mirror of
https://github.com/zebrajr/pytorch.git
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a9e6a673ae
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/11876 Modern C++ api instead of macros, item() is aligned with Python frontend. caffe2::Tensor::capacity_nbytes is effecitvely unused and confusing w.r.t. caffe2::Tensor::nbytes(). codemod -d caffe2 --extensions cc,cpp,cu,cuh,h,py,hpp,mm toCByte "item<uint8_t>" codemod -d caffe2 --extensions cc,cpp,cu,cuh,h,py,hpp,mm toCLong "item<int64_t>" codemod -d caffe2 --extensions cc,cpp,cu,cuh,h,py,hpp,mm toCInt "item<int32_t>" codemod -d caffe2 --extensions cc,cpp,cu,cuh,h,py,hpp,mm toCDouble "item<double>" codemod -d caffe2 --extensions cc,cpp,cu,cuh,h,py,hpp,mm toCFloat "item<float>" codemod -d caffe2 --extensions cc,cpp,cu,cuh,h,py,hpp,mm toByteData "data<uint8_t>" codemod -d caffe2 --extensions cc,cpp,cu,cuh,h,py,hpp,mm toLongData "data<int64_t>" codemod -d caffe2 --extensions cc,cpp,cu,cuh,h,py,hpp,mm toIntData "data<int32_t>" codemod -d caffe2 --extensions cc,cpp,cu,cuh,h,py,hpp,mm toDoubleData "data<double>" codemod -d caffe2 --extensions cc,cpp,cu,cuh,h,py,hpp,mm toFloatData "data<float>" codemod -d hphp --extensions cc,cpp,cu,cuh,h,py,hpp,mm toCByte "item<uint8_t>" codemod -d hphp --extensions cc,cpp,cu,cuh,h,py,hpp,mm toCLong "item<int64_t>" codemod -d hphp --extensions cc,cpp,cu,cuh,h,py,hpp,mm toCInt "item<int32_t>" codemod -d hphp --extensions cc,cpp,cu,cuh,h,py,hpp,mm toCDouble "item<double>" codemod -d hphp --extensions cc,cpp,cu,cuh,h,py,hpp,mm toCFloat "item<float>" codemod -d hphp --extensions cc,cpp,cu,cuh,h,py,hpp,mm toByteData "data<uint8_t>" codemod -d hphp --extensions cc,cpp,cu,cuh,h,py,hpp,mm toLongData "data<int64_t>" codemod -d hphp --extensions cc,cpp,cu,cuh,h,py,hpp,mm toIntData "data<int32_t>" codemod -d hphp --extensions cc,cpp,cu,cuh,h,py,hpp,mm toDoubleData "data<double>" codemod -d hphp --extensions cc,cpp,cu,cuh,h,py,hpp,mm toFloatData "data<float>" codemod -d caffe2 --extensions cc,cpp,cu,cuh,h,py,hpp,mm toCComplexDouble "item<std::complex<double>>" codemod -d tc --extensions cc,cpp,cu,cuh,h,py,hpp,mm toCFloat "item<float>" Reviewed By: ezyang Differential Revision: D9948572 fbshipit-source-id: 70c9f5390d92b82c85fdd5f8a5aebca338ab413c
99 lines
2.8 KiB
C++
99 lines
2.8 KiB
C++
#pragma once
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#include "torch/csrc/python_headers.h"
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#include <ATen/ATen.h>
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#include <pybind11/pybind11.h>
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#include <pybind11/stl.h>
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#include "torch/csrc/DynamicTypes.h"
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#include "torch/csrc/autograd/python_variable.h"
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#include "torch/csrc/utils/python_tuples.h"
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#include "torch/csrc/utils/python_numbers.h"
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#include <stdexcept>
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namespace py = pybind11;
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namespace pybind11 { namespace detail {
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// torch.autograd.Variable <-> at::Tensor conversions (without unwrapping)
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template <>
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struct type_caster<at::Tensor> {
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public:
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PYBIND11_TYPE_CASTER(at::Tensor, _("at::Tensor"));
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bool load(handle src, bool) {
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PyObject* obj = src.ptr();
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if (THPVariable_Check(obj)) {
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value = reinterpret_cast<THPVariable*>(obj)->cdata;
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return true;
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}
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return false;
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}
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static handle
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cast(at::Tensor src, return_value_policy /* policy */, handle /* parent */) {
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if (!src.is_variable()) {
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throw std::runtime_error(
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"Expected tensor's dynamic type to be Variable, not Tensor");
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}
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return handle(THPVariable_Wrap(torch::autograd::Variable(src)));
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}
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};
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template<> struct type_caster<torch::autograd::Variable> {
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public:
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PYBIND11_TYPE_CASTER(torch::autograd::Variable, _("torch::autograd::Variable"));
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bool load(handle src, bool) {
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PyObject *source = src.ptr();
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if (THPVariable_Check(source)) {
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value = ((THPVariable*)source)->cdata;
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return true;
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} else {
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return false;
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}
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}
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static handle cast(torch::autograd::Variable src, return_value_policy /* policy */, handle /* parent */) {
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return handle(THPVariable_Wrap(src));
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}
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};
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template<> struct type_caster<at::IntList> {
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public:
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PYBIND11_TYPE_CASTER(at::IntList, _("at::IntList"));
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bool load(handle src, bool) {
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PyObject *source = src.ptr();
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auto tuple = PyTuple_Check(source);
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if (tuple || PyList_Check(source)) {
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auto size = tuple ? PyTuple_GET_SIZE(source) : PyList_GET_SIZE(source);
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v_value.resize(size);
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for (int idx = 0; idx < size; idx++) {
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PyObject* obj = tuple ? PyTuple_GET_ITEM(source, idx) : PyList_GET_ITEM(source, idx);
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if (THPVariable_Check(obj)) {
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v_value[idx] = THPVariable_Unpack(obj).item<int64_t>();
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} else if (PyLong_Check(obj)) {
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// use THPUtils_unpackLong after it is safe to include python_numbers.h
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v_value[idx] = THPUtils_unpackLong(obj);
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} else {
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return false;
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}
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}
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value = v_value;
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return true;
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}
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return false;
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}
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static handle cast(at::IntList src, return_value_policy /* policy */, handle /* parent */) {
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return handle(THPUtils_packInt64Array(src.size(), src.data()));
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}
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private:
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std::vector<int64_t> v_value;
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};
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// http://pybind11.readthedocs.io/en/stable/advanced/cast/stl.html#c-17-library-containers
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template <typename T>
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struct type_caster<at::optional<T>> : optional_caster<at::optional<T>> {};
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}} // namespace pybind11::detail
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