1 /* 2 * Copyright (C) 2017 The Android Open Source Project 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 ANDROID_FRAMEWORKS_ML_NN_COMMON_UTILS_H 18 #define ANDROID_FRAMEWORKS_ML_NN_COMMON_UTILS_H 19 20 #include <android-base/logging.h> 21 22 #include <set> 23 #include <string> 24 #include <tuple> 25 #include <utility> 26 #include <vector> 27 28 #include "HalInterfaces.h" 29 #include "NeuralNetworks.h" 30 #include "ValidateHal.h" 31 32 namespace android { 33 namespace nn { 34 35 // The number of data types (OperandCode) defined in NeuralNetworks.h. 36 const int kNumberOfDataTypes = 16; 37 38 // The number of operation types (OperationCode) defined in NeuralNetworks.h. 39 const int kNumberOfOperationTypes = 102; 40 41 // The number of execution preferences defined in NeuralNetworks.h. 42 const int kNumberOfPreferences = 3; 43 44 // The number of data types (OperandCode) defined in NeuralNetworksOEM.h. 45 const int kNumberOfDataTypesOEM = 2; 46 47 // The number of operation types (OperationCode) defined in NeuralNetworksOEM.h. 48 const int kNumberOfOperationTypesOEM = 1; 49 50 // The lowest number assigned to any OEM Code in NeuralNetworksOEM.h. 51 const int kOEMCodeBase = 10000; 52 53 /* IMPORTANT: if you change the following list, don't 54 * forget to update the corresponding 'tags' table in 55 * the initVlogMask() function implemented in Utils.cpp. 56 */ 57 enum VLogFlags { MODEL = 0, COMPILATION, EXECUTION, CPUEXE, MANAGER, DRIVER, MEMORY }; 58 59 #define VLOG_IS_ON(TAG) ((vLogMask & (1 << (TAG))) != 0) 60 61 #define VLOG(TAG) \ 62 if (LIKELY(!VLOG_IS_ON(TAG))) \ 63 ; \ 64 else \ 65 LOG(INFO) 66 67 extern int vLogMask; 68 void initVLogMask(); 69 70 #ifdef NN_DEBUGGABLE 71 #define SHOW_IF_DEBUG(msg) msg 72 #else 73 #define SHOW_IF_DEBUG(msg) "" 74 #endif 75 76 // DEPRECATED(b/118737105). Use CHECK. 77 #define nnAssert(v) CHECK(v) 78 79 #define NN_RETURN_IF_ERROR(expr) \ 80 do { \ 81 int _errorCode = (expr); \ 82 if (_errorCode != ANEURALNETWORKS_NO_ERROR) { \ 83 return _errorCode; \ 84 } \ 85 } while (0) 86 87 // The NN_RET_CHECK family of macros defined below is similar to the CHECK family defined in 88 // system/core/base/include/android-base/logging.h 89 // 90 // The difference is that NN_RET_CHECK macros use LOG(ERROR) instead of LOG(FATAL) 91 // and return false instead of aborting. 92 93 // Logs an error and returns false. Append context using << after. For example: 94 // 95 // NN_RET_CHECK_FAIL() << "Something went wrong"; 96 // 97 // The containing function must return a bool. 98 #define NN_RET_CHECK_FAIL() \ 99 return ::android::nn::FalseyErrorStream() \ 100 << "NN_RET_CHECK failed (" << __FILE__ << ":" << __LINE__ << "): " 101 102 // Logs an error and returns false if condition is false. Extra logging can be appended using << 103 // after. For example: 104 // 105 // NN_RET_CHECK(false) << "Something went wrong"; 106 // 107 // The containing function must return a bool. 108 #define NN_RET_CHECK(condition) \ 109 while (UNLIKELY(!(condition))) NN_RET_CHECK_FAIL() << #condition << " " 110 111 // Helper for NN_CHECK_xx(x, y) macros. 112 #define NN_RET_CHECK_OP(LHS, RHS, OP) \ 113 for (auto _values = ::android::base::MakeEagerEvaluator(LHS, RHS); \ 114 UNLIKELY(!