Kevin May | 42477c1 | 2020-03-26 13:34:14 +0000 | [diff] [blame] | 1 | // |
| 2 | // Copyright © 2020 Arm Ltd. All rights reserved. |
| 3 | // SPDX-License-Identifier: MIT |
| 4 | // |
Sadik Armagan | d7be72e | 2020-04-23 12:56:05 +0100 | [diff] [blame] | 5 | // Note: the ArmnnFencedExecutionCallback and code snippet in the executeFenced() function |
| 6 | // in this file is based on Android code |
| 7 | // under the Apache 2.0 license. See comments below for details. |
| 8 | // |
Kevin May | 42477c1 | 2020-03-26 13:34:14 +0000 | [diff] [blame] | 9 | |
| 10 | #define LOG_TAG "ArmnnDriver" |
| 11 | |
| 12 | #include "ArmnnPreparedModel_1_3.hpp" |
| 13 | #include "Utils.hpp" |
| 14 | |
| 15 | #include <Utils.h> |
Sadik Armagan | d7be72e | 2020-04-23 12:56:05 +0100 | [diff] [blame] | 16 | #include <android/sync.h> |
Kevin May | 42477c1 | 2020-03-26 13:34:14 +0000 | [diff] [blame] | 17 | #include <log/log.h> |
| 18 | #include <OperationsUtils.h> |
| 19 | #include <ExecutionBurstServer.h> |
| 20 | #include <ValidateHal.h> |
| 21 | |
| 22 | #include <cassert> |
| 23 | #include <cinttypes> |
| 24 | |
| 25 | using namespace android; |
| 26 | using namespace android::hardware; |
| 27 | |
| 28 | namespace { |
| 29 | |
| 30 | static const Timing g_NoTiming = {.timeOnDevice = UINT64_MAX, .timeInDriver = UINT64_MAX}; |
| 31 | using namespace armnn_driver; |
| 32 | using TimePoint = std::chrono::steady_clock::time_point; |
| 33 | |
| 34 | TimePoint Now() |
| 35 | { |
| 36 | return std::chrono::steady_clock::now(); |
| 37 | } |
| 38 | |
| 39 | unsigned long MicrosecondsDuration(TimePoint endPoint, TimePoint startPoint) |
| 40 | { |
| 41 | return static_cast<unsigned long>(std::chrono::duration_cast<std::chrono::microseconds>( |
| 42 | endPoint - startPoint).count()); |
| 43 | } |
| 44 | |
| 45 | void NotifyCallbackAndCheck(const ::android::sp<V1_0::IExecutionCallback>& callback, |
| 46 | V1_3::ErrorStatus errorStatus, |
| 47 | std::vector<OutputShape>, |
| 48 | const Timing, |
| 49 | std::string callingFunction) |
| 50 | { |
| 51 | Return<void> returned = callback->notify(convertToV1_0(errorStatus)); |
| 52 | // This check is required, if the callback fails and it isn't checked it will bring down the service |
| 53 | if (!returned.isOk()) |
| 54 | { |
| 55 | ALOGE("ArmnnDriver::%s: hidl callback failed to return properly: %s", |
| 56 | callingFunction.c_str(), returned.description().c_str()); |
| 57 | } |
| 58 | } |
| 59 | |
| 60 | void NotifyCallbackAndCheck(const ::android::sp<V1_2::IExecutionCallback>& callback, |
| 61 | V1_3::ErrorStatus errorStatus, |
| 62 | std::vector<OutputShape> outputShapes, |
| 63 | const Timing timing, |
| 64 | std::string callingFunction) |
| 65 | { |
| 66 | Return<void> returned = callback->notify_1_2(convertToV1_0(errorStatus), outputShapes, timing); |
| 67 | // This check is required, if the callback fails and it isn't checked it will bring down the service |
| 68 | if (!returned.isOk()) |
| 69 | { |
| 70 | ALOGE("ArmnnDriver::%s: hidl callback failed to return properly: %s", |
| 71 | callingFunction.c_str(), returned.description().c_str()); |
| 72 | } |
| 73 | } |
| 74 | |
| 75 | void NotifyCallbackAndCheck(const ::android::sp<V1_3::IExecutionCallback>& callback, |
| 76 | V1_3::ErrorStatus errorStatus, |
| 77 | std::vector<OutputShape> outputShapes, |
| 78 | const Timing timing, |
| 79 | std::string callingFunction) |
| 80 | { |
| 81 | Return<void> returned = callback->notify_1_3(errorStatus, outputShapes, timing); |
| 82 | // This check is required, if the callback fails and it isn't checked it will bring down the service |
| 83 | if (!returned.isOk()) |
| 84 | { |
| 85 | ALOGE("ArmnnDriver::%s: hidl callback failed to return properly: %s", |
| 86 | callingFunction.c_str(), returned.description().c_str()); |
| 87 | } |
| 88 | } |
| 89 | |
| 90 | bool ValidateRequestArgument(const RequestArgument& requestArg, const armnn::TensorInfo& tensorInfo) |
| 91 | { |
| 92 | if (requestArg.dimensions.size() != 0) |
| 93 | { |
| 94 | if (requestArg.dimensions.size() != tensorInfo.GetNumDimensions()) |
| 95 | { |
| 96 | ALOGE("Mismatched dimensions (request argument: %zu, expected: %u)", |
| 97 | requestArg.dimensions.size(), tensorInfo.GetNumDimensions()); |
| 98 | return false; |
| 99 | } |
| 100 | |
| 101 | for (unsigned int d = 0; d < tensorInfo.GetNumDimensions(); ++d) |
| 102 | { |
Finn Williams | a4983ce | 2020-07-23 12:55:12 +0100 | [diff] [blame] | 103 | if (requestArg.dimensions[d] != 0 && requestArg.dimensions[d] != tensorInfo.GetShape()[d]) |
Kevin May | 42477c1 | 2020-03-26 13:34:14 +0000 | [diff] [blame] | 104 | { |
| 105 | ALOGE("Mismatched size for dimension %d (request argument: %u, expected %u)", |
| 106 | d, requestArg.dimensions[d], tensorInfo.GetShape()[d]); |
| 107 | return false; |
| 108 | } |
| 109 | } |
| 110 | } |
| 111 | |
| 112 | return true; |
| 113 | } |
| 114 | |
| 115 | armnn::Tensor GetTensorForRequestArgument(const RequestArgument& requestArg, |
| 116 | const armnn::TensorInfo& tensorInfo, |
| 117 | const std::vector<::android::nn::RunTimePoolInfo>& requestPools) |
| 118 | { |
| 119 | if (!ValidateRequestArgument(requestArg, tensorInfo)) |
| 120 | { |
| 121 | return armnn::Tensor(); |
| 122 | } |
| 123 | |
