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/*
* Copyright (C) 2018 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 "CpuOperationUtils.h"
#include "Operations.h"
#include "Tracing.h"
namespace android {
namespace nn {
template <typename T>
inline bool channelShuffleImpl(const T* inputData, const Shape& inputShape, int32_t numGroups,
int32_t axis, T* outputData, const Shape& outputShape) {
const uint32_t outerSize = getNumberOfElements(inputShape, 0, axis);
const uint32_t axisSize = getSizeOfDimension(inputShape, axis);
const uint32_t innerSize =
getNumberOfElements(inputShape, axis + 1, getNumberOfDimensions(inputShape));
const uint32_t groupSize = axisSize / numGroups;
for (uint32_t outer = 0; outer < outerSize; ++outer) {
for (uint32_t inner = 0; inner < innerSize; ++inner) {
const T* inputBase = inputData + outer * axisSize * innerSize + inner;
T* outputBase = outputData + outer * axisSize * innerSize + inner;
for (uint32_t i = 0; i < groupSize; i++) {
for (uint32_t j = 0; j < numGroups; j++, outputBase += innerSize) {
*outputBase = inputBase[innerSize * (i + j * groupSize)];
}
}
}
}
return true;
}
bool channelShuffleGeneric(const uint8_t* inputData, const Shape& inputShape, int32_t numGroups,
int32_t axis, uint8_t* outputData, const Shape& outputShape) {
NNTRACE_TRANS("channelShuffleGeneric");
NN_CHECK(handleNegativeAxis(inputShape, &axis));
if (inputShape.type == OperandType::TENSOR_FLOAT32) {
return channelShuffleImpl<float>(reinterpret_cast<const float*>(inputData), inputShape,
numGroups, axis, reinterpret_cast<float*>(outputData),
outputShape);
} else if (inputShape.type == OperandType::TENSOR_QUANT8_ASYMM) {
return channelShuffleImpl<uint8_t>(reinterpret_cast<const uint8_t*>(inputData), inputShape,
numGroups, axis, reinterpret_cast<uint8_t*>(outputData),
outputShape);
} else {
LOG(ERROR) << "Unsupported data type";
return false;
}
}
} // namespace nn
} // namespace android
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