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 // A Device is a something that can perform computations as part of a 17 // model. Devices can be local (runs computation on this machine), or 18 // remote (contacts a device local to another machine using an RPC to 19 // do the work). Devices are registered in a DeviceSet, which is also 20 // responsible for the Device <-> id mapping. 21 // 22 // Device names 23 // * Every Device should have a unique name with the format: 24 // /job:___/replica:___/task:___/(gpu|cpu):___ 25 // An example name would be "/job:train/replica:0/task:3/device:GPU:2". 26 // * Task numbers are within the specified replica, so there are as 27 // many "task zeros" as replicas. 28 29 #ifndef TENSORFLOW_CORE_FRAMEWORK_DEVICE_H_ 30 #define TENSORFLOW_CORE_FRAMEWORK_DEVICE_H_ 31 32 #include <memory> 33 #include <string> 34 35 #include "tensorflow/core/framework/allocator.h" 36 #include "tensorflow/core/framework/control_flow.h" 37 #include "tensorflow/core/framework/device_attributes.pb.h" 38 #include "tensorflow/core/framework/device_base.h" 39 #include "tensorflow/core/framework/graph.pb.h" 40 #include "tensorflow/core/framework/op_kernel.h" 41 #include "tensorflow/core/framework/op_segment.h" 42 #include "tensorflow/core/framework/resource_mgr.h" 43 #include "tensorflow/core/framework/types.h" 44 #include "tensorflow/core/graph/graph.h" 45 #include "tensorflow/core/graph/types.h" 46 #include "tensorflow/core/platform/errors.h" 47 #include "tensorflow/core/platform/macros.h" 48 #include "tensorflow/core/platform/status.h" 49 #include "tensorflow/core/platform/types.h" 50 #include "tensorflow/core/util/device_name_utils.h" 51 52 namespace tensorflow { 53 54 class Device : public DeviceBase { 55 public: 56 // Callback type that takes a Status and returns void. 57 typedef std::function<void(const Status&)> DoneCallback; 58 59 Device(Env* env, const DeviceAttributes& device_attributes); 60 ~Device() override; 61 62 // Full name of this device (see top comment). name()63 const std::string& name() const override { return device_attributes_.name(); } 64 65 // Parsed name of this device parsed_name()66 const DeviceNameUtils::ParsedName& parsed_name() const { 67 return parsed_name_; 68 } 69 70 // Describes what kind of device this is. This is intended to be 71 // human-readable and not computer-parsed, except that two devices 72 // with the same device_type() are expected to perform similarly 73 // (both from a computation and communication perspective). device_type()74 const std::string& device_type() const { 75 return device_attributes_.device_type(); 76 } 77 78 // Returns an aggregation of device attributes. attributes()79 const DeviceAttributes& attributes() const override { 80 return device_attributes_; 81 } 82 83 // Performs the actual compute function. 84 // 85 // Subclasses may override this function if they wish to perform 86 // some initialization before each compute. Compute(OpKernel * op_kernel,OpKernelContext * context)87 virtual void Compute(OpKernel* op_kernel, OpKernelContext* context) { 88 op_kernel->Compute(context); 89 } 90 91 // Asynchronous kernel's compute. ComputeAsync(AsyncOpKernel * op_kernel,OpKernelContext * context,AsyncOpKernel::DoneCallback done)92 virtual void ComputeAsync(AsyncOpKernel* op_kernel, OpKernelContext* context, 93 AsyncOpKernel::DoneCallback done) { 94 op_kernel->ComputeAsync(context, std::move(done)); 95 } 96 97 // Blocks until all operations queued on the device at the time of 98 // the call have completed. Returns any error pending on the device 99 // at completion. 100 virtual Status Sync() = 0; 101 102 // Calls the given callback when all operations queued on the device at the 103 // time of the call have completed. The callback is passed any error pending 104 // on the device at completion. 105 // TODO(b/112409994): Consolidate these two APIs, removing the synchronous 106 // version. 107 virtual void Sync(const DoneCallback& done); 108 109 // On session completion, the executor may call Device::Sync() depending on 110 // flag settings. Override this to return false for devices that don't allow 111 // such calls. Instead, these devices must use other mechanisms (such as 112 // num_deferred_ops) to ensure the device has finished processing necessary 113 // work at session completion. In addition, for these devices, RefreshStatus 114 // must be called at session completion to retrieve execution result status. 