revert-15774-anakin_subgraph_engine
tensor-tang
6 years ago
commit
c2ccf14590
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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 "paddle/fluid/framework/details/memory_early_delete_pass.h"
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#include <queue>
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#include <string>
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#include <vector>
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#include "paddle/fluid/framework/details/memory_optimize_helper.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_helper.h"
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#include "paddle/fluid/framework/ir/graph_helper.h"
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namespace paddle {
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namespace framework {
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namespace details {
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static ComputationOpHandle* FindNextComputationOpHandle(VarHandle* var_in) {
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std::queue<VarHandleBase*> queue;
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queue.push(var_in);
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do {
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auto* var = queue.front();
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queue.pop();
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for (auto* op : var->PendingOps()) {
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auto* compute_op = dynamic_cast<ComputationOpHandle*>(op);
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if (compute_op != nullptr && compute_op->GetPlace() == var_in->place()) {
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return compute_op;
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}
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for (auto* out_var : op->Outputs()) {
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queue.push(out_var);
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}
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}
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} while (!queue.empty());
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return nullptr;
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}
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std::unique_ptr<ir::Graph> MemoryEarlyDeletePass::ApplyImpl(
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std::unique_ptr<ir::Graph> graph) const {
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auto& graph_pool = Get<GraphNodePool>(kGraphNodePool);
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auto& gcs = Get<GarbageCollectorMap>(kGarbageCollector);
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std::unordered_map<std::string, std::unordered_set<OpDesc*>> unlived_vars;
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unlived_vars.reserve(graph_pool.size());
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for (auto& pair : graph_pool) {
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unlived_vars.insert(std::make_pair(pair.first, pair.second));
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}
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auto compare_and_insert_early_delete_op = [&](
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OpHandleBase* op, const std::vector<VarHandleBase*>& vars) {
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if (unlived_vars.empty()) return;
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// unlived vars can be deleted after the last used op has finished.
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auto* compute_op = dynamic_cast<ComputationOpHandle*>(op);
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const auto& places = Get<std::vector<platform::Place>>(kAllPlaces);
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for (auto& var : vars) {
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auto* var_handle = dynamic_cast<VarHandle*>(var);
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auto var_name = var->Node()->Name();
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auto& var_place = var_handle->place();
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if (unlived_vars.count(var_name) == 0) continue;
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if (!unlived_vars[var_name].empty()) {
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if (compute_op != nullptr &&
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unlived_vars[var_name].count(compute_op->Node()->Op()) != 0) {
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unlived_vars[var_name].erase(compute_op->Node()->Op());
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}
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continue;
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}
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if (var_handle == nullptr || !var_handle->Node()->IsVar() ||
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var_handle->Node()->IsCtrlVar())
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continue;
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// shameless copyed from reference count pass.
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if (compute_op == nullptr) {
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// use next computation op scope
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compute_op = FindNextComputationOpHandle(var_handle);
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}
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auto* early_delete_node =
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graph->CreateEmptyNode("early_delete", ir::Node::Type::kOperation);
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GarbageCollector* gc = gcs.at(places[compute_op->GetScopeIdx()]).get();
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auto* early_delete_handle = new EarlyDeleteOpHandle(
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early_delete_node, compute_op->GetScope(), var_place, {var_name}, gc);
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if (compute_op->Outputs().empty()) {
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auto* dep_var = new DummyVarHandle(graph->CreateControlDepVar());
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compute_op->AddOutput(dep_var);
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graph->Get<GraphDepVars>(kGraphDepVars).emplace(dep_var);
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}
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early_delete_handle->AddInput(compute_op->Outputs().front());
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VLOG(5) << "Add early delete op " << var_name << " to Operator"
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<< compute_op->Name();
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}
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};
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auto all_ops = ir::FilterByNodeWrapper<OpHandleBase>(*graph);
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for (auto& op : all_ops) {
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compare_and_insert_early_delete_op(op, op->Inputs());
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compare_and_insert_early_delete_op(op, op->Outputs());
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}
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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(memory_early_delete_pass,
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paddle::framework::details::MemoryEarlyDeletePass)
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.RequireGraphAttr(paddle::framework::details::kGraphNodePool)
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.RequireGraphAttr(paddle::framework::details::kGarbageCollector);
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@ -1,32 +0,0 @@
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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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#pragma once
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#include "paddle/fluid/framework/details/early_delete_op_handle.h"
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#include "paddle/fluid/framework/ir/graph.h"
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#include "paddle/fluid/framework/ir/pass.h"
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namespace paddle {
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namespace framework {
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namespace details {
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class MemoryEarlyDeletePass : public ir::Pass {
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protected:
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std::unique_ptr<ir::Graph> ApplyImpl(
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std::unique_ptr<ir::Graph> graph) const override;
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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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