| 124 | return armnn::Tensor(tensorInfo, GetMemoryFromPool(requestArg.location, requestPools)); |
| 125 | } |
| 126 | |
| 127 | inline std::string BuildTensorName(const char* tensorNamePrefix, std::size_t index) |
| 128 | { |
| 129 | return tensorNamePrefix + std::to_string(index); |
| 130 | } |
| 131 | |
| 132 | } // anonymous namespace |
| 133 | |
| 134 | using namespace android::hardware; |
| 135 | |
| 136 | namespace armnn_driver |
| 137 | { |
| 138 | |
| 139 | template<typename HalVersion> |
Narumol Prangnawarat | cad4e91 | 2020-06-02 12:07:43 +0100 | [diff] [blame] | 140 | RequestThread_1_3<ArmnnPreparedModel_1_3, HalVersion, CallbackContext_1_3> |
Kevin May | 42477c1 | 2020-03-26 13:34:14 +0000 | [diff] [blame] | 141 | ArmnnPreparedModel_1_3<HalVersion>::m_RequestThread; |
| 142 | |
| 143 | template<typename HalVersion> |
| 144 | template<typename TensorBindingCollection> |
| 145 | void ArmnnPreparedModel_1_3<HalVersion>::DumpTensorsIfRequired(char const* tensorNamePrefix, |
| 146 | const TensorBindingCollection& tensorBindings) |
| 147 | { |
| 148 | if (!m_RequestInputsAndOutputsDumpDir.empty()) |
| 149 | { |
Colm Donelan | 08d9a1c | 2020-09-09 17:56:55 +0100 | [diff] [blame] | 150 | const std::string requestName = std::to_string(m_NetworkId) + "_" + std::to_string(m_RequestCount) + ".dump"; |
Kevin May | 42477c1 | 2020-03-26 13:34:14 +0000 | [diff] [blame] | 151 | for (std::size_t i = 0u; i < tensorBindings.size(); ++i) |
| 152 | { |
| 153 | DumpTensor(m_RequestInputsAndOutputsDumpDir, |
| 154 | requestName, |
| 155 | BuildTensorName(tensorNamePrefix, i), |
| 156 | tensorBindings[i].second); |
| 157 | } |
| 158 | } |
| 159 | } |
| 160 | |
| 161 | template<typename HalVersion> |
| 162 | ArmnnPreparedModel_1_3<HalVersion>::ArmnnPreparedModel_1_3(armnn::NetworkId networkId, |
| 163 | armnn::IRuntime* runtime, |
| 164 | const V1_3::Model& model, |
| 165 | const std::string& requestInputsAndOutputsDumpDir, |
Narumol Prangnawarat | cad4e91 | 2020-06-02 12:07:43 +0100 | [diff] [blame] | 166 | const bool gpuProfilingEnabled, |
| 167 | V1_3::Priority priority) |
Kevin May | 42477c1 | 2020-03-26 13:34:14 +0000 | [diff] [blame] | 168 | : m_NetworkId(networkId) |
| 169 | , m_Runtime(runtime) |
| 170 | , m_Model(model) |
| 171 | , m_RequestCount(0) |
| 172 | , m_RequestInputsAndOutputsDumpDir(requestInputsAndOutputsDumpDir) |
| 173 | , m_GpuProfilingEnabled(gpuProfilingEnabled) |
Narumol Prangnawarat | cad4e91 | 2020-06-02 12:07:43 +0100 | [diff] [blame] | 174 | , m_ModelPriority(priority) |
Kevin May | 42477c1 | 2020-03-26 13:34:14 +0000 | [diff] [blame] | 175 | { |
| 176 | // Enable profiling if required. |
| 177 | m_Runtime->GetProfiler(m_NetworkId)->EnableProfiling(m_GpuProfilingEnabled); |
| 178 | } |
| 179 | |
| 180 | template<typename HalVersion> |
| 181 | ArmnnPreparedModel_1_3<HalVersion>::~ArmnnPreparedModel_1_3() |
| 182 | { |
| 183 | // Get a hold of the profiler used by this model. |
| 184 | std::shared_ptr<armnn::IProfiler> profiler = m_Runtime->GetProfiler(m_NetworkId); |
| 185 | |
| 186 | // Unload the network associated with this model. |
| 187 | m_Runtime->UnloadNetwork(m_NetworkId); |
| 188 | |
| 189 | // Dump the profiling info to a file if required. |
| 190 | DumpJsonProfilingIfRequired(m_GpuProfilingEnabled, m_RequestInputsAndOutputsDumpDir, m_NetworkId, profiler.get()); |
| 191 | } |
| 192 | |
| 193 | template<typename HalVersion> |
| 194 | Return <V1_0::ErrorStatus> ArmnnPreparedModel_1_3<HalVersion>::execute(const V1_0::Request& request, |
| 195 | const ::android::sp<V1_0::IExecutionCallback>& callback) |
| 196 | { |
| 197 | if (callback.get() == nullptr) |
| 198 | { |
| 199 | ALOGE("ArmnnPreparedModel_1_3::execute invalid callback passed"); |
| 200 | return V1_0::ErrorStatus::INVALID_ARGUMENT; |
| 201 | } |
| 202 | |
| 203 | auto cb = [callback](V1_3::ErrorStatus errorStatus, |
| 204 | std::vector<OutputShape> outputShapes, |
| 205 | const Timing& timing, |
| 206 | std::string callingFunction) |
| 207 | { |
| 208 | NotifyCallbackAndCheck(callback, errorStatus, outputShapes, timing, callingFunction); |
| 209 | }; |
| 210 | |
| 211 | |
| 212 | return convertToV1_0(Execute(convertToV1_3(request), MeasureTiming::NO, cb)); |
| 213 | } |
| 214 | |
| 215 | template<typename HalVersion> |
| 216 | Return <V1_0::ErrorStatus> ArmnnPreparedModel_1_3<HalVersion>::execute_1_2( |
| 217 | const V1_0::Request& request, |
| 218 | MeasureTiming measureTiming, |
| 219 | const sp<V1_2::IExecutionCallback>& callback) |
| 220 | { |
| 221 | if (callback.get() == nullptr) |
| 222 | { |
| 223 | ALOGE("ArmnnPreparedModel_1_3::execute_1_2 invalid callback passed"); |
| 224 | return V1_0::ErrorStatus::INVALID_ARGUMENT; |
| 225 | } |
| 226 | |
| 227 | auto cb = [callback](V1_3::ErrorStatus errorStatus, |
| 228 | std::vector<OutputShape> outputShapes, |
| 229 | const Timing& timing, |
| 230 | std::string callingFunction) |
| 231 | { |
| 232 | NotifyCallbackAndCheck(callback, errorStatus, outputShapes, timing, callingFunction); |
| 233 | }; |
| 234 | |
| 235 | return convertToV1_0(Execute(convertToV1_3(request), measureTiming, cb)); |
| 236 | } |
| 237 | |
| 238 | template<typename HalVersion> |
| 239 | Return <V1_3::ErrorStatus> ArmnnPreparedModel_1_3<HalVersion>::execute_1_3( |
