// 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 #include "paddle/fluid/framework/op_desc.h" #include "paddle/fluid/framework/op_registry.h" #include "paddle/fluid/framework/scope.h" #include "paddle/fluid/imperative/engine.h" #include "paddle/fluid/imperative/layer.h" namespace paddle { namespace imperative { void CreateGradOp(const framework::OpDesc& op_desc, const std::unordered_set& no_grad_set, const std::vector& grad_sub_block, framework::OpDesc** grad_op_desc, std::unordered_map* grad_to_var) { std::vector> grad_op_descs = framework::OpInfoMap::Instance() .Get(op_desc.Type()) .GradOpMaker()(op_desc, no_grad_set, grad_to_var, grad_sub_block); PADDLE_ENFORCE(grad_op_descs.size() == 1, "Only support 1 grad op now."); // TODO(panyx0718): Leak? *grad_op_desc = grad_op_descs[0].release(); } class Tracer { public: explicit Tracer(framework::BlockDesc* root_block) : root_scope_(new framework::Scope()) {} virtual ~Tracer() {} void Trace(OpBase* op, const std::vector& inputs, const std::vector& outputs, framework::BlockDesc* block, const bool stop_gradient) { framework::OpDesc* op_desc = op->op_desc_; VLOG(3) << "tracer tracing " << op_desc->Type(); op_desc->InferShape(*block); op_desc->InferVarType(block); std::unique_ptr op_base = framework::OpRegistry::CreateOp(*op_desc); *op->input_vars_ = inputs; for (VarBase* input : inputs) { const std::string vname = input->var_desc_->Name(); framework::Variable* var = root_scope_->Var(vname); input->var_ = var; if (!var->IsInitialized()) { framework::VarDesc* var_desc = block->FindVar(vname); if (var_desc->GetType() == framework::proto::VarType::LOD_TENSOR) { var->GetMutable(); } else { LOG(ERROR) << "tracer doesn't support yet"; } } if (input->pre_op_) { op->pre_ops_->push_back(input->pre_op_); op->pre_ops_out_idx_->push_back(input->pre_op_out_idx_); } else { op->pre_ops_->push_back(nullptr); } VLOG(3) << "input vname " << vname << " " << var->Get().dims().size(); } *op->output_vars_ = outputs; for (size_t i = 0; i < outputs.size(); ++i) { const std::string vname = outputs[i]->var_desc_->Name(); framework::Variable* var = root_scope_->Var(vname); if (!var->IsInitialized()) { framework::VarDesc* var_desc = block->FindVar(vname); if (var_desc->GetType() == framework::proto::VarType::LOD_TENSOR) { var->GetMutable(); } else { LOG(ERROR) << "tracer doesn't support yet"; } } outputs[i]->var_ = var; outputs[i]->pre_op_ = op; outputs[i]->pre_op_out_idx_ = i; } VLOG(3) << "tracer running " << op_desc->Type(); op_base->Run(*root_scope_, platform::CPUPlace()); if (!stop_gradient) { framework::OpDesc* grad_op_desc; auto grad_to_var = new std::unordered_map(); CreateGradOp(*op_desc, {}, {block}, &grad_op_desc, grad_to_var); op->grad_op_desc_ = grad_op_desc; op->grad_to_var_ = grad_to_var; } op->block_ = block; } framework::Scope* GetScope() { return root_scope_.get(); } private: std::unique_ptr root_scope_; }; } // namespace imperative } // namespace paddle