(_values.lhs OP _values.rhs)); \ 115 /* empty */) \ 116 NN_RET_CHECK_FAIL() << #LHS << " " << #OP << " " << #RHS << " (" << #LHS << " = " \ 117 << _values.lhs << ", " << #RHS << " = " << _values.rhs << ") " 118 119 // Logs an error and returns false if a condition between x and y does not hold. Extra logging can 120 // be appended using << after. For example: 121 // 122 // NN_RET_CHECK_EQ(a, b) << "Something went wrong"; 123 // 124 // The values must implement the appropriate comparison operator as well as 125 // `operator<<(std::ostream&, ...)`. 126 // The containing function must return a bool. 127 #define NN_RET_CHECK_EQ(x, y) NN_RET_CHECK_OP(x, y, ==) 128 #define NN_RET_CHECK_NE(x, y) NN_RET_CHECK_OP(x, y, !=) 129 #define NN_RET_CHECK_LE(x, y) NN_RET_CHECK_OP(x, y, <=) 130 #define NN_RET_CHECK_LT(x, y) NN_RET_CHECK_OP(x, y, <) 131 #define NN_RET_CHECK_GE(x, y) NN_RET_CHECK_OP(x, y, >=) 132 #define NN_RET_CHECK_GT(x, y) NN_RET_CHECK_OP(x, y, >) 133 134 // Type to represent a deadline time point across processes. 135 using Deadline = std::chrono::steady_clock::time_point; 136 137 // Make an Deadline from a duration. If the sum of the current time and the 138 // duration exceeds the max time, return a time point holding the maximum 139 // expressible time. 140 Deadline makeDeadline(uint64_t duration); 141 142 // Convenience function. If the duration is provided, this function creates a 143 // Deadline using makeDeadline. If the duration is not provided, this function 144 // returns std::nullopt. 145 std::optional<Deadline> makeDeadline(std::optional<uint64_t> duration); 146 147 // Make an optional Deadline from an OptionalTimePoint. If 148 // timePoint.nanosecondsSinceEpoch cannot be represented in Deadline, return a 149 // time point holding the maximum Deadline. If the OptionalTimePoint is none, 150 // this function returns std::nullopt. 151 std::optional<Deadline> makeDeadline(const hal::OptionalTimePoint& timePoint); 152 153 // Returns true if the deadline has passed. Returns false if either the deadline 154 // has not been exceeded or if the deadline is not present. 155 bool hasDeadlinePassed(const std::optional<Deadline>& deadline); 156 157 // Make an OptionalTimePoint from an optional Deadline. If the Deadline is not 158 // provided, this function returns none for OptionalTimePoint. 159 hal::OptionalTimePoint makeTimePoint(const std::optional<Deadline>& deadline); 160 161 // Ensure that every user of FalseyErrorStream is linked to the 162 // correct instance, using the correct LOG_TAG 163 namespace { 164 165 // A wrapper around LOG(ERROR) that can be implicitly converted to bool (always evaluates to false). 166 // Used to implement stream logging in NN_RET_CHECK. 167 class FalseyErrorStream { 168 DISALLOW_COPY_AND_ASSIGN(FalseyErrorStream); 169 170 public: FalseyErrorStream()171 FalseyErrorStream() {} 172 173 template <typename T> 174 FalseyErrorStream& operator<<(const T& value) { 175 mBuffer << value; 176 return *this; 177 } 178 ~FalseyErrorStream()179 ~FalseyErrorStream() { LOG(ERROR) << mBuffer.str(); } 180 181 operator bool() const { return false; } 182 183 private: 184 std::ostringstream mBuffer; 185 }; 186 187 template <HalVersion version> 188 struct VersionedType {}; 189 190 template <> 191 struct VersionedType<HalVersion::V1_2> { 192 using OperandPerformance = hal::V1_2::Capabilities::OperandPerformance; 193 using OperandType = hal::V1_2::OperandType; 194 }; 195 196 template <> 197 struct VersionedType<HalVersion::V1_3> { 198 using OperandPerformance = hal::V1_3::Capabilities::OperandPerformance; 199 using OperandType = hal::V1_3::OperandType; 200 }; 201 202 template <HalVersion version> 203 using VersionedOperandPerformance = typename VersionedType<version>::OperandPerformance; 204 template <HalVersion version> 205 using VersionedOperandType = typename VersionedType<version>::OperandType; 206 207 } // namespace 208 209 // Return a vector with one entry for each non-extension OperandType except 210 // SUBGRAPH, set to the specified PerformanceInfo value. The vector will be 211 // sorted by OperandType. 212 // 213 // Control flow (OperandType::SUBGRAPH) operation performance is specified 214 // separately using Capabilities::ifPerformance and 215 // Capabilities::whilePerformance. 216 template <HalVersion version> 217 hal::hidl_vec<VersionedOperandPerformance<version>> nonExtensionOperandPerformance( 218 hal::PerformanceInfo perf); 219 220 // Update the vector entry corresponding to the specified OperandType with the 221 // specified PerformanceInfo value. The vector must already have an entry for 222 // that OperandType, and must be sorted by OperandType. 223 void update(hal::hidl_vec<hal::V1_2::Capabilities::OperandPerformance>* operandPerformance, 224 hal::V1_2::OperandType type, hal::PerformanceInfo perf); 225 void update(hal::hidl_vec<hal::V1_3::Capabilities::OperandPerformance>* operandPerformance, 226 hal::V1_3::OperandType type, hal::PerformanceInfo perf); 227 228 // Look for a vector entry corresponding to the specified OperandType. If 229 // found, return the associated PerformanceInfo. If not, return a pessimistic 230 // PerformanceInfo (FLT_MAX). The vector must be sorted by OperandType. 231 hal::PerformanceInfo lookup( 232 const hal::hidl_vec<hal::V1_2::Capabilities::OperandPerformance>& operandPerformance, 233 hal::V1_2::OperandType type); 234 hal::PerformanceInfo lookup( 235 const hal::hidl_vec<hal::V1_3::Capabilities::OperandPerformance>& operandPerformance, 236 hal::V1_3::OperandType type); 237 238 // Returns true if an operand type is an extension type. 239 bool isExtensionOperandType(hal::OperandType type); 240 241 // Returns true if an operation type is an extension type. 242 bool isExtensionOperationType(hal::OperationType type); 243 244 // Returns the amount of space needed to store a value of the specified 245 // dimensions and type. For a tensor with unspecified rank or at least one 246 // unspecified dimension, returns zero. 247 // 248 // Aborts if the specified type is an extension type. 249 // Aborts if the size would overflow the return type. 250 // 251 // See also TypeManager::getSizeOfData(OperandType, const std::vector<uint32_t>&). 252 uint32_t nonExtensionOperandSizeOfData(hal::OperandType type, 253 const std::vector<uint32_t>& dimensions); 254 255 // Returns the amount of space needed to store a value of the dimensions and 256 // type of this operand. For a tensor with unspecified rank or at least one 257 // unspecified dimension, returns zero. 258 // 259 // Aborts if the specified type is an extension type. 260 // Aborts if the size would overflow the return type. 261 // 262 // See also TypeManager::getSizeOfData(const Operand&). 