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 | // |
| 5 | |
| 6 | #define LOG_TAG "ArmnnDriver" |
| 7 | |
| 8 | #include "ArmnnPreparedModel_1_3.hpp" |
| 9 | #include "Utils.hpp" |
| 10 | |
| 11 | #include <Utils.h> |
| 12 | #include <boost/format.hpp> |
| 13 | #include <log/log.h> |
| 14 | #include <OperationsUtils.h> |
| 15 | #include <ExecutionBurstServer.h> |
| 16 | #include <ValidateHal.h> |
| 17 | |
| 18 | #include <cassert> |
| 19 | #include <cinttypes> |
| 20 | |
| 21 | using namespace android; |
| 22 | using namespace android::hardware; |
| 23 | |
| 24 | namespace { |
| 25 | |
| 26 | static const Timing g_NoTiming = {.timeOnDevice = UINT64_MAX, .timeInDriver = UINT64_MAX}; |
| 27 | using namespace armnn_driver; |
| 28 | using TimePoint = std::chrono::steady_clock::time_point; |
| 29 | |
| 30 | TimePoint Now() |
| 31 | { |
| 32 | return std::chrono::steady_clock::now(); |
| 33 | } |
| 34 | |
| 35 | unsigned long MicrosecondsDuration(TimePoint endPoint, TimePoint startPoint) |
| 36 | { |
| 37 | return static_cast<unsigned long>(std::chrono::duration_cast<std::chrono::microseconds>( |
| 38 | endPoint - startPoint).count()); |
| 39 | } |
| 40 | |
| 41 | void NotifyCallbackAndCheck(const ::android::sp<V1_0::IExecutionCallback>& callback, |
| 42 | V1_3::ErrorStatus errorStatus, |
| 43 | std::vector<OutputShape>, |
| 44 | const Timing, |
| 45 | std::string callingFunction) |
| 46 | { |
| 47 | Return<void> returned = callback->notify(convertToV1_0(errorStatus)); |
| 48 | // This check is required, if the callback fails and it isn't checked it will bring down the service |
| 49 | if (!returned.isOk()) |
| 50 | { |
| 51 | ALOGE("ArmnnDriver::%s: hidl callback failed to return properly: %s", |
| 52 | callingFunction.c_str(), returned.description().c_str()); |
| 53 | } |
| 54 | } |
| 55 | |
| 56 | void NotifyCallbackAndCheck(const ::android::sp<V1_2::IExecutionCallback>& callback, |
| 57 | V1_3::ErrorStatus errorStatus, |
| 58 | std::vector<OutputShape> outputShapes, |
| 59 | const Timing timing, |
| 60 | std::string callingFunction) |
| 61 | { |
| 62 | Return<void> returned = callback->notify_1_2(convertToV1_0(errorStatus), outputShapes, timing); |
| 63 | // This check is required, if the callback fails and it isn't checked it will bring down the service |
| 64 | if (!returned.isOk()) |
| 65 | { |
| 66 | ALOGE("ArmnnDriver::%s: hidl callback failed to return properly: %s", |
| 67 | callingFunction.c_str(), returned.description().c_str()); |
| 68 | } |
| 69 | } |
| 70 | |
| 71 | void NotifyCallbackAndCheck(const ::android::sp<V1_3::IExecutionCallback>& callback, |
| 72 | V1_3::ErrorStatus errorStatus, |
| 73 | std::vector<OutputShape> outputShapes, |
| 74 | const Timing timing, |
| 75 | std::string callingFunction) |
| 76 | { |
| 77 | Return<void> returned = callback->notify_1_3(errorStatus, outputShapes, timing); |
| 78 | // This check is required, if the callback fails and it isn't checked it will bring down the service |
| 79 | if (!returned.isOk()) |
| 80 | { |
| 81 | ALOGE("ArmnnDriver::%s: hidl callback failed to return properly: %s", |
| 82 | callingFunction.c_str(), returned.description().c_str()); |
| 83 | } |
| 84 | } |
| 85 | |
| 86 | bool ValidateRequestArgument(const RequestArgument& requestArg, const armnn::TensorInfo& tensorInfo) |
| 87 | { |
| 88 | if (requestArg.dimensions.size() != 0) |
| 89 | { |
| 90 | if (requestArg.dimensions.size() != tensorInfo.GetNumDimensions()) |
| 91 | { |
| 92 | ALOGE("Mismatched dimensions (request argument: %zu, expected: %u)", |
| 93 | requestArg.dimensions.size(), tensorInfo.GetNumDimensions()); |
| 94 | return false; |
| 95 | } |
| 96 | |
| 97 | for (unsigned int d = 0; d < tensorInfo.GetNumDimensions(); ++d) |
