Feature/mem opt pass refactor (#18735)
* first version memory optimize pass, test=develop * remove move_tensor_sharing_pass, test=develop * refine code comments, add unittests, test=develop * turn off memory_optimize by default, test=develop * follow huihuang's comments, test=develop * follow chengduoZH's comments, test=develop * fix grammar error, add const qualifier, fix pass_test exception message, test=develop * follow chengduoZH's comments 2nd, test=developDDDivano-patch-1
Zeng Jinle
6 years ago
committed by
GitHub
parent
c5f47c2107
commit
a802da650b
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// Copyright (c) 2019 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/share_tensor_buffer_functor.h"
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#include <string>
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#include <unordered_map>
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#include <unordered_set>
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#include "paddle/fluid/framework/lod_tensor.h"
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#include "paddle/fluid/framework/selected_rows.h"
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#include "paddle/fluid/platform/enforce.h"
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namespace paddle {
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namespace framework {
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namespace details {
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// TODO(zjl): support SelectedRows
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static inline const Tensor &GetTensorFromVar(const Variable *var) {
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if (var->IsType<LoDTensor>()) {
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return var->Get<LoDTensor>();
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} else {
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PADDLE_THROW("Variable must be type of LoDTensor");
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}
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}
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static inline Tensor *GetMutableTensorFromVar(Variable *var) {
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if (var->IsType<LoDTensor>()) {
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return var->GetMutable<LoDTensor>();
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} else {
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PADDLE_THROW("Variable must be type of LoDTensor");
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}
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}
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ShareTensorBufferFunctor::ShareTensorBufferFunctor(
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Scope *scope, size_t scope_idx, const std::string &op_type,
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const std::vector<const ir::MemOptVarInfo *> &in_var_infos,
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const std::vector<std::string> &out_var_names)
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: scope_(scope),
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scope_idx_(scope_idx),
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op_type_(op_type),
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in_var_infos_(in_var_infos),
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out_var_names_(out_var_names) {
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PADDLE_ENFORCE_EQ(in_var_infos_.size(), out_var_names_.size());
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for (size_t i = 0; i < in_var_infos_.size(); ++i) {
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AddReuseVarPair(in_var_infos_[i], out_var_names_[i]);
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}
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}
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std::unordered_map<std::string, std::string>
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ShareTensorBufferFunctor::ReusedVars() const {
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std::unordered_map<std::string, std::string> result;
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for (size_t i = 0; i < in_var_infos_.size(); ++i) {
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result.insert({in_var_infos_[i]->Name(), out_var_names_[i]});
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}
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return result;
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}
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void ShareTensorBufferFunctor::AddReuseVarPair(
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const ir::MemOptVarInfo *in_var_info, const std::string &out_var_name) {
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PADDLE_ENFORCE_NOT_NULL(in_var_info, "in_var_info cannot be nullptr");
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PADDLE_ENFORCE_NE(in_var_info->Name(), out_var_name,
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"in/out cannot have same name: %s", out_var_name);
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in_var_infos_.emplace_back(in_var_info);
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out_var_names_.emplace_back(out_var_name);
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}
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void ShareTensorBufferFunctor::CallOnce() {
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PADDLE_ENFORCE(in_out_vars_.empty(), "in_out_vars_ must be initialized here");
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for (size_t i = 0; i < in_var_infos_.size(); ++i) {
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auto *in_var = exec_scope_->FindVar(in_var_infos_[i]->Name());
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auto *out_var = exec_scope_->FindVar(out_var_names_[i]);
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PADDLE_ENFORCE_NOT_NULL(in_var);
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PADDLE_ENFORCE_NOT_NULL(out_var);
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PADDLE_ENFORCE_NE(in_var, out_var);
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in_out_vars_.emplace_back(in_var, out_var);
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}
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}
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void ShareTensorBufferFunctor::operator()(Scope *exec_scope) {
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if (!exec_scope_) {
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PADDLE_ENFORCE_NOT_NULL(exec_scope);
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exec_scope_ = exec_scope;
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CallOnce();
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} else {
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PADDLE_ENFORCE(exec_scope_ == exec_scope, "Scope must be the same");
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}
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for (size_t i = 0; i < in_var_infos_.size(); ++i) {
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const auto &in_tensor = GetTensorFromVar(in_out_vars_[i].first);
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auto *out_tensor = GetMutableTensorFromVar(in_out_vars_[i].second);
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auto *in_var_info = in_var_infos_[i];
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if (UNLIKELY(in_var_info->IsSkipped())) {
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// If in_var is inplaced in the previous batch and we want to fetch
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// in_var in the current batch, we have to reset memory of out_var
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// to avoid wrong calculation result.
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if (in_tensor.Holder() == out_tensor->Holder()) {
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VLOG(1) << "Clear " << out_var_names_[i]
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<< " because you may want to fetch an inplaced variable "
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<< in_var_info->Name()
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<< " in previous batch: " << in_var_info->Name() << " -> "
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<< out_var_names_[i];
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out_tensor->clear();
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}
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} else {
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out_tensor->ShareBufferWith(in_tensor);
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VLOG(2) << "Share tensor buffer when running " << op_type_ << " : "
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<< in_var_info->Name() << " -> " << out_var_names_[i];
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}
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}
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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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@ -0,0 +1,73 @@
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// Copyright (c) 2019 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 <string>
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#include <unordered_map>
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#include <unordered_set>
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#include <utility>
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#include <vector>
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#include "paddle/fluid/framework/details/op_handle_base.h"
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#include "paddle/fluid/framework/ir/memory_optimize_pass/memory_optimization_var_info.h"
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#include "paddle/fluid/framework/scope.h"
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#include "paddle/fluid/framework/variable.h"
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namespace paddle {
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namespace framework {
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namespace details {
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// NOTE(paddle-dev): ShareTensorBufferFunctor is responsible for
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// performing memory reuse in run-time. ShareTensorBufferOpHandle
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// is only a wrapper of ShareTensorBufferFunctor.
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// Once we find the run-time memory reuse strategy is time-consuming in
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// scheduling, we should need a pass to move ShareTensorBufferFunctor into
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// each ComputationOpHandle. ShareTensorBufferFunctor is preserved for
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// this probable movement.
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class ShareTensorBufferFunctor {
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public:
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ShareTensorBufferFunctor(
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Scope *scope, size_t scope_idx, const std::string &op_type,
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const std::vector<const ir::MemOptVarInfo *> &in_var_infos,
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const std::vector<std::string> &out_var_names);
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void AddReuseVarPair(const ir::MemOptVarInfo *in_var_info,
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const std::string &out_var_name);
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void operator()(Scope *exec_scope);
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std::unordered_map<std::string, std::string> ReusedVars() const;
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size_t GetScopeIdx() const { return scope_idx_; }
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Scope *GetScope() { return scope_; }
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private:
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void CallOnce();
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private:
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Scope *scope_;
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Scope *exec_scope_{nullptr};
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size_t scope_idx_;
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std::string op_type_;
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std::vector<const ir::MemOptVarInfo *> in_var_infos_;
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std::vector<std::string> out_var_names_;
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std::vector<std::pair<const Variable *, Variable *>> in_out_vars_;
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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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