// Copyright (c) 2021 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/framework/infershape_utils.h" #include "paddle/fluid/framework/op_proto_maker.h" #include "paddle/fluid/framework/op_registry.h" #include "paddle/fluid/framework/operator.h" #include "paddle/phi/core/infermeta_utils.h" #include "paddle/phi/infermeta/backward.h" #include "paddle/phi/infermeta/unary.h" namespace paddle { namespace operators { class DeterminantOp : public framework::OperatorWithKernel { public: using framework::OperatorWithKernel::OperatorWithKernel; }; class DeterminantOpMaker : public framework::OpProtoAndCheckerMaker { public: void Make() override { AddInput("Input", "(Tensor) The input tensor of determinant."); AddOutput("Out", "(Tensor) The output Tensor containing the determinant" "value of a square matrix or batches of square matrices "); AddComment(R"DOC( Determinant Operator.)DOC"); } }; class DeterminantGradOp : public framework::OperatorWithKernel { public: using framework::OperatorWithKernel::OperatorWithKernel; protected: framework::OpKernelType GetExpectedKernelType( const framework::ExecutionContext &ctx) const override { return framework::OpKernelType(OperatorWithKernel::IndicateVarDataType( ctx, framework::GradVarName("Out")), ctx.GetPlace()); } }; template class DeterminantGradOpMaker : public framework::SingleGradOpMaker { public: using framework::SingleGradOpMaker::SingleGradOpMaker; protected: void Apply(GradOpPtr grad_op) const override { grad_op->SetType("determinant_grad"); grad_op->SetInput("Input", this->Input("Input")); grad_op->SetInput("Out", this->Output("Out")); grad_op->SetInput(framework::GradVarName("Out"), this->OutputGrad("Out")); grad_op->SetOutput(framework::GradVarName("Input"), this->InputGrad("Input")); grad_op->SetAttrMap(this->Attrs()); } }; DECLARE_NO_NEED_BUFFER_VARS_INFERER(DeterminantGradNoNeedBufferVarsInferer, "Input"); class SlogDeterminantOp : public framework::OperatorWithKernel { public: using framework::OperatorWithKernel::OperatorWithKernel; void InferShape(framework::InferShapeContext *ctx) const override { OP_INOUT_CHECK(ctx->HasInput("Input"), "Input", "Input", "determinant"); OP_INOUT_CHECK(ctx->HasOutput("Out"), "Output", "Out", "determinant"); } }; class SlogDeterminantOpMaker : public framework::OpProtoAndCheckerMaker { public: void Make() override { AddInput("Input", "(Tensor) The input tensor of SlogDeterminant."); AddOutput("Out", "(Tensor) The output tensor containing the sign of the" "determinant and the natural logarithm" "of the absolute value of determinant,"); AddComment(R"DOC( SlogDeterminant Operator.)DOC"); } }; class SlogDeterminantGradOp : public framework::OperatorWithKernel { public: using framework::OperatorWithKernel::OperatorWithKernel; void InferShape(framework::InferShapeContext *ctx) const override { OP_INOUT_CHECK( ctx->HasInput("Input"), "Input", "Input", "SlogDeterminantGradOp"); OP_INOUT_CHECK( ctx->HasInput("Out"), "Input", "Out", "SlogDeterminantGradOp"); OP_INOUT_CHECK(ctx->HasInput(framework::GradVarName("Out")), "Input", framework::GradVarName("Out"), "SlogDeterminantGradOp"); OP_INOUT_CHECK(ctx->HasOutput(framework::GradVarName("Input")), "Output", framework::GradVarName("Input"), "SlogDeterminantGradOp"); ctx->SetOutputDim(framework::GradVarName("Input"), ctx->GetInputDim("Input")); } protected: framework::OpKernelType GetExpectedKernelType( const framework::ExecutionContext &ctx) const override { return framework::OpKernelType(OperatorWithKernel::IndicateVarDataType( ctx, framework::GradVarName("Out")), ctx.GetPlace()); } }; template class SlogDeterminantGradOpMaker : public framework::SingleGradOpMaker { public: using framework::SingleGradOpMaker::SingleGradOpMaker; protected: void Apply(GradOpPtr grad_op) const override { grad_op->SetType("slogdeterminant_grad"); grad_op->SetInput("Input", this->Input("Input")); grad_op->SetInput("Out", this->Output("Out")); grad_op->SetInput(framework::GradVarName("Out"), this->OutputGrad("Out")); grad_op->SetOutput(framework::GradVarName("Input"), this->InputGrad("Input")); grad_op->SetAttrMap(this->Attrs()); } }; DECLARE_NO_NEED_BUFFER_VARS_INFERER(SlogDeterminantGradNoNeedBufferVarsInferer, "Input"); } // namespace operators } // namespace paddle namespace ops = paddle::operators; namespace plat = paddle::platform; DECLARE_INFER_SHAPE_FUNCTOR(determinant, DeterminantInferShapeFunctor, PD_INFER_META(phi::UnchangedInferMeta)); REGISTER_OPERATOR(determinant, ops::DeterminantOp, ops::DeterminantOpMaker, ops::DeterminantGradOpMaker, ops::DeterminantGradOpMaker, DeterminantInferShapeFunctor); DECLARE_INFER_SHAPE_FUNCTOR(determinant_grad, DeterminantGradInferShapeFunctor, PD_INFER_META(phi::GeneralUnaryGradInferMeta)); REGISTER_OPERATOR(determinant_grad, ops::DeterminantGradOp, DeterminantGradInferShapeFunctor); DECLARE_INFER_SHAPE_FUNCTOR(slogdeterminant, SlogDeterminantInferShapeFunctor, PD_INFER_META(phi::UnchangedInferMeta)); REGISTER_OPERATOR(slogdeterminant, ops::SlogDeterminantOp, ops::SlogDeterminantOpMaker, ops::SlogDeterminantGradOpMaker, ops::SlogDeterminantGradOpMaker, SlogDeterminantInferShapeFunctor); DECLARE_INFER_SHAPE_FUNCTOR(slogdeterminant_grad, SlogDeterminantGradInferShapeFunctor, PD_INFER_META(phi::GeneralUnaryGradInferMeta)); REGISTER_OPERATOR(slogdeterminant_grad, ops::SlogDeterminantGradOp, SlogDeterminantGradInferShapeFunctor) // reuse det grad op