| 240 | const V1_3::Request& request, |
| 241 | MeasureTiming measureTiming, |
| 242 | const V1_3::OptionalTimePoint&, |
Kevin May | 352d838 | 2020-03-31 15:03:42 +0100 | [diff] [blame] | 243 | const V1_3::OptionalTimeoutDuration&, |
Kevin May | 42477c1 | 2020-03-26 13:34:14 +0000 | [diff] [blame] | 244 | const sp<V1_3::IExecutionCallback>& callback) |
| 245 | { |
| 246 | if (callback.get() == nullptr) |
| 247 | { |
| 248 | ALOGE("ArmnnPreparedModel_1_3::execute_1_3 invalid callback passed"); |
| 249 | return V1_3::ErrorStatus::INVALID_ARGUMENT; |
| 250 | } |
| 251 | |
| 252 | auto cb = [callback](V1_3::ErrorStatus errorStatus, |
| 253 | std::vector<OutputShape> outputShapes, |
| 254 | const Timing& timing, |
| 255 | std::string callingFunction) |
| 256 | { |
| 257 | NotifyCallbackAndCheck(callback, errorStatus, outputShapes, timing, callingFunction); |
| 258 | }; |
| 259 | |
| 260 | return Execute(request, measureTiming, cb); |
| 261 | } |
| 262 | |
Sadik Armagan | d7be72e | 2020-04-23 12:56:05 +0100 | [diff] [blame] | 263 | /// This class is inspired by the sample implementation in Android named SampleFencedExecutionCallback. |
| 264 | /// The original code is licensed under Apache-2.0 and can be found at the following link: |
| 265 | /// https://android.googlesource.com/platform/frameworks/ml/+/master/nn/driver/sample/SampleDriver.h |
| 266 | class ArmnnFencedExecutionCallback : public V1_3::IFencedExecutionCallback |
| 267 | { |
| 268 | public: |
| 269 | ArmnnFencedExecutionCallback(V1_3::ErrorStatus errorStatus, Timing timing, Timing fenceTiming) |
| 270 | : m_ErrorStatus(errorStatus), m_Timing(timing), m_FenceTiming(fenceTiming) {} |
| 271 | ~ArmnnFencedExecutionCallback() {} |
| 272 | |
| 273 | Return<void> getExecutionInfo(getExecutionInfo_cb callback) override |
| 274 | { |
| 275 | callback(m_ErrorStatus, m_Timing, m_FenceTiming); |
| 276 | return Void(); |
| 277 | } |
| 278 | private: |
| 279 | V1_3::ErrorStatus m_ErrorStatus; |
| 280 | Timing m_Timing; |
| 281 | Timing m_FenceTiming; |
| 282 | }; |
| 283 | |
Kevin May | 42477c1 | 2020-03-26 13:34:14 +0000 | [diff] [blame] | 284 | template<typename HalVersion> |
Sadik Armagan | d7be72e | 2020-04-23 12:56:05 +0100 | [diff] [blame] | 285 | Return<void> ArmnnPreparedModel_1_3<HalVersion>::executeFenced(const V1_3::Request& request, |
| 286 | const hidl_vec<hidl_handle>& fenceWaitFor, |
| 287 | MeasureTiming measureTiming, |
Sadik Armagan | 7b9ce8d | 2020-04-21 10:39:28 +0100 | [diff] [blame] | 288 | const OptionalTimePoint& deadline, |
| 289 | const OptionalTimeoutDuration& loopTimeoutDuration, |
Kevin May | 352d838 | 2020-03-31 15:03:42 +0100 | [diff] [blame] | 290 | const OptionalTimeoutDuration&, |
Kevin May | 42477c1 | 2020-03-26 13:34:14 +0000 | [diff] [blame] | 291 | executeFenced_cb cb) |
| 292 | { |
Sadik Armagan | 7b9ce8d | 2020-04-21 10:39:28 +0100 | [diff] [blame] | 293 | ALOGV("ArmnnPreparedModel_1_3::executeFenced(...)"); |
| 294 | if (cb == nullptr) |
| 295 | { |
| 296 | ALOGE("ArmnnPreparedModel_1_3::executeFenced invalid callback passed"); |
| 297 | cb(ErrorStatus::INVALID_ARGUMENT, hidl_handle(nullptr), nullptr); |
| 298 | return Void(); |
| 299 | } |
| 300 | |
| 301 | if (deadline.getDiscriminator() != OptionalTimePoint::hidl_discriminator::none) |
| 302 | { |
| 303 | ALOGW("ArmnnPreparedModel_1_3::executeFenced parameter deadline is set but not supported."); |
| 304 | } |
| 305 | |
| 306 | if (loopTimeoutDuration.getDiscriminator() != OptionalTimeoutDuration::hidl_discriminator::none) |
| 307 | { |
| 308 | ALOGW("ArmnnPreparedModel_1_3::executeFenced parameter loopTimeoutDuration is set but not supported."); |
| 309 | } |
| 310 | |
Finn Williams | a4983ce | 2020-07-23 12:55:12 +0100 | [diff] [blame] | 311 | if (!android::nn::validateRequest(request, m_Model, /*allowUnspecifiedOutput=*/false)) |
| 312 | { |
| 313 | ALOGV("ArmnnPreparedModel_1_3::executeFenced outputs must be specified for fenced execution "); |
| 314 | cb(ErrorStatus::INVALID_ARGUMENT, hidl_handle(nullptr), nullptr); |
| 315 | return Void(); |
| 316 | } |
| 317 | |
Sadik Armagan | d7be72e | 2020-04-23 12:56:05 +0100 | [diff] [blame] | 318 | ExecutionContext_1_3 ctx; |
| 319 | if (measureTiming == MeasureTiming::YES) |
| 320 | { |
| 321 | ctx.measureTimings = measureTiming; |
| 322 | ctx.driverStart = Now(); |
| 323 | } |
| 324 | |
| 325 | ALOGV("ArmnnPreparedModel_1_3::executeFenced(): %s", GetModelSummary(m_Model).c_str()); |
| 326 | m_RequestCount++; |
| 327 | |
Sadik Armagan | d7be72e | 2020-04-23 12:56:05 +0100 | [diff] [blame] | 328 | if (!m_RequestInputsAndOutputsDumpDir.empty()) |
| 329 | { |
| 330 | ALOGD("Dumping inputs and outputs for request %" PRIuPTR, reinterpret_cast<std::uintptr_t>(&cb)); |
| 331 | } |
| 332 | |
| 333 | // This code snippet is inspired by the sample implementation in Android named SampleDriver::executeFenced() |
| 334 | // function. The original code is licensed under Apache-2.0 and can be found at the following link: |
| 335 | // https://android.googlesource.com/platform/frameworks/ml/+/master/nn/driver/sample/SampleDriver.cpp |
| 336 | const auto fenceSize = fenceWaitFor.size(); |
| 337 | for (unsigned int index = 0; index < fenceSize; ++index) |
| 338 | { |
| 339 | auto fenceNativeHandle = fenceWaitFor[index].getNativeHandle(); |
