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/*
* 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 "Validation.h"
#include "Macro.h"
#include "Assert.h"
static inline bool validCode(uint32_t codeCount, uint32_t code)
{
return (code < codeCount);
}
int validateOperationType(const OperationType &type)
{
return validCode(kNumberOfOperationTypes, static_cast<uint32_t>(type));
}
// 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, 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 std::vector<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 std::vector<Operand> &operands, const std::vector<uint8_t> &operandValues)
{
for (auto &operand : operands)
{
if (!validCode(kNumberOfDataTypes, 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 0
if (operand.location.poolIndex >= poolCount)
{
LOG(ERROR) << "Invalid poolIndex " << operand.location.poolIndex << "/" << poolCount;
return false;
}
#endif
break;
// TODO: Validate that we are within the pool.
default:
LOG(ERROR) << "Invalid lifetime";
return false;
}
}
return true;
}
static bool validOperations(const std::vector<Operation> &operations, size_t operandCount)
{
for (auto &op : operations)
{
if (!validCode(kNumberOfOperationTypes, 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) &&
validOperations(model.operations, operandCount) &&
validOperandIndexes(model.inputIndexes, operandCount) &&
validOperandIndexes(model.outputIndexes, operandCount));
}
bool validRequestArguments(const std::vector<RequestArgument> &arguments,
const std::vector<uint32_t> &operandIndexes,
const std::vector<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();
const size_t poolCount = 0;
return (validRequestArguments(request.inputs, model.inputIndexes, model.operands, poolCount,
"input") &&
validRequestArguments(request.outputs, model.outputIndexes, model.operands, poolCount,
"output"));
}
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