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112 lines
3.7 KiB
112 lines
3.7 KiB
/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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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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http://www.apache.org/licenses/LICENSE-2.0
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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 <memory>
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#include <set>
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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 <vector>
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#include "paddle/fluid/framework/operator.h"
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#include "paddle/fluid/framework/program_desc.h"
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#include "paddle/fluid/framework/var_desc.h"
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#include "ngraph/ngraph.hpp"
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namespace paddle {
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namespace operators {
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// cache engine repetitives
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struct EngineCache {
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std::shared_ptr<ngraph::runtime::Executable> ngraph_handle;
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std::set<std::string> persistables;
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std::vector<std::string> var_in;
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std::vector<std::string> var_out;
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std::vector<size_t> var_in_updates;
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bool is_test = true;
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};
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// perform graph build through bridge and execute computation
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class NgraphEngine {
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public:
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explicit NgraphEngine(const framework::Scope& scope,
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const platform::Place& place,
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const framework::ExecutionContext& ctx);
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void Run(const framework::Scope& scope, const platform::Place& place) const;
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static bool is_training;
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static const framework::BlockDesc* p_bdesc;
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static std::vector<std::string> feed_vars, fetch_vars;
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static void FuseNgraphOps(
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const framework::BlockDesc& prog,
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std::vector<std::unique_ptr<framework::OperatorBase>>* ops);
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private:
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static std::unordered_map<std::string, EngineCache> engine_cache;
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static std::unordered_map<
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std::string, std::vector<std::shared_ptr<ngraph::runtime::Tensor>>>
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t_in_cache_;
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static framework::Variable* pre_var_ptr;
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const framework::Scope& scope_;
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const platform::Place& place_;
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std::vector<std::shared_ptr<framework::OperatorBase>> fused_ops_;
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std::unordered_map<std::string, ngraph::element::Type> var_type_map_;
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std::set<std::string> persistables_;
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std::unordered_set<std::string> post_op_inputs_;
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bool is_test_{true};
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std::string func_cache_key_;
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// ngraph backend eg. CPU
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static std::shared_ptr<ngraph::runtime::Backend> backend_;
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// var_name of inputs
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std::vector<std::string> var_in_;
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// var_name of outputs from fetch in order
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std::vector<std::string> var_out_;
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// non-persitable var_in
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std::vector<size_t> var_in_updates_;
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// map input vars to nodes
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std::shared_ptr<
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std::unordered_map<std::string, std::shared_ptr<ngraph::Node>>>
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var_in_node_map_;
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// map each var name with a ngraph node
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std::shared_ptr<
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std::unordered_map<std::string, std::shared_ptr<ngraph::Node>>>
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var_node_map_;
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// prepare info for ngraph engine need
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void Prepare(const framework::ExecutionContext& ctx);
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// get ngraph engine input and output list
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void BuildNgIO(const std::vector<framework::OpDesc*>& op_descs,
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const std::vector<int>& interval);
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// get ngraph input and define ngraph input parameters
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void GetNgInputShape();
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// Call ngraph bridge to map ops
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void BuildNgNodes();
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// build ngraph function call
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std::shared_ptr<ngraph::Function> BuildNgFunction(
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const framework::ExecutionContext& ctx);
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// clear ngraph engine cache and t_in cache
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void ClearNgCache();
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// Check cache for ngraph function or otherwise build the function
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void GetNgFunction(const framework::ExecutionContext& ctx);
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};
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} // namespace operators
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} // namespace paddle
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