/*
* 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 "TopK_V2.h"
#include "OperationsUtils.h"
#include <algorithm>
namespace android {
namespace nn {
namespace topk_v2 {
namespace {
template <typename T>
bool evalGeneric(const T* inputData, const Shape& inputShape, const int32_t k, T* valuesData,
const Shape& /*valuesShape*/, int32_t* indicesData,
const Shape& /*indicesShape*/) {
const int rowSize = inputShape.dimensions.back();
const int totalSize = getNumberOfElements(inputShape);
std::vector<std::pair<T, int32_t>> values(rowSize);
T* curOutputValue = valuesData;
int32_t* curOutputIndex = indicesData;
for (int rowBegin = 0; rowBegin < totalSize; rowBegin += rowSize) {
for (int i = 0; i < rowSize; ++i) {
values[i] = std::make_pair(inputData[rowBegin + i], i);
}
std::nth_element(values.begin(), values.begin() + (rowSize - k), values.end());
std::sort(values.begin() + (rowSize - k), values.end());
std::reverse(values.begin(), values.end());
for (int i = 0; i < k; ++i) {
*curOutputValue = values[i].first;
*curOutputIndex = values[i].second;
curOutputValue++;
curOutputIndex++;
}
}
return true;
}
} // namespace
bool prepare(const Shape& input, int32_t k, Shape* values, Shape* indices) {
NN_CHECK(k > 0);
NN_CHECK(k <= input.dimensions.back());
values->dimensions = input.dimensions;
values->dimensions.back() = k;
indices->dimensions = input.dimensions;
indices->dimensions.back() = k;
return true;
}
bool eval(const void* inputData, const Shape& inputShape, const int32_t k, void* valuesData,
const Shape& valuesShape, void* indicesData, const Shape& indicesShape) {
switch (inputShape.type) {
case OperandType::TENSOR_FLOAT16: {
return evalGeneric(reinterpret_cast<const _Float16*>(inputData), inputShape, k,
reinterpret_cast<_Float16*>(valuesData), valuesShape,
reinterpret_cast<int32_t*>(indicesData), indicesShape);
} break;
case OperandType::TENSOR_FLOAT32: {
return evalGeneric(reinterpret_cast<const float*>(inputData), inputShape, k,
reinterpret_cast<float*>(valuesData), valuesShape,
reinterpret_cast<int32_t*>(indicesData), indicesShape);
} break;
case OperandType::TENSOR_INT32: {
return evalGeneric(reinterpret_cast<const int32_t*>(inputData), inputShape, k,
reinterpret_cast<int32_t*>(valuesData), valuesShape,
reinterpret_cast<int32_t*>(indicesData), indicesShape);
} break;
case OperandType::TENSOR_QUANT8_ASYMM: {
return evalGeneric(reinterpret_cast<const uint8_t*>(inputData), inputShape, k,
reinterpret_cast<uint8_t*>(valuesData), valuesShape,
reinterpret_cast<int32_t*>(indicesData), indicesShape);
} break;
default: {
LOG(ERROR) << "Unsupported data type: " << toString(inputShape.type);
return false;
}
}
}
} // namespace topk_v2
} // namespace nn
} // namespace android