115 // 116 // Devices that override this function must also implement RefreshStatus. AllowsSyncOnCompletion()117 virtual bool AllowsSyncOnCompletion() const { return true; } 118 119 // This is used in conjunction with AllowsSyncOnCompletion to allow the 120 // executor to get execution result status at session completion. 121 // 122 // For supported devices, this call returns the underlying device stream's 123 // current status in a non-blocking way, without using blocking calls such as 124 // Stream::BlockHostUntilDone or Device::Sync. When applicable, the device 125 // status is also updated with the retrieved stream status. RefreshStatus()126 virtual Status RefreshStatus() { 127 return errors::Unimplemented( 128 "RefreshStatus is not supported on this device."); 129 } 130 131 // Optionally modify the device's GraphDef before execution. 132 // 133 // This method should be considered experimental and is supplied to enable 134 // prototyping of TensorFlow device implementations that need to modify 135 // the GraphDef before execution. 136 // 137 // 'graph' supplies the partition of the graph assigned to this 138 // device. MaybeRewriteGraph(std::unique_ptr<Graph> *)139 virtual Status MaybeRewriteGraph(std::unique_ptr<Graph>* /*graph*/) { 140 return OkStatus(); 141 } 142 143 // Sets `out_context` a new DeviceContext* for executing a graph, or nullptr 144 // if the device does not support contexts. Returns an error status if any 145 // error occurred while trying to create a context, otherwise OK. 146 // 147 // The caller takes ownership of one reference on the output DeviceContext*, 148 // and should call Unref(). TryGetDeviceContext(DeviceContext ** out_context)149 virtual Status TryGetDeviceContext(DeviceContext** out_context) { 150 *out_context = nullptr; 151 return OkStatus(); 152 } 153 154 // Returns the op segment of this device. The caller can reuse op 155 // kernels registered for the same session running on this device. op_segment()156 OpSegment* op_segment() { return &op_seg_; } 157 158 // Returns the resource manager associated w/ this device. resource_manager()159 virtual ResourceMgr* resource_manager() { return rmgr_; } 160 161 // Summarizes the status of this Device, for debugging. DebugString()162 std::string DebugString() const { return device_attributes_.DebugString(); } 163 164 // Assembles the parameter components into a complete DeviceAttributes value. 165 static DeviceAttributes BuildDeviceAttributes( 166 const std::string& name, DeviceType device, Bytes memory_limit, 167 const DeviceLocality& locality, const std::string& physical_device_desc); 168 BuildDeviceAttributes(const std::string & name,DeviceType device,Bytes memory_limit,const DeviceLocality & locality)169 static DeviceAttributes BuildDeviceAttributes( 170 const std::string& name, DeviceType device, Bytes memory_limit, 171 const DeviceLocality& locality) { 172 // Pass in an empty string as physical device name. 173 return BuildDeviceAttributes(name, device, memory_limit, locality, ""); 174 } 175 176 // Updates `attributes()`, indicating the XLA global ID associated with this 177 // device. This ID is unique across clients in a multi-client setup. For TPUs 178 // this does not happen until the TPU system has been initialized. set_xla_global_id(int64_t id)179 void set_xla_global_id(int64_t id) override { 180 device_attributes_.set_xla_global_id(id); 181 } 182 183 // Clears the resource manager associated with this device. ClearResourceMgr()184 void ClearResourceMgr() { rmgr_->Clear(); } 185 IsLocal()186 virtual bool IsLocal() const { return true; } 187 188 // Informs if this Device can be used as a caller in RemoteCall operation. 189 virtual bool IsRemoteCallAllowed() const; 190 191 protected: DeleteResourceMgr()192 void DeleteResourceMgr() { 193 delete rmgr_; 194 rmgr_ = nullptr; 195 } 196 197 private: 198 DeviceAttributes device_attributes_; 199 DeviceNameUtils::ParsedName parsed_name_; 200 201 // op_seg_ maps session handle and op name to OpKernel objects. 202 OpSegment op_seg_; 203 204 // Resources associated w/ this device. E.g., shared variables, etc. 205 ResourceMgr* rmgr_ = nullptr; 206 207 TF_DISALLOW_COPY_AND_ASSIGN(Device); 208 }; 209 210 } // namespace tensorflow 211 212 #endif // TENSORFLOW_CORE_FRAMEWORK_DEVICE_H_ 213