Implement basic `Load()` and modify example based on updated inference design (#7690)
* Initial commit * Remove resolution bug * Modify IsParam * Remove small bugs * First commit unifying Run and Load * Fix bugs * Fix Cmake * Modify Cmake and dir structure * Add io.* files to inference dir * Fix include in example * Address review comments: part 1 * Address review comments: round 2 * Address review comments: round 3 * Address review comments: round 4emailweixu-patch-1
Siddharth Goyal
7 years ago
committed by
Yiqun Liu
parent
308f6022f5
commit
311334e083
@ -1,187 +0,0 @@
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/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
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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 "inference.h"
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#include <fstream>
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#include "paddle/framework/executor.h"
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#include "paddle/framework/init.h"
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#include "paddle/framework/scope.h"
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namespace paddle {
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void InferenceEngine::LoadInferenceModel(const std::string& dirname) {
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std::string model_filename = dirname + "/__model__";
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LOG(INFO) << "loading model from " << model_filename;
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std::ifstream inputfs(model_filename, std::ios::in | std::ios::binary);
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std::string program_desc_str;
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inputfs.seekg(0, std::ios::end);
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program_desc_str.resize(inputfs.tellg());
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inputfs.seekg(0, std::ios::beg);
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LOG(INFO) << "program_desc_str's size: " << program_desc_str.size();
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inputfs.read(&program_desc_str[0], program_desc_str.size());
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inputfs.close();
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program_ = new framework::ProgramDesc(program_desc_str);
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GenerateLoadProgram(dirname);
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framework::BlockDesc* global_block = program_->MutableBlock(0);
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feed_var_names_.clear();
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fetch_var_names_.clear();
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for (auto* op : global_block->AllOps()) {
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if (op->Type() == "feed") {
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feed_var_names_.insert(feed_var_names_.begin(), op->Output("Out")[0]);
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} else if (op->Type() == "fetch") {
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fetch_var_names_.push_back(op->Input("X")[0]);
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}
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}
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}
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bool InferenceEngine::IsParameter(const framework::VarDesc* var) {
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if (var->Persistable()) {
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// There are many unreachable variables in the program
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for (size_t i = 0; i < program_->Size(); ++i) {
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const framework::BlockDesc& block = program_->Block(i);
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for (auto* op : block.AllOps()) {
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if (op->Type() == "feed") {
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continue;
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}
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for (auto input_argument_name : op->InputArgumentNames()) {
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if (input_argument_name == var->Name()) {
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return true;
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}
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}
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}
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}
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}
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return false;
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}
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void InferenceEngine::GenerateLoadProgram(const std::string& dirname) {
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framework::BlockDesc* global_block = program_->MutableBlock(0);
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load_program_ = new framework::ProgramDesc();
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framework::BlockDesc* load_block = load_program_->MutableBlock(0);
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for (auto* var : global_block->AllVars()) {
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if (IsParameter(var)) {
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LOG(INFO) << "parameter's name: " << var->Name();
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framework::VarDesc* new_var = load_block->Var(var->Name());
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new_var->SetShape(var->Shape());
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new_var->SetDataType(var->GetDataType());
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new_var->SetType(var->GetType());
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new_var->SetLoDLevel(var->GetLoDLevel());
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new_var->SetPersistable(true);
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// append_op
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framework::OpDesc* op = load_block->AppendOp();
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op->SetType("load");
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op->SetOutput("Out", {new_var->Name()});
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op->SetAttr("file_path", {dirname + "/" + new_var->Name()});
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op->CheckAttrs();
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}
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}
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}
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void InferenceEngine::PrependFeedOp() {
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if (!program_) {
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LOG(FATAL) << "Please initialize the program_ first.";
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}
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framework::BlockDesc* global_block = program_->MutableBlock(0);
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// create_var
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framework::VarDesc* feed_var = global_block->Var("feed");
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feed_var->SetType(framework::proto::VarDesc::FEED_MINIBATCH);
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feed_var->SetPersistable(true);
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// prepend feed_op
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for (size_t i = 0; i < feed_var_names_.size(); ++i) {
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std::string var_name = feed_var_names_[i];
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LOG(INFO) << "feed var's name: " << var_name;
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// prepend_op
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framework::OpDesc* op = global_block->PrependOp();
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op->SetType("feed");
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op->SetInput("X", {"feed"});
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op->SetOutput("Out", {var_name});
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op->SetAttr("col", {static_cast<int>(i)});
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op->CheckAttrs();
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}
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}
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void InferenceEngine::AppendFetchOp() {
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if (!program_) {
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LOG(FATAL) << "Please initialize the program_ first.";
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}
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framework::BlockDesc* global_block = program_->MutableBlock(0);
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// create_var
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framework::VarDesc* fetch_var = global_block->Var("fetch");
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fetch_var->SetType(framework::proto::VarDesc::FETCH_LIST);
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fetch_var->SetPersistable(true);
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// append fetch_op
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for (size_t i = 0; i < fetch_var_names_.size(); ++i) {
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std::string var_name = fetch_var_names_[i];
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LOG(INFO) << "fetch var's name: " << var_name;
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// append_op
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framework::OpDesc* op = global_block->AppendOp();
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op->SetType("fetch");
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op->SetInput("X", {var_name});
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op->SetOutput("Out", {"fetch"});
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op->SetAttr("col", {static_cast<int>(i)});
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op->CheckAttrs();
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}
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}
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void InferenceEngine::Execute(const std::vector<framework::LoDTensor>& feeds,
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std::vector<framework::LoDTensor>& fetchs) {
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if (!program_ || !load_program_) {
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LOG(FATAL) << "Please initialize the program_ and load_program_ first.";
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}
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if (feeds.size() != feed_var_names_.size()) {
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LOG(FATAL) << "Please feed " << feed_var_names_.size() << " input Tensors.";
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}
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auto* place = new platform::CPUPlace();
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framework::InitDevices();
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framework::Executor* executor = new framework::Executor(*place);
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framework::Scope* scope = new framework::Scope();
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executor->Run(*load_program_, scope, 0, true, true);
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std::map<std::string, const framework::LoDTensor*> feed_targets;
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std::map<std::string, framework::LoDTensor*> fetch_targets;