| 340 | if (!fenceNativeHandle) |
| 341 | { |
| 342 | cb(ErrorStatus::INVALID_ARGUMENT, hidl_handle(nullptr), nullptr); |
| 343 | return Void(); |
| 344 | } |
| 345 | |
| 346 | if (sync_wait(fenceNativeHandle->data[0], -1) < 0) |
| 347 | { |
| 348 | ALOGE("ArmnnPreparedModel_1_3::executeFenced sync fence failed."); |
| 349 | cb(ErrorStatus::GENERAL_FAILURE, hidl_handle(nullptr), nullptr); |
| 350 | return Void(); |
| 351 | } |
| 352 | } |
| 353 | |
| 354 | TimePoint fenceExecutionStart; |
| 355 | if (measureTiming == MeasureTiming::YES) |
| 356 | { |
| 357 | fenceExecutionStart = Now(); |
| 358 | } |
| 359 | |
| 360 | // map the memory pool into shared pointers |
| 361 | // use a shared memory pools vector on the heap, as it is passed to the request thread |
| 362 | auto memPools = std::make_shared<std::vector<android::nn::RunTimePoolInfo>>(); |
| 363 | |
| 364 | // allocate the tensors on the heap, as they are passed to the request thread |
| 365 | auto inputs = std::make_shared<armnn::InputTensors>(); |
| 366 | auto outputs = std::make_shared<armnn::OutputTensors>(); |
| 367 | |
| 368 | auto [status, outShapes, timings, message] = PrepareMemoryForIO(*inputs, *outputs, *memPools, request); |
| 369 | if (status != V1_3::ErrorStatus::NONE) |
| 370 | { |
| 371 | cb(ErrorStatus::INVALID_ARGUMENT, hidl_handle(nullptr), nullptr); |
| 372 | return Void(); |
| 373 | } |
| 374 | |
| 375 | ALOGV("ArmnnPreparedModel_1_3::executeFenced(...) before ExecuteGraph"); |
| 376 | |
| 377 | // call it with nullCallback for now as we will report the error status from here.. |
| 378 | auto nullCallback = [](V1_3::ErrorStatus, std::vector<OutputShape>, const Timing&, std::string) {}; |
| 379 | CallbackContext_1_3 cbCtx; |
| 380 | cbCtx.callback = nullCallback; |
| 381 | cbCtx.ctx = ctx; |
| 382 | |
| 383 | auto errorStatus = ExecuteGraph(memPools, *inputs, *outputs, cbCtx); |
| 384 | if (errorStatus != V1_3::ErrorStatus::NONE) |
| 385 | { |
| 386 | cb(errorStatus, hidl_handle(nullptr), nullptr); |
| 387 | return Void(); |
| 388 | } |
| 389 | ALOGV("ArmnnPreparedModel_1_3::executeFenced(...) after ExecuteGraph"); |
| 390 | |
| 391 | Timing timing = g_NoTiming; |
| 392 | Timing fenceTiming = g_NoTiming; |
| 393 | if (measureTiming == MeasureTiming::YES) |
| 394 | { |
Sadik Armagan | d7be72e | 2020-04-23 12:56:05 +0100 | [diff] [blame] | 395 | fenceTiming.timeOnDevice = MicrosecondsDuration(ctx.deviceEnd, ctx.deviceStart); |
Kevin May | 949a69e | 2020-04-24 10:21:40 +0100 | [diff] [blame] | 396 | fenceTiming.timeInDriver = MicrosecondsDuration(ctx.driverEnd, fenceExecutionStart); |
| 397 | ALOGV("ArmnnPreparedModel_1_3::fenceFinishExecutionTiming - Device = %lu Driver = %lu", |
Sadik Armagan | d7be72e | 2020-04-23 12:56:05 +0100 | [diff] [blame] | 398 | fenceTiming.timeOnDevice, fenceTiming.timeInDriver); |
| 399 | } |
| 400 | |
| 401 | sp<ArmnnFencedExecutionCallback> armnnFencedExecutionCallback = |
| 402 | new ArmnnFencedExecutionCallback(ErrorStatus::NONE, timing, fenceTiming); |
| 403 | cb(ErrorStatus::NONE, hidl_handle(nullptr), armnnFencedExecutionCallback); |
Kevin May | 42477c1 | 2020-03-26 13:34:14 +0000 | [diff] [blame] | 404 | return Void(); |
| 405 | } |
| 406 | |
| 407 | template<typename HalVersion> |
| 408 | Return<V1_3::ErrorStatus> ArmnnPreparedModel_1_3<HalVersion>::PrepareMemoryForInputs( |
| 409 | armnn::InputTensors& inputs, |
| 410 | const V1_3::Request& request, |
| 411 | const std::vector<android::nn::RunTimePoolInfo>& memPools) |
| 412 | { |
| 413 | inputs.reserve(request.inputs.size()); |
| 414 | for (unsigned int i = 0; i < request.inputs.size(); i++) |
| 415 | { |
| 416 | const auto& inputArg = request.inputs[i]; |
| 417 | |
| 418 | const armnn::TensorInfo inputTensorInfo = m_Runtime->GetInputTensorInfo(m_NetworkId, i); |
| 419 | const armnn::Tensor inputTensor = GetTensorForRequestArgument(inputArg, inputTensorInfo, memPools); |
| 420 | |
| 421 | if (inputTensor.GetMemoryArea() == nullptr) |
| 422 | { |
| 423 | ALOGE("Cannot execute request. Error converting request input %u to tensor", i); |
| 424 | return V1_3::ErrorStatus::GENERAL_FAILURE; |
| 425 | } |
| 426 | |
| 427 | inputs.emplace_back(i, inputTensor); |
| 428 | } |
| 429 | |
| 430 | return V1_3::ErrorStatus::NONE; |
| 431 | } |
| 432 | |
| 433 | template<typename HalVersion> |
| 434 | Return<V1_3::ErrorStatus> ArmnnPreparedModel_1_3<HalVersion>::PrepareMemoryForOutputs( |
| 435 | armnn::OutputTensors& outputs, |
| 436 | std::vector<OutputShape> &outputShapes, |
| 437 | const V1_3::Request& request, |
| 438 | const std::vector<android::nn::RunTimePoolInfo>& memPools) |
| 439 | { |
| 440 | outputs.reserve(request.outputs.size()); |
| 441 | for (unsigned int i = 0; i < request.outputs.size(); i++) |
| 442 | { |
| 443 | const auto& outputArg = request.outputs[i]; |
| 444 | |
Finn Williams | a4983ce | 2020-07-23 12:55:12 +0100 | [diff] [blame] | 445 | armnn::TensorInfo outputTensorInfo = m_Runtime->GetOutputTensorInfo(m_NetworkId, i); |
Kevin May | 42477c1 | 2020-03-26 13:34:14 +0000 | [diff] [blame] | 446 | const armnn::Tensor outputTensor = GetTensorForRequestArgument(outputArg, outputTensorInfo, memPools); |
| 447 | if (outputTensor.GetMemoryArea() == nullptr) |
| 448 | { |
