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Paddle/paddle/fluid/framework/details/reference_count_pass.cc

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