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153 lines
6.0 KiB
153 lines
6.0 KiB
7 years ago
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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 <string>
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#include <vector>
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#include "paddle/fluid/framework/details/computation_op_handle.h"
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#include "paddle/fluid/framework/details/multi_devices_helper.h"
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#include "paddle/fluid/framework/details/reference_count_pass.h"
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namespace paddle {
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namespace framework {
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namespace details {
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std::unique_ptr<ir::Graph> ReferenceCountPass::ApplyImpl(
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std::unique_ptr<ir::Graph> graph) const {
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auto &ref_cnts = Get<DeviceReferenceCountMap>(kGlobalReferenceCount);
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auto &cur_ref_cnts = Get<AtomicDeviceReferenceCountMap>(kCurReferenceCount);
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auto &gcs = Get<DeviceGarbageCollectorMap>(kGarbageCollector);
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// It is not easy to find the right reference counts of varaibles in graph
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// Step 1: Find all variables in computation ops
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// Step 2: Find all variables in non-computation ops which refers to variables
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// in computation ops
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std::unordered_set<std::string> names;
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auto get_ref_cnts_from_compute_op = [&](
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const std::unique_ptr<OpHandleBase> &op,
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const std::vector<VarHandleBase *> &vars) {
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std::vector<std::string> var_names_in_op;
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auto *compute_op = dynamic_cast<ComputationOpHandle *>(op.get());
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if (compute_op == nullptr ||
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!platform::is_gpu_place(compute_op->GetPlace()))
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return var_names_in_op;
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auto place = boost::get<platform::CUDAPlace>(compute_op->GetPlace());
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for (VarHandleBase *var_handle_base : vars) {
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auto *var_handle = dynamic_cast<VarHandle *>(var_handle_base);
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if (var_handle == nullptr || !var_handle->Node()->IsVar()) continue;
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if (!platform::is_gpu_place(var_handle->place_) ||
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boost::get<platform::CUDAPlace>(var_handle->place_) != place)
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continue;
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VarDesc *var_desc = var_handle->Node()->Var();
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auto var_name = var_handle->Node()->Name();
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// This is wierd but there is really some variables without var_desc
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// in computation_op
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if (var_desc == nullptr) {
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if (compute_op->Node()->Op()->Block()->FindVar(var_name) == nullptr)
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continue;
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} else {
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if (var_desc->Persistable() ||
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var_desc->Proto()->type().type() != proto::VarType::LOD_TENSOR)
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continue;
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}
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// compute op only runs in one device
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if (ref_cnts[place.device]->count(var_name))
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++(*ref_cnts[place.device])[var_name];
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else
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(*ref_cnts[place.device])[var_name] = 1;
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names.insert(var_name);
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var_names_in_op.push_back(var_name);
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}
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return var_names_in_op;
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};
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auto update_ref_cnts_from_non_compute_op = [&](
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const std::unique_ptr<OpHandleBase> &op,
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const std::vector<VarHandleBase *> &vars) {
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if (dynamic_cast<ComputationOpHandle *>(op.get()) != nullptr) return;
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for (VarHandleBase *var_handle_base : vars) {
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auto *var_handle = dynamic_cast<VarHandle *>(var_handle_base);
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if (var_handle == nullptr || !var_handle->Node()->IsVar()) continue;
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auto var_name = var_handle->Node()->Name();
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auto var_place = var_handle->place_;
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if (!platform::is_gpu_place(var_place)) continue;
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auto place = boost::get<platform::CUDAPlace>(var_place);
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if (names.count(var_name) == 0) continue;
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if (ref_cnts.count(place.device) &&
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ref_cnts[place.device]->count(var_name)) {
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++(*ref_cnts[place.device])[var_name];
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}
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}
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};
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std::unordered_map<OpHandleBase *, ReferenceCountOpHandle *>
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compute_ref_cnt_map;
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auto &all_ops = graph->Get<GraphOps>(kGraphOps);
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for (auto &op : all_ops) {
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auto in_var_names = get_ref_cnts_from_compute_op(op, op->Inputs());
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auto out_var_names = get_ref_cnts_from_compute_op(op, op->Outputs());
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if (in_var_names.empty() && out_var_names.empty()) continue;
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in_var_names.insert(in_var_names.end(), out_var_names.begin(),
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out_var_names.end());
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auto *compute_op = dynamic_cast<ComputationOpHandle *>(op.get());
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auto place = boost::get<platform::CUDAPlace>(compute_op->GetPlace());
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ir::Node *ref_cnt_node =
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graph->CreateEmptyNode("reference_count", ir::Node::Type::kOperation);
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auto *ref_cnt_handle = new ReferenceCountOpHandle(
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ref_cnt_node, compute_op->GetScope(), place, in_var_names,
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gcs[place.device].get(), cur_ref_cnts[place.device].get());
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auto *dep_var = new DummyVarHandle(graph->CreateControlDepVar());
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compute_op->AddOutput(dep_var);
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ref_cnt_handle->AddInput(dep_var);
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graph->Get<GraphDepVars>(kGraphDepVars).emplace(dep_var);
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compute_ref_cnt_map[compute_op] = ref_cnt_handle;
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}
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for (auto &op : all_ops) {
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update_ref_cnts_from_non_compute_op(op, op->Inputs());
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update_ref_cnts_from_non_compute_op(op, op->Outputs());
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}
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std::vector<std::unique_ptr<OpHandleBase>> new_all_ops;
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new_all_ops.reserve(compute_ref_cnt_map.size() + all_ops.size());
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for (auto &op : all_ops) {
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auto it = compute_ref_cnt_map.find(op.get());
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if (it != compute_ref_cnt_map.end()) {
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new_all_ops.emplace_back(std::move(op));
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new_all_ops.emplace_back(std::unique_ptr<OpHandleBase>(it->second));
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} else {
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new_all_ops.emplace_back(std::move(op));
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}
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}
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all_ops.swap(new_all_ops);
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return graph;
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}
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} // namespace details
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} // namespace framework
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} // namespace paddle
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REGISTER_PASS(reference_count_pass,
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paddle::framework::details::ReferenceCountPass)
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.RequirePassAttr(paddle::framework::details::kGlobalReferenceCount)
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.RequirePassAttr(paddle::framework::details::kCurReferenceCount)
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.RequirePassAttr(paddle::framework::details::kGarbageCollector);
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