| 449 | ALOGE("Cannot execute request. Error converting request output %u to tensor", i); |
| 450 | return V1_3::ErrorStatus::GENERAL_FAILURE; |
| 451 | } |
| 452 | |
Teresa Charlin | 4bd9a74 | 2020-08-12 12:58:50 +0100 | [diff] [blame] | 453 | const size_t outputSize = outputTensorInfo.GetNumBytes(); |
| 454 | |
Finn Williams | a4983ce | 2020-07-23 12:55:12 +0100 | [diff] [blame] | 455 | unsigned int count = 0; |
| 456 | std::for_each(outputArg.dimensions.begin(), outputArg.dimensions.end(), [&](auto dim) |
| 457 | { |
| 458 | if (dim != 0) |
| 459 | { |
| 460 | outputTensorInfo.GetShape()[count] = dim; |
| 461 | } |
| 462 | else |
| 463 | { |
| 464 | outputTensorInfo.GetShape()[count] = outputArg.dimensions.size(); |
| 465 | } |
| 466 | |
| 467 | count++; |
| 468 | }); |
| 469 | |
Finn Williams | a4983ce | 2020-07-23 12:55:12 +0100 | [diff] [blame] | 470 | outputs.emplace_back(i, outputTensor); |
| 471 | outputShapes[i] = ComputeShape(outputTensorInfo); |
| 472 | |
| 473 | if (outputArg.location.length < outputSize) |
| 474 | { |
Teresa Charlin | 4bd9a74 | 2020-08-12 12:58:50 +0100 | [diff] [blame] | 475 | ALOGW("ArmnnPreparedModel_1_3::Execute failed outputArg.location.length (%s) < outputSize (%s)", |
| 476 | std::to_string(outputArg.location.length).c_str(), std::to_string(outputSize).c_str()); |
Finn Williams | a4983ce | 2020-07-23 12:55:12 +0100 | [diff] [blame] | 477 | outputShapes[i].isSufficient = false; |
| 478 | return V1_3::ErrorStatus::OUTPUT_INSUFFICIENT_SIZE; |
| 479 | } |
| 480 | |
Kevin May | 42477c1 | 2020-03-26 13:34:14 +0000 | [diff] [blame] | 481 | const size_t bufferSize = memPools.at(outputArg.location.poolIndex).getHidlMemory().size(); |
| 482 | if (bufferSize < outputSize) |
| 483 | { |
Teresa Charlin | 4bd9a74 | 2020-08-12 12:58:50 +0100 | [diff] [blame] | 484 | ALOGW("ArmnnPreparedModel_1_3::Execute failed bufferSize (%s) < outputSize (%s)", |
| 485 | std::to_string(bufferSize).c_str(), std::to_string(outputSize).c_str()); |
Finn Williams | a4983ce | 2020-07-23 12:55:12 +0100 | [diff] [blame] | 486 | outputShapes[i].isSufficient = false; |
Kevin May | 42477c1 | 2020-03-26 13:34:14 +0000 | [diff] [blame] | 487 | return V1_3::ErrorStatus::OUTPUT_INSUFFICIENT_SIZE; |
| 488 | } |
Kevin May | 42477c1 | 2020-03-26 13:34:14 +0000 | [diff] [blame] | 489 | } |
| 490 | |
| 491 | return V1_3::ErrorStatus::NONE; |
| 492 | } |
| 493 | |
| 494 | template<typename HalVersion> |
| 495 | std::tuple<V1_3::ErrorStatus, hidl_vec<OutputShape>, Timing, std::string> |
| 496 | ArmnnPreparedModel_1_3<HalVersion>::PrepareMemoryForIO(armnn::InputTensors& inputs, |
| 497 | armnn::OutputTensors& outputs, |
| 498 | std::vector<android::nn::RunTimePoolInfo>& memPools, |
| 499 | const V1_3::Request& request) |
| 500 | { |
| 501 | if (!setRunTimePoolInfosFromMemoryPools(&memPools, request.pools)) |
| 502 | { |
Sadik Armagan | ef8a393 | 2020-04-09 17:21:50 +0100 | [diff] [blame] | 503 | return {ErrorStatus::INVALID_ARGUMENT, {}, g_NoTiming, "ArmnnPreparedModel_1_3::execute"}; |
Kevin May | 42477c1 | 2020-03-26 13:34:14 +0000 | [diff] [blame] | 504 | } |
| 505 | |
| 506 | // add the inputs and outputs with their data |
| 507 | try |
| 508 | { |
| 509 | if (PrepareMemoryForInputs(inputs, request, memPools) != V1_3::ErrorStatus::NONE) |
| 510 | { |
| 511 | return {ErrorStatus::GENERAL_FAILURE, {}, g_NoTiming, "ArmnnPreparedModel_1_3::execute"}; |
| 512 | } |
| 513 | |
| 514 | std::vector<OutputShape> outputShapes(request.outputs.size()); |
| 515 | |
| 516 | auto errorStatus = PrepareMemoryForOutputs(outputs, outputShapes, request, memPools); |
| 517 | if (errorStatus != V1_3::ErrorStatus::NONE) |
| 518 | { |
| 519 | return {errorStatus, outputShapes, g_NoTiming, "ArmnnPreparedModel_1_3::execute"}; |
| 520 | } |
| 521 | } |
| 522 | catch (armnn::Exception& e) |
| 523 | { |
| 524 | ALOGW("armnn::Exception caught while preparing for EnqueueWorkload: %s", e.what()); |
| 525 | return {ErrorStatus::GENERAL_FAILURE, {}, g_NoTiming, "ArmnnPreparedModel_1_3::execute"}; |
| 526 | } |
| 527 | catch (std::exception& e) |
| 528 | { |
| 529 | ALOGE("std::exception caught while preparing for EnqueueWorkload: %s", e.what()); |
| 530 | return {ErrorStatus::GENERAL_FAILURE, {}, g_NoTiming, "ArmnnPreparedModel_1_3::execute"}; |
| 531 | } |
| 532 | |
| 533 | return {V1_3::ErrorStatus::NONE, {}, g_NoTiming, "ArmnnPreparedModel_1_3::execute"}; |
| 534 | } |
| 535 | |
| 536 | template<typename HalVersion> |
| 537 | template<typename CallbackContext> |
| 538 | Return<void> ArmnnPreparedModel_1_3<HalVersion>::ExecuteSynchronously(const V1_3::Request& request, |
| 539 | CallbackContext cbCtx) |
| 540 | { |
| 541 | if (cbCtx.ctx.measureTimings == MeasureTiming::YES) |
| 542 | { |
| 543 | cbCtx.ctx.driverStart = Now(); |
| 544 | } |
| 545 | |
| 546 | if (!android::nn::validateRequest(convertToV1_3(request), m_Model)) |
| 547 | { |
| 548 | ALOGE("ArmnnPreparedModel_1_3::ExecuteSynchronously invalid request model"); |
| 549 | cbCtx.callback(V1_3::ErrorStatus::INVALID_ARGUMENT, |
| 550 | {}, |
| 551 | g_NoTiming, |
| 552 | "ArmnnPreparedModel_1_3::ExecuteSynchronously invalid request model"); |
| 553 | return Void(); |
| 554 | } |
| 555 | |
| 556 | if (!android::nn::validateRequest(request, m_Model)) |
| 557 | { |
