/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. */ #include "paddle/fluid/operators/sign_op.h" #include namespace paddle { namespace operators { class SignOp : public framework::OperatorWithKernel { public: using framework::OperatorWithKernel::OperatorWithKernel; void InferShape(framework::InferShapeContext *ctx) const override { PADDLE_ENFORCE(ctx->HasInput("X"), "Input(X) of SignOp should not be null."); PADDLE_ENFORCE(ctx->HasOutput("Out"), "Output(Out) of SignOp should not be null."); ctx->SetOutputDim("Out", ctx->GetInputDim("X")); ctx->ShareLoD("X", /*->*/ "Out"); } }; template class SignOpMaker : public framework::OpProtoAndCheckerMaker { public: void Make() override { AddInput("X", "(Tensor) Input tensor of sign operator."); AddOutput("Out", "(Tensor) Output tensor of sign operator."); AddComment(R"DOC( Sign operator $$Out = X.sign()$$ )DOC"); } }; template class SignGradMaker : public framework::SingleGradOpMaker { public: using framework::SingleGradOpMaker::SingleGradOpMaker; std::unique_ptr Apply() const override { auto *grad_op = new T(); grad_op->SetType("scale"); grad_op->SetInput("X", this->OutputGrad("Out")); grad_op->SetOutput("Out", this->InputGrad("X")); grad_op->SetAttr("scale", 0.0f); return std::unique_ptr(grad_op); } }; } // namespace operators } // namespace paddle namespace ops = paddle::operators; REGISTER_OPERATOR(sign, ops::SignOp, ops::SignOpMaker, ops::SignGradMaker, ops::SignGradMaker); REGISTER_OP_CPU_KERNEL( sign, ops::SignKernel, ops::SignKernel);