| 98 | { |
| 99 | if (requestArg.dimensions[d] != tensorInfo.GetShape()[d]) |
| 100 | { |
| 101 | ALOGE("Mismatched size for dimension %d (request argument: %u, expected %u)", |
| 102 | d, requestArg.dimensions[d], tensorInfo.GetShape()[d]); |
| 103 | return false; |
| 104 | } |
| 105 | } |
| 106 | } |
| 107 | |
| 108 | return true; |
| 109 | } |
| 110 | |
| 111 | armnn::Tensor GetTensorForRequestArgument(const RequestArgument& requestArg, |
| 112 | const armnn::TensorInfo& tensorInfo, |
| 113 | const std::vector<::android::nn::RunTimePoolInfo>& requestPools) |
| 114 | { |
| 115 | if (!ValidateRequestArgument(requestArg, tensorInfo)) |
| 116 | { |
| 117 | return armnn::Tensor(); |
| 118 | } |
| 119 | |
| 120 | return armnn::Tensor(tensorInfo, GetMemoryFromPool(requestArg.location, requestPools)); |
| 121 | } |
| 122 | |
| 123 | inline std::string BuildTensorName(const char* tensorNamePrefix, std::size_t index) |
| 124 | { |
| 125 | return tensorNamePrefix + std::to_string(index); |
| 126 | } |
| 127 | |
| 128 | } // anonymous namespace |
| 129 | |
| 130 | using namespace android::hardware; |
| 131 | |
| 132 | namespace armnn_driver |
| 133 | { |
| 134 | |
| 135 | template<typename HalVersion> |
| 136 | RequestThread<ArmnnPreparedModel_1_3, HalVersion, CallbackContext_1_3> |
| 137 | ArmnnPreparedModel_1_3<HalVersion>::m_RequestThread; |
| 138 | |
| 139 | template<typename HalVersion> |
| 140 | template<typename TensorBindingCollection> |
| 141 | void ArmnnPreparedModel_1_3<HalVersion>::DumpTensorsIfRequired(char const* tensorNamePrefix, |
| 142 | const TensorBindingCollection& tensorBindings) |
| 143 | { |
| 144 | if (!m_RequestInputsAndOutputsDumpDir.empty()) |
| 145 | { |
| 146 | const std::string requestName = boost::str(boost::format("%1%_%2%.dump") % m_NetworkId % m_RequestCount); |
| 147 | for (std::size_t i = 0u; i < tensorBindings.size(); ++i) |
| 148 | { |
| 149 | DumpTensor(m_RequestInputsAndOutputsDumpDir, |
| 150 | requestName, |
| 151 | BuildTensorName(tensorNamePrefix, i), |
| 152 | tensorBindings[i].second); |
| 153 | } |
| 154 | } |
| 155 | } |
| 156 | |
| 157 | template<typename HalVersion> |
| 158 | ArmnnPreparedModel_1_3<HalVersion>::ArmnnPreparedModel_1_3(armnn::NetworkId networkId, |
| 159 | armnn::IRuntime* runtime, |
| 160 | const V1_3::Model& model, |
| 161 | const std::string& requestInputsAndOutputsDumpDir, |
| 162 | const bool gpuProfilingEnabled) |
| 163 | : m_NetworkId(networkId) |
| 164 | , m_Runtime(runtime) |
| 165 | , m_Model(model) |
| 166 | , m_RequestCount(0) |
| 167 | , m_RequestInputsAndOutputsDumpDir(requestInputsAndOutputsDumpDir) |
| 168 | , m_GpuProfilingEnabled(gpuProfilingEnabled) |
| 169 | { |
| 170 | // Enable profiling if required. |
| 171 | m_Runtime->GetProfiler(m_NetworkId)->EnableProfiling(m_GpuProfilingEnabled); |
| 172 | } |
| 173 | |
| 174 | template<typename HalVersion> |
| 175 | ArmnnPreparedModel_1_3<HalVersion>::~ArmnnPreparedModel_1_3() |
| 176 | { |
| 177 | // Get a hold of the profiler used by this model. |
| 178 | std::shared_ptr<armnn::IProfiler> profiler = m_Runtime->GetProfiler(m_NetworkId); |
| 179 | |
| 180 | // Unload the network associated with this model. |
| 181 | m_Runtime->UnloadNetwork(m_NetworkId); |
| 182 | |
| 183 | // Dump the profiling info to a file if required. |
| 184 | DumpJsonProfilingIfRequired(m_GpuProfilingEnabled, m_RequestInputsAndOutputsDumpDir, m_NetworkId, profiler.get()); |
| 185 | } |
| 186 | |
| 187 | template<typename HalVersion> |
| 188 | Return <V1_0::ErrorStatus> ArmnnPreparedModel_1_3<HalVersion>::execute(const V1_0::Request& request, |
| 189 | const ::android::sp<V1_0::IExecutionCallback>& callback) |
| 190 | { |
