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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 "ModelArgumentInfo.h"
#include "NeuralNetworks.h" // For ANEURALNETWORKS_XXX
#include "Logging.h"
#include "Assert.h"
// TODO-NNRT: Consider removing ModelArgumentInfo completely if it's not necessary
int ModelArgumentInfo::setFromPointer(const Operand &operand,
const ANeuralNetworksOperandType *type, void *data,
uint32_t length)
{
if ((data == nullptr) != (length == 0))
{
LOG(ERROR) << "Data pointer must be nullptr if and only if length is zero (data = " << data
<< ", length = " << length << ")";
return ANEURALNETWORKS_BAD_DATA;
}
if (data == nullptr)
{
state = ModelArgumentInfo::HAS_NO_VALUE;
}
else
{
int n = updateDimensionInfo(operand, type);
if (n != ANEURALNETWORKS_NO_ERROR)
{
return n;
}
uint32_t neededLength = sizeOfData(operand.type, dimensions);
if (neededLength != length)
{
LOG(ERROR) << "Setting argument with invalid length: " << length
<< ", expected length: " << neededLength;
return ANEURALNETWORKS_BAD_DATA;
}
state = ModelArgumentInfo::POINTER;
}
buffer = data;
locationAndLength = {.poolIndex = 0, .offset = 0, .length = length};
return ANEURALNETWORKS_NO_ERROR;
}
int ModelArgumentInfo::setFromMemory(const Operand &operand, const ANeuralNetworksOperandType *type,
uint32_t poolIndex, uint32_t offset, uint32_t length)
{
int n = updateDimensionInfo(operand, type);
if (n != ANEURALNETWORKS_NO_ERROR)
{
return n;
}
uint32_t neededLength = sizeOfData(operand.type, dimensions);
if (neededLength != length)
{
LOG(ERROR) << "Setting argument with invalid length: " << length
<< ", expected length: " << neededLength;
return ANEURALNETWORKS_BAD_DATA;
}
state = ModelArgumentInfo::MEMORY;
locationAndLength = {.poolIndex = poolIndex, .offset = offset, .length = length};
buffer = nullptr;
return ANEURALNETWORKS_NO_ERROR;
}
int ModelArgumentInfo::updateDimensionInfo(const Operand &operand,
const ANeuralNetworksOperandType *newType)
{
ASSERT(dimensions.empty());
if (newType == nullptr)
{
for (auto i : operand.dimensions)
{
if (i == 0)
{
LOG(ERROR) << "Setting input/output with unspecified dimensions";
return ANEURALNETWORKS_BAD_DATA;
}
}
dimensions = operand.dimensions;
}
else
{
uint32_t count = newType->dimensionCount;
if (static_cast<OperandType>(newType->type) != operand.type ||
count != operand.dimensions.size())
{
LOG(ERROR) << "Setting input/output with incompatible types";
return ANEURALNETWORKS_BAD_DATA;
}
dimensions = std::vector<uint32_t>(count);
for (uint32_t i = 0; i < count; i++)
{
if (operand.dimensions[i] != 0 && operand.dimensions[i] != newType->dimensions[i])
{
LOG(ERROR) << "Overriding a fully specified dimension is disallowed";
return ANEURALNETWORKS_BAD_DATA;
}
else
{
dimensions[i] = newType->dimensions[i];
}
}
}
return ANEURALNETWORKS_NO_ERROR;
}
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