/* 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 #include #include #include #include #include #include #include "paddle/fluid/distributed/auto_parallel/dist_attr.h" #include "paddle/fluid/framework/attribute.h" #include "paddle/fluid/framework/type_defs.h" #include "paddle/fluid/framework/var_desc.h" namespace paddle { namespace framework { class VarDesc; class BlockDesc; class ProgramDesc; using paddle::distributed::auto_parallel::OperatorDistAttr; class OpDesc { public: OpDesc() {} OpDesc(const std::string &type, const VariableNameMap &inputs, const VariableNameMap &outputs, const AttributeMap &attrs); OpDesc(const OpDesc &desc); OpDesc(const proto::OpDesc &desc, BlockDesc *block); explicit OpDesc(BlockDesc *block) : block_(block) {} OpDesc(const OpDesc &other, BlockDesc *block); OpDesc &operator=(const OpDesc &other); void CopyFrom(const OpDesc &op_desc); proto::OpDesc *Proto(); std::string Type() const { return desc_.type(); } void SetType(const std::string &type) { desc_.set_type(type); } const std::vector &Input(const std::string &name) const; std::vector Input(const std::string &name, bool with_attr_var) const; std::vector InputArgumentNames(bool with_attr_var = false) const; void SetInput(const std::string ¶m_name, const std::vector &args); const std::vector &Output(const std::string &name) const; bool HasOutput(const std::string &name) const; std::vector OutputArgumentNames() const; void SetOutput(const std::string ¶m_name, const std::vector &args); void RemoveOutput(const std::string &name); void RemoveInput(const std::string &name); bool HasAttr(const std::string &name, bool with_attr_var = false) const; bool HasProtoAttr(const std::string &name) const; proto::AttrType GetAttrType(const std::string &name, bool with_attr_var = false) const; std::vector AttrNames(bool with_attr_var = false) const; void SetAttr(const std::string &name, const Attribute &v); void RemoveAttr(const std::string &name); // NOTE(chenfeiyu): this template is added to avoid using a variant(Attribute) // as a parameter of a function which is bound to python, which causes // unexpected type conversion due to the overload resolution mechanism // https://pybind11.readthedocs.io/en/stable/advanced/cast/stl.html#c-17-library-containers template void SetPlainAttr(const std::string &name, const T &value) { SetAttr(name, value); } void SetVarAttr(const std::string &name, VarDesc *var); void SetVarsAttr(const std::string &name, std::vector vars); void SetBlockAttr(const std::string &name, BlockDesc *block); void SetBlocksAttr(const std::string &name, std::vector blocks); Attribute GetAttr(const std::string &name, bool with_attr_var = false) const; template T GetAttrIfExists(const std::string &name) const { T result{}; if (HasAttr(name)) { result = PADDLE_GET_CONST(T, GetAttr(name)); } return result; } const proto::OpProto::Attr &GetProtoAttr(const std::string &name) const; Attribute GetNullableAttr(const std::string &name) const; int GetBlockAttrId(const std::string &name) const; std::vector GetBlocksAttrIds(const std::string &name) const; void Rename(const std::string &old_name, const std::string &new_name); void RenameOutput(const std::string &old_name, const std::string &new_name); void RenameInput(const std::string &old_name, const std::string &new_name); // Only be used in C++ const AttributeMap &GetAttrMap() const; // Only be used in C++ void SetAttrMap(const AttributeMap &attr_map); void SetRuntimeAttrMap(const AttributeMap &attr_map); const AttributeMap &GetRuntimeAttrMap() const; std::vector InputNames(bool with_attr_var = false) const { return MapKeys(inputs_); } std::vector OutputNames() const { return MapKeys(outputs_); } const VariableNameMap &Inputs() const { return inputs_; } VariableNameMap Inputs(bool with_attr_var) const; const VariableNameMap &Outputs() const { return outputs_; } VariableNameMap *MutableInputs() { this->need_update_ = true; return &this->inputs_; } VariableNameMap *MutableOutputs() { this->need_update_ = true; return &this->outputs_; } AttributeMap *MutableAttrMap() { this->need_update_ = true; return &this->attrs_; } void CheckAttrs(); void InferShape(const BlockDesc &block); void InferVarType(BlockDesc *block) const; void SetIsTarget(bool is_target) { desc_.set_is_target(is_target); } void Flush(); BlockDesc *Block() { return this->block_; } const BlockDesc *Block() const { return this->block_; } void UpdateVarAttr(const std::string &name, const Attribute &attr); bool NeedUpdate() const { return need_update_; } // The following methods are only used for auto parallel. uint64_t Id() const { return id_; } uint64_t OriginalId() const { return original_id_; } void SetOriginalId(uint64_t original_id) { original_id_ = original_id; } const OperatorDistAttr *DistAttr() const; OperatorDistAttr *MutableDistAttr(); void SetDistAttr(const OperatorDistAttr &dist_attr); private: friend class ProgramDesc; // Find VarDesc from OpDesc located Block into global Block VarDesc *FindVarRecursive(const std::string &name); template static std::vector MapKeys(const MapType &map) { std::vector ret_val; ret_val.reserve(map.size()); std::transform( map.begin(), map.end(), std::back_inserter(ret_val), [](const typename MapType::value_type &pair) { return pair.first; }); return ret_val; } // it it really needed? or just maintain a ptr from block? proto::OpDesc desc_; BlockDesc *block_{nullptr}; // not_own // input arg name => input variable names VariableNameMap inputs_; // output arg name => output variable names VariableNameMap outputs_; // attribute name => all original attrs AttributeMap attrs_; // runtime_attrs_ contains the attributes which used for dispatching kernel // (use_mkldnn, use_cudnn, ...) or passing additional configuration for // special heterogeneous kernel (workspace_size_MB, ...). // The attributes in runtime_attrs_ are setted by framework (such as PASS), // and not in the python api. AttributeMap runtime_attrs_; // need_update_ indicate there some local changes not be synchronized. If // local changes should be synchronized, need_update_ should be set to true. bool need_update_{false}; // Note: the following members are only used for auto_parallel for now. static uint64_t GenerateId() { static std::atomic uid{0}; // Must start from one return ++uid; } uint64_t id_ = GenerateId(); uint64_t original_id_ = id_; std::unique_ptr dist_attr_; }; std::vector AttrVarNames(const Attribute &attr); } // namespace framework } // namespace paddle