| 191 | if (callback.get() == nullptr) |
| 192 | { |
| 193 | ALOGE("ArmnnPreparedModel_1_3::execute invalid callback passed"); |
| 194 | return V1_0::ErrorStatus::INVALID_ARGUMENT; |
| 195 | } |
| 196 | |
| 197 | auto cb = [callback](V1_3::ErrorStatus errorStatus, |
| 198 | std::vector<OutputShape> outputShapes, |
| 199 | const Timing& timing, |
| 200 | std::string callingFunction) |
| 201 | { |
| 202 | NotifyCallbackAndCheck(callback, errorStatus, outputShapes, timing, callingFunction); |
| 203 | }; |
| 204 | |
| 205 | |
| 206 | return convertToV1_0(Execute(convertToV1_3(request), MeasureTiming::NO, cb)); |
| 207 | } |
| 208 | |
| 209 | template<typename HalVersion> |
| 210 | Return <V1_0::ErrorStatus> ArmnnPreparedModel_1_3<HalVersion>::execute_1_2( |
| 211 | const V1_0::Request& request, |
| 212 | MeasureTiming measureTiming, |
| 213 | const sp<V1_2::IExecutionCallback>& callback) |
| 214 | { |
| 215 | if (callback.get() == nullptr) |
| 216 | { |
| 217 | ALOGE("ArmnnPreparedModel_1_3::execute_1_2 invalid callback passed"); |
| 218 | return V1_0::ErrorStatus::INVALID_ARGUMENT; |
| 219 | } |
| 220 | |
| 221 | auto cb = [callback](V1_3::ErrorStatus errorStatus, |
| 222 | std::vector<OutputShape> outputShapes, |
| 223 | const Timing& timing, |
| 224 | std::string callingFunction) |
| 225 | { |
| 226 | NotifyCallbackAndCheck(callback, errorStatus, outputShapes, timing, callingFunction); |
| 227 | }; |
| 228 | |
| 229 | return convertToV1_0(Execute(convertToV1_3(request), measureTiming, cb)); |
| 230 | } |
| 231 | |
| 232 | template<typename HalVersion> |
| 233 | Return <V1_3::ErrorStatus> ArmnnPreparedModel_1_3<HalVersion>::execute_1_3( |
| 234 | const V1_3::Request& request, |
| 235 | MeasureTiming measureTiming, |
| 236 | const V1_3::OptionalTimePoint&, |
Kevin May | 352d838 | 2020-03-31 15:03:42 +0100 | [diff] [blame] | 237 | const V1_3::OptionalTimeoutDuration&, |
Kevin May | 42477c1 | 2020-03-26 13:34:14 +0000 | [diff] [blame] | 238 | const sp<V1_3::IExecutionCallback>& callback) |
| 239 | { |
| 240 | if (callback.get() == nullptr) |
| 241 | { |
| 242 | ALOGE("ArmnnPreparedModel_1_3::execute_1_3 invalid callback passed"); |
| 243 | return V1_3::ErrorStatus::INVALID_ARGUMENT; |
| 244 | } |
| 245 | |
| 246 | auto cb = [callback](V1_3::ErrorStatus errorStatus, |
| 247 | std::vector<OutputShape> outputShapes, |
| 248 | const Timing& timing, |
| 249 | std::string callingFunction) |
| 250 | { |
| 251 | NotifyCallbackAndCheck(callback, errorStatus, outputShapes, timing, callingFunction); |
| 252 | }; |
| 253 | |
| 254 | return Execute(request, measureTiming, cb); |
| 255 | } |
| 256 | |
| 257 | template<typename HalVersion> |
| 258 | Return<void> ArmnnPreparedModel_1_3<HalVersion>::executeFenced(const V1_3::Request&, |
| 259 | const hidl_vec<hidl_handle>&, |
| 260 | MeasureTiming, |
| 261 | const OptionalTimePoint&, |
| 262 | const OptionalTimeoutDuration&, |
Kevin May | 352d838 | 2020-03-31 15:03:42 +0100 | [diff] [blame] | 263 | const OptionalTimeoutDuration&, |
Kevin May | 42477c1 | 2020-03-26 13:34:14 +0000 | [diff] [blame] | 264 | executeFenced_cb cb) |
| 265 | { |
Sadik Armagan | 871fe6d | 2020-04-03 15:32:39 +0100 | [diff] [blame] | 266 | cb(ErrorStatus::INVALID_ARGUMENT, hidl_handle(nullptr), nullptr); |
Kevin May | 42477c1 | 2020-03-26 13:34:14 +0000 | [diff] [blame] | 267 | return Void(); |
| 268 | } |
| 269 | |
| 270 | template<typename HalVersion> |
| 271 | Return<V1_3::ErrorStatus> ArmnnPreparedModel_1_3<HalVersion>::PrepareMemoryForInputs( |
| 272 | armnn::InputTensors& inputs, |
| 273 | const V1_3::Request& request, |
| 274 | const std::vector<android::nn::RunTimePoolInfo>& memPools) |
| 275 | { |
| 276 | inputs.reserve(request.inputs.size()); |
