Merge branch 'develop' of https://github.com/PaddlePaddle/Paddle into disable_prelu_test_local
minqiyang
7 years ago
commit
efe88ab9f9
@ -0,0 +1,192 @@
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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_fuse_pass.h"
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#include <string>
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#include <vector>
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#include "paddle/fluid/platform/enforce.h"
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namespace paddle {
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namespace framework {
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namespace ir {
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bool VarOutLinksToOp(Node* node, const std::string& op_type) {
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for (auto* out : node->outputs) {
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if (out->IsOp() && out->Op()->Type() == op_type) {
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return true;
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}
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}
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return false;
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}
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void BuildFCPattern(PDPattern* pattern) {
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// make sure the selected MUL op has one input argument is a parameter.
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auto* mul_parameter_var = pattern->NewNode(
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[](Node* node) {
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return node->IsVar() && node->outputs.size() == 1UL &&
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node->outputs.front()->Op()->Type() == "mul" && node->Var() &&
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node->Var()->Persistable(); // check is a parameter
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},
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"mul_weight" /*name*/);
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auto* mul_tmp_input_var = pattern->NewNode(
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[](Node* node) {
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bool result =
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node->IsVar() && node->outputs.size() >= 1UL && node->Var() &&
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!node->Var()->Persistable(); // this input is not an parameter.
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if (!result) return false;
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// check whether one output is MUL op.
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for (auto* op : node->outputs) {
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if (op->IsOp() && op->Op()->Type() == "mul") return true;
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}
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return false;
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},
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"mul_tmp_var" /*name*/);
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// select a MUL op
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auto* mul_op = pattern->NewNode(
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[](Node* node) {
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return node->IsOp() && // start from an Op
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node->Op()->Type() == "mul"; // type is mul
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// the output should be consumed only by one element_add, that check
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// leaves in a Var PDNode.
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},
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"mul" /*name*/);
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// make sure the MUL op's output has only one consumer and links to an
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// ELEMENTWISE_ADD op.
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auto* mul_out_var = pattern->NewNode(
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[](Node* node) {
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return node->IsVar() && // starts from a Var
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node->outputs.size() == 1UL && // only has one consumer
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node->outputs.front()->IsOp() && // check basic logic
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node->Var() && // not a ControlDepVar
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node->outputs.front()->Op()->Type() ==
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"elementwise_add"; // a very strong validation
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},
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"mul_out");
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// this check is not essential, just to make the corresponding variable Node
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// retrival easier.
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auto* elementwise_add_tmp_var = pattern->NewNode(
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[](Node* node) {
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return node->IsVar() && node->outputs.size() >= 1UL && node->Var() &&
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VarOutLinksToOp(node, "elementwise_add");
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},
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"elementwise_add_tmpvar");
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// select an ELEMENTWISE_ADD op
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auto* elementwise_add_op = pattern->NewNode(
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[](Node* node) {
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return node->IsOp() && node->Op()->Type() == "elementwise_add";
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},
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"elementwise_add" /*name*/);
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// get the ELEMENTWISE_ADD op's output
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auto* elementwise_add_out_var = pattern->NewNode(
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[](Node* node) {
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return node->IsVar() && node->inputs.size() == 1UL && node->Var() &&
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node->inputs.front()->Op()->Type() == "elementwise_add";
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},
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"elementwise_add_out");
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pattern->AddEdge(mul_parameter_var, mul_op);
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pattern->AddEdge(mul_tmp_input_var, mul_op);
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pattern->AddEdge(mul_op, mul_out_var);
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pattern->AddEdge(mul_out_var, elementwise_add_op);
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pattern->AddEdge(elementwise_add_tmp_var, elementwise_add_op);
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pattern->AddEdge(elementwise_add_op, elementwise_add_out_var);
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}
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// Replace the node `from` in the links to `to`
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bool LinksReplace(std::vector<Node*>* links, Node* from, Node* to) {
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for (auto*& n : *links) {
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if (n == from) {
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n = to;
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return true;
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}
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}
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return false;
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}
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std::unique_ptr<ir::Graph> FCFusePass::ApplyImpl(
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std::unique_ptr<ir::Graph> graph) const {
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PADDLE_ENFORCE(graph.get());
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std::unordered_set<Node*> nodes2delete;
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GraphPatternDetecter gpd;
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BuildFCPattern(gpd.mutable_pattern());
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#define GET_NODE(id) \
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PADDLE_ENFORCE(subgraph.count(gpd.pattern().RetriveNode(#id)), \
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"pattern has no Node called %s", #id); \
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auto* id = subgraph.at(gpd.pattern().RetriveNode(#id)); \
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PADDLE_ENFORCE_NOT_NULL(id, "subgraph has no node %s", #id);
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auto handler = [&](const GraphPatternDetecter::subgraph_t& subgraph,
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Graph* g) {
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VLOG(4) << "handle FC fuse";
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// Currently, there is no FC op available, so I will just simulate the
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// scenerio.
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// FC's fusion is simple, just op fuse, no need to process the
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// parameters.
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GET_NODE(mul_tmp_var); // x
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GET_NODE(mul_weight); // Y
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GET_NODE(elementwise_add_tmpvar); // bias
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GET_NODE(elementwise_add_out); // Out
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GET_NODE(mul); // MUL op
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GET_NODE(elementwise_add); // ELEMENT_ADD op
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GET_NODE(mul_out); // tmp
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#undef GET_NODE
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// Create an FC Node.
