mirror of
https://github.com/saymrwulf/pytorch.git
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2a698682e4
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/21964 ghimport-source-id: fdfb555ac4efbf31ae7d2c700a5aa44ad0cc4d7f Test Plan: Imported from OSS Differential Revision: D15897424 Pulled By: li-roy fbshipit-source-id: 3cd6744254e34d70e6875ffde749b5cf959b663c
56 lines
1.7 KiB
C++
56 lines
1.7 KiB
C++
#include <torch/extension.h>
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#include <c10/core/Allocator.h>
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#include <ATen/CPUGenerator.h>
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#include <ATen/DeviceGuard.h>
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#include <ATen/NativeFunctions.h>
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#include <ATen/Utils.h>
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#include <ATen/WrapDimUtils.h>
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#include <c10/util/Half.h>
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#include <c10/core/TensorImpl.h>
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#include <c10/core/UndefinedTensorImpl.h>
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#include <c10/util/Optional.h>
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#include <ATen/core/ATenDispatch.h>
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#include <cstddef>
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#include <functional>
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#include <memory>
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#include <utility>
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#include <ATen/Config.h>
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namespace at {
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static Tensor empty_complex(IntArrayRef size, const TensorOptions & options, c10::optional<c10::MemoryFormat> optional_memory_format) {
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TORCH_CHECK(!optional_memory_format.has_value(), "memory format is not supported")
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AT_ASSERT(options.device().is_cpu());
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for (auto x: size) {
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TORCH_CHECK(x >= 0, "Trying to create tensor using size with negative dimension: ", size);
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}
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auto* allocator = at::getCPUAllocator();
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int64_t nelements = at::prod_intlist(size);
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auto dtype = options.dtype();
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auto storage_impl = c10::make_intrusive<StorageImpl>(
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dtype,
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nelements,
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allocator->allocate(nelements * dtype.itemsize()),
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allocator,
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/*resizable=*/true);
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auto tensor = detail::make_tensor<TensorImpl>(storage_impl, at::ComplexCPUTensorId());
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// Default TensorImpl has size [0]
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if (size.size() != 1 || size[0] != 0) {
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tensor.unsafeGetTensorImpl()->set_sizes_contiguous(size);
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}
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return tensor;
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}
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static auto& complex_empty_registration = globalATenDispatch().registerOp(
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Backend::ComplexCPU,
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"aten::empty(int[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, MemoryFormat? memory_format=None) -> Tensor",
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&empty_complex);
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}
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PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) { }
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