// Copyright (c) 2019 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 #include #include #include #include #include #include #include "paddle/fluid/lite/core/context.h" #include "paddle/fluid/lite/core/kernel.h" #include "paddle/fluid/lite/core/scope.h" #include "paddle/fluid/lite/model_parser/cpp/op_desc.h" namespace paddle { namespace lite { // For registry factory. struct Registry { void Touch() {} }; namespace mir { class Node; class SSAGraph; } class OpInfo; /** * The base class of an light-weight operators, currently just used in inference * to eliminate overhead of some operations in current framework. * * The Operator are designed as follows: * - it can has some members to hold the argument and some other computation * resources, * - it should act like a function call, no more logic included. */ class OpLite : public Registry { public: OpLite() = default; explicit OpLite(const std::string &type) : op_type_(type) {} explicit OpLite(const std::vector &valid_places) : valid_places_(valid_places) { LOG(INFO) << "valid places " << valid_places.size(); } void SetValidPlaces(const std::vector &places) { VLOG(3) << "valid places " << valid_places_.size(); valid_places_ = places; } const std::vector &valid_places() const { return valid_places_; } // Check the shape. virtual bool CheckShape() const { return true; } // Inference the outputs' shape. virtual bool InferShape() const { return true; } // Run this operator. virtual bool Run(); // Link the external execution environ to internal context. bool Attach(const cpp::OpDesc &opdesc, lite::Scope *scope); const OpInfo *op_info() const { return op_info_.get(); } OpInfo *mutable_op_info() { return op_info_.get(); } // Human-readable information. virtual std::string DebugString() const = 0; const Place &kernel_place() const { return kernel_place_; } // Create all the kernels for the valid targets. std::vector> CreateKernels( const std::vector &places, const std::string &kernel_type = ""); lite::Scope *scope() { return scope_; } // Assign op param to kernel. virtual void AttachKernel(KernelBase *kernel) = 0; virtual ~OpLite() = default; protected: // Attach it with the runtime environment. virtual bool AttachImpl(const cpp::OpDesc &opdesc, lite::Scope *scope) = 0; // Specify the kernel to run by default. This will specify the value of // `kernel_place_`. virtual void StaticPickKernel(const std::vector &valid_targets) { auto kernels = CreateKernels(valid_targets); kernel_ = std::move(kernels.front()); } // Wait until all the inputs' events are ready. void SyncInputEvents() {} // Record the output events, and that will tell all the dependent operators // some inputs are ready. void RecordOutputEvents() {} const Tensor *GetTensor(lite::Scope *scope, const std::string &name) const; Tensor *GetMutableTensor(lite::Scope *scope, const std::string &name) const; friend class mir::Node; friend class mir::SSAGraph; protected: // some helper functions. template const T *GetVar(Scope *scope, const std::string &name) { auto *var = scope->FindVar(name); CHECK(var) << "No var found for " << name; return &var->Get(); } template T *GetMutableVar(Scope *scope, const std::string &name) { auto *var = scope->FindVar(name); CHECK(var) << "No var found for " << name; return var->GetMutable(); } protected: lite::Scope *scope_{}; std::unique_ptr kernel_; std::string op_type_; std::vector valid_places_; Place kernel_place_{TARGET(kHost), PRECISION(kFloat)}; std::unique_ptr op_info_; }; /* * Operator Information, such as some description. It will be shared by all the * kernels of the same operator. */ class OpInfo : public cpp::OpDesc { public: OpInfo(const OpInfo &) = default; explicit OpInfo(const cpp::OpDesc &other) : cpp::OpDesc(other) {} // Collect all the input variable's name. std::vector input_names() const { std::vector res; for (auto ¶m : InputArgumentNames()) { for (auto &x : Input(param)) { res.push_back(x); } } return res; } // Collect all the output variable's name. std::vector output_names() const { std::vector res; for (auto ¶m : OutputArgumentNames()) { for (auto &x : Output(param)) { res.push_back(x); } } return res; } std::vector input_argnames() const { return InputArgumentNames(); } std::vector output_argnames() const { return OutputArgumentNames(); } bool GetInputArgname(const std::string &value_name, std::string *out) const { for (auto &item : inputs_) { auto it = std::find(item.second.begin(), item.second.end(), value_name); if (it != item.second.end()) { *out = item.first; return true; } } return false; } bool GetOutputArgname(const std::string &value_name, std::string *out) const { for (auto &item : outputs_) { auto it = std::find(item.second.begin(), item.second.end(), value_name); if (it != item.second.end()) { *out = item.first; return true; } } return false; } }; } // namespace lite } // namespace paddle