mirror of
https://github.com/zebrajr/pytorch.git
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01aea1f268
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/28468 We don't need this anymore. ghstack-source-id: 92595388 Test Plan: unit tests Differential Revision: D18073339 fbshipit-source-id: d0ef1332c83e47117fe0a5eadc8faedb259cfba0
59 lines
1.9 KiB
C++
59 lines
1.9 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/op_registration/op_registration.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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namespace {
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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::TensorTypeId::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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}
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static auto complex_empty_registration = torch::RegisterOperators()
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.op(torch::RegisterOperators::options()
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.schema("aten::empty.memory_format(int[] size, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None, MemoryFormat? memory_format=None) -> Tensor")
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.impl_unboxedOnlyKernel<decltype(empty_complex), &empty_complex>(TensorTypeId::ComplexCPUTensorId)
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.aliasAnalysis(c10::AliasAnalysisKind::FROM_SCHEMA));
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}
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PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) { }
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