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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
2.0 KiB
C++
67 lines
2.0 KiB
C++
#include "caffe2/operators/normalize_op.h"
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#include "caffe2/core/tensor.h"
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namespace caffe2 {
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template <typename T, class Context>
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void NormalizeGradientOp<T, Context>::DoNormalize(
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const T* xData,
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const T* gOutData,
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T* gInData,
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const int m,
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const int n,
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const int sf) {
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using InnerStride = Eigen::InnerStride<Eigen::Dynamic>;
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using StridedVec =
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Eigen::Map<Eigen::Matrix<T, 1, Eigen::Dynamic>, 0, InnerStride>;
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using ConstStridedVec =
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Eigen::Map<const Eigen::Matrix<T, 1, Eigen::Dynamic>, 0, InnerStride>;
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for (int i = 0; i < n; ++i) {
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auto base = (i / sf) * sf * m + (i % sf);
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ConstStridedVec xVec(xData + base, 1, m, InnerStride(sf));
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ConstStridedVec gOutVec(gOutData + base, 1, m, InnerStride(sf));
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auto row_sum = xVec.dot(gOutVec);
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auto row_norm = xVec.template lpNorm<2>();
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row_norm = std::max(row_norm, kEps_);
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auto row_norm_3 = pow(row_norm, 3);
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StridedVec gInVec(gInData + base, 1, m, InnerStride(sf));
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gInVec = (gOutVec / row_norm) - ((xVec / row_norm_3) * row_sum);
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}
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};
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REGISTER_CPU_OPERATOR(Normalize, NormalizeOp<float, CPUContext>);
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OPERATOR_SCHEMA(Normalize)
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.NumInputs(1)
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.NumOutputs(1)
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.Arg("axis", "axis to normalize")
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.SetDoc(R"DOC(
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Given a matrix, apply L2-normalization along the specified dimension.
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)DOC")
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.IdenticalTypeAndShape();
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REGISTER_CPU_GRADIENT_OPERATOR(
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NormalizeGradient,
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NormalizeGradientOp<float, CPUContext>);
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GRADIENT_OPERATOR_SCHEMA(NormalizeGradient)
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.NumInputs(2)
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.NumOutputs(1)
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.Arg("axis", "axis to normalize");
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class GetNormalizeGradient final : public GradientMakerBase {
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using GradientMakerBase::GradientMakerBase;
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vector<OperatorDef> GetGradientDefs() override {
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CAFFE_ENFORCE_EQ(def_.input_size(), 1);
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return SingleGradientDef(
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"NormalizeGradient",
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"",
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vector<string>{I(0), GO(0)},
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vector<string>{GI(0)});
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}
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};
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REGISTER_GRADIENT(Normalize, GetNormalizeGradient);
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} // namespace caffe2
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