| 558 | ALOGE("ArmnnPreparedModel_1_3::ExecuteSynchronously invalid request model"); |
| 559 | cbCtx.callback(V1_3::ErrorStatus::INVALID_ARGUMENT, |
| 560 | {}, |
| 561 | g_NoTiming, |
| 562 | "ArmnnPreparedModel_1_3::ExecuteSynchronously invalid request model"); |
Sadik Armagan | ef8a393 | 2020-04-09 17:21:50 +0100 | [diff] [blame] | 563 | return Void(); |
Kevin May | 42477c1 | 2020-03-26 13:34:14 +0000 | [diff] [blame] | 564 | } |
| 565 | |
| 566 | |
| 567 | // map the memory pool into shared pointers |
| 568 | // use a shared memory pools vector on the heap, as it is passed to the request thread |
| 569 | auto memPools = std::make_shared<std::vector<android::nn::RunTimePoolInfo>>(); |
| 570 | |
| 571 | // allocate the tensors on the heap, as they are passed to the request thread |
| 572 | auto inputs = std::make_shared<armnn::InputTensors>(); |
| 573 | auto outputs = std::make_shared<armnn::OutputTensors>(); |
| 574 | |
| 575 | auto [status, outputShapes, timing, message] = PrepareMemoryForIO(*inputs, *outputs, *memPools, request); |
| 576 | if (status != V1_3::ErrorStatus::NONE) |
| 577 | { |
| 578 | cbCtx.callback(status, outputShapes, timing, message); |
Sadik Armagan | ef8a393 | 2020-04-09 17:21:50 +0100 | [diff] [blame] | 579 | return Void(); |
Kevin May | 42477c1 | 2020-03-26 13:34:14 +0000 | [diff] [blame] | 580 | } |
| 581 | |
| 582 | ALOGV("ArmnnPreparedModel_1_3::ExecuteSynchronously() before Execution"); |
| 583 | |
| 584 | ExecuteGraph(memPools, *inputs, *outputs, cbCtx); |
| 585 | return Void(); |
| 586 | } |
| 587 | |
| 588 | template<typename HalVersion> |
| 589 | Return<void> ArmnnPreparedModel_1_3<HalVersion>::executeSynchronously(const V1_0::Request& request, |
| 590 | MeasureTiming measureTiming, |
| 591 | executeSynchronously_cb cb) |
| 592 | { |
| 593 | ALOGV("ArmnnPreparedModel_1_3::executeSynchronously(): %s", GetModelSummary(m_Model).c_str()); |
| 594 | m_RequestCount++; |
| 595 | |
| 596 | if (cb == nullptr) |
| 597 | { |
| 598 | ALOGE("ArmnnPreparedModel_1_3::executeSynchronously invalid callback passed"); |
| 599 | return Void(); |
| 600 | } |
| 601 | |
| 602 | auto cbWrapper = [cb](V1_3::ErrorStatus errorStatus, |
| 603 | std::vector<OutputShape> outputShapes, |
| 604 | const Timing& timing, |
| 605 | std::string) |
| 606 | { |
| 607 | cb(convertToV1_0(errorStatus), outputShapes, timing); |
| 608 | }; |
| 609 | |
| 610 | CallbackContext_1_3 cbCtx; |
| 611 | cbCtx.callback = cbWrapper; |
| 612 | cbCtx.ctx.measureTimings = measureTiming; |
| 613 | |
| 614 | ExecuteSynchronously(convertToV1_3(request), cbCtx); |
| 615 | return Void(); |
| 616 | } |
| 617 | |
| 618 | template<typename HalVersion> |
Kevin May | 352d838 | 2020-03-31 15:03:42 +0100 | [diff] [blame] | 619 | Return<void> ArmnnPreparedModel_1_3<HalVersion>::executeSynchronously_1_3( |
| 620 | const V1_3::Request& request, |
| 621 | MeasureTiming measureTiming, |
| 622 | const V1_3::OptionalTimePoint& deadline, |
| 623 | const V1_3::OptionalTimeoutDuration& loopTimeoutDuration, |
| 624 | executeSynchronously_1_3_cb cb) |
Kevin May | 42477c1 | 2020-03-26 13:34:14 +0000 | [diff] [blame] | 625 | { |
| 626 | ALOGV("ArmnnPreparedModel_1_3::executeSynchronously_1_3(): %s", GetModelSummary(m_Model).c_str()); |
| 627 | m_RequestCount++; |
| 628 | |
| 629 | if (cb == nullptr) |
| 630 | { |
| 631 | ALOGE("ArmnnPreparedModel_1_3::executeSynchronously_1_3 invalid callback passed"); |
| 632 | return Void(); |
| 633 | } |
| 634 | |
| 635 | if (deadline.getDiscriminator() != OptionalTimePoint::hidl_discriminator::none) |
| 636 | { |
Sadik Armagan | 7b9ce8d | 2020-04-21 10:39:28 +0100 | [diff] [blame] | 637 | ALOGW("ArmnnPreparedModel_1_3::executeSynchronously_1_3 parameter deadline is set but not supported."); |
Kevin May | 42477c1 | 2020-03-26 13:34:14 +0000 | [diff] [blame] | 638 | } |
| 639 | |
Kevin May | 352d838 | 2020-03-31 15:03:42 +0100 | [diff] [blame] | 640 | if (loopTimeoutDuration.getDiscriminator() != OptionalTimeoutDuration::hidl_discriminator::none) |
Sadik Armagan | 7b9ce8d | 2020-04-21 10:39:28 +0100 | [diff] [blame] | 641 | { |
| 642 | ALOGW( |
| 643 | "ArmnnPreparedModel_1_3::executeSynchronously_1_3 parameter loopTimeoutDuration is set but not supported."); |
Kevin May | 352d838 | 2020-03-31 15:03:42 +0100 | [diff] [blame] | 644 | } |
| 645 | |
Kevin May | 42477c1 | 2020-03-26 13:34:14 +0000 | [diff] [blame] | 646 | auto cbWrapper = [cb](V1_3::ErrorStatus errorStatus, |
| 647 | std::vector<OutputShape> outputShapes, |
| 648 | const Timing& timing, |
| 649 | std::string) |
| 650 | { |
| 651 | cb(errorStatus, outputShapes, timing); |
| 652 | }; |
| 653 | |
| 654 | CallbackContext_1_3 cbCtx; |
| 655 | cbCtx.callback = cbWrapper; |
| 656 | cbCtx.ctx.measureTimings = measureTiming; |
| 657 | |
| 658 | ExecuteSynchronously(request, cbCtx); |
| 659 | return Void(); |
| 660 | } |
| 661 | |
| 662 | template<typename HalVersion> |
| 663 | Return<void> ArmnnPreparedModel_1_3<HalVersion>::configureExecutionBurst( |
| 664 | const sp<V1_2::IBurstCallback>& callback, |
| 665 | const MQDescriptorSync<V1_2::FmqRequestDatum>& requestChannel, |
| 666 | const MQDescriptorSync<V1_2::FmqResultDatum>& resultChannel, |
| 667 | V1_3::IPreparedModel::configureExecutionBurst_cb cb) |
| 668 | { |
