// 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 #include #include "paddle/fluid/framework/infershape_utils.h" #include "paddle/fluid/framework/op_registry.h" #include "paddle/fluid/framework/tensor_util.h" #include "paddle/phi/core/infermeta_utils.h" #include "paddle/phi/infermeta/unary.h" namespace paddle { namespace operators { class MatrixPowerOp : public framework::OperatorWithKernel { public: using framework::OperatorWithKernel::OperatorWithKernel; }; class MatrixPowerOpMaker : public framework::OpProtoAndCheckerMaker { public: void Make() override { AddInput( "X", "(Tensor), The input tensor of matrix_power op. Its shape should be " "[*, M, M] where * is zero or more batch dimensions, and matrices " "on the inner-most 2 dimensions all should be square matrices."); AddOutput("Out", "(Tensor), The output tensor of matrix_power op. It has the same " "shape as the input."); AddAttr("n", "(int), The exponent used to calculate the power of X."); AddComment(R"DOC( Matrix Power Operator. Computes the n-th power of a square matrix or a batch of square matrices. )DOC"); } }; class MatrixPowerOpInferVarType : public framework::PassInDtypeAndVarTypeToOutput { protected: std::unordered_map& GetInputOutputWithSameType() const override { static std::unordered_map u_map{ {"X", /*->*/ "Out"}}; return u_map; } }; class MatrixPowerGradOp : public framework::OperatorWithKernel { public: using framework::OperatorWithKernel::OperatorWithKernel; protected: void InferShape(framework::InferShapeContext* context) const override { OP_INOUT_CHECK(context->HasInput("X"), "Input", "X", "matrix_power_grad"); OP_INOUT_CHECK( context->HasInput("Out"), "Input", "Out", "matrix_power_grad"); OP_INOUT_CHECK(context->HasInput(framework::GradVarName("Out")), "Input", "Out@GRAD", "matrix_power_grad"); auto x_dims = context->GetInputDim("X"); auto x_grad_name = framework::GradVarName("X"); if (context->HasOutput(x_grad_name)) { context->SetOutputDim(x_grad_name, x_dims); } } }; template class MatrixPowerGradOpMaker : public framework::SingleGradOpMaker { public: using framework::SingleGradOpMaker::SingleGradOpMaker; protected: void Apply(GradOpPtr op) const override { op->SetType(this->ForwardOpType() + "_grad"); op->SetInput("X", this->Input("X")); op->SetInput("Out", this->Output("Out")); op->SetInput(framework::GradVarName("Out"), this->OutputGrad("Out")); op->SetOutput(framework::GradVarName("X"), this->InputGrad("X")); op->SetAttrMap(this->Attrs()); } }; } // namespace operators } // namespace paddle namespace ops = paddle::operators; DECLARE_INFER_SHAPE_FUNCTOR(matrix_power, MatrixPowerInferShapeFunctor, PD_INFER_META(phi::MatrixPowerInferMeta)); REGISTER_OPERATOR(matrix_power, ops::MatrixPowerOp, ops::MatrixPowerOpMaker, ops::MatrixPowerOpInferVarType, ops::MatrixPowerGradOpMaker, ops::MatrixPowerGradOpMaker, MatrixPowerInferShapeFunctor); REGISTER_OPERATOR(matrix_power_grad, ops::MatrixPowerGradOp);