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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.
*/
// Contains the implementation of the operations.
#define LOG_TAG "Operations"
#include "CpuOperationUtils.h"
#include "Operations.h"
#include "Tracing.h"
namespace android {
namespace nn {
template <typename In, typename Out>
static void argMinMaxImpl(const In* inputData, const Shape& inputShape, int32_t axis, bool isArgMin,
Out* outputData, const Shape& outputShape) {
const int outerSize = getNumberOfElements(inputShape, 0, axis);
const int axisSize = getSizeOfDimension(inputShape, axis);
const int innerSize =
getNumberOfElements(inputShape, axis + 1, getNumberOfDimensions(inputShape));
for (int outer = 0; outer < outerSize; ++outer) {
for (int inner = 0; inner < innerSize; ++inner) {
auto minMaxValue = inputData[outer * axisSize * innerSize + inner];
int minMaxIndex = 0;
for (int i = 1; i < axisSize; ++i) {
const auto& value = inputData[(outer * axisSize + i) * innerSize + inner];
if ((isArgMin && value < minMaxValue) || (!isArgMin && value > minMaxValue)) {
minMaxValue = value;
minMaxIndex = i;
}
}
outputData[outer * innerSize + inner] = minMaxIndex;
}
}
}
bool argMinMaxGeneric(const uint8_t* inputData, const Shape& inputShape, int32 axis, bool isArgMin,
uint8_t* outputData, const Shape& outputShape) {
NNTRACE_TRANS("argMinMaxGeneric");
NN_CHECK(handleNegativeAxis(inputShape, &axis));
#define NNAPI_IMPL_ARG_MIN_MAX(operandType, dataType) \
if (inputShape.type == operandType) { \
NNTRACE_COMP_SWITCH("argMinMaxImpl::" #dataType); \
argMinMaxImpl(reinterpret_cast<const dataType*>(inputData), inputShape, axis, isArgMin, \
reinterpret_cast<int32_t*>(outputData), outputShape); \
return true; \
}
NNAPI_IMPL_ARG_MIN_MAX(OperandType::TENSOR_FLOAT16, _Float16);
NNAPI_IMPL_ARG_MIN_MAX(OperandType::TENSOR_FLOAT32, float);
NNAPI_IMPL_ARG_MIN_MAX(OperandType::TENSOR_INT32, int32_t);
NNAPI_IMPL_ARG_MIN_MAX(OperandType::TENSOR_QUANT8_ASYMM, uint8_t);
NNAPI_IMPL_ARG_MIN_MAX(OperandType::TENSOR_QUANT8_ASYMM_SIGNED, int8_t);
#undef NNAPI_IMPL_ARG_MIN_MAX
LOG(ERROR) << "Unsupported data type";
return false;
}
} // namespace nn
} // namespace android