263 inline uint32_t nonExtensionOperandSizeOfData(const hal::Operand& operand) { 264 return nonExtensionOperandSizeOfData(operand.type, operand.dimensions); 265 } 266 267 // Returns the amount of space needed to store a value of the specified 268 // dimensions and element size. For a tensor with unspecified rank or at least 269 // one unspecified dimension, returns zero. 270 // 271 // Aborts if the size would overflow the return type. 272 // 273 // See also TypeManager::getSizeOfData(const Operand&). 274 uint32_t sizeOfTensorData(uint32_t sizeOfElement, const std::vector<uint32_t>& dimensions); 275 276 // Returns true if the amount of space needed to store a value of the specified 277 // dimensions and element size overflows the uint32_t type. 278 // 279 // Aborts if the specified type is an extension type. 280 // 281 // See also TypeManager::sizeOfDataOverflowsUInt32(OperandType, const std::vector<uint32_t>&). 282 bool nonExtensionOperandSizeOfDataOverflowsUInt32(hal::OperandType type, 283 const std::vector<uint32_t>& dimensions); 284 285 // Returns true if the amount of space needed to store a value of the specified 286 // dimensions and element size overflows the uint32_t type. 287 // 288 // See also TypeManager::sizeOfDataOverflowsUInt32(OperandType, const std::vector<uint32_t>&). 289 bool sizeOfTensorDataOverflowsUInt32(uint32_t elementSize, const std::vector<uint32_t>& dimensions); 290 291 // Returns true if a non-extension operand type is a scalar type. 292 // 293 // Aborts if the specified type is an extension type. 294 // 295 // See also TypeManager::isTensorType(OperandType). 296 bool nonExtensionOperandTypeIsScalar(int type); 297 298 // Returns the name of the operation type in ASCII. 299 std::string getOperationName(hal::OperationType opCode); 300 301 // Returns the name of the operand type in ASCII. 302 std::string getOperandTypeName(hal::OperandType type); 303 304 // Whether an operand of tensor type has unspecified dimensions. 305 // 306 // Undefined behavior if the operand type is a scalar type. 307 bool tensorHasUnspecifiedDimensions(int type, const uint32_t* dim, uint32_t dimCount); 308 bool tensorHasUnspecifiedDimensions(hal::OperandType type, const std::vector<uint32_t>& dimensions); 309 bool tensorHasUnspecifiedDimensions(const hal::Operand& operand); 310 bool tensorHasUnspecifiedDimensions(const ANeuralNetworksOperandType* type); 311 312 // Returns the number of padding bytes needed to align data of the 313 // specified length. It aligns object of length: 314 // 2, 3 on a 2 byte boundary, 315 // 4+ on a 4 byte boundary. 316 // We may want to have different alignments for tensors. 317 // TODO: This is arbitrary, more a proof of concept. We need 318 // to determine what this should be. 319 uint32_t alignBytesNeeded(uint32_t index, size_t length); 320 321 // Does a detailed LOG(INFO) of the model 322 void logModelToInfo(const hal::V1_0::Model& model); 323 void logModelToInfo(const hal::V1_1::Model& model); 324 void logModelToInfo(const hal::V1_2::Model& model); 325 void logModelToInfo(const hal::V1_3::Model& model); 326 327 inline std::string toString(uint32_t obj) { 328 return std::to_string(obj); 329 } 330 331 template <typename Type> 332 std::string toString(const std::vector<Type>& range) { 333 std::string os = "["; 334 for (size_t i = 0; i < range.size(); ++i) { 335 os += (i == 0 ? "" : ", ") + toString(range[i]); 336 } 337 return os += "]"; 338 } 339 340 template <typename A, typename B> 341 std::string toString(const std::pair<A, B>& pair) { 342 std::ostringstream oss; 343 oss << "(" << toString(pair.first) << ", " << toString(pair.second) << ")"; 