| 277 | for (unsigned int i = 0; i < request.inputs.size(); i++) |
| 278 | { |
| 279 | const auto& inputArg = request.inputs[i]; |
| 280 | |
| 281 | const armnn::TensorInfo inputTensorInfo = m_Runtime->GetInputTensorInfo(m_NetworkId, i); |
| 282 | const armnn::Tensor inputTensor = GetTensorForRequestArgument(inputArg, inputTensorInfo, memPools); |
| 283 | |
| 284 | if (inputTensor.GetMemoryArea() == nullptr) |
| 285 | { |
| 286 | ALOGE("Cannot execute request. Error converting request input %u to tensor", i); |
| 287 | return V1_3::ErrorStatus::GENERAL_FAILURE; |
| 288 | } |
| 289 | |
| 290 | inputs.emplace_back(i, inputTensor); |
| 291 | } |
| 292 | |
| 293 | return V1_3::ErrorStatus::NONE; |
| 294 | } |
| 295 | |
| 296 | template<typename HalVersion> |
| 297 | Return<V1_3::ErrorStatus> ArmnnPreparedModel_1_3<HalVersion>::PrepareMemoryForOutputs( |
| 298 | armnn::OutputTensors& outputs, |
| 299 | std::vector<OutputShape> &outputShapes, |
| 300 | const V1_3::Request& request, |
| 301 | const std::vector<android::nn::RunTimePoolInfo>& memPools) |
| 302 | { |
| 303 | outputs.reserve(request.outputs.size()); |
| 304 | for (unsigned int i = 0; i < request.outputs.size(); i++) |
| 305 | { |
| 306 | const auto& outputArg = request.outputs[i]; |
| 307 | |
| 308 | const armnn::TensorInfo outputTensorInfo = m_Runtime->GetOutputTensorInfo(m_NetworkId, i); |
| 309 | const armnn::Tensor outputTensor = GetTensorForRequestArgument(outputArg, outputTensorInfo, memPools); |
| 310 | if (outputTensor.GetMemoryArea() == nullptr) |
| 311 | { |
| 312 | ALOGE("Cannot execute request. Error converting request output %u to tensor", i); |
| 313 | return V1_3::ErrorStatus::GENERAL_FAILURE; |
| 314 | } |
| 315 | |
| 316 | const size_t outputSize = outputTensorInfo.GetNumBytes(); |
| 317 | const size_t bufferSize = memPools.at(outputArg.location.poolIndex).getHidlMemory().size(); |
| 318 | if (bufferSize < outputSize) |
| 319 | { |
| 320 | ALOGW("ArmnnPreparedModel_1_3::Execute failed"); |
| 321 | return V1_3::ErrorStatus::OUTPUT_INSUFFICIENT_SIZE; |
| 322 | } |
| 323 | |
| 324 | outputs.emplace_back(i, outputTensor); |
| 325 | outputShapes[i] = ComputeShape(outputTensorInfo); |
| 326 | } |
| 327 | |
| 328 | return V1_3::ErrorStatus::NONE; |
| 329 | } |
| 330 | |
| 331 | template<typename HalVersion> |
| 332 | std::tuple<V1_3::ErrorStatus, hidl_vec<OutputShape>, Timing, std::string> |
| 333 | ArmnnPreparedModel_1_3<HalVersion>::PrepareMemoryForIO(armnn::InputTensors& inputs, |
| 334 | armnn::OutputTensors& outputs, |
| 335 | std::vector<android::nn::RunTimePoolInfo>& memPools, |
| 336 | const V1_3::Request& request) |
| 337 | { |
| 338 | if (!setRunTimePoolInfosFromMemoryPools(&memPools, request.pools)) |
| 339 | { |
Sadik Armagan | ef8a393 | 2020-04-09 17:21:50 +0100 | [diff] [blame^] | 340 | return {ErrorStatus::INVALID_ARGUMENT, {}, g_NoTiming, "ArmnnPreparedModel_1_3::execute"}; |
Kevin May | 42477c1 | 2020-03-26 13:34:14 +0000 | [diff] [blame] | 341 | } |
| 342 | |
| 343 | // add the inputs and outputs with their data |
| 344 | try |
| 345 | { |
| 346 | if (PrepareMemoryForInputs(inputs, request, memPools) != V1_3::ErrorStatus::NONE) |
| 347 | { |
| 348 | return {ErrorStatus::GENERAL_FAILURE, {}, g_NoTiming, "ArmnnPreparedModel_1_3::execute"}; |
| 349 | } |
| 350 | |
| 351 | std::vector<OutputShape> outputShapes(request.outputs.size()); |
| 352 | |
| 353 | auto errorStatus = PrepareMemoryForOutputs(outputs, outputShapes, request, memPools); |
| 354 | if (errorStatus != V1_3::ErrorStatus::NONE) |
| 355 | { |
| 356 | return {errorStatus, outputShapes, g_NoTiming, "ArmnnPreparedModel_1_3::execute"}; |
| 357 | } |
| 358 | } |
| 359 | catch (armnn::Exception& e) |