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// set_feed_variable
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for (size_t i = 0; i < feed_var_names_.size(); ++i) {
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feed_targets[feed_var_names_[i]] = &feeds[i];
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}
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// get_fetch_variable
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fetchs.resize(fetch_var_names_.size());
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for (size_t i = 0; i < fetch_var_names_.size(); ++i) {
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fetch_targets[fetch_var_names_[i]] = &fetchs[i];
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}
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executor->Run(*program_, scope, feed_targets, fetch_targets);
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delete place;
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delete scope;
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delete executor;
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}
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} // namespace paddle
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@ -1,48 +0,0 @@
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/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
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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/framework/block_desc.h"
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#include "paddle/framework/lod_tensor.h"
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#include "paddle/framework/program_desc.h"
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namespace paddle {
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class InferenceEngine {
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public:
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InferenceEngine() : program_(nullptr), load_program_(nullptr) {}
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~InferenceEngine() {
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delete program_;
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delete load_program_;
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}
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void LoadInferenceModel(const std::string& dirname);
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void Execute(const std::vector<framework::LoDTensor>& feeds,
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std::vector<framework::LoDTensor>& fetchs);
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private:
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bool IsParameter(const framework::VarDesc* var);
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void GenerateLoadProgram(const std::string& dirname);
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void PrependFeedOp();
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void AppendFetchOp();
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private:
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framework::ProgramDesc* program_;
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framework::ProgramDesc* load_program_;
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std::vector<std::string> feed_var_names_;
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std::vector<std::string> fetch_var_names_;
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};
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} // namespace paddle
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@ -0,0 +1,97 @@
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/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserve.
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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/inference/io.h"
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#include <fstream>
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namespace paddle {
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namespace inference {
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const std::string kFeedOpType = "feed";
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bool IsParameter(const framework::VarDesc* var,
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const framework::ProgramDesc* main_program) {
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if (var->Persistable()) {
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// There are many unreachable variables in the program
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for (size_t i = 0; i < main_program->Size(); ++i) {
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const framework::BlockDesc& block = main_program->Block(i);
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for (auto* op : block.AllOps()) {
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if (op->Type() == kFeedOpType) {
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continue;
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}
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for (auto input_argument_name : op->InputArgumentNames()) {
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if (input_argument_name == var->Name()) {
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return true;
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}
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}
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}
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}
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}
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return false;
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}
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void LoadPersistables(framework::Executor& executor,
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framework::Scope& scope,
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const std::string& dirname,
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framework::ProgramDesc* main_program) {
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framework::BlockDesc* global_block = main_program->MutableBlock(0);
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framework::ProgramDesc* load_program = new framework::ProgramDesc();
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framework::BlockDesc* load_block = load_program->MutableBlock(0);
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for (auto* var : global_block->AllVars()) {
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if (IsParameter(var, main_program)) {
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LOG(INFO) << "parameter's name: " << var->Name();
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framework::VarDesc* new_var = load_block->Var(var->Name());
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new_var->SetShape(var->Shape());
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new_var->SetDataType(var->GetDataType());
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new_var->SetType(var->GetType());
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new_var->SetLoDLevel(var->GetLoDLevel());
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new_var->SetPersistable(true);
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// append_op
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framework::OpDesc* op = load_block->AppendOp();
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op->SetType("load");
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op->SetOutput("Out", {new_var->Name()});
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op->SetAttr("file_path", {dirname + "/" + new_var->Name()});
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op->CheckAttrs();
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}
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}
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executor.Run(*load_program, &scope, 0, true, true);
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delete load_program;
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}
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framework::ProgramDesc* Load(framework::Executor& executor,
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framework::Scope& scope,
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const std::string& dirname) {
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std::string model_filename = dirname + "/__model__";
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LOG(INFO) << "loading model from " << model_filename;
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std::ifstream inputfs(model_filename, std::ios::in | std::ios::binary);
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std::string program_desc_str;
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inputfs.seekg(0, std::ios::end);
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program_desc_str.resize(inputfs.tellg());
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inputfs.seekg(0, std::ios::beg);
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LOG(INFO) << "program_desc_str's size: " << program_desc_str.size();
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inputfs.read(&program_desc_str[0], program_desc_str.size());
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inputfs.close();
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framework::ProgramDesc* main_program =
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new framework::ProgramDesc(program_desc_str);
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LoadPersistables(executor, scope, dirname, main_program);
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return main_program;
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}
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} // namespace inference
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} // namespace paddle
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@ -0,0 +1,41 @@
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/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserve.
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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 <string>
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#include <vector>
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#include "paddle/framework/block_desc.h"
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#include "paddle/framework/executor.h"
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#include "paddle/framework/program_desc.h"
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#include "paddle/framework/scope.h"
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#include "paddle/framework/var_desc.h"
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namespace paddle {
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namespace inference {
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bool IsParameter(const framework::VarDesc* var,
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const framework::ProgramDesc* main_program);
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void LoadPersistables(framework::Executor& executor,
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framework::Scope& scope,
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const std::string& dirname,
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framework::ProgramDesc* main_program);
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framework::ProgramDesc* Load(framework::Executor& executor,
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framework::Scope& scope,
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const std::string& dirname);
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} // namespace inference
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} // namespace paddle
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