344 return oss.str(); 345 } 346 347 inline std::string toString(HalVersion halVersion) { 348 switch (halVersion) { 349 case HalVersion::UNKNOWN: 350 return "UNKNOWN HAL version"; 351 case HalVersion::V1_0: 352 return "HAL version 1.0"; 353 case HalVersion::V1_1: 354 return "HAL version 1.1"; 355 case HalVersion::V1_2: 356 return "HAL version 1.2"; 357 case HalVersion::V1_3: 358 return "HAL version 1.3"; 359 } 360 } 361 362 inline bool validCode(uint32_t codeCount, uint32_t codeCountOEM, uint32_t code) { 363 return (code < codeCount) || (code >= kOEMCodeBase && (code - kOEMCodeBase) < codeCountOEM); 364 } 365 366 bool validateOperandSymmPerChannelQuantParams( 367 const hal::Operand& halOperand, 368 const ANeuralNetworksSymmPerChannelQuantParams& channelQuant, const char* tag); 369 370 // Validates an operand type. 371 // 372 // extensionOperandTypeInfo must be nullptr iff the type is not an extension type. 373 // 374 // If allowPartial is true, the dimensions may be underspecified. 375 int validateOperandType( 376 const ANeuralNetworksOperandType& type, 377 const hal::Extension::OperandTypeInformation* const extensionOperandTypeInfo, 378 const char* tag, bool allowPartial); 379 int validateOperandList(uint32_t count, const uint32_t* list, uint32_t operandCount, 380 const char* tag); 381 382 // A set of functions to help validate models containing IF or WHILE operations. 383 struct SubgraphValidationHelper { 384 // Checks if a given operand is a SUBGRAPH operand with a valid offset. 385 std::function<bool(const hal::Operand&)> isValidSubgraphReference; 386 // Gets the input count of a subgraph referenced by a given operand. 387 std::function<uint32_t(const hal::Operand&)> getSubgraphInputCount; 388 // Gets the output count of a subgraph referenced by a given operand. 389 std::function<uint32_t(const hal::Operand&)> getSubgraphOutputCount; 390 // Gets the specified input operand of a subgraph referenced by a given operand. 391 std::function<const hal::Operand*(const hal::Operand&, uint32_t)> getSubgraphInputOperand; 392 // Gets the specified output operand of a subgraph referenced by a given operand. 393 std::function<const hal::Operand*(const hal::Operand&, uint32_t)> getSubgraphOutputOperand; 394 // Whether control flow operations with inner or outer input or output 395 // operands of unknown size are allowed. 396 bool allowControlFlowOperationWithOperandOfUnknownSize; 397 }; 398 399 // Returns ANEURALNETWORKS_NO_ERROR if the corresponding operation is defined and can handle the 400 // provided operand types in the given HAL version, otherwise returns ANEURALNETWORKS_BAD_DATA. 401 // The last argument is only used for validating IF and WHILE operations. 402 int validateOperation(ANeuralNetworksOperationType opType, uint32_t inputCount, 403 const uint32_t* inputIndexes, uint32_t outputCount, 404 const uint32_t* outputIndexes, const std::vector<hal::Operand>& operands, 405 HalVersion halVersion, const SubgraphValidationHelper& helper); 406 407 inline size_t getSizeFromInts(int lower, int higher) { 408 return (uint32_t)(lower) + ((uint64_t)(uint32_t)(higher) << 32); 409 } 410 411 // Convert ANEURALNETWORKS_* result code to ErrorStatus. 412 // Not guaranteed to be a 1-to-1 mapping. 413 hal::ErrorStatus convertResultCodeToErrorStatus(int resultCode); 414 415 // Convert ErrorStatus to ANEURALNETWORKS_* result code. 416 // Not guaranteed to be a 1-to-1 mapping. 