| 360 | { |
| 361 | ALOGW("armnn::Exception caught while preparing for EnqueueWorkload: %s", e.what()); |
| 362 | return {ErrorStatus::GENERAL_FAILURE, {}, g_NoTiming, "ArmnnPreparedModel_1_3::execute"}; |
| 363 | } |
| 364 | catch (std::exception& e) |
| 365 | { |
| 366 | ALOGE("std::exception caught while preparing for EnqueueWorkload: %s", e.what()); |
| 367 | return {ErrorStatus::GENERAL_FAILURE, {}, g_NoTiming, "ArmnnPreparedModel_1_3::execute"}; |
| 368 | } |
| 369 | |
| 370 | return {V1_3::ErrorStatus::NONE, {}, g_NoTiming, "ArmnnPreparedModel_1_3::execute"}; |
| 371 | } |
| 372 | |
| 373 | template<typename HalVersion> |
| 374 | template<typename CallbackContext> |
| 375 | Return<void> ArmnnPreparedModel_1_3<HalVersion>::ExecuteSynchronously(const V1_3::Request& request, |
| 376 | CallbackContext cbCtx) |
| 377 | { |
| 378 | if (cbCtx.ctx.measureTimings == MeasureTiming::YES) |
| 379 | { |
| 380 | cbCtx.ctx.driverStart = Now(); |
| 381 | } |
| 382 | |
| 383 | if (!android::nn::validateRequest(convertToV1_3(request), m_Model)) |
| 384 | { |
| 385 | ALOGE("ArmnnPreparedModel_1_3::ExecuteSynchronously invalid request model"); |
| 386 | cbCtx.callback(V1_3::ErrorStatus::INVALID_ARGUMENT, |
| 387 | {}, |
| 388 | g_NoTiming, |
| 389 | "ArmnnPreparedModel_1_3::ExecuteSynchronously invalid request model"); |
| 390 | return Void(); |
| 391 | } |
| 392 | |
| 393 | if (!android::nn::validateRequest(request, m_Model)) |
| 394 | { |
| 395 | ALOGE("ArmnnPreparedModel_1_3::ExecuteSynchronously invalid request model"); |
| 396 | cbCtx.callback(V1_3::ErrorStatus::INVALID_ARGUMENT, |
| 397 | {}, |
| 398 | g_NoTiming, |
| 399 | "ArmnnPreparedModel_1_3::ExecuteSynchronously invalid request model"); |
Sadik Armagan | ef8a393 | 2020-04-09 17:21:50 +0100 | [diff] [blame^] | 400 | return Void(); |
Kevin May | 42477c1 | 2020-03-26 13:34:14 +0000 | [diff] [blame] | 401 | } |
| 402 | |
| 403 | |
| 404 | // map the memory pool into shared pointers |
| 405 | // use a shared memory pools vector on the heap, as it is passed to the request thread |
| 406 | auto memPools = std::make_shared<std::vector<android::nn::RunTimePoolInfo>>(); |
| 407 | |
| 408 | // allocate the tensors on the heap, as they are passed to the request thread |
| 409 | auto inputs = std::make_shared<armnn::InputTensors>(); |
| 410 | auto outputs = std::make_shared<armnn::OutputTensors>(); |
| 411 | |
| 412 | auto [status, outputShapes, timing, message] = PrepareMemoryForIO(*inputs, *outputs, *memPools, request); |
| 413 | if (status != V1_3::ErrorStatus::NONE) |
| 414 | { |
| 415 | cbCtx.callback(status, outputShapes, timing, message); |
Sadik Armagan | ef8a393 | 2020-04-09 17:21:50 +0100 | [diff] [blame^] | 416 | return Void(); |
Kevin May | 42477c1 | 2020-03-26 13:34:14 +0000 | [diff] [blame] | 417 | } |
| 418 | |
| 419 | ALOGV("ArmnnPreparedModel_1_3::ExecuteSynchronously() before Execution"); |
| 420 | |
| 421 | ExecuteGraph(memPools, *inputs, *outputs, cbCtx); |
| 422 | return Void(); |
| 423 | } |
| 424 | |
| 425 | template<typename HalVersion> |
| 426 | Return<void> ArmnnPreparedModel_1_3<HalVersion>::executeSynchronously(const V1_0::Request& request, |
| 427 | MeasureTiming measureTiming, |
| 428 | executeSynchronously_cb cb) |
| 429 | { |
| 430 | ALOGV("ArmnnPreparedModel_1_3::executeSynchronously(): %s", GetModelSummary(m_Model).c_str()); |
| 431 | m_RequestCount++; |
| 432 | |
| 433 | if (cb == nullptr) |
| 434 | { |
| 435 | ALOGE("ArmnnPreparedModel_1_3::executeSynchronously invalid callback passed"); |
| 436 | return Void(); |
| 437 | } |
| 438 | |
| 439 | auto cbWrapper = [cb](V1_3::ErrorStatus errorStatus, |
| 440 | std::vector<OutputShape> outputShapes, |
| 441 | const Timing& timing, |
