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119 lines
4.0 KiB
119 lines
4.0 KiB
/* 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 "paddle/framework/executor.h"
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#include <algorithm>
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#include <iostream>
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#include <memory>
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#include <set>
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#include <vector>
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#include "paddle/framework/feed_fetch_type.h"
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#include "paddle/framework/lod_rank_table.h"
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#include "paddle/framework/lod_tensor.h"
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#include "paddle/framework/lod_tensor_array.h"
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#include "paddle/framework/op_registry.h"
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#include "paddle/framework/scope.h"
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namespace paddle {
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namespace framework {
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const std::string kFeedOpType = "feed";
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const std::string kFetchOpType = "fetch";
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DeviceContextPool* DeviceContextPool::pool = nullptr;
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Executor::Executor(const std::vector<platform::Place>& places) {
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DeviceContextPool& pool = DeviceContextPool::Get();
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auto borrowed_contexts = pool.Borrow(places);
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device_contexts_.swap(borrowed_contexts);
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}
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static void CreateTensor(Variable* var, proto::VarDesc::VarType var_type) {
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if (var_type == proto::VarDesc::LOD_TENSOR) {
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var->GetMutable<LoDTensor>();
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} else if (var_type == proto::VarDesc::SELECTED_ROWS) {
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var->GetMutable<SelectedRows>();
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} else if (var_type == proto::VarDesc::FEED_MINIBATCH) {
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var->GetMutable<FeedFetchList>();
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} else if (var_type == proto::VarDesc::FETCH_LIST) {
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var->GetMutable<FeedFetchList>();
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} else if (var_type == proto::VarDesc::STEP_SCOPES) {
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var->GetMutable<std::vector<framework::Scope>>();
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} else if (var_type == proto::VarDesc::LOD_RANK_TABLE) {
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var->GetMutable<LoDRankTable>();
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} else if (var_type == proto::VarDesc::LOD_TENSOR_ARRAY) {
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var->GetMutable<LoDTensorArray>();
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} else {
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PADDLE_THROW(
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"Variable type %d is not in "
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"[LoDTensor, SelectedRows, FEED_MINIBATCH, FETCH_LIST, LOD_RANK_TABLE]",
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var_type);
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}
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}
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void Executor::Run(const ProgramDesc& pdesc, Scope* scope, int block_id,
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bool create_local_scope, bool create_vars) {
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// TODO(tonyyang-svail):
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// - only runs on the first device (i.e. no interdevice communication)
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// - will change to use multiple blocks for RNN op and Cond Op
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PADDLE_ENFORCE_LT(static_cast<size_t>(block_id), pdesc.Size());
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auto& block = pdesc.Block(block_id);
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auto& device = device_contexts_[0];
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Scope* local_scope = scope;
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if (create_vars) {
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if (create_local_scope) {
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local_scope = &scope->NewScope();
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for (auto& var : block.AllVars()) {
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if (var->Name() == framework::kEmptyVarName) {
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continue;
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}
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if (var->Persistable()) {
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auto* ptr = scope->Var(var->Name());
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CreateTensor(ptr, var->GetType());
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VLOG(3) << "Create Variable " << var->Name()
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<< " global, which pointer is " << ptr;
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} else {
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auto* ptr = local_scope->Var(var->Name());
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CreateTensor(ptr, var->GetType());
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VLOG(3) << "Create Variable " << var->Name()
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<< " locally, which pointer is " << ptr;
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}
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}
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} else {
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for (auto& var : block.AllVars()) {
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auto* ptr = local_scope->Var(var->Name());
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CreateTensor(ptr, var->GetType());
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VLOG(3) << "Create variable " << var->Name() << ", which pointer is "
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<< ptr;
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}
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} // if (create_local_scope)
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} // if (create_vars)
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for (auto& op_desc : block.AllOps()) {
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auto op = paddle::framework::OpRegistry::CreateOp(*op_desc);
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VLOG(3) << op->DebugString();
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op->Run(*local_scope, *device);
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}
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if (create_local_scope) {
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scope->DeleteScope(local_scope);
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}
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}
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} // namespace framework
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} // namespace paddle
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