/*
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* Copyright (C) 2018 The Android Open Source Project
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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#include "TopK_V2.h"
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#include "OperationsUtils.h"
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#include <algorithm>
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namespace android {
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namespace nn {
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namespace topk_v2 {
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namespace {
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template <typename T>
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bool evalGeneric(const T* inputData, const Shape& inputShape, const int32_t k, T* valuesData,
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const Shape& /*valuesShape*/, int32_t* indicesData,
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const Shape& /*indicesShape*/) {
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const int rowSize = inputShape.dimensions.back();
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const int totalSize = getNumberOfElements(inputShape);
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std::vector<std::pair<T, int32_t>> values(rowSize);
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T* curOutputValue = valuesData;
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int32_t* curOutputIndex = indicesData;
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for (int rowBegin = 0; rowBegin < totalSize; rowBegin += rowSize) {
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for (int i = 0; i < rowSize; ++i) {
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values[i] = std::make_pair(inputData[rowBegin + i], i);
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}
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std::nth_element(values.begin(), values.begin() + (rowSize - k), values.end());
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std::sort(values.begin() + (rowSize - k), values.end());
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std::reverse(values.begin(), values.end());
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for (int i = 0; i < k; ++i) {
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*curOutputValue = values[i].first;
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*curOutputIndex = values[i].second;
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curOutputValue++;
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curOutputIndex++;
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}
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}
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return true;
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}
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} // namespace
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bool prepare(const Shape& input, int32_t k, Shape* values, Shape* indices) {
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NN_CHECK(k > 0);
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NN_CHECK(k <= input.dimensions.back());
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values->dimensions = input.dimensions;
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values->dimensions.back() = k;
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indices->dimensions = input.dimensions;
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indices->dimensions.back() = k;
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return true;
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}
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bool eval(const void* inputData, const Shape& inputShape, const int32_t k, void* valuesData,
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const Shape& valuesShape, void* indicesData, const Shape& indicesShape) {
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switch (inputShape.type) {
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case OperandType::TENSOR_FLOAT16: {
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return evalGeneric(reinterpret_cast<const _Float16*>(inputData), inputShape, k,
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reinterpret_cast<_Float16*>(valuesData), valuesShape,
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reinterpret_cast<int32_t*>(indicesData), indicesShape);
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} break;
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case OperandType::TENSOR_FLOAT32: {
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return evalGeneric(reinterpret_cast<const float*>(inputData), inputShape, k,
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reinterpret_cast<float*>(valuesData), valuesShape,
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reinterpret_cast<int32_t*>(indicesData), indicesShape);
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} break;
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case OperandType::TENSOR_INT32: {
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return evalGeneric(reinterpret_cast<const int32_t*>(inputData), inputShape, k,
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reinterpret_cast<int32_t*>(valuesData), valuesShape,
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reinterpret_cast<int32_t*>(indicesData), indicesShape);
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} break;
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case OperandType::TENSOR_QUANT8_ASYMM: {
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return evalGeneric(reinterpret_cast<const uint8_t*>(inputData), inputShape, k,
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reinterpret_cast<uint8_t*>(valuesData), valuesShape,
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reinterpret_cast<int32_t*>(indicesData), indicesShape);
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} break;
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default: {
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LOG(ERROR) << "Unsupported data type: " << toString(inputShape.type);
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return false;
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}
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}
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}
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} // namespace topk_v2
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} // namespace nn
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} // namespace android
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