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Diffstat (limited to 'runtimes/nn/common/Utils.cpp')
| -rw-r--r-- | runtimes/nn/common/Utils.cpp | 397 |
1 files changed, 0 insertions, 397 deletions
diff --git a/runtimes/nn/common/Utils.cpp b/runtimes/nn/common/Utils.cpp deleted file mode 100644 index 7f0adea8e..000000000 --- a/runtimes/nn/common/Utils.cpp +++ /dev/null @@ -1,397 +0,0 @@ -/* - * Copyright (c) 2018 Samsung Electronics Co., Ltd. All Rights Reserved - * Copyright (C) 2017 The Android Open Source Project - * - * Licensed under the Apache License, Version 2.0 (the "License"); - * you may not use this file except in compliance with the License. - * You may obtain a copy of the License at - * - * http://www.apache.org/licenses/LICENSE-2.0 - * - * Unless required by applicable law or agreed to in writing, software - * distributed under the License is distributed on an "AS IS" BASIS, - * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. - * See the License for the specific language governing permissions and - * limitations under the License. - */ - -#include "Utils.h" -#include "NeuralNetworks.h" - -namespace nnfw { -namespace rt { - -#define COUNT(X) (sizeof(X) / sizeof(X[0])) - -const char* kTypeNames[kNumberOfDataTypes] = { - "FLOAT32", "INT32", "UINT32", - "TENSOR_FLOAT32", "TENSOR_INT32", "TENSOR_QUANT8_ASYMM", -}; - -static_assert(COUNT(kTypeNames) == kNumberOfDataTypes, "kTypeNames is incorrect"); - -const char* kTypeNamesOEM[kNumberOfDataTypesOEM] = { - "OEM", "TENSOR_OEM_BYTE", -}; - -static_assert(COUNT(kTypeNamesOEM) == kNumberOfDataTypesOEM, "kTypeNamesOEM is incorrect"); - -// TODO Check if this useful -const char* kErrorNames[] = { - "NO_ERROR", "OUT_OF_MEMORY", "INCOMPLETE", "NULL", "BAD_DATA", -}; - -namespace { - -template <typename EntryType, uint32_t entryCount, uint32_t entryCountOEM> -EntryType tableLookup(const EntryType (&table)[entryCount], - const EntryType (&tableOEM)[entryCountOEM], - uint32_t code) { - if (code < entryCount) { - return table[code]; - } else if (code >= kOEMCodeBase && (code - kOEMCodeBase) < entryCountOEM) { - return tableOEM[code - kOEMCodeBase]; - } else { - nnAssert(!"tableLookup: bad code"); - return EntryType(); - } -} - -}; // anonymous namespace - -const char* kOperationNames[kNumberOfOperationTypes] = { - "ADD", - "AVERAGE_POOL", - "CONCATENATION", - "CONV", - "DEPTHWISE_CONV", - "DEPTH_TO_SPACE", - "DEQUANTIZE", - "EMBEDDING_LOOKUP", - "FLOOR", - "FULLY_CONNECTED", - "HASHTABLE_LOOKUP", - "L2_NORMALIZATION", - "L2_POOL", - "LOCAL_RESPONSE_NORMALIZATION", - "LOGISTIC", - "LSH_PROJECTION", - "LSTM", - "MAX_POOL", - "MUL", - "RELU", - "RELU1", - "RELU6", - "RESHAPE", - "RESIZE_BILINEAR", - "RNN", - "SOFTMAX", - "SPACE_TO_DEPTH", - "SVDF", - "TANH", -}; - -static_assert(COUNT(kOperationNames) == kNumberOfOperationTypes, "kOperationNames is incorrect"); - -const char* kOperationNamesOEM[kNumberOfOperationTypesOEM] = { - "OEM_OPERATION", -}; - -static_assert(COUNT(kOperationNamesOEM) == kNumberOfOperationTypesOEM, - "kOperationNamesOEM is incorrect"); - -const char* getOperationName(OperationType type) { - uint32_t n = static_cast<uint32_t>(type); - return tableLookup(kOperationNames, kOperationNamesOEM, n); -} - -const uint32_t kSizeOfDataType[]{ - 4, // ANEURALNETWORKS_FLOAT32 - 4, // ANEURALNETWORKS_INT32 - 4, // ANEURALNETWORKS_UINT32 - 4, // ANEURALNETWORKS_TENSOR_FLOAT32 - 4, // ANEURALNETWORKS_TENSOR_INT32 - 1 // ANEURALNETWORKS_TENSOR_SYMMETRICAL_QUANT8 -}; - -static_assert(COUNT(kSizeOfDataType) == kNumberOfDataTypes, "kSizeOfDataType is incorrect"); - -const bool kScalarDataType[]{ - true, // ANEURALNETWORKS_FLOAT32 - true, // ANEURALNETWORKS_INT32 - true, // ANEURALNETWORKS_UINT32 - false, // ANEURALNETWORKS_TENSOR_FLOAT32 - false, // ANEURALNETWORKS_TENSOR_INT32 - false, // ANEURALNETWORKS_TENSOR_SYMMETRICAL_QUANT8 -}; - -static_assert(COUNT(kScalarDataType) == kNumberOfDataTypes, "kScalarDataType is incorrect"); - -const uint32_t kSizeOfDataTypeOEM[]{ - 0, // ANEURALNETWORKS_OEM - 1, // ANEURALNETWORKS_TENSOR_OEM_BYTE -}; - -static_assert(COUNT(kSizeOfDataTypeOEM) == kNumberOfDataTypesOEM, - "kSizeOfDataTypeOEM is incorrect"); - -const bool kScalarDataTypeOEM[]{ - true, // ANEURALNETWORKS_OEM - false, // ANEURALNETWORKS_TENSOR_OEM_BYTE -}; - -static_assert(COUNT(kScalarDataTypeOEM) == kNumberOfDataTypesOEM, - "kScalarDataTypeOEM is incorrect"); - -uint32_t sizeOfData(OperandType type, const std::vector<uint32_t>& dimensions) { - int n = static_cast<int>(type); - - uint32_t size = tableLookup(kSizeOfDataType, kSizeOfDataTypeOEM, n); - - if (tableLookup(kScalarDataType, kScalarDataTypeOEM, n) == true) { - return size; - } - - for (auto d : dimensions) { - size *= d; - } - return size; -} - -// TODO-NNRT : Should be changed to allocate hidl_memory using Allocator. -// And Should change naming to "allocateMemory". -hidl_memory allocateSharedMemory(int64_t size) { - hidl_memory memory; -#if 0 // TODO-NNRT : Use shared memory or hidl memory - - // TODO: should we align memory size to nearest page? doesn't seem necessary... - const std::string& type = "ashmem"; - sp<IAllocator> allocator = IAllocator::getService(type); - allocator->allocate(size, [&](bool success, const hidl_memory& mem) { - if (!success) { - LOG(ERROR) << "unable to allocate " << size << " bytes of " << type; - } else { - memory = mem; - } - }); -#endif - LOG(ERROR) << "Not support to allocate shared memory now."; - return memory; -} - -uint32_t alignBytesNeeded(uint32_t index, size_t length) { - uint32_t pattern; - if (length < 2) { - pattern = 0; // No alignment necessary - } else if (length < 4) { - pattern = 1; // Align on 2-byte boundary - } else { - pattern = 3; // Align on 4-byte boundary - } - uint32_t extra = (~(index - 1)) & pattern; - return extra; -} - -// Validates the type. The used dimensions can be underspecified. -int validateOperandType(const ANeuralNetworksOperandType& type, const char* tag, - bool allowPartial) { - if (!allowPartial) { - for (uint32_t i = 0; i < type.dimensionCount; i++) { - if (type.dimensions[i] == 0) { - LOG(ERROR) << tag << " OperandType invalid dimensions[" << i - << "] = " << type.dimensions[i]; - return ANEURALNETWORKS_BAD_DATA; - } - } - } - if (!validCode(kNumberOfDataTypes, kNumberOfDataTypesOEM, type.type)) { - LOG(ERROR) << tag << " OperandType invalid type " << type.type; - return ANEURALNETWORKS_BAD_DATA; - } - if (type.type == ANEURALNETWORKS_TENSOR_QUANT8_ASYMM) { - if (type.zeroPoint < 0 || type.zeroPoint > 255) { - LOG(ERROR) << tag << " OperandType invalid zeroPoint " << type.zeroPoint; - return ANEURALNETWORKS_BAD_DATA; - } - if (type.scale < 0.f) { - LOG(ERROR) << tag << " OperandType invalid scale " << type.scale; - return ANEURALNETWORKS_BAD_DATA; - } - } - - // TODO-NNRT : add 'type.type == ANEURALNETWORKS_OEM_SCALAR' later. - // OEM operaters are not supported now. - if (type.type == ANEURALNETWORKS_FLOAT32 || - type.type == ANEURALNETWORKS_INT32 || - type.type == ANEURALNETWORKS_UINT32) { - if (type.dimensionCount != 0 || type.dimensions != nullptr) { - LOG(ERROR) << tag << " Invalid dimensions for scalar type"; - return ANEURALNETWORKS_BAD_DATA; - } - } - - return ANEURALNETWORKS_NO_ERROR; -} - -int validateOperandList(uint32_t count, const uint32_t* list, uint32_t operandCount, - const char* tag) { - for (uint32_t i = 0; i < count; i++) { - if (list[i] >= operandCount) { - LOG(ERROR) << tag << " invalid operand index at " << i << " = " << list[i] - << ", operandCount " << operandCount; - return ANEURALNETWORKS_BAD_DATA; - } - } - return ANEURALNETWORKS_NO_ERROR; -} - -static bool validOperandIndexes(const hidl_vec<uint32_t> indexes, size_t operandCount) { - for (uint32_t i : indexes) { - if (i >= operandCount) { - LOG(ERROR) << "Index out of range " << i << "/" << operandCount; - return false; - } - } - return true; -} - -static bool validOperands(const hidl_vec<Operand>& operands, const hidl_vec<uint8_t>& operandValues, - size_t poolCount) { - for (auto& operand : operands) { - if (!validCode(kNumberOfDataTypes, kNumberOfDataTypesOEM, - static_cast<uint32_t>(operand.type))) { - LOG(ERROR) << "Invalid operand type "; - return false; - } - /* TODO validate dim with type - if (!validOperandIndexes(operand.dimensions, mDimensions)) { - return false; - } - */ - switch (operand.lifetime) { - case OperandLifeTime::CONSTANT_COPY: - if (operand.location.offset + operand.location.length > operandValues.size()) { - LOG(ERROR) << "OperandValue