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https://github.com/zebrajr/pytorch.git
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c1ee8835b6
Summary: Added on top of ezyang's https://github.com/pytorch/pytorch/pull/9278 Pull Request resolved: https://github.com/pytorch/pytorch/pull/9357 Reviewed By: ezyang Differential Revision: D8863934 Pulled By: cpuhrsch fbshipit-source-id: a45c955c0b1e9e0866749b3a7e8a36de931bdff1
49 lines
1.0 KiB
C++
49 lines
1.0 KiB
C++
#define __STDC_FORMAT_MACROS
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#include "torch/csrc/python_headers.h"
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#ifdef _MSC_VER
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#include <Windows.h>
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#endif
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#include <structmember.h>
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#define THP_HOST_HALF
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#include <stdbool.h>
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#include <TH/TH.h>
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// See Note [TH abstraction violation]
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// - Used to get at the allocator associated with a storage
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#include <TH/THStorageFunctions.hpp>
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#include <torch/csrc/finalizer.h>
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#include <libshm.h>
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#include "THP.h"
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#include "copy_utils.h"
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#include "DynamicTypes.h"
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#ifdef USE_CUDA
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#include <THC/THCStorage.hpp>
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#endif
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#include "generic/Storage.cpp"
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#include <TH/THGenerateAllTypes.h>
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#include "generic/Storage.cpp"
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#include <TH/THGenerateHalfType.h>
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// NB: If you ever divest libtorch of USE_CUDA, you'll have to virtualize
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// the CUDA call.
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template<>
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void THPPointer<THStorage>::free() {
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if (ptr) {
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if (ptr->data_ptr.device().is_cpu()) {
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THStorage_free(ptr);
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} else {
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AT_ASSERT(ptr->data_ptr.device().is_cuda());
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#ifdef USE_CUDA
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THStorage_free(ptr);
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#else
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AT_ERROR("Cannot free THCStorage when not built with CUDA");
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#endif
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}
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}
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}
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