// Copyright (c) 2018 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. #pragma once #include #include #include "paddle/fluid/framework/op_desc.h" #include "paddle/fluid/framework/operator.h" #include "paddle/fluid/framework/scope.h" #include "paddle/fluid/framework/var_desc.h" #include "paddle/fluid/platform/enforce.h" namespace paddle { namespace imperative { class OpBase; class VarBase { public: explicit VarBase(bool stop_gradient = false) : pre_op_(nullptr), pre_op_out_idx_(-1), var_desc_(nullptr), var_(nullptr), grads_(nullptr), stop_gradient_(stop_gradient) {} virtual ~VarBase() {} void ApplyGrad(framework::Scope* scope, framework::Variable* grad); void RunBackward(framework::Scope* scope); framework::LoDTensor& Grad(); OpBase* pre_op_; int pre_op_out_idx_; framework::VarDesc* var_desc_; framework::Variable* var_; framework::Variable* grads_; bool stop_gradient_; }; class OpBase { public: OpBase() : input_vars_(new std::vector()), output_vars_(new std::vector()), pre_ops_(new std::vector()), pre_ops_out_idx_(new std::vector()), op_desc_(nullptr), grad_op_desc_(nullptr), grad_to_var_(nullptr) {} virtual ~OpBase() { delete input_vars_; delete output_vars_; delete pre_ops_; delete pre_ops_out_idx_; if (grad_op_desc_) delete grad_op_desc_; if (grad_to_var_) delete grad_to_var_; } std::vector ApplyGrad(framework::Scope* scope); std::vector* input_vars_; std::vector* output_vars_; std::vector* pre_ops_; std::vector* pre_ops_out_idx_; framework::OpDesc* op_desc_; framework::OpDesc* grad_op_desc_; std::unordered_map* grad_to_var_; framework::BlockDesc* block_; }; class Layer { public: virtual ~Layer() {} virtual std::vector Forward(const std::vector& inputs) { std::vector vars; return vars; } virtual void Backward() { LOG(ERROR) << "To support customize"; } }; } // namespace imperative } // namespace paddle