| 669 | ALOGV("ArmnnPreparedModel_1_3::configureExecutionBurst"); |
| 670 | const sp<V1_2::IBurstContext> burst = ExecutionBurstServer::create(callback, |
| 671 | requestChannel, |
| 672 | resultChannel, |
| 673 | this); |
| 674 | |
| 675 | if (burst == nullptr) |
| 676 | { |
| 677 | cb(V1_0::ErrorStatus::GENERAL_FAILURE, {}); |
| 678 | } |
| 679 | else |
| 680 | { |
| 681 | cb(V1_0::ErrorStatus::NONE, burst); |
| 682 | } |
| 683 | return Void(); |
| 684 | } |
| 685 | |
| 686 | template<typename HalVersion> |
| 687 | template<typename CallbackContext> |
Sadik Armagan | d7be72e | 2020-04-23 12:56:05 +0100 | [diff] [blame] | 688 | Return <V1_3::ErrorStatus> ArmnnPreparedModel_1_3<HalVersion>::ExecuteGraph( |
Kevin May | 42477c1 | 2020-03-26 13:34:14 +0000 | [diff] [blame] | 689 | std::shared_ptr<std::vector<::android::nn::RunTimePoolInfo>>& pMemPools, |
| 690 | armnn::InputTensors& inputTensors, |
| 691 | armnn::OutputTensors& outputTensors, |
| 692 | CallbackContext cb) |
| 693 | { |
| 694 | ALOGV("ArmnnPreparedModel_1_3::ExecuteGraph(...)"); |
| 695 | |
Kevin May | 42477c1 | 2020-03-26 13:34:14 +0000 | [diff] [blame] | 696 | DumpTensorsIfRequired("Input", inputTensors); |
| 697 | |
| 698 | std::vector<OutputShape> outputShapes(outputTensors.size()); |
| 699 | for (unsigned int i = 0; i < outputTensors.size(); i++) |
| 700 | { |
| 701 | std::pair<int, armnn::Tensor> outputTensorPair = outputTensors[i]; |
| 702 | const armnn::Tensor outputTensor = outputTensorPair.second; |
| 703 | const armnn::TensorInfo outputTensorInfo = outputTensor.GetInfo(); |
| 704 | |
| 705 | outputShapes[i] = ComputeShape(outputTensorInfo); |
| 706 | } |
| 707 | |
| 708 | // run it |
| 709 | try |
| 710 | { |
| 711 | if (cb.ctx.measureTimings == MeasureTiming::YES) |
| 712 | { |
Sadik Armagan | d7be72e | 2020-04-23 12:56:05 +0100 | [diff] [blame] | 713 | cb.ctx.deviceStart = Now(); |
Kevin May | 42477c1 | 2020-03-26 13:34:14 +0000 | [diff] [blame] | 714 | } |
| 715 | |
| 716 | armnn::Status status = m_Runtime->EnqueueWorkload(m_NetworkId, inputTensors, outputTensors); |
| 717 | |
| 718 | if (cb.ctx.measureTimings == MeasureTiming::YES) |
| 719 | { |
Sadik Armagan | d7be72e | 2020-04-23 12:56:05 +0100 | [diff] [blame] | 720 | cb.ctx.deviceEnd = Now(); |
Kevin May | 42477c1 | 2020-03-26 13:34:14 +0000 | [diff] [blame] | 721 | } |
| 722 | if (status != armnn::Status::Success) |
| 723 | { |
| 724 | ALOGW("EnqueueWorkload failed"); |
Sadik Armagan | d7be72e | 2020-04-23 12:56:05 +0100 | [diff] [blame] | 725 | cb.callback(V1_3::ErrorStatus::GENERAL_FAILURE, {}, g_NoTiming, "ArmnnPreparedModel_1_3::ExecuteGraph"); |
| 726 | return V1_3::ErrorStatus::GENERAL_FAILURE; |
Kevin May | 42477c1 | 2020-03-26 13:34:14 +0000 | [diff] [blame] | 727 | } |
| 728 | } |
| 729 | catch (armnn::Exception& e) |
| 730 | { |
| 731 | ALOGW("armnn:Exception caught from EnqueueWorkload: %s", e.what()); |
| 732 | cb.callback(V1_3::ErrorStatus::GENERAL_FAILURE, {}, g_NoTiming, "ArmnnPreparedModel_1_3::ExecuteGraph"); |
Sadik Armagan | d7be72e | 2020-04-23 12:56:05 +0100 | [diff] [blame] | 733 | return V1_3::ErrorStatus::GENERAL_FAILURE; |
Kevin May | 42477c1 | 2020-03-26 13:34:14 +0000 | [diff] [blame] | 734 | } |
| 735 | catch (std::exception& e) |
| 736 | { |
| 737 | ALOGE("std::exception caught from EnqueueWorkload: %s", e.what()); |
| 738 | cb.callback(V1_3::ErrorStatus::GENERAL_FAILURE, {}, g_NoTiming, "ArmnnPreparedModel_1_3::ExecuteGraph"); |
Sadik Armagan | d7be72e | 2020-04-23 12:56:05 +0100 | [diff] [blame] | 739 | return V1_3::ErrorStatus::GENERAL_FAILURE; |
Kevin May | 42477c1 | 2020-03-26 13:34:14 +0000 | [diff] [blame] | 740 | } |
| 741 | |
| 742 | CommitPools(*pMemPools); |
| 743 | |
| 744 | DumpTensorsIfRequired("Output", outputTensors); |
| 745 | |
| 746 | if (cb.ctx.measureTimings == MeasureTiming::YES) |
| 747 | { |
Kevin May | 949a69e | 2020-04-24 10:21:40 +0100 | [diff] [blame] | 748 | cb.ctx.driverEnd = Now(); |
Kevin May | 42477c1 | 2020-03-26 13:34:14 +0000 | [diff] [blame] | 749 | Timing timing; |
Sadik Armagan | d7be72e | 2020-04-23 12:56:05 +0100 | [diff] [blame] | 750 | timing.timeOnDevice = MicrosecondsDuration(cb.ctx.deviceEnd, cb.ctx.deviceStart); |
Kevin May | 949a69e | 2020-04-24 10:21:40 +0100 | [diff] [blame] | 751 | timing.timeInDriver = MicrosecondsDuration(cb.ctx.driverEnd, cb.ctx.driverStart); |
| 752 | ALOGV("ArmnnPreparedModel_1_3::execute timing - Device = %lu Driver = %lu", timing.timeOnDevice, |
Kevin May | 42477c1 | 2020-03-26 13:34:14 +0000 | [diff] [blame] | 753 | timing.timeInDriver); |
| 754 | cb.callback(V1_3::ErrorStatus::NONE, outputShapes, timing, "ArmnnPreparedModel_1_3::ExecuteGraph"); |
Sadik Armagan | d7be72e | 2020-04-23 12:56:05 +0100 | [diff] [blame] | 755 | } else |
| 756 | { |
Kevin May | 42477c1 | 2020-03-26 13:34:14 +0000 | [diff] [blame] | 757 | cb.callback(V1_3::ErrorStatus::NONE, outputShapes, g_NoTiming, "ArmnnPreparedModel_1_3::ExecuteGraph"); |
| 758 | } |
Sadik Armagan | d7be72e | 2020-04-23 12:56:05 +0100 | [diff] [blame] | 759 | return V1_3::ErrorStatus::NONE; |
Kevin May | 42477c1 | 2020-03-26 13:34:14 +0000 | [diff] [blame] | 760 | } |
| 761 | |
| 762 | template<typename HalVersion> |
| 763 | bool ArmnnPreparedModel_1_3<HalVersion>::ExecuteWithDummyInputs() |