| 442 | std::string) |
| 443 | { |
| 444 | cb(convertToV1_0(errorStatus), outputShapes, timing); |
| 445 | }; |
| 446 | |
| 447 | CallbackContext_1_3 cbCtx; |
| 448 | cbCtx.callback = cbWrapper; |
| 449 | cbCtx.ctx.measureTimings = measureTiming; |
| 450 | |
| 451 | ExecuteSynchronously(convertToV1_3(request), cbCtx); |
| 452 | return Void(); |
| 453 | } |
| 454 | |
| 455 | template<typename HalVersion> |
Kevin May | 352d838 | 2020-03-31 15:03:42 +0100 | [diff] [blame] | 456 | Return<void> ArmnnPreparedModel_1_3<HalVersion>::executeSynchronously_1_3( |
| 457 | const V1_3::Request& request, |
| 458 | MeasureTiming measureTiming, |
| 459 | const V1_3::OptionalTimePoint& deadline, |
| 460 | const V1_3::OptionalTimeoutDuration& loopTimeoutDuration, |
| 461 | executeSynchronously_1_3_cb cb) |
Kevin May | 42477c1 | 2020-03-26 13:34:14 +0000 | [diff] [blame] | 462 | { |
| 463 | ALOGV("ArmnnPreparedModel_1_3::executeSynchronously_1_3(): %s", GetModelSummary(m_Model).c_str()); |
| 464 | m_RequestCount++; |
| 465 | |
| 466 | if (cb == nullptr) |
| 467 | { |
| 468 | ALOGE("ArmnnPreparedModel_1_3::executeSynchronously_1_3 invalid callback passed"); |
| 469 | return Void(); |
| 470 | } |
| 471 | |
| 472 | if (deadline.getDiscriminator() != OptionalTimePoint::hidl_discriminator::none) |
| 473 | { |
| 474 | ALOGE("ArmnnPreparedModel_1_3::executeSynchronously_1_3 invalid request model"); |
| 475 | cb(V1_3::ErrorStatus::INVALID_ARGUMENT, {}, g_NoTiming); |
| 476 | return Void(); |
| 477 | } |
| 478 | |
Kevin May | 352d838 | 2020-03-31 15:03:42 +0100 | [diff] [blame] | 479 | if (loopTimeoutDuration.getDiscriminator() != OptionalTimeoutDuration::hidl_discriminator::none) |
| 480 | { |
| 481 | ALOGE("ArmnnPreparedModel_1_3::executeSynchronously_1_3 invalid request model"); |
| 482 | cb(V1_3::ErrorStatus::INVALID_ARGUMENT, {}, g_NoTiming); |
| 483 | return Void(); |
| 484 | } |
| 485 | |
Kevin May | 42477c1 | 2020-03-26 13:34:14 +0000 | [diff] [blame] | 486 | auto cbWrapper = [cb](V1_3::ErrorStatus errorStatus, |
| 487 | std::vector<OutputShape> outputShapes, |
| 488 | const Timing& timing, |
| 489 | std::string) |
| 490 | { |
| 491 | cb(errorStatus, outputShapes, timing); |
| 492 | }; |
| 493 | |
| 494 | CallbackContext_1_3 cbCtx; |
| 495 | cbCtx.callback = cbWrapper; |
| 496 | cbCtx.ctx.measureTimings = measureTiming; |
| 497 | |
| 498 | ExecuteSynchronously(request, cbCtx); |
| 499 | return Void(); |
| 500 | } |
| 501 | |
| 502 | template<typename HalVersion> |
| 503 | Return<void> ArmnnPreparedModel_1_3<HalVersion>::configureExecutionBurst( |
| 504 | const sp<V1_2::IBurstCallback>& callback, |
| 505 | const MQDescriptorSync<V1_2::FmqRequestDatum>& requestChannel, |
| 506 | const MQDescriptorSync<V1_2::FmqResultDatum>& resultChannel, |
| 507 | V1_3::IPreparedModel::configureExecutionBurst_cb cb) |
| 508 | { |
| 509 | ALOGV("ArmnnPreparedModel_1_3::configureExecutionBurst"); |
| 510 | const sp<V1_2::IBurstContext> burst = ExecutionBurstServer::create(callback, |
| 511 | requestChannel, |
| 512 | resultChannel, |
| 513 | this); |
| 514 | |
| 515 | if (burst == nullptr) |
| 516 | { |
| 517 | cb(V1_0::ErrorStatus::GENERAL_FAILURE, {}); |
| 518 | } |
| 519 | else |
| 520 | { |
| 521 | cb(V1_0::ErrorStatus::NONE, burst); |
| 522 | } |
| 523 | return Void(); |
| 524 | } |
| 525 | |
| 526 | template<typename HalVersion> |
| 527 | template<typename CallbackContext> |
| 528 | bool ArmnnPreparedModel_1_3<HalVersion>::ExecuteGraph( |
| 529 | std::shared_ptr<std::vector<::android::nn::RunTimePoolInfo>>& pMemPools, |
| 530 | armnn::InputTensors& inputTensors, |
| 531 | armnn::OutputTensors& outputTensors, |
| 532 | CallbackContext cb) |
| 533 | { |
