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Paddle/paddle/fluid/framework/naive_executor.cc

129 lines
4.5 KiB

// 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 <string>
#include <vector>
#include "paddle/fluid/framework/feed_fetch_method.h"
#include "paddle/fluid/framework/lod_rank_table.h"
#include "paddle/fluid/framework/lod_tensor_array.h"
#include "paddle/fluid/framework/naive_executor.h"
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/framework/reader.h"
#include "paddle/fluid/framework/variable_helper.h"
#include "paddle/fluid/string/pretty_log.h"
namespace paddle {
namespace framework {
void NaiveExecutor::Prepare(Scope *scope, const ProgramDesc &program_desc,
int block_id, bool with_feed_fetch_ops) {
if (!scope) {
scope_ = new framework::Scope;
} else {
scope_ = scope;
}
VLOG(3) << "NaiveExecutor init with scope " << scope;
CreateOps(program_desc, block_id, with_feed_fetch_ops);
}
void NaiveExecutor::Run() {
#ifndef PADDLE_ON_INFERENCE
LOG_FIRST_N(WARNING, 15) << "The NaiveExecutor can not work properly if the "
"cmake flag ON_INFER is not set.";
LOG_FIRST_N(WARNING, 15) << "Unlike the training phase, all the scopes and "
"variables will be reused to save the allocation "
"overhead.";
LOG_FIRST_N(WARNING, 15) << "Please re-compile the inference library by "
"setting the cmake flag ON_INFER=ON if you are "
"running Paddle Inference";
#endif // PADDLE_ON_INFERENCE
for (auto &op : ops_) {
VLOG(3) << std::this_thread::get_id() << " run " << op->Type()
<< " on scope " << scope_;
op->SetIsCalledByExecutor(false);
op->Run(*scope_, place_);
}
}
void NaiveExecutor::CreateVariables(const ProgramDesc &desc, int block_id,
bool persistable, Scope *scope) {
PADDLE_ENFORCE_NOT_NULL(scope);
auto &global_block = desc.Block(block_id);
const auto *anc = scope;
PADDLE_ENFORCE(anc->parent() != anc);
while (anc->parent()) {
anc = anc->parent();
}
for (auto &var : global_block.AllVars()) {
if (var->Name() == framework::kEmptyVarName) {
continue;
}
if (persistable == var->Persistable()) {
if (persistable) {
if (!anc->FindVar(var->Name())) {
auto *ptr = const_cast<Scope *>(anc)->Var(var->Name());
VLOG(3) << scope << " Create persistable variable " << var->Name()
<< ", which pointer is " << ptr;
InitializeVariable(ptr, var->GetType());
}
} else {
auto *ptr = const_cast<Scope *>(scope)->Var(var->Name());
VLOG(3) << scope << " Create variable " << var->Name()
<< ", which pointer is " << ptr;
InitializeVariable(ptr, var->GetType());
}
}
}
}
void NaiveExecutor::CreateOps(const ProgramDesc &desc, int block_id,
bool with_feed_fetch_ops) {
for (const auto &op_desc : desc.Block(block_id).AllOps()) {
if (!with_feed_fetch_ops &&
(op_desc->Type() == "feed" || op_desc->Type() == "fetch")) {
string::PrettyLogEndl(string::Style::detail(), "--- skip [%s], %s -> %s",
op_desc->Input("X")[0], op_desc->Type(),
op_desc->Output("Out")[0]);
continue;
}
ops_.emplace_back(OpRegistry::CreateOp(*op_desc));
}
}
LoDTensor *NaiveExecutor::FindTensor(const std::string &name) {
PADDLE_ENFORCE(scope_, "Need to init scope first");
auto *var = scope_->FindVar(name);
PADDLE_ENFORCE(var, "No variable [%s] in the scope");
auto *tensor = const_cast<LoDTensor *>(&var->Get<LoDTensor>());
return tensor;
}
void NaiveExecutor::CleanFeedFetchOps() {
std::vector<std::unique_ptr<OperatorBase>> ops;
for (auto &op : ops_) {
if (op->Type() != "feed" && op->Type() != "fetch") {
ops.emplace_back(std::move(op));
}
}
ops_.swap(ops);
}
} // namespace framework
} // namespace paddle