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      1 /*
      2  * Copyright (C) 2018 The Android Open Source Project
      3  *
      4  * Licensed under the Apache License, Version 2.0 (the "License");
      5  * you may not use this file except in compliance with the License.
      6  * You may obtain a copy of the License at
      7  *
      8  *      http://www.apache.org/licenses/LICENSE-2.0
      9  *
     10  * Unless required by applicable law or agreed to in writing, software
     11  * distributed under the License is distributed on an "AS IS" BASIS,
     12  * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
     13  * See the License for the specific language governing permissions and
     14  * limitations under the License.
     15  */
     16 
     17 #define LOG_TAG "Operations"
     18 
     19 #include "MaximumMinimum.h"
     20 #include "IndexedShapeWrapper.h"
     21 #include "OperationsUtils.h"
     22 #include "Tracing.h"
     23 
     24 namespace android {
     25 namespace nn {
     26 namespace maximum_minimum {
     27 
     28 namespace {
     29 
     30 template <typename T>
     31 bool evalGeneric(const T* aData, const Shape& aShape, const T* bData, const Shape& bShape,
     32                  bool isMinimum, T* outputData, const Shape& outputShape) {
     33     IndexedShapeWrapper aShapeIndexed(aShape);
     34     IndexedShapeWrapper bShapeIndexed(bShape);
     35     IndexedShapeWrapper outputShapeIndexed(outputShape);
     36 
     37     std::vector<uint32_t> curIndex(outputShape.dimensions.size(), 0);
     38     bool lastIndex = false;
     39     do {
     40         uint32_t outputFlatIndex;
     41         NN_CHECK(outputShapeIndexed.indexToFlatIndex(curIndex, &outputFlatIndex));
     42         uint32_t aFlatIndex;
     43         NN_CHECK(aShapeIndexed.broadcastedIndexToFlatIndex(curIndex, &aFlatIndex));
     44         uint32_t bFlatIndex;
     45         NN_CHECK(bShapeIndexed.broadcastedIndexToFlatIndex(curIndex, &bFlatIndex));
     46 
     47         outputData[outputFlatIndex] = isMinimum ? std::min(aData[aFlatIndex], bData[bFlatIndex])
     48                                                 : std::max(aData[aFlatIndex], bData[bFlatIndex]);
     49 
     50         NN_CHECK(outputShapeIndexed.nextIndexInplace(&curIndex, &lastIndex));
     51     } while (!lastIndex);
     52 
     53     return true;
     54 }
     55 
     56 bool evalQuant8(const uint8_t* aData, const Shape& aShape, const uint8_t* bData,
     57                 const Shape& bShape, bool isMinimum, uint8_t* outputData,
     58                 const Shape& outputShape) {
     59     IndexedShapeWrapper aShapeIndexed(aShape);
     60     IndexedShapeWrapper bShapeIndexed(bShape);
     61     IndexedShapeWrapper outputShapeIndexed(outputShape);
     62 
     63     std::vector<uint32_t> curIndex(outputShape.dimensions.size(), 0);
     64     bool lastIndex = false;
     65     do {
     66         uint32_t outputFlatIndex;
     67         NN_CHECK(outputShapeIndexed.indexToFlatIndex(curIndex, &outputFlatIndex));
     68         uint32_t aFlatIndex;
     69         NN_CHECK(aShapeIndexed.broadcastedIndexToFlatIndex(curIndex, &aFlatIndex));
     70         uint32_t bFlatIndex;
     71         NN_CHECK(bShapeIndexed.broadcastedIndexToFlatIndex(curIndex, &bFlatIndex));
     72 
     73         uint8_t aValue = requantize(aData[aFlatIndex], aShape, outputShape);
     74         uint8_t bValue = requantize(bData[bFlatIndex], bShape, outputShape);
     75         outputData[outputFlatIndex] =
     76                 isMinimum ? std::min(aValue, bValue) : std::max(aValue, bValue);
     77 
     78         NN_CHECK(outputShapeIndexed.nextIndexInplace(&curIndex, &lastIndex));
     79     } while (!lastIndex);
     80 
     81     return true;
     82 }
     83 
     84 }  // namespace
     85 
     86 bool prepare(const Shape& in1, const Shape& in2, Shape* out) {
     87     NN_CHECK(in1.type == in2.type);
     88     return calculateBroadcastedShape(in1, in2, out);
     89 }
     90 
     91 bool eval(const void* in1, const Shape& shape1, const void* in2, const Shape& shape2,
     92           bool isMinimum, void* output, const Shape& outputShape) {
     93     NNTRACE_COMP("maximum_minimum::eval");
     94     switch (shape1.type) {
     95         case OperandType::TENSOR_FLOAT16: {
     96             return evalGeneric(reinterpret_cast<const _Float16*>(in1), shape1,
     97                                reinterpret_cast<const _Float16*>(in2), shape2, isMinimum,
     98                                reinterpret_cast<_Float16*>(output), outputShape);
     99         }
    100         case OperandType::TENSOR_FLOAT32: {
    101             return evalGeneric(reinterpret_cast<const float*>(in1), shape1,
    102                                reinterpret_cast<const float*>(in2), shape2, isMinimum,
    103                                reinterpret_cast<float*>(output), outputShape);
    104         }
    105         case OperandType::TENSOR_INT32: {
    106             return evalGeneric(reinterpret_cast<const int32_t*>(in1), shape1,
    107                                reinterpret_cast<const int32_t*>(in2), shape2, isMinimum,
    108                                reinterpret_cast<int32_t*>(output), outputShape);
    109         }
    110         case OperandType::TENSOR_QUANT8_ASYMM: {
    111             return evalQuant8(reinterpret_cast<const uint8_t*>(in1), shape1,
    112                               reinterpret_cast<const uint8_t*>(in2), shape2, isMinimum,
    113                               reinterpret_cast<uint8_t*>(output), outputShape);
    114         }
    115         default: {
    116             LOG(ERROR) << "Unsupported data type: " << toString(shape1.type);
    117             return false;
    118         }
    119     }
    120 }
    121 
    122 }  // namespace maximum_minimum
    123 }  // namespace nn
    124 }  // namespace android
    125