| 764 | { |
| 765 | std::vector<std::vector<char>> storage; |
| 766 | armnn::InputTensors inputTensors; |
| 767 | for (unsigned int i = 0; i < getMainModel(m_Model).inputIndexes.size(); i++) |
| 768 | { |
| 769 | const armnn::TensorInfo inputTensorInfo = m_Runtime->GetInputTensorInfo(m_NetworkId, i); |
| 770 | storage.emplace_back(inputTensorInfo.GetNumBytes()); |
| 771 | const armnn::ConstTensor inputTensor(inputTensorInfo, storage.back().data()); |
| 772 | |
| 773 | inputTensors.emplace_back(i, inputTensor); |
| 774 | } |
| 775 | |
| 776 | armnn::OutputTensors outputTensors; |
| 777 | for (unsigned int i = 0; i < getMainModel(m_Model).outputIndexes.size(); i++) |
| 778 | { |
| 779 | const armnn::TensorInfo outputTensorInfo = m_Runtime->GetOutputTensorInfo(m_NetworkId, i); |
| 780 | storage.emplace_back(outputTensorInfo.GetNumBytes()); |
| 781 | const armnn::Tensor outputTensor(outputTensorInfo, storage.back().data()); |
| 782 | |
| 783 | outputTensors.emplace_back(i, outputTensor); |
| 784 | } |
| 785 | |
| 786 | auto nullCallback = [](V1_3::ErrorStatus, std::vector<OutputShape>, const Timing&, std::string) {}; |
| 787 | CallbackContext_1_3 callbackContext; |
| 788 | callbackContext.callback = nullCallback; |
| 789 | callbackContext.ctx.measureTimings = MeasureTiming::NO; |
| 790 | auto memPools = std::make_shared<std::vector<::android::nn::RunTimePoolInfo>>(); |
Sadik Armagan | d7be72e | 2020-04-23 12:56:05 +0100 | [diff] [blame] | 791 | |
| 792 | auto errorStatus = ExecuteGraph(memPools, |
| 793 | inputTensors, |
| 794 | outputTensors, |
| 795 | callbackContext); |
| 796 | return errorStatus == V1_3::ErrorStatus::NONE; |
Kevin May | 42477c1 | 2020-03-26 13:34:14 +0000 | [diff] [blame] | 797 | } |
| 798 | |
| 799 | template<typename HalVersion> |
| 800 | Return <V1_3::ErrorStatus> ArmnnPreparedModel_1_3<HalVersion>::Execute(const V1_3::Request& request, |
| 801 | MeasureTiming measureTiming, |
| 802 | CallbackAsync_1_3 callback) |
| 803 | { |
| 804 | ExecutionContext_1_3 ctx; |
| 805 | if (measureTiming == MeasureTiming::YES) |
| 806 | { |
| 807 | ctx.measureTimings = measureTiming; |
| 808 | ctx.driverStart = Now(); |
| 809 | } |
| 810 | |
| 811 | ALOGV("ArmnnPreparedModel_1_3::execute(): %s", GetModelSummary(m_Model).c_str()); |
| 812 | m_RequestCount++; |
| 813 | |
| 814 | if (!android::nn::validateRequest(request, m_Model)) |
| 815 | { |
| 816 | callback(V1_3::ErrorStatus::INVALID_ARGUMENT, {}, g_NoTiming, "ArmnnPreparedModel_1_3::execute"); |
| 817 | return V1_3::ErrorStatus::INVALID_ARGUMENT; |
| 818 | } |
| 819 | |
| 820 | if (!m_RequestInputsAndOutputsDumpDir.empty()) |
| 821 | { |
| 822 | ALOGD("Dumping inputs and outputs for request %" PRIuPTR, reinterpret_cast<std::uintptr_t>(&callback)); |
| 823 | } |
| 824 | |
| 825 | // map the memory pool into shared pointers |
| 826 | // use a shared memory pools vector on the heap, as it is passed to the request thread |
| 827 | auto memPools = std::make_shared<std::vector<android::nn::RunTimePoolInfo>>(); |
| 828 | |
| 829 | // allocate the tensors on the heap, as they are passed to the request thread |
| 830 | auto inputTensors = std::make_shared<armnn::InputTensors>(); |
| 831 | auto outputTensors = std::make_shared<armnn::OutputTensors>(); |
| 832 | |
| 833 | auto [status, outShapes, timing, message] = PrepareMemoryForIO(*inputTensors, *outputTensors, |
| 834 | *memPools, request); |
| 835 | if (status != V1_3::ErrorStatus::NONE) |
| 836 | { |
| 837 | callback(status, outShapes, timing, message); |
| 838 | } |
| 839 | |
| 840 | switch(status) |
| 841 | { |
| 842 | case V1_3::ErrorStatus::OUTPUT_INSUFFICIENT_SIZE: |
| 843 | return V1_3::ErrorStatus::NONE; |
| 844 | case V1_3::ErrorStatus::GENERAL_FAILURE: |
| 845 | return V1_3::ErrorStatus::GENERAL_FAILURE; |
| 846 | default: |
| 847 | {} |
| 848 | } |
| 849 | |
| 850 | ALOGV("ArmnnPreparedModel_1_3::execute(...) before PostMsg"); |
| 851 | |
| 852 | // post the request for asynchronous execution |
| 853 | CallbackContext_1_3 cb; |
| 854 | cb.callback = callback; |
| 855 | cb.ctx = ctx; |
| 856 | m_RequestThread.PostMsg(this, memPools, inputTensors, outputTensors, cb); |
| 857 | ALOGV("ArmnnPreparedModel_1_3::execute(...) after PostMsg"); |
| 858 | return V1_3::ErrorStatus::NONE; |
| 859 | } |
| 860 | |
Narumol Prangnawarat | cad4e91 | 2020-06-02 12:07:43 +0100 | [diff] [blame] | 861 | template<typename HalVersion> |
| 862 | V1_3::Priority ArmnnPreparedModel_1_3<HalVersion>::GetModelPriority() |
| 863 | { |
| 864 | return m_ModelPriority; |
| 865 | } |
| 866 | |
Kevin May | 42477c1 | 2020-03-26 13:34:14 +0000 | [diff] [blame] | 867 | #ifdef ARMNN_ANDROID_NN_V1_3 |
| 868 | template class ArmnnPreparedModel_1_3<hal_1_3::HalPolicy>; |
Sadik Armagan | d7be72e | 2020-04-23 12:56:05 +0100 | [diff] [blame] | 869 | template Return <V1_3::ErrorStatus> ArmnnPreparedModel_1_3<hal_1_3::HalPolicy>::ExecuteGraph<CallbackContext_1_3>( |
Kevin May | 42477c1 | 2020-03-26 13:34:14 +0000 | [diff] [blame] | 870 | std::shared_ptr<std::vector<::android::nn::RunTimePoolInfo>>& pMemPools, |
| 871 | armnn::InputTensors& pInputTensors, |
| 872 | armnn::OutputTensors& pOutputTensors, |
| 873 | CallbackContext_1_3 cb); |
| 874 | #endif |
| 875 | |
| 876 | } // namespace armnn_driver |