| 534 | ALOGV("ArmnnPreparedModel_1_3::ExecuteGraph(...)"); |
| 535 | |
| 536 | TimePoint driverEnd, deviceStart, deviceEnd; |
| 537 | |
| 538 | DumpTensorsIfRequired("Input", inputTensors); |
| 539 | |
| 540 | std::vector<OutputShape> outputShapes(outputTensors.size()); |
| 541 | for (unsigned int i = 0; i < outputTensors.size(); i++) |
| 542 | { |
| 543 | std::pair<int, armnn::Tensor> outputTensorPair = outputTensors[i]; |
| 544 | const armnn::Tensor outputTensor = outputTensorPair.second; |
| 545 | const armnn::TensorInfo outputTensorInfo = outputTensor.GetInfo(); |
| 546 | |
| 547 | outputShapes[i] = ComputeShape(outputTensorInfo); |
| 548 | } |
| 549 | |
| 550 | // run it |
| 551 | try |
| 552 | { |
| 553 | if (cb.ctx.measureTimings == MeasureTiming::YES) |
| 554 | { |
| 555 | deviceStart = Now(); |
| 556 | } |
| 557 | |
| 558 | armnn::Status status = m_Runtime->EnqueueWorkload(m_NetworkId, inputTensors, outputTensors); |
| 559 | |
| 560 | if (cb.ctx.measureTimings == MeasureTiming::YES) |
| 561 | { |
| 562 | deviceEnd = Now(); |
| 563 | } |
| 564 | if (status != armnn::Status::Success) |
| 565 | { |
| 566 | ALOGW("EnqueueWorkload failed"); |
| 567 | cb.callback(V1_3::ErrorStatus::GENERAL_FAILURE, {}, g_NoTiming, |
| 568 | "ArmnnPreparedModel_1_3::ExecuteGraph"); |
| 569 | return false; |
| 570 | } |
| 571 | } |
| 572 | catch (armnn::Exception& e) |
| 573 | { |
| 574 | ALOGW("armnn:Exception caught from EnqueueWorkload: %s", e.what()); |
| 575 | cb.callback(V1_3::ErrorStatus::GENERAL_FAILURE, {}, g_NoTiming, "ArmnnPreparedModel_1_3::ExecuteGraph"); |
| 576 | return false; |
| 577 | } |
| 578 | catch (std::exception& e) |
| 579 | { |
| 580 | ALOGE("std::exception caught from EnqueueWorkload: %s", e.what()); |
| 581 | cb.callback(V1_3::ErrorStatus::GENERAL_FAILURE, {}, g_NoTiming, "ArmnnPreparedModel_1_3::ExecuteGraph"); |
| 582 | return false; |
| 583 | } |
| 584 | |
| 585 | CommitPools(*pMemPools); |
| 586 | |
| 587 | DumpTensorsIfRequired("Output", outputTensors); |
| 588 | |
| 589 | if (cb.ctx.measureTimings == MeasureTiming::YES) |
| 590 | { |
| 591 | driverEnd = Now(); |
| 592 | Timing timing; |
| 593 | timing.timeOnDevice = MicrosecondsDuration(deviceEnd, deviceStart); |
| 594 | timing.timeInDriver = MicrosecondsDuration(driverEnd, cb.ctx.driverStart); |
| 595 | ALOGV("ArmnnPreparedModel_1_2::execute timing - Device = %lu Driver = %lu", timing.timeOnDevice, |
| 596 | timing.timeInDriver); |
| 597 | cb.callback(V1_3::ErrorStatus::NONE, outputShapes, timing, "ArmnnPreparedModel_1_3::ExecuteGraph"); |
| 598 | } else { |
| 599 | cb.callback(V1_3::ErrorStatus::NONE, outputShapes, g_NoTiming, "ArmnnPreparedModel_1_3::ExecuteGraph"); |
| 600 | } |
| 601 | |
| 602 | return true; |
| 603 | } |
| 604 | |
| 605 | template<typename HalVersion> |
| 606 | bool ArmnnPreparedModel_1_3<HalVersion>::ExecuteWithDummyInputs() |
| 607 | { |
| 608 | std::vector<std::vector<char>> storage; |
| 609 | armnn::InputTensors inputTensors; |
| 610 | for (unsigned int i = 0; i < getMainModel(m_Model).inputIndexes.size(); i++) |
| 611 | { |
| 612 | const armnn::TensorInfo inputTensorInfo = m_Runtime->GetInputTensorInfo(m_NetworkId, i); |
| 613 | storage.emplace_back(inputTensorInfo.GetNumBytes()); |
| 614 | const armnn::ConstTensor inputTensor(inputTensorInfo, storage.back().data()); |
| 615 | |
| 616 | inputTensors.emplace_back(i, inputTensor); |
| 617 | } |
| 618 | |
| 619 | armnn::OutputTensors outputTensors; |
| 620 | for (unsigned int i = 0; i < getMainModel(m_Model).outputIndexes.size(); i++) |
| 621 | { |
| 622 | const armnn::TensorInfo outputTensorInfo = m_Runtime->GetOutputTensorInfo(m_NetworkId, i); |
| 623 | storage.emplace_back(outputTensorInfo.GetNumBytes()); |