417 int convertErrorStatusToResultCode(hal::ErrorStatus status); 418 419 // Convert execution results to runtime format. Additionally checks that the 420 // returned results abide by the HAL specification, and logs an error if the 421 // result violates the specification. 422 std::tuple<int, std::vector<hal::OutputShape>, hal::Timing> getExecutionResult( 423 hal::ErrorStatus status, std::vector<hal::OutputShape> outputShapes, hal::Timing timing); 424 425 // Combine two tensor dimensions, both may have unspecified dimensions or rank. 426 std::optional<std::vector<uint32_t>> combineDimensions(const std::vector<uint32_t>& lhs, 427 const std::vector<uint32_t>& rhs); 428 429 // Versioning 430 431 bool compliantWithV1_0(const hal::V1_0::Capabilities& capabilities); 432 bool compliantWithV1_0(const hal::V1_1::Capabilities& capabilities); 433 bool compliantWithV1_0(const hal::V1_2::Capabilities& capabilities); 434 bool compliantWithV1_0(const hal::V1_3::Capabilities& capabilities); 435 bool compliantWithV1_1(const hal::V1_0::Capabilities& capabilities); 436 bool compliantWithV1_1(const hal::V1_1::Capabilities& capabilities); 437 bool compliantWithV1_1(const hal::V1_2::Capabilities& capabilities); 438 bool compliantWithV1_1(const hal::V1_3::Capabilities& capabilities); 439 bool compliantWithV1_2(const hal::V1_0::Capabilities& capabilities); 440 bool compliantWithV1_2(const hal::V1_1::Capabilities& capabilities); 441 bool compliantWithV1_2(const hal::V1_2::Capabilities& capabilities); 442 bool compliantWithV1_2(const hal::V1_3::Capabilities& capabilities); 443 bool compliantWithV1_3(const hal::V1_0::Capabilities& capabilities); 444 bool compliantWithV1_3(const hal::V1_1::Capabilities& capabilities); 445 bool compliantWithV1_3(const hal::V1_2::Capabilities& capabilities); 446 bool compliantWithV1_3(const hal::V1_3::Capabilities& capabilities); 447 448 // If noncompliantOperations != nullptr, then 449 // precondition: noncompliantOperations->empty() 450 // postcondition: *noncompliantOperations consists of the indices of the noncompliant 451 // operations; if the compliance check fails for some reason 452 // other than a noncompliant operation, 453 // *noncompliantOperations consists of the indices of all operations 454 bool compliantWithV1_0(const hal::V1_0::Model& model); 455 bool compliantWithV1_0(const hal::V1_1::Model& model); 456 bool compliantWithV1_0(const hal::V1_2::Model& model, 457 std::set<uint32_t>* noncompliantOperations = nullptr); 458 bool compliantWithV1_0(const hal::V1_3::Model& model, 459 std::set<uint32_t>* noncompliantOperations = nullptr); 460 bool compliantWithV1_1(const hal::V1_0::Model& model); 461 bool compliantWithV1_1(const hal::V1_1::Model& model); 462 bool compliantWithV1_1(const hal::V1_2::Model& model, 463 std::set<uint32_t>* noncompliantOperations = nullptr); 464 bool compliantWithV1_1(const hal::V1_3::Model& model, 465 std::set<uint32_t>* noncompliantOperations = nullptr); 466 bool compliantWithV1_2(const hal::V1_0::Model& model); 467 bool compliantWithV1_2(const hal::V1_1::Model& model); 468 bool compliantWithV1_2(const hal::V1_2::Model& model, 469 std::set<uint32_t>* noncompliantOperations = nullptr); 470 bool compliantWithV1_2(const hal::V1_3::Model& model, 471 std::set<uint32_t>* noncompliantOperations = nullptr); 472 473 hal::V1_0::ErrorStatus