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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
43 lines
1.1 KiB
C++
43 lines
1.1 KiB
C++
#include "caffe2/operators/square_root_divide_op.h"
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namespace caffe2 {
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REGISTER_CPU_OPERATOR(SquareRootDivide, SquareRootDivideOp<CPUContext>);
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OPERATOR_SCHEMA(SquareRootDivide)
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.NumInputs(2)
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.NumOutputs(1)
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.AllowInplace({{0, 0}})
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.SetDoc(R"DOC(
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Given DATA tensor with first dimension N and SCALE vector of the same size N
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produces an output tensor with same dimensions as DATA. Which consists of DATA
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slices. i-th slice is divided by sqrt(SCALE[i]) elementwise. If SCALE[i] == 0
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output slice is identical to the input one (no scaling)
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Example:
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Data = [
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[2.0, 4.0],
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[9.0, 12.0]
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]
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SCALE = [4, 9]
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OUTPUT = [
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[1.0, 2.0],
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[3.0, 4.0]
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]
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)DOC");
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class GetSquareRootDivideGradient : public GradientMakerBase {
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using GradientMakerBase::GradientMakerBase;
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vector<OperatorDef> GetGradientDefs() override {
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return SingleGradientDef(
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"SquareRootDivide",
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"",
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vector<string>{GO(0), I(1)},
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vector<string>{GI(0)});
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}
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};
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REGISTER_GRADIENT(SquareRootDivide, GetSquareRootDivideGradient);
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} // namespace caffe2
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