1 /** 2 * Copyright 2021 Huawei Technologies Co., Ltd 3 * 4 * Licensed under the Apache License, Version 2.0 (the "License"); 5 * you may not use this file except in compliance with the License. 6 * You may obtain a copy of the License at 7 * 8 * http://www.apache.org/licenses/LICENSE-2.0 9 * 10 * Unless required by applicable law or agreed to in writing, software 11 * distributed under the License is distributed on an "AS IS" BASIS, 12 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 13 * See the License for the specific language governing permissions and 14 * limitations under the License. 15 */ 16 17 #ifndef MINDSPORE_CCSRC_RUNTIME_FRAMEWORK_ACTOR_ABSTRACT_ACTOR_H_ 18 #define MINDSPORE_CCSRC_RUNTIME_FRAMEWORK_ACTOR_ABSTRACT_ACTOR_H_ 19 20 #include <vector> 21 #include <string> 22 #include <memory> 23 #include <utility> 24 #include "mindrt/include/actor/op_actor.h" 25 #include "runtime/framework/actor/actor_common.h" 26 #include "runtime/framework/device_tensor_store.h" 27 #include "runtime/hardware/device_context.h" 28 29 namespace mindspore { 30 namespace runtime { 31 using mindspore::device::DeviceContext; 32 33 // The abstract common attributes of actors. The actor inheritance relationship: OpActor --> AbstractActor --> 34 // MemoryAwareActor --> DebugAwareActor --> KernelActor/DataSourceActor/CopyActor/LoopCountActor/OutputActor. 35 class AbstractActor : public OpActor<DeviceTensor> { 36 public: AbstractActor(const std::string & name,KernelTransformType type,const AID * recorder_aid)37 explicit AbstractActor(const std::string &name, KernelTransformType type, const AID *recorder_aid) 38 : OpActor(name), 39 type_(type), 40 recorder_aid_(recorder_aid), 41 input_datas_num_(0), 42 input_controls_num_(0), 43 running_dependent_msg_num_(0) {} 44 virtual ~AbstractActor() = default; 45 IsActive(int msg_num)46 bool IsActive(int msg_num) override { return msg_num >= running_dependent_msg_num_ ? true : false; } 47 48 // Get the position of node in the actor. FetchNodePosition(const AnfNodePtr & node)49 virtual size_t FetchNodePosition(const AnfNodePtr &node) const { return 0; } 50 51 protected: 52 friend class GraphScheduler; 53 54 // Check whether satisfy the actor running condition. 55 bool CheckRunningCondition(const OpContext<DeviceTensor> *context) const; 56 // Erase input data and input controls when finish actor running. 57 void EraseInput(const OpContext<DeviceTensor> *const context); 58 59 KernelTransformType type_; 60 61 // The device interface. 62 std::vector<const DeviceContext *> device_contexts_; 63 64 // The id of recorder actor. Send message to it for recording info. 65 const AID *recorder_aid_; 66 67 // The output result arrows of graph output. 68 std::vector<DataArrowPtr> output_result_arrows_; 69 70 // The dependent device tensor stores, the dependent expression is pair<index, AnfNode>. 71 // Index is the input position, AnfNode is the key of the device tensor store. 72 std::vector<std::pair<size_t, AnfNodePtr>> device_tensor_store_keys_; 73 74 // The dependent input actors. 75 std::vector<AID> input_data_arrow_aids_; 76 std::vector<AID> input_control_arrow_aids_; 77 // The dependent inputs number. 78 size_t input_datas_num_; 79 size_t input_controls_num_; 80 81 // The dependent messages number of actor running. 82 int running_dependent_msg_num_; 83 }; 84 85 using AbstractActorPtr = std::shared_ptr<AbstractActor>; 86 } // namespace runtime 87 } // namespace mindspore 88 89 #endif // MINDSPORE_CCSRC_RUNTIME_FRAMEWORK_ACTOR_ABSTRACT_ACTOR_H_ 90