convertToV1_0(hal::V1_0::ErrorStatus status); 474 hal::V1_0::ErrorStatus convertToV1_0(hal::V1_3::ErrorStatus status); 475 hal::V1_3::ErrorStatus convertToV1_3(hal::V1_0::ErrorStatus status); 476 hal::V1_3::ErrorStatus convertToV1_3(hal::V1_3::ErrorStatus status); 477 478 hal::V1_0::Capabilities convertToV1_0(const hal::V1_0::Capabilities& capabilities); 479 hal::V1_0::Capabilities convertToV1_0(const hal::V1_1::Capabilities& capabilities); 480 hal::V1_0::Capabilities convertToV1_0(const hal::V1_2::Capabilities& capabilities); 481 hal::V1_0::Capabilities convertToV1_0(const hal::V1_3::Capabilities& capabilities); 482 hal::V1_1::Capabilities convertToV1_1(const hal::V1_0::Capabilities& capabilities); 483 hal::V1_1::Capabilities convertToV1_1(const hal::V1_1::Capabilities& capabilities); 484 hal::V1_1::Capabilities convertToV1_1(const hal::V1_2::Capabilities& capabilities); 485 hal::V1_1::Capabilities convertToV1_1(const hal::V1_3::Capabilities& capabilities); 486 hal::V1_2::Capabilities convertToV1_2(const hal::V1_0::Capabilities& capabilities); 487 hal::V1_2::Capabilities convertToV1_2(const hal::V1_1::Capabilities& capabilities); 488 hal::V1_2::Capabilities convertToV1_2(const hal::V1_2::Capabilities& capabilities); 489 hal::V1_2::Capabilities convertToV1_2(const hal::V1_3::Capabilities& capabilities); 490 hal::V1_3::Capabilities convertToV1_3(const hal::V1_0::Capabilities& capabilities); 491 hal::V1_3::Capabilities convertToV1_3(const hal::V1_1::Capabilities& capabilities); 492 hal::V1_3::Capabilities convertToV1_3(const hal::V1_2::Capabilities& capabilities); 493 hal::V1_3::Capabilities convertToV1_3(const hal::V1_3::Capabilities& capabilities); 494 495 hal::V1_0::Model convertToV1_0(const hal::V1_0::Model& model); 496 hal::V1_0::Model convertToV1_0(const hal::V1_1::Model& model); 497 hal::V1_0::Model convertToV1_0(const hal::V1_2::Model& model); 498 hal::V1_0::Model convertToV1_0(const hal::V1_3::Model& model); 499 hal::V1_1::Model convertToV1_1(const hal::V1_0::Model& model); 500 hal::V1_1::Model convertToV1_1(const hal::V1_1::Model& model); 501 hal::V1_1::Model convertToV1_1(const hal::V1_2::Model& model); 502 hal::V1_1::Model convertToV1_1(const hal::V1_3::Model& model); 503 hal::V1_2::Model convertToV1_2(const hal::V1_0::Model& model); 504 hal::V1_2::Model convertToV1_2(const hal::V1_1::Model& model); 505 hal::V1_2::Model convertToV1_2(const hal::V1_2::Model& model); 506 hal::V1_2::Model convertToV1_2(const hal::V1_3::Model& model); 507 hal::V1_3::Model convertToV1_3(const hal::V1_0::Model& model); 508 hal::V1_3::Model convertToV1_3(const hal::V1_1::Model& model); 509 hal::V1_3::Model convertToV1_3(const hal::V1_2::Model& model); 510 hal::V1_3::Model convertToV1_3(const hal::V1_3::Model& model); 511 512 hal::V1_0::OperationType uncheckedConvertToV1_0(hal::V1_3::OperationType type); 513 hal::V1_1::OperationType uncheckedConvertToV1_1(hal::V1_3::OperationType type); 514 hal::V1_2::OperationType uncheckedConvertToV1_2(hal::V1_3::OperationType type); 515 516 hal::V1_0::Operand convertToV1_0(const hal::V1_2::Operand& operand); 517 hal::V1_0::Operand convertToV1_0(const hal::V1_3::Operand& operand); 518 hal::V1_2::Operand convertToV1_2(const hal::V1_0::Operand& operand); 519 hal::V1_2::Operand convertToV1_2(const hal::V1_3::Operand& operand); 520 hal::V1_3::Operand convertToV1_3(const hal::V1_0::Operand& operand); 521 