| 624 | const armnn::Tensor outputTensor(outputTensorInfo, storage.back().data()); |
| 625 | |
| 626 | outputTensors.emplace_back(i, outputTensor); |
| 627 | } |
| 628 | |
| 629 | auto nullCallback = [](V1_3::ErrorStatus, std::vector<OutputShape>, const Timing&, std::string) {}; |
| 630 | CallbackContext_1_3 callbackContext; |
| 631 | callbackContext.callback = nullCallback; |
| 632 | callbackContext.ctx.measureTimings = MeasureTiming::NO; |
| 633 | auto memPools = std::make_shared<std::vector<::android::nn::RunTimePoolInfo>>(); |
| 634 | return ExecuteGraph(memPools, |
| 635 | inputTensors, |
| 636 | outputTensors, |
| 637 | callbackContext); |
| 638 | } |
| 639 | |
| 640 | template<typename HalVersion> |
| 641 | Return <V1_3::ErrorStatus> ArmnnPreparedModel_1_3<HalVersion>::Execute(const V1_3::Request& request, |
| 642 | MeasureTiming measureTiming, |
| 643 | CallbackAsync_1_3 callback) |
| 644 | { |
| 645 | ExecutionContext_1_3 ctx; |
| 646 | if (measureTiming == MeasureTiming::YES) |
| 647 | { |
| 648 | ctx.measureTimings = measureTiming; |
| 649 | ctx.driverStart = Now(); |
| 650 | } |
| 651 | |
| 652 | ALOGV("ArmnnPreparedModel_1_3::execute(): %s", GetModelSummary(m_Model).c_str()); |
| 653 | m_RequestCount++; |
| 654 | |
| 655 | if (!android::nn::validateRequest(request, m_Model)) |
| 656 | { |
| 657 | callback(V1_3::ErrorStatus::INVALID_ARGUMENT, {}, g_NoTiming, "ArmnnPreparedModel_1_3::execute"); |
| 658 | return V1_3::ErrorStatus::INVALID_ARGUMENT; |
| 659 | } |
| 660 | |
| 661 | if (!m_RequestInputsAndOutputsDumpDir.empty()) |
| 662 | { |
| 663 | ALOGD("Dumping inputs and outputs for request %" PRIuPTR, reinterpret_cast<std::uintptr_t>(&callback)); |
| 664 | } |
| 665 | |
| 666 | // map the memory pool into shared pointers |
| 667 | // use a shared memory pools vector on the heap, as it is passed to the request thread |
| 668 | auto memPools = std::make_shared<std::vector<android::nn::RunTimePoolInfo>>(); |
| 669 | |
| 670 | // allocate the tensors on the heap, as they are passed to the request thread |
| 671 | auto inputTensors = std::make_shared<armnn::InputTensors>(); |
| 672 | auto outputTensors = std::make_shared<armnn::OutputTensors>(); |
| 673 | |
| 674 | auto [status, outShapes, timing, message] = PrepareMemoryForIO(*inputTensors, *outputTensors, |
| 675 | *memPools, request); |
| 676 | if (status != V1_3::ErrorStatus::NONE) |
| 677 | { |
| 678 | callback(status, outShapes, timing, message); |
| 679 | } |
| 680 | |
| 681 | switch(status) |
| 682 | { |
| 683 | case V1_3::ErrorStatus::OUTPUT_INSUFFICIENT_SIZE: |
| 684 | return V1_3::ErrorStatus::NONE; |
| 685 | case V1_3::ErrorStatus::GENERAL_FAILURE: |
| 686 | return V1_3::ErrorStatus::GENERAL_FAILURE; |
| 687 | default: |
| 688 | {} |
| 689 | } |
| 690 | |
| 691 | ALOGV("ArmnnPreparedModel_1_3::execute(...) before PostMsg"); |
| 692 | |
| 693 | // post the request for asynchronous execution |
| 694 | CallbackContext_1_3 cb; |
| 695 | cb.callback = callback; |
| 696 | cb.ctx = ctx; |
| 697 | m_RequestThread.PostMsg(this, memPools, inputTensors, outputTensors, cb); |
| 698 | ALOGV("ArmnnPreparedModel_1_3::execute(...) after PostMsg"); |
| 699 | return V1_3::ErrorStatus::NONE; |
| 700 | } |
| 701 | |
| 702 | #ifdef ARMNN_ANDROID_NN_V1_3 |
| 703 | template class ArmnnPreparedModel_1_3<hal_1_3::HalPolicy>; |
| 704 | template bool ArmnnPreparedModel_1_3<hal_1_3::HalPolicy>::ExecuteGraph<CallbackContext_1_3>( |
| 705 | std::shared_ptr<std::vector<::android::nn::RunTimePoolInfo>>& pMemPools, |
| 706 | armnn::InputTensors& pInputTensors, |
| 707 | armnn::OutputTensors& pOutputTensors, |
| 708 | CallbackContext_1_3 cb); |
| 709 | #endif |
| 710 | |
| 711 | } // namespace armnn_driver |