Merge branch 'develop' of https://github.com/PaddlePaddle/Paddle into fix_bug_for_lstmp
test=developrevert-15774-anakin_subgraph_engine
xuezhong
6 years ago
commit
dff7461ea8
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// Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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#pragma once
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#include <algorithm>
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#include <iostream>
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#include <iterator>
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#include <string>
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#include "glog/logging.h"
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#include "gtest/gtest.h"
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#include "paddle/fluid/framework/ir/graph.h"
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#include "paddle/fluid/framework/ir/graph_helper.h"
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#include "paddle/fluid/framework/op_registry.h"
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#include "paddle/fluid/framework/program_desc.h"
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namespace paddle {
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namespace framework {
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class DummyOp : public OperatorBase {
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public:
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DummyOp(const std::string& type, const VariableNameMap& inputs,
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const VariableNameMap& outputs, const AttributeMap& attrs)
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: OperatorBase(type, inputs, outputs, attrs) {}
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private:
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void RunImpl(const Scope& scope,
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const platform::Place& place) const override {}
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};
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class SumOpMaker : public OpProtoAndCheckerMaker {
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public:
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void Make() {
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AddInput("X", "").AsDuplicable();
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AddOutput("Out", "");
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AddComment("");
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}
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};
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class AssignOpMaker : public OpProtoAndCheckerMaker {
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public:
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void Make() {
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AddInput("X", "").AsDuplicable();
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AddOutput("Out", "");
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AddComment("");
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}
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};
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class SplitOpMaker : public OpProtoAndCheckerMaker {
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public:
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void Make() {
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AddInput("X", "");
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AddOutput("Out", "").AsDuplicable();
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AddComment("");
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}
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};
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class DummyVarTypeInference : public VarTypeInference {
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public:
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void operator()(const OpDesc& op_desc, BlockDesc* block) const override {
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auto& inputs = op_desc.Input("X");
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auto type = block->Var(inputs.front())->GetType();
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auto out_var_name = op_desc.Output("Out").front();
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block->Var(out_var_name)->SetType(type);
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}
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};
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} // namespace framework
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} // namespace paddle
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// Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may abtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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#pragma once
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#include <map>
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#include <string>
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#include <unordered_map>
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#include <unordered_set>
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#include <utility>
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#include <vector>
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#include "paddle/fluid/framework/details/memory_optimize_helper.h"
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#include "paddle/fluid/framework/ir/graph.h"
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#include "paddle/fluid/framework/ir/pass.h"
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namespace paddle {
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namespace framework {
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namespace details {
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class GraphView {
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public:
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GraphView() = default;
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void Build(ir::Graph* g);
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const std::vector<ir::Node*>& AllOps();
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ir::Node* GetNodeByName(const std::string& name,
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const std::vector<ir::Node*>& nodes) const;
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std::vector<ir::Node*> PendingOpsOnVar(ir::Node* var);
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// Will Deperated in the future.
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// NOTE(dzhwinter) :
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// 1. Python memory optimize will reuse
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// memory based var name, so different op output may
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// have the same variable name. enable inplace on such node
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// will generate a circle in ssa graph.
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// 2. DistributeTranspiler will use unique name to
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// map the parameter and gradient, must be skipped.
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bool InSkipSet(const std::string& var) const;
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private:
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std::vector<ir::Node*> ops_;
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std::unordered_set<std::string> dup_nodes_; // mem opt affect nodes
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std::map<ir::Node*, std::unordered_set<ir::Node*>> adj_list_;
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};
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typedef std::vector<std::pair<ir::Node*, ir::Node*>> SSANodePair;
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class InplacePass : public ir::Pass {
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public:
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InplacePass();
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protected:
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std::unique_ptr<ir::Graph> ApplyImpl(
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std::unique_ptr<ir::Graph> graph) const override;
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void InitSSAGraphNodes() const;
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private:
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const SSANodePair TryInplaceModifyVar(const std::string& var,
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const std::string& cache_var,
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const size_t& idx,
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ir::Graph* graph) const;
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void CommitModify(const SSANodePair&, ir::Graph* graph) const;
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void WithdrawModify(const SSANodePair& nodes, ir::Graph* graph) const;
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void InplaceModifyDesc(const std::string& in_var, const std::string& out_var,
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const size_t& idx) const;
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void TryInplaceOpInputOutput(ir::Node* op, ir::Graph* graph) const;
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mutable std::map<std::string, std::vector<ir::Node*>> var_nodes_;
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mutable std::unordered_set<std::string> whitelist_;
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mutable GraphView view_;
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};
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} // namespace details
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} // namespace framework
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} // namespace paddle
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@ -0,0 +1,115 @@
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// Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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#pragma once
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#include <functional>
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#include <numeric>
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#include <string>
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#include <unordered_map>
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#include "glog/logging.h"
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#include "paddle/fluid/framework/block_desc.h"
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#include "paddle/fluid/framework/details/memory_optimize_helper.h"
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#include "paddle/fluid/framework/op_desc.h"
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#include "paddle/fluid/framework/type_defs.h"
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namespace paddle {
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namespace framework {
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/*
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Inplace Inference for create In->Out pairs for inplaced operator.
