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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
78 lines
1.8 KiB
C++
78 lines
1.8 KiB
C++
#include "caffe2/operators/loss_op.h"
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namespace caffe2 {
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REGISTER_CPU_OPERATOR(AveragedLoss, AveragedLoss<float, CPUContext>);
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REGISTER_CPU_OPERATOR(AveragedLossGradient,
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AveragedLossGradient<float, CPUContext>);
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OPERATOR_SCHEMA(AveragedLoss)
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.NumInputs(1)
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.NumOutputs(1)
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.ScalarType(TensorProto::FLOAT)
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.SetDoc(R"DOC(
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The *AveragedLoss* op takes a single 1-D input tensor *input* and returns a single output float value *output*. The output represents the average of the values in *input*. This op is commonly used for averaging losses, hence the name, however it does not exclusively operate on losses.
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Github Links:
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- https://github.com/caffe2/caffe2/blob/master/caffe2/operators/loss_op.h
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- https://github.com/caffe2/caffe2/blob/master/caffe2/operators/loss_op.cc
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<details>
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<summary> <b>Example</b> </summary>
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**Code**
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```
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workspace.ResetWorkspace()
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op = core.CreateOperator(
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"AveragedLoss",
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["input"],
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["output"],
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)
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workspace.FeedBlob("input", np.array([8, 10, 12]).astype(np.float32))
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print("input:\n", workspace.FetchBlob("input"))
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workspace.RunOperatorOnce(op)
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print("output: \n", workspace.FetchBlob("output"))
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```
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**Result**
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```
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input:
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[ 8. 10. 12.]
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output:
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10.0
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```
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</details>
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)DOC")
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.Input(0, "input", "The input data as Tensor")
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.Output(0, "output", "The output tensor of size 1 containing the averaged value.");
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OPERATOR_SCHEMA(AveragedLossGradient).NumInputs(2).NumOutputs(1);
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class GetAveragedLossGradient : 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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"AveragedLossGradient", "",
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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(AveragedLoss, GetAveragedLossGradient);
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} // namespace caffe2
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