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https://github.com/pytorch/pytorch.git
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a9b0a921d5
Summary: As GoogleTest `TEST` macro is non-compliant with it as well as `DEFINE_DISPATCH` All changes but the ones to `.clang-tidy` are generated using following script: ``` for i in `find . -type f -iname "*.c*" -or -iname "*.h"|xargs grep cppcoreguidelines-avoid-non-const-global-variables|cut -f1 -d:|sort|uniq`; do sed -i "/\/\/ NOLINTNEXTLINE(cppcoreguidelines-avoid-non-const-global-variables)/d" $i; done ``` Pull Request resolved: https://github.com/pytorch/pytorch/pull/62008 Reviewed By: driazati, r-barnes Differential Revision: D29838584 Pulled By: malfet fbshipit-source-id: 1b2f8602c945bd4ce50a9bfdd204755556e31d13
67 lines
2.1 KiB
C++
67 lines
2.1 KiB
C++
#include "caffe2/operators/minmax_ops.h"
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#include <string>
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#include <vector>
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#include "caffe2/utils/eigen_utils.h"
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namespace caffe2 {
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template <typename T, class Context>
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bool SelectGradientOpBase<T, Context>::RunOnDevice() {
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const auto& Y = Input(0);
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const auto& dY = Input(1);
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const int N = Y.numel();
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ConstEigenVectorArrayMap<T> Y_arr(Y.template data<T>(), N);
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ConstEigenVectorArrayMap<T> dY_arr(dY.template data<T>(), N);
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for (int i = 0; i < OutputSize(); i++) {
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const auto& Xi = Input(i + 2);
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auto* dXi = Output(i, Xi.sizes(), at::dtype<T>());
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ConstEigenVectorArrayMap<T> Xi_arr(Xi.template data<T>(), N);
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EigenVectorArrayMap<T> dXi_arr(dXi->template mutable_data<T>(), N);
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dXi_arr = (Xi_arr == Y_arr).template cast<T>() * dY_arr;
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}
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return true;
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}
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REGISTER_CPU_OPERATOR(MaxGradient, MaxGradientOp<float, CPUContext>);
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REGISTER_CPU_OPERATOR(MinGradient, MinGradientOp<float, CPUContext>);
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OPERATOR_SCHEMA(MaxGradient).NumInputs(3, INT_MAX).NumOutputs(1, INT_MAX);
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OPERATOR_SCHEMA(MinGradient).NumInputs(3, INT_MAX).NumOutputs(1, INT_MAX);
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namespace {
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class GetMaxGradient : public GradientMakerBase {
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using GradientMakerBase::GradientMakerBase;
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std::vector<OperatorDef> GetGradientDefs() override {
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std::vector<std::string> inputs = {O(0), GO(0)};
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std::vector<std::string> grad_inputs;
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for (int i = 0; i < def_.input_size(); ++i) {
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inputs.push_back(I(i));
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grad_inputs.push_back(GI(i));
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}
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return SingleGradientDef("MaxGradient", "", inputs, grad_inputs);
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}
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};
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class GetMinGradient : public GradientMakerBase {
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using GradientMakerBase::GradientMakerBase;
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vector<OperatorDef> GetGradientDefs() override {
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std::vector<std::string> inputs = {O(0), GO(0)};
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std::vector<std::string> grad_inputs;
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for (int i = 0; i < def_.input_size(); ++i) {
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inputs.push_back(I(i));
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grad_inputs.push_back(GI(i));
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}
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return SingleGradientDef("MinGradient", "", inputs, grad_inputs);
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}
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};
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} // namespace
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REGISTER_GRADIENT(Max, GetMaxGradient);
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REGISTER_GRADIENT(Min, GetMinGradient);
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} // namespace caffe2
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