1 /* Copyright 2015 The TensorFlow Authors. All Rights Reserved. 2 3 Licensed under the Apache License, Version 2.0 (the "License"); 4 you may not use this file except in compliance with the License. 5 You may obtain a copy of the License at 6 7 http://www.apache.org/licenses/LICENSE-2.0 8 9 Unless required by applicable law or agreed to in writing, software 10 distributed under the License is distributed on an "AS IS" BASIS, 11 WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 12 See the License for the specific language governing permissions and 13 limitations under the License. 14 ==============================================================================*/ 15 16 #ifndef TENSORFLOW_CORE_FRAMEWORK_DEVICE_FACTORY_H_ 17 #define TENSORFLOW_CORE_FRAMEWORK_DEVICE_FACTORY_H_ 18 19 #include <string> 20 #include <vector> 21 22 #include "tensorflow/core/platform/status.h" 23 #include "tensorflow/core/platform/types.h" 24 25 namespace tensorflow { 26 27 class Device; 28 struct SessionOptions; 29 30 class DeviceFactory { 31 public: ~DeviceFactory()32 virtual ~DeviceFactory() {} 33 static void Register(const std::string& device_type, DeviceFactory* factory, 34 int priority); 35 static DeviceFactory* GetFactory(const std::string& device_type); 36 37 // Append to "*devices" all suitable devices, respecting 38 // any device type specific properties/counts listed in "options". 39 // 40 // CPU devices are added first. 41 static Status AddDevices(const SessionOptions& options, 42 const std::string& name_prefix, 43 std::vector<std::unique_ptr<Device>>* devices); 44 45 // Helper for tests. Create a single device of type "type". The 46 // returned device is always numbered zero, so if creating multiple 47 // devices of the same type, supply distinct name_prefix arguments. 48 static std::unique_ptr<Device> NewDevice(const string& type, 49 const SessionOptions& options, 50 const string& name_prefix); 51 52 // Iterate through all device factories and build a list of all of the 53 // possible physical devices. 54 // 55 // CPU is are added first. 56 static Status ListAllPhysicalDevices(std::vector<string>* devices); 57 58 // Get details for a specific device among all device factories. 59 // 'device_index' indexes into devices from ListAllPhysicalDevices. 60 static Status GetAnyDeviceDetails( 61 int device_index, std::unordered_map<string, string>* details); 62 63 // For a specific device factory list all possible physical devices. 64 virtual Status ListPhysicalDevices(std::vector<string>* devices) = 0; 65 66 // Get details for a specific device for a specific factory. Subclasses 67 // can store arbitrary device information in the map. 'device_index' indexes 68 // into devices from ListPhysicalDevices. GetDeviceDetails(int device_index,std::unordered_map<string,string> * details)69 virtual Status GetDeviceDetails(int device_index, 70 std::unordered_map<string, string>* details) { 71 return Status::OK(); 72 } 73 74 // Most clients should call AddDevices() instead. 75 virtual Status CreateDevices( 76 const SessionOptions& options, const std::string& name_prefix, 77 std::vector<std::unique_ptr<Device>>* devices) = 0; 78 79 // Return the device priority number for a "device_type" string. 80 // 81 // Higher number implies higher priority. 82 // 83 // In standard TensorFlow distributions, GPU device types are 84 // preferred over CPU, and by default, custom devices that don't set 85 // a custom priority during registration will be prioritized lower 86 // than CPU. Custom devices that want a higher priority can set the 87 // 'priority' field when registering their device to something 88 // higher than the packaged devices. See calls to 89 // REGISTER_LOCAL_DEVICE_FACTORY to see the existing priorities used 90 // for built-in devices. 91 static int32 DevicePriority(const std::string& device_type); 92 }; 93 94 namespace dfactory { 95 96 template <class Factory> 97 class Registrar { 98 public: 99 // Multiple registrations for the same device type with different priorities 100 // are allowed. Priorities are used in two different ways: 101 // 102 // 1) When choosing which factory (that is, which device 103 // implementation) to use for a specific 'device_type', the 104 // factory registered with the highest priority will be chosen. 105 // For example, if there are two registrations: 106 // 107 // Registrar<CPUFactory1>("CPU", 125); 108 // Registrar<CPUFactory2>("CPU", 150); 109 // 110 // then CPUFactory2 will be chosen when 111 // DeviceFactory::GetFactory("CPU") is called. 112 // 113 // 2) When choosing which 'device_type' is preferred over other 114 // DeviceTypes in a DeviceSet, the ordering is determined 115 // by the 'priority' set during registration. For example, if there 116 // are two registrations: 117 // 118 // Registrar<CPUFactory>("CPU", 100); 119 // Registrar<GPUFactory>("GPU", 200); 120 // 121 // then DeviceType("GPU") will be prioritized higher than 122 // DeviceType("CPU"). 123 // 124 // The default priority values for built-in devices is: 125 // GPU: 210 126 // GPUCompatibleCPU: 70 127 // ThreadPoolDevice: 60 128 // Default: 50 129 explicit Registrar(const std::string& device_type, int priority = 50) { 130 DeviceFactory::Register(device_type, new Factory(), priority); 131 } 132 }; 133 134 } // namespace dfactory 135 136 #define REGISTER_LOCAL_DEVICE_FACTORY(device_type, device_factory, ...) \ 137 INTERNAL_REGISTER_LOCAL_DEVICE_FACTORY(device_type, device_factory, \ 138 __COUNTER__, ##__VA_ARGS__) 139 140 #define INTERNAL_REGISTER_LOCAL_DEVICE_FACTORY(device_type, device_factory, \ 141 ctr, ...) \ 142 static ::tensorflow::dfactory::Registrar<device_factory> \ 143 INTERNAL_REGISTER_LOCAL_DEVICE_FACTORY_NAME(ctr)(device_type, \ 144 ##__VA_ARGS__) 145 146 // __COUNTER__ must go through another macro to be properly expanded 147 #define INTERNAL_REGISTER_LOCAL_DEVICE_FACTORY_NAME(ctr) ___##ctr##__object_ 148 149 } // namespace tensorflow 150 151 #endif // TENSORFLOW_CORE_FRAMEWORK_DEVICE_FACTORY_H_ 152