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111 lines
3.4 KiB
111 lines
3.4 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_tensor.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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Executor::Executor(const std::vector<platform::Place>& places) {
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PADDLE_ENFORCE_GT(places.size(), 0);
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device_contexts_.resize(places.size());
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for (size_t i = 0; i < places.size(); i++) {
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if (platform::is_cpu_place(places[i])) {
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device_contexts_[i] = new platform::CPUDeviceContext(
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boost::get<platform::CPUPlace>(places[i]));
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} else if (platform::is_gpu_place(places[i])) {
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#ifdef PADDLE_WITH_CUDA
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device_contexts_[i] = new platform::CUDADeviceContext(
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boost::get<platform::GPUPlace>(places[i]));
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#else
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PADDLE_THROW(
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"'GPUPlace' is not supported, Please re-compile with WITH_GPU "
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"option");
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#endif
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}
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}
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}
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Executor::~Executor() {
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for (auto& device_context : device_contexts_) {
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delete device_context;
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}
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}
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static void CreateTensor(Variable* var, VarDesc::VarType var_type) {
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if (var_type == VarDesc::LOD_TENSOR) {
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var->GetMutable<LoDTensor>();
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} else if (var_type == VarDesc::SELECTED_ROWS) {
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var->GetMutable<SelectedRows>();
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} else if (var_type == VarDesc::FEED_MINIBATCH) {
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var->GetMutable<FeedFetchList>();
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} else if (var_type == VarDesc::FETCH_LIST) {
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var->GetMutable<FeedFetchList>();
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} else {
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PADDLE_THROW(
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"Variable type must be "
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"LoDTensor/SelectedRows/FEED_MINIBATCH/FETCH_LIST.");
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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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// 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_GT(pdesc.blocks_size(), block_id);
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auto& block = pdesc.blocks(block_id);
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auto& device = device_contexts_[0];
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Scope& local_scope = scope->NewScope();
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for (auto& var : block.vars()) {
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if (var.persistable()) {
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auto* ptr = scope->Var(var.name());
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CreateTensor(ptr, var.type());
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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.type());
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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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for (auto& op_desc : block.ops()) {
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auto op = paddle::framework::OpRegistry::CreateOp(
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op_desc, const_cast<ProgramDesc*>(&pdesc));
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op->Run(local_scope, *device);
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}
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scope->DeleteScope(&local_scope);
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}
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} // namespace framework
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} // namespace paddle
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