Merge branch 'sequence_enumerate_op' of https://github.com/chenwhql/Paddle into sequence_enumerate_op
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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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#include "paddle/fluid/framework/ir/fc_lstm_fuse_pass.h"
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namespace paddle {
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namespace framework {
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namespace ir {
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std::unique_ptr<ir::Graph> FCLstmFusePass::ApplyImpl(
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std::unique_ptr<ir::Graph> graph) const {
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GraphPatternDetector gpd;
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auto* pattern = gpd.mutable_pattern();
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std::unordered_set<int> fused_ops({// first lstm
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13, 15, 16,
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// second lstm
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23, 25, 26});
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pattern->NewNode([&](Node* x) { return fused_ops.count(x->id()); },
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"any_node");
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std::unordered_set<Node*> marked_nodes;
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auto handler = [&](const GraphPatternDetector::subgraph_t& subgraph,
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Graph* g) {
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auto* id = subgraph.at(gpd.pattern().RetriveNode("any_node"));
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marked_nodes.insert(id);
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};
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gpd(graph.get(), handler);
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// Create New OpDesc
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auto lstm_creator = [&](int lstm, int input, int weight_x, int weight_h,
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int bias, int hidden, int cell, int xx) {
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#define GET_NODE(x) auto* x##_n = graph->RetriveNode(x);
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GET_NODE(input);
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GET_NODE(weight_x);
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GET_NODE(weight_h);
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GET_NODE(bias);
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GET_NODE(hidden);
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GET_NODE(cell);
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GET_NODE(xx);
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GET_NODE(lstm);
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OpDesc op_desc;
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op_desc.SetType("fusion_lstm");
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#define SET_IN(Key, node__) op_desc.SetInput(#Key, {node__##_n->Name()});
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SET_IN(X, input);
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SET_IN(WeightX, weight_x);
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SET_IN(WeightH, weight_h);
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SET_IN(Bias, bias);
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#undef GET_NODE
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#undef SET_IN
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LOG(INFO) << "hidden_n: " << hidden_n->Name();
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LOG(INFO) << "cell: " << cell_n->Name();
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LOG(INFO) << "xx: " << xx_n->Name();
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op_desc.SetInput("H0", {});
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op_desc.SetInput("C0", {});
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op_desc.SetOutput("Hidden", {hidden_n->Name()});
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op_desc.SetOutput("Cell", {cell_n->Name()});
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op_desc.SetOutput("XX", {xx_n->Name()});
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op_desc.SetOutput("BatchedGate", {"blstm_0.tmp_2"});
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op_desc.SetOutput("BatchCellPreAct", {"blstm_1.tmp_2"});
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op_desc.SetAttr("is_reverse", lstm_n->Op()->GetAttr("is_reverse"));
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op_desc.SetAttr("use_peepholes", false);
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auto* op = graph->CreateOpNode(&op_desc);
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#define LINK_TO(a, b) \
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a->outputs.push_back(b); \
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b->inputs.push_back(a);
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LINK_TO(input_n, op);
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LINK_TO(weight_x_n, op);
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LINK_TO(weight_h_n, op);
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LINK_TO(bias_n, op);
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LINK_TO(op, hidden_n);
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#undef LINK_TO
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return op;
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};
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lstm_creator(16, 12, 14, 18, 17, 22, 21, 19);
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lstm_creator(26, 12, 24, 28, 27, 32, 31, 29);
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// remove all the nodes
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for (auto* node : marked_nodes) {
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graph->RemoveNode(const_cast<Node*>(node));
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}
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for (auto* node : graph->Nodes()) {
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for (auto it = node->inputs.begin(); it != node->inputs.end();) {
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if (marked_nodes.count(*it)) {
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it = const_cast<Node*>(node)->inputs.erase(it);
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} else
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it++;
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}
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for (auto it = node->outputs.begin(); it != node->outputs.end();) {
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if (marked_nodes.count(*it)) {
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it = const_cast<Node*>(node)->outputs.erase(it);
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} else
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it++;
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}
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}
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return graph;
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}
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} // namespace ir
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} // namespace framework
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} // namespace paddle
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REGISTER_PASS(fc_lstm_fuse_pass, paddle::framework::ir::FCLstmFusePass);
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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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#include "paddle/fluid/framework/ir/graph.h"
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#include "paddle/fluid/framework/ir/graph_pattern_detector.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 ir {
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class FCLstmFusePass : public Pass {
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public:
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virtual ~FCLstmFusePass() {}
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protected:
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std::unique_ptr<ir::Graph> ApplyImpl(std::unique_ptr<ir::Graph> graph) const;
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};
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} // namespace ir
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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 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 "paddle/fluid/framework/ir/graph.h"
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#include "paddle/fluid/framework/ir/pass.h"
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#include "paddle/fluid/framework/scope.h"
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namespace paddle {
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namespace framework {
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namespace ir {
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static const char kParamScopeAttr[] = "param_scope";
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class FusePassBase : public Pass {
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public:
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void Init(Graph* graph) const { graph_ = graph; }
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Scope* param_scope() const {
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PADDLE_ENFORCE(graph_->Has(kParamScopeAttr));
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return graph_->Get<framework::Scope*>(kParamScopeAttr);
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}
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virtual ~FusePassBase() {}
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protected:
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mutable Graph* graph_;
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};
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} // namespace ir
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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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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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http://www.apache.org/licenses/LICENSE-2.0
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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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#include "paddle/fluid/framework/ir/graph_to_program_pass.h"
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#include <map>
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#include <string>
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#include <vector>
