cast<int>(device)));
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}
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}} // namespace c10::cuda
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