wehub-resource-sync
107 lines
3.7 KiB
C++
107 lines
3.7 KiB
C++
// Copyright (c) 2022 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/jit/engine/interpreter_engine.h"
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#include "paddle/fluid/framework/block_desc.h"
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#include "paddle/fluid/framework/ir/graph.h"
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#include "paddle/fluid/framework/ir/graph_helper.h"
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#include "paddle/fluid/framework/ir/pass.h"
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#include "paddle/fluid/framework/new_executor/interpretercore.h"
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#include "paddle/fluid/framework/program_desc.h"
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#include "paddle/phi/core/enforce.h"
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#include "paddle/pir/include/core/program.h"
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#include "paddle/pir/include/core/value.h"
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namespace paddle::jit {
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InterpreterEngine::InterpreterEngine(
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const std::shared_ptr<FunctionInfo> &info,
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const std::shared_ptr<VariableMap> ¶ms_dict,
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const phi::Place &place)
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: info_(info), params_dict_(params_dict), place_(place) {
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info_->RemoveDescFeedFetch();
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PADDLE_ENFORCE_GT(
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static_cast<int64_t>(info_->ProgramDesc().Block(0).OpSize()),
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0,
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common::errors::PreconditionNotMet(
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"There is no operator in ProgramDesc."));
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utils::ShareParamsIntoScope(info_->ParamNames(), params_dict_, &scope_);
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VLOG(6) << framework::GenScopeTreeDebugInfo(&scope_);
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CreateInterpreterCore();
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}
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void InterpreterEngine::CreateInterpreterCore() {
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auto &program_desc = info_->ProgramDesc();
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// apply inference pass
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framework::ir::Graph graph{program_desc};
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auto pass =
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framework::ir::PassRegistry::Instance().Get("delete_dropout_op_x_pass");
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pass->Apply(&graph);
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#ifdef PADDLE_WITH_DNNL
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auto onednn_pass =
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framework::ir::PassRegistry::Instance().Get("onednn_placement_pass");
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onednn_pass->Set("onednn_enabled_op_types",
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new std::unordered_set<std::string>({}));
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onednn_pass->Apply(&graph);
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#endif
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GraphToProgram(graph, &converted_prog_, nullptr);
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framework::interpreter::ExecutionConfig execution_config;
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execution_config.create_local_scope = false;
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execution_config.used_for_jit = true;
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auto in_names = info_->InputArgNames();
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auto out_names = info_->OutputArgNames();
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execution_config.skip_gc_vars.insert(in_names.begin(), in_names.end());
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execution_config.skip_gc_vars.insert(out_names.begin(), out_names.end());
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inner_interpreter_ = std::make_shared<InterpreterCore>(
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place_, converted_prog_.Block(0), &scope_, execution_config);
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}
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std::vector<Tensor> InterpreterEngine::operator()(
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const std::vector<Tensor> &inputs) {
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auto dense_tensors = utils::ToDenseTensors(inputs);
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return utils::ToTensors(this->operator()(dense_tensors));
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}
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std::vector<DenseTensor> InterpreterEngine::operator()(
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const std::vector<DenseTensor> &inputs) {
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utils::ShareIntoScope(info_->InputArgNames(), inputs, &scope_);
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// the latter can be moved to python side.
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auto &feed_names = info_->InputArgNames();
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phi::FetchList outs = inner_interpreter_->Run(feed_names);
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std::vector<DenseTensor> outputs;
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utils::FetchOuts(info_->OutputArgNames(), scope_, &outputs);
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scope_.DropKids();
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return outputs;
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}
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const std::shared_ptr<FunctionInfo> &InterpreterEngine::Info() const {
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return info_;
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}
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std::unique_ptr<BaseEngine> InterpreterEngine::Clone(void *stream) {
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auto *x = new InterpreterEngine(info_, params_dict_, place_);
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return std::unique_ptr<BaseEngine>(x);
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}
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} // namespace paddle::jit
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