location out of range. Starts at " - << operand.location.offset << ", length " << operand.location.length - << ", max " << operandValues.size(); - return false; - } - break; - case OperandLifeTime::TEMPORARY_VARIABLE: - case OperandLifeTime::MODEL_INPUT: - case OperandLifeTime::MODEL_OUTPUT: - case OperandLifeTime::NO_VALUE: - if (operand.location.offset != 0 || operand.location.length != 0) { - LOG(ERROR) << "Unexpected offset " << operand.location.offset << " or length " - << operand.location.length << " for runtime location."; - return false; - } - break; - case OperandLifeTime::CONSTANT_REFERENCE: - if (operand.location.poolIndex >= poolCount) { - LOG(ERROR) << "Invalid poolIndex " << operand.location.poolIndex << "/" - << poolCount; - return false; - } - break; - // TODO: Validate that we are within the pool. - default: - LOG(ERROR) << "Invalid lifetime"; - return false; - } - } - return true; -} - -static bool validOperations(const hidl_vec<Operation>& operations, size_t operandCount) { - for (auto& op : operations) { - if (!validCode(kNumberOfOperationTypes, kNumberOfOperationTypesOEM, - static_cast<uint32_t>(op.type))) { - LOG(ERROR) << "Invalid operation type "; - return false; - } - if (!validOperandIndexes(op.inputs, operandCount) || - !validOperandIndexes(op.outputs, operandCount)) { - return false; - } - } - return true; -} - -// TODO doublecheck -bool validateModel(const Model& model) { - const size_t operandCount = model.operands.size(); - return (validOperands(model.operands, model.operandValues, model.pools.size()) && - validOperations(model.operations, operandCount) && - validOperandIndexes(model.inputIndexes, operandCount) && - validOperandIndexes(model.outputIndexes, operandCount)); -} - -bool validRequestArguments(const hidl_vec<RequestArgument>& arguments, - const hidl_vec<uint32_t>& operandIndexes, - const hidl_vec<Operand>& operands, size_t poolCount, - const char* type) { - const size_t argumentCount = arguments.size(); - if (argumentCount != operandIndexes.size()) { - LOG(ERROR) << "Request specifies " << argumentCount << " " << type << "s but the model has " - << operandIndexes.size(); - return false; - } - for (size_t argumentIndex = 0; argumentIndex < argumentCount; argumentIndex++) { - const RequestArgument& argument = arguments[argumentIndex]; - const uint32_t operandIndex = operandIndexes[argumentIndex]; - const Operand& operand = operands[operandIndex]; - if (argument.hasNoValue) { - if (argument.location.poolIndex != 0 || - argument.location.offset != 0 || - argument.location.length != 0 || - argument.dimensions.size() != 0) { - LOG(ERROR) << "Request " << type << " " << argumentIndex - << " has no value yet has details."; - return false; - } - } - if (argument.location.poolIndex >= poolCount) { - LOG(ERROR) << "Request " << type << " " << argumentIndex << " has an invalid poolIndex " - << argument.location.poolIndex << "/" << poolCount; - return false; - } - // TODO: Validate that we are within the pool. - uint32_t rank = argument.dimensions.size(); - if (rank > 0) { - if (rank != operand.dimensions.size()) { - LOG(ERROR) << "Request " << type << " " << argumentIndex - << " has number of dimensions (" << rank - << ") different than the model's (" << operand.dimensions.size() << ")"; - return false; - } - for (size_t i = 0; i < rank; i++) { - if (argument.dimensions[i] != operand.dimensions[i] && - operand.dimensions[i] != 0) { - LOG(ERROR) << "Request " << type << " " << argumentIndex - << " has dimension " << i << " of " << operand.dimensions[i] - << " different than the model's " << operand.dimensions[i]; - return false; - } - if (argument.dimensions[i] == 0) { - LOG(ERROR) << "Request " << type << " " << argumentIndex - << " has dimension " << i << " of zero"; - return false; - } - } - } - } - return true; -} - -// TODO doublecheck -bool validateRequest(const Request& request, const Model& model) { - const size_t poolCount = request.pools.size(); - return (validRequestArguments(request.inputs, model.inputIndexes, model.operands, poolCount, - "input") && - validRequestArguments(request.outputs, model.outputIndexes, model.operands, poolCount, - "output")); -} - -} // namespace rt -} // namespace nnfw |