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OpDesc desc;
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std::string fc_x_in = mul_tmp_var->Name();
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std::string fc_Y_in = mul_weight->Name();
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std::string fc_bias_in = elementwise_add_tmpvar->Name();
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std::string fc_out = elementwise_add_out->Name();
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desc.SetInput("Input", std::vector<std::string>({fc_x_in}));
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desc.SetInput("W", std::vector<std::string>({fc_Y_in}));
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desc.SetInput("Bias", std::vector<std::string>({fc_bias_in}));
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desc.SetOutput("Out", std::vector<std::string>({fc_out}));
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desc.SetType("fc");
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auto fc_node = g->CreateOpNode(&desc); // OpDesc will be copied.
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fc_node->inputs =
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std::vector<Node*>({mul_tmp_var, mul_weight, elementwise_add_tmpvar});
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fc_node->outputs.push_back(elementwise_add_out);
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// Update link relatons
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PADDLE_ENFORCE(LinksReplace(&mul_tmp_var->outputs, mul, fc_node));
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PADDLE_ENFORCE(LinksReplace(&mul_weight->outputs, mul, fc_node));
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PADDLE_ENFORCE(LinksReplace(&elementwise_add_tmpvar->outputs,
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elementwise_add, fc_node));
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PADDLE_ENFORCE(
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LinksReplace(&elementwise_add_out->inputs, elementwise_add, fc_node));
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// Drop old nodes
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graph->RemoveNode(mul);
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graph->RemoveNode(elementwise_add);
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graph->RemoveNode(mul_out); // tmp variable
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};
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gpd(graph.get(), handler);
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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_fuse_pass, paddle::framework::ir::FCFusePass);
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@ -0,0 +1,36 @@
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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.
|
||||
// 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_detecter.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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/*
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* Fuse the MUL and ELEMENTWISE_ADD to a FCOp.
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*/
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class FCFusePass : public Pass {
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public:
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virtual ~FCFusePass() {}
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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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@ -0,0 +1,90 @@
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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_fuse_pass.h"
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#include <gtest/gtest.h>
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namespace paddle {
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namespace framework {
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namespace ir {
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void SetOp(ProgramDesc* prog, const std::string& type,
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const std::vector<std::string>& inputs,
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const std::vector<std::string>& outputs) {
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auto* op = prog->MutableBlock(0)->AppendOp();
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op->SetType(type);
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op->SetInput("Xs", inputs);
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op->SetOutput("Ys", outputs);
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}
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// a->OP0->b
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// a->OP1->c
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// (b, c)->mul->d
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// (d, e)->elementwise_add->f
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ProgramDesc BuildProgramDesc() {
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ProgramDesc prog;
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for (auto& v : std::vector<std::string>({"a", "b", "c", "d", "e", "f"})) {
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auto* var = prog.MutableBlock(0)->Var(v);
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var->SetType(proto::VarType::SELECTED_ROWS);
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if (v == "c") {
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var->SetPersistable(true);
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}
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}
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SetOp(&prog, "OP0", std::vector<std::string>({"a"}),
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std::vector<std::string>({"b"}));
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SetOp(&prog, "OP1", std::vector<std::string>({"a"}),
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std::vector<std::string>({"c"}));
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SetOp(&prog, "mul", std::vector<std::string>({"b", "c"}),
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std::vector<std::string>({"d"}));
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SetOp(&prog, "elementwise_add", std::vector<std::string>({"d", "e"}),
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std::vector<std::string>({"f"}));
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return prog;
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}
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TEST(FCFusePass, basic) {
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auto prog = BuildProgramDesc();
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std::unique_ptr<ir::Graph> graph(new ir::Graph(prog));
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auto pass = PassRegistry::Instance().Get("fc_fuse_pass");
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int pre_nodes = graph->Nodes().size();
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graph = pass->Apply(std::move(graph));
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int after_nodes = graph->Nodes().size();
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// Remove 3 Nodes: MUL,ELEMENTWISE_ADD, mul_out
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// Add 1 Node: FC
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EXPECT_EQ(pre_nodes - 2, after_nodes);
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// Assert fc op in newly generated graph
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int fc_count = 0;
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for (auto* node : graph->Nodes()) {
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if (node->IsOp() && node->Op()->Type() == "fc") {
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++fc_count;
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}
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}
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EXPECT_EQ(fc_count, 1);
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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(fc_fuse_pass);
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@ -0,0 +1,69 @@
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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.
|
||||
// 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.
|
||||
|
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#include <algorithm>
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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 ir {
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class InferCleanGraphPass : public Pass {
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public:
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virtual ~InferCleanGraphPass() {}
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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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PADDLE_ENFORCE(graph.get());
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auto is_valid_node = [](Node* x) {
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return x && IsControlDepVar(*x) && x->IsVar() && !x->Var();
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};
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std::unordered_set<Node*> invalid_nodes;
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for (auto* node : graph->Nodes()) {
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if (is_valid_node(node)) {
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invalid_nodes.insert(node);
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}
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}
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// remove nodes from the graph.
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for (auto* node : invalid_nodes) {
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graph->RemoveNode(node);
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}
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// clean edges.
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for (auto* node : graph->Nodes()) {
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CleanEdges(&node->inputs, invalid_nodes);
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CleanEdges(&node->outputs, invalid_nodes);
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}
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return graph;
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}
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void CleanEdges(std::vector<Node*>* nodes,
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const std::unordered_set<Node*>& to_remove) const {
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auto it = std::remove_if(nodes->begin(), nodes->end(),
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[&](Node* x) { return to_remove.count(x); });
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nodes->erase(it, nodes->end());
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}
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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(infer_clean_graph_pass,
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paddle::framework::ir::InferCleanGraphPass);
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@ -0,0 +1,15 @@
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// 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.
|
||||
|
||||
#include "paddle/fluid/inference/analysis/fluid_to_ir_pass.h"
|
||||
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