| #include "caffe2/operators/loss_op.h" |
| |
| namespace caffe2 { |
| namespace { |
| |
| REGISTER_CPU_OPERATOR(AveragedLoss, AveragedLoss<float, CPUContext>); |
| REGISTER_CPU_OPERATOR(AveragedLossGradient, |
| AveragedLossGradient<float, CPUContext>); |
| |
| OPERATOR_SCHEMA(AveragedLoss) |
| .NumInputs(1) |
| .NumOutputs(1) |
| .ScalarType(TensorProto::FLOAT) |
| .SetDoc(R"DOC( |
| AveragedLoss takes in a 1-D tensor as input and returns a single output float |
| value which represents the average of input data (average of the losses). |
| )DOC") |
| .Input(0, "input", "The input data as Tensor") |
| .Output(0, "output", "The output tensor of size 1 containing the averaged " |
| "value."); |
| |
| OPERATOR_SCHEMA(AveragedLossGradient).NumInputs(2).NumOutputs(1); |
| |
| class GetAveragedLossGradient : public GradientMakerBase { |
| using GradientMakerBase::GradientMakerBase; |
| vector<OperatorDef> GetGradientDefs() override { |
| return SingleGradientDef( |
| "AveragedLossGradient", "", |
| vector<string>{I(0), GO(0)}, |
| vector<string>{GI(0)}); |
| } |
| }; |
| REGISTER_GRADIENT(AveragedLoss, GetAveragedLossGradient); |
| |
| } // namespace |
| } // namespace caffe2 |