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If we specify a pair of corresponding names. For example, X->Out.
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then Out will inplaced use X's memory. The base class will do
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legality validation for both variables.
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*/
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class InplaceOpInference {
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public:
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virtual ~InplaceOpInference() {}
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virtual std::unordered_map<std::string, std::string> operator()(
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const OpDesc& op_desc, BlockDesc* block) const = 0;
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};
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class InplaceInToOut : public InplaceOpInference {
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public:
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std::unordered_map<std::string, std::string> operator()(
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const OpDesc& op_desc, BlockDesc* block) const {
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std::unordered_map<std::string, std::string> ret;
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auto in_out_var_names_pair = this->Apply(op_desc, block);
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for (auto& pair : in_out_var_names_pair) {
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PADDLE_ENFORCE(!op_desc.Input(pair.first).empty(),
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string::Sprintf("op %s do not have input of %s!",
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op_desc.Type(), pair.first));
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PADDLE_ENFORCE(!op_desc.Output(pair.second).empty(),
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string::Sprintf("op %s do not have output of %s!",
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op_desc.Type(), pair.second));
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auto& in_name = op_desc.Input(pair.first).at(0);
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auto& out_name = op_desc.Output(pair.second).at(0);
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auto in = block->FindRecursiveOrCreateVar(in_name);
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auto out = block->FindRecursiveOrCreateVar(out_name);
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if (TryInplaceInputOutput(in, out)) ret.insert({in_name, out_name});
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}
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return ret;
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}
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protected:
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virtual std::unordered_map<std::string, std::string> Apply(
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const OpDesc& op_desc, BlockDesc* block) const = 0;
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bool TryInplaceInputOutput(const VarDesc& in, const VarDesc& out) const {
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return in.Name() != out.Name() && details::NodeCanReused(in) &&
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details::NodeCanReused(out) &&
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details::NodeSizeInBytes(out) <= details::NodeSizeInBytes(in);
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}
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};
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/*
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Inplace In and Out for operator only have an Input and an Output.
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For example, activation op.
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*/
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class SingleOpInplaceInToOut : public InplaceInToOut {
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protected:
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std::unordered_map<std::string, std::string> Apply(
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const OpDesc& op_desc, BlockDesc* block) const override {
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PADDLE_ENFORCE(!op_desc.InputNames().empty(),
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"Op inputs must not be empty");
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PADDLE_ENFORCE(!op_desc.OutputNames().empty(),
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"Op outputs must not be empty");
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auto x_name = op_desc.InputNames().at(0);
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auto out_name = op_desc.OutputNames().at(0);
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return std::unordered_map<std::string, std::string>{{x_name, out_name}};
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}
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};
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/*
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Gradient op. Inplace output use it's Input.
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For example, Input@Grad->Input reuse strategy.
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*/
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class GradOpInplaceInToOut : public InplaceInToOut {
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protected:
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std::unordered_map<std::string, std::string> Apply(
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const OpDesc& op_desc, BlockDesc* block) const override {
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std::unordered_map<std::string, std::string> ret;
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std::unordered_set<std::string> output_names(op_desc.OutputNames().begin(),
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op_desc.OutputNames().end());
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for (auto& input_name : op_desc.InputNames()) {
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if (output_names.count(GradVarName(input_name))) {
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ret.insert({input_name, GradVarName(input_name)});
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}
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}
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return ret;
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}
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};
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} // namespace framework
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} // namespace paddle
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