/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve. 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 "paddle/framework/executor.h" #include "paddle/framework/op_registry.h" #include "paddle/framework/operator.h" namespace paddle { namespace operators { using StepScopeVar = std::vector; using LoDTensor = framework::LoDTensor; constexpr char kStepBlock[] = "step_block"; constexpr char kCondition[] = "Condition"; constexpr char kStepScopes[] = "StepScopes"; constexpr char kParamGrads[] = "X@Grad"; constexpr char kParameters[] = "X"; class WhileOp : public framework::OperatorBase { public: WhileOp(const std::string &type, const framework::VariableNameMap &inputs, const framework::VariableNameMap &outputs, const framework::AttributeMap &attrs) : framework::OperatorBase(type, inputs, outputs, attrs) {} void Run(const framework::Scope &scope, const platform::DeviceContext &dev_ctx) const override { PADDLE_ENFORCE_NOT_NULL(scope.FindVar(Input(kCondition))); auto &cond = scope.FindVar(Input(kCondition))->Get(); PADDLE_ENFORCE_EQ(cond.dims(), paddle::framework::make_ddim({1})); framework::Executor executor(dev_ctx); auto *block = Attr(kStepBlock); auto *program = block->Program(); auto step_scopes = scope.FindVar(Output(kStepScopes))->GetMutable(); while (cond.data()[0]) { auto ¤t_scope = scope.NewScope(); step_scopes->push_back(¤t_scope); executor.Run(*program, ¤t_scope, block->ID(), false /*create_local_scope*/); } } }; class WhileOpMaker : public framework::OpProtoAndCheckerMaker { public: WhileOpMaker(framework::OpProto *proto, framework::OpAttrChecker *op_checker) : OpProtoAndCheckerMaker(proto, op_checker) { AddInput(kParameters, "A set of variables, which are required by operators inside the " "block of While Op.") .AsDuplicable(); AddInput( kCondition, "(Bool) An scalar. When it's False, the While Op will be terminated.") .AsDuplicable(); AddOutput("Out", "A set of variables, which will be assigned with values " "generated by perators inside the block of While Op.") .AsDuplicable(); AddOutput(kStepScopes, "(StepScopeVar) A vector of local scope, which size equals the " "step number of While Op. The i'th scope storages temporary " "variables generated in the i'th step."); AddAttr(kStepBlock, "The step block inside WhileOp"); AddComment(R"DOC( )DOC"); } }; class WhileGradOp : public framework::OperatorBase { public: WhileGradOp(const std::string &type, const framework::VariableNameMap &inputs, const framework::VariableNameMap &outputs, const framework::AttributeMap &attrs) : framework::OperatorBase(type, inputs, outputs, attrs) {} void Run(const framework::Scope &scope, const platform::DeviceContext &dev_ctx) const override { // PADDLE_ENFORCE(...) framework::Executor executor(dev_ctx); auto *block = Attr(kStepBlock); auto *program = block->Program(); auto *step_scopes = scope.FindVar(Input(kStepScopes))->GetMutable(); for (auto cur_scope_iter = step_scopes->rbegin(); cur_scope_iter != step_scopes->rend(); ++cur_scope_iter) { executor.Run(*program, *cur_scope_iter, block->ID(), false); auto &pg_names = Outputs(kParamGrads); auto &p_names = Inputs(kParameters); PADDLE_ENFORCE_EQ(pg_names.size(), p_names.size()); for (size_t prog_id = 0; prog_id < pg_names.size(); ++prog_id) { auto inside_grad_name = framework::GradVarName(p_names[prog_id]); // // TODO(tonyyang-savil: Not sure we need the following // // If does not compute gradient of that variable inside rnn, // just // // continue // if (local_var_names.find(inside_grad_name) == // local_var_names.end()) { // continue; // } // zero gradient variable in step 0 if (cur_scope_iter == step_scopes->rbegin()) { auto *var = (*cur_scope_iter)->FindVar(inside_grad_name); PADDLE_ENFORCE_NOT_NULL(var); if (var->IsType()) { auto &inside_tensor = var->Get(); framework::AttributeMap attrs; attrs["data_type"] = framework::ToDataType(inside_tensor.type()); attrs["shape"] = framework::vectorize2int(inside_tensor.dims()); attrs["value"] = 0.0f; auto zero_op = framework::OpRegistry::CreateOp( "fill_constant", {}, {{"Out", {pg_names[prog_id]}}}, attrs); zero_op->Run(scope, dev_ctx); } } // sum gradient auto *outside_var = scope.FindVar(pg_names[prog_id]); PADDLE_ENFORCE_NOT_NULL(outside_var); auto &outside_tensor = *outside_var->GetMutable(); std::string result_var_name; auto *local_result_var = (*cur_scope_iter)->Var(&result_var_name); auto &local_result_tensor = *local_result_var->GetMutable(); local_result_tensor.ShareDataWith(outside_tensor); auto sum_op = framework::OpRegistry::CreateOp( "sum", {{"X", {result_var_name, inside_grad_name}}}, {{"Out", {result_var_name}}}, {}); sum_op->Run(**cur_scope_iter, dev_ctx); } } } }; class WhileGradOpDescMaker : public framework::SingleGradOpDescMaker { public: using framework::SingleGradOpDescMaker::SingleGradOpDescMaker; protected: virtual std::unique_ptr Apply() const { auto *grad = new framework::OpDescBind(); grad->SetType("while_grad"); for (auto &input_param : this->InputNames()) { grad->SetInput(input_param, this->Input(input_param)); grad->SetOutput(framework::GradVarName(input_param), this->InputGrad(input_param)); } for (auto &output_param : this->OutputNames()) { grad->SetInput(output_param, this->Output(output_param)); if (output_param != kStepScopes) { grad->SetInput(framework::GradVarName(output_param), this->OutputGrad(output_param)); } } grad->SetAttrMap(this->Attrs()); grad->SetBlockAttr(kStepBlock, *grad_block_[0]); return std::unique_ptr(grad); } }; } // namespace operators } // namespace paddle REGISTER_OPERATOR(while, paddle::operators::WhileOp, paddle::operators::WhileOpMaker, paddle::operators::WhileGradOpDescMaker);