hal::V1_3::Operand convertToV1_3(const hal::V1_2::Operand& operand); 522 hal::V1_3::Operand convertToV1_3(const hal::V1_3::Operand& operand); 523 524 hal::hidl_vec<hal::V1_0::Operand> convertToV1_0(const hal::hidl_vec<hal::V1_0::Operand>& operands); 525 hal::hidl_vec<hal::V1_0::Operand> convertToV1_0(const hal::hidl_vec<hal::V1_2::Operand>& operands); 526 hal::hidl_vec<hal::V1_0::Operand> convertToV1_0(const hal::hidl_vec<hal::V1_3::Operand>& operands); 527 hal::hidl_vec<hal::V1_2::Operand> convertToV1_2(const hal::hidl_vec<hal::V1_0::Operand>& operands); 528 hal::hidl_vec<hal::V1_2::Operand> convertToV1_2(const hal::hidl_vec<hal::V1_2::Operand>& operands); 529 hal::hidl_vec<hal::V1_2::Operand> convertToV1_2(const hal::hidl_vec<hal::V1_3::Operand>& operands); 530 hal::hidl_vec<hal::V1_3::Operand> convertToV1_3(const hal::hidl_vec<hal::V1_0::Operand>& operands); 531 hal::hidl_vec<hal::V1_3::Operand> convertToV1_3(const hal::hidl_vec<hal::V1_2::Operand>& operands); 532 hal::hidl_vec<hal::V1_3::Operand> convertToV1_3(const hal::hidl_vec<hal::V1_3::Operand>& operands); 533 534 bool compliantWithV1_0(const hal::V1_0::Request& request); 535 bool compliantWithV1_0(const hal::V1_3::Request& request); 536 bool compliantWithV1_2(const hal::V1_3::Request& request); 537 538 hal::V1_0::Request convertToV1_0(const hal::V1_0::Request& request); 539 hal::V1_0::Request convertToV1_0(const hal::V1_3::Request& request); 540 hal::V1_0::Request convertToV1_2(const hal::V1_3::Request& request); 541 hal::V1_3::Request convertToV1_3(const hal::V1_0::Request& request); 542 hal::V1_3::Request convertToV1_3(const hal::V1_3::Request& request); 543 544 bool compliantWithV1_0(hal::V1_0::OperandLifeTime lifetime); 545 bool compliantWithV1_0(hal::V1_3::OperandLifeTime lifetime); 546 bool compliantWithV1_3(hal::V1_0::OperandLifeTime lifetime); 547 bool compliantWithV1_3(hal::V1_3::OperandLifeTime lifetime); 548 549 hal::V1_0::OperandLifeTime convertToV1_0(hal::V1_0::OperandLifeTime lifetime); 550 hal::V1_0::OperandLifeTime convertToV1_0(hal::V1_3::OperandLifeTime lifetime); 551 hal::V1_3::OperandLifeTime convertToV1_3(hal::V1_0::OperandLifeTime lifetime); 552 hal::V1_3::OperandLifeTime convertToV1_3(hal::V1_3::OperandLifeTime lifetime); 553 554 constexpr hal::Priority convertToHalPriority(int32_t priority) { 555 switch (priority) { 556 case ANEURALNETWORKS_PRIORITY_LOW: 557 return hal::Priority::LOW; 558 case ANEURALNETWORKS_PRIORITY_MEDIUM: 559 return hal::Priority::MEDIUM; 560 case ANEURALNETWORKS_PRIORITY_HIGH: 561 return hal::Priority::HIGH; 562 } 563 LOG(FATAL) << "unrecognized priority: " << priority; 564 return {}; 565 } 566 567 // The function syncWait() has the same semantics as the system function 568 // ::sync_wait(), except that the syncWait() return value is semantically 569 // richer. The timeout parameter is in msecs. 570 enum class FenceState { 571 ACTIVE, // fence has not been signaled 572 SIGNALED, // fence has been signaled 573 ERROR, // fence has been placed in the error state 574 UNKNOWN, // either bad argument passed to syncWait(), or internal error 575 }; 576 FenceState syncWait(int fd, int timeout); 577 578 #ifdef NN_DEBUGGABLE 579 uint32_t getProp(const char* str, uint32_t defaultValue = 0); 580 #endif // NN_DEBUGGABLE 581 582 } // namespace nn 583 } // namespace android 584 585 #endif // ANDROID_FRAMEWORKS_ML_NN_COMMON_UTILS_H 586