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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/program_desc.h"
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namespace paddle {
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namespace framework {
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namespace ir {
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std::unique_ptr<Graph> GraphToProgramPass::ApplyImpl(
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std::unique_ptr<Graph> graph) const {
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ProgramDesc& program = Get<ProgramDesc>("program");
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std::unique_ptr<proto::ProgramDesc> program_pb(
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new proto::ProgramDesc(*program.Proto()));
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auto block = program_pb->mutable_blocks(kRootBlockIndex);
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block->clear_vars();
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std::unordered_set<std::string> visited_vars;
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for (ir::Node* n : graph->Nodes()) {
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if (n->NodeType() == ir::Node::Type::kVariable) {
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if (n->Var() && visited_vars.count(n->Var()->Name()) == 0) {
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visited_vars.insert(n->Var()->Name());
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block->add_vars()->MergeFrom(*n->Var()->Proto());
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}
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}
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}
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block->clear_ops();
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std::vector<ir::Node*> nodes = TopologySortOperations(*graph);
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for (ir::Node* n : nodes) {
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if (!n->Op()) {
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continue;
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}
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block->add_ops()->MergeFrom(*n->Op()->Proto());
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}
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program.CopyFrom(*program_pb);
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return graph;
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}
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} // namespace ir
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} // namespace framework
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} // namespace paddle
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REGISTER_PASS(graph_to_program_pass, paddle::framework::ir::GraphToProgramPass);
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/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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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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http://www.apache.org/licenses/LICENSE-2.0
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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 "paddle/fluid/framework/ir/pass.h"
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namespace paddle {
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namespace framework {
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namespace ir {
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class GraphToProgramPass : public Pass {
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protected:
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std::unique_ptr<Graph> ApplyImpl(std::unique_ptr<Graph> graph) const override;
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};
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} // namespace ir
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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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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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#include "paddle/fluid/framework/ir/graph_to_program_pass.h"
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#include <string>
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#include <vector>
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#include "gtest/gtest.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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namespace ir {
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void BuildNoCircleGraph(Graph* g) {
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OpDesc op1;
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op1.SetType("op1");
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OpDesc op2;
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op2.SetType("op2");
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OpDesc op3;
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op3.SetType("op3");
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OpDesc op4;
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op4.SetType("op4");
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OpDesc op5;
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op5.SetType("op5");
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VarDesc var1("var1");
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VarDesc var2("var2");
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VarDesc var3("var3");
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VarDesc var4("var4");
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ir::Node* o1 = g->CreateOpNode(&op1);
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ir::Node* o2 = g->CreateOpNode(&op2);
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ir::Node* o3 = g->CreateOpNode(&op3);
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ir::Node* o4 = g->CreateOpNode(&op4);
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ir::Node* o5 = g->CreateOpNode(&op5);
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ir::Node* v1 = g->CreateVarNode(&var1);
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ir::Node* v2 = g->CreateVarNode(&var2);
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ir::Node* v3 = g->CreateVarNode(&var3);
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ir::Node* v4 = g->CreateVarNode(&var4);
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// o1->v1->o2
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o1->outputs.push_back(v1);
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o2->inputs.push_back(v1);
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v1->inputs.push_back(o1);
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v1->outputs.push_back(o2);
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// o2->v2->o3
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// o2->v2->o4
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o2->outputs.push_back(v2);
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o3->inputs.push_back(v2);
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o4->inputs.push_back(v2);
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v2->outputs.push_back(o3);
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v2->outputs.push_back(o4);
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v2->inputs.push_back(o2);
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// o2->v3->o5
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o2->outputs.push_back(v3);
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o5->inputs.push_back(v3);
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v3->inputs.push_back(o2);
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v3->outputs.push_back(o5);
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// o3-v4->o5
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o3->outputs.push_back(v4);
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o5->inputs.push_back(v4);
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v4->inputs.push_back(o3);
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v4->outputs.push_back(o5);
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}
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TEST(GraphToProgramPass, Basic) {
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ProgramDesc prog;
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std::unique_ptr<Graph> g(new Graph(prog));
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BuildNoCircleGraph(g.get());
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auto pass = paddle::framework::ir::PassRegistry::Instance().Get(
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"graph_to_program_pass");
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ProgramDesc compiled_prog;
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pass->SetNotOwned<paddle::framework::ProgramDesc>("program", &compiled_prog);
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pass->Apply(std::move(g));
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std::vector<OpDesc*> ops = compiled_prog.Block(0).AllOps();
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EXPECT_EQ(ops[0]->Type(), "op1");
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EXPECT_EQ(ops[1]->Type(), "op2");
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if (ops[2]->Type() == "op3") {
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EXPECT_EQ(ops[3]->Type(), "op4");
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} else if (ops[2]->Type() == "op4") {
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EXPECT_EQ(ops[3]->Type(), "op3");
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}
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EXPECT_EQ(ops[4]->Type(), "op5");
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std::unordered_set<std::string> vars;
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for (VarDesc* v : compiled_prog.Block(0).AllVars()) {
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vars.insert(v->Name());
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}
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EXPECT_TRUE(vars.find("var1") != vars.end());
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EXPECT_TRUE(vars.find("var2") != vars.end());
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EXPECT_TRUE(vars.find("var3") != vars.end());
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}
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} // namespace ir
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} // namespace framework
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||||
} // namespace paddle
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USE_PASS(graph_to_program_pass);
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||||
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