/* Copyright (c) 2016 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. */ #pragma once #ifdef PADDLE_WITH_CUDA #include #include #include #include #include #include #include #include "paddle/fluid/framework/executor.h" #include "paddle/fluid/framework/op_registry.h" #include "paddle/fluid/framework/operator.h" #include "paddle/fluid/inference/anakin/convert/op_converter.h" #include "paddle/fluid/inference/anakin/engine.h" #include "paddle/fluid/inference/analysis/helper.h" namespace paddle { namespace operators { using FluidDT = framework::proto::VarType_Type; using inference::Singleton; using anakin::graph::GraphGlobalMem; using anakin::AK_FLOAT; using anakin::Precision; using anakin::saber::NV; using anakin::saber::X86; using anakin::saber::Shape; using anakin::PBlock; using anakin::PTuple; using inference::anakin::AnakinEngine; class AnakinEngineOp : public framework::OperatorBase { using AnakinNvEngineT = AnakinEngine; private: std::vector input_names_; std::unordered_set param_names_; mutable AnakinNvEngineT *anakin_engine_; std::string engine_key_; std::string engine_serialized_data_; public: AnakinEngineOp(const std::string &type, const framework::VariableNameMap &inputs, const framework::VariableNameMap &outputs, const framework::AttributeMap &attrs) : framework::OperatorBase(type, inputs, outputs, attrs) { input_names_ = Inputs("Xs"); engine_key_ = Attr("engine_key"); auto params = Attr>("parameters"); for (const auto ¶m : params) { param_names_.insert(param); } anakin_engine_ = nullptr; } protected: void RunImpl(const framework::Scope &scope, const platform::Place &dev_place) const override { RunAnakin(scope, dev_place); } void RunAnakin(const framework::Scope &scope, const platform::Place &dev_place) const { auto *engine = GetEngine(scope, dev_place); platform::DeviceContextPool &pool = platform::DeviceContextPool::Instance(); auto &dev_ctx = *pool.Get(dev_place); auto stream = reinterpret_cast(dev_ctx).stream(); PADDLE_ENFORCE(!input_names_.empty(), "should pass more than one inputs"); std::vector output_maps = Attr>("output_name_mapping"); std::map inputs; // Convert input tensor from fluid to engine. for (const auto &x : Inputs("Xs")) { if (param_names_.count(x)) continue; auto &t = inference::analysis::GetFromScope(scope, x); inputs.insert({x, &t}); } std::map outputs; int output_index = 0; for (const auto &y : Outputs("Ys")) { auto *fluid_v = scope.FindVar(y); PADDLE_ENFORCE_NOT_NULL(fluid_v, "no output variable called %s", y); auto *fluid_t = fluid_v->GetMutable(); outputs.insert({output_maps[output_index], fluid_t}); output_index += 1; } engine->Execute(inputs, outputs, stream); } AnakinNvEngineT *GetEngine(const framework::Scope &scope, const platform::Place &dev_place) const { if (anakin_engine_ == nullptr) { anakin_engine_ = inference::Singleton::Global() .Get(engine_key_); } return anakin_engine_; } }; } // namespace operators } // namespace paddle #endif // PADDLE_WITH_CUDA