| /* |
| * 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. |
| */ |
| |
| #define LOG_TAG "Operations" |
| |
| #include "Comparisons.h" |
| |
| #include <functional> |
| #include <vector> |
| |
| #include "IndexedShapeWrapper.h" |
| #include "OperationResolver.h" |
| #include "OperationsExecutionUtils.h" |
| |
| namespace android { |
| namespace nn { |
| namespace comparisons { |
| namespace { |
| |
| template <typename DataType, typename ComparisonType> |
| bool compute(const std::function<bool(ComparisonType, ComparisonType)>& func, const DataType* aData, |
| const Shape& aShape, const DataType* bData, const Shape& bShape, bool8* outputData, |
| const Shape& outputShape) { |
| IndexedShapeWrapper aShapeIndexed(aShape); |
| IndexedShapeWrapper bShapeIndexed(bShape); |
| IndexedShapeWrapper outputShapeIndexed(outputShape); |
| std::vector<uint32_t> curIndex(outputShape.dimensions.size(), 0); |
| bool lastIndex = false; |
| do { |
| uint32_t outputFlatIndex; |
| NN_RET_CHECK(outputShapeIndexed.indexToFlatIndex(curIndex, &outputFlatIndex)); |
| uint32_t aFlatIndex; |
| NN_RET_CHECK(aShapeIndexed.broadcastedIndexToFlatIndex(curIndex, &aFlatIndex)); |
| uint32_t bFlatIndex; |
| NN_RET_CHECK(bShapeIndexed.broadcastedIndexToFlatIndex(curIndex, &bFlatIndex)); |
| |
| if (aShape.type == OperandType::TENSOR_QUANT8_ASYMM || |
| aShape.type == OperandType::TENSOR_QUANT8_ASYMM_SIGNED) { |
| const float realA = (aData[aFlatIndex] - aShape.offset) * aShape.scale; |
| const float realB = (bData[bFlatIndex] - bShape.offset) * bShape.scale; |
| outputData[outputFlatIndex] = func(realA, realB); |
| } else { |
| outputData[outputFlatIndex] = func(aData[aFlatIndex], bData[bFlatIndex]); |
| } |
| |
| NN_RET_CHECK(outputShapeIndexed.nextIndexInplace(&curIndex, &lastIndex)); |
| } while (!lastIndex); |
| return true; |
| } |
| |
| template <typename DataType, typename ComparisonType> |
| bool executeLessTyped(IOperationExecutionContext* context) { |
| return compute<DataType, ComparisonType>( |
| std::less<ComparisonType>(), context->getInputBuffer<DataType>(kInputTensor1), |
| context->getInputShape(kInputTensor1), context->getInputBuffer<DataType>(kInputTensor2), |
| context->getInputShape(kInputTensor2), context->getOutputBuffer<bool8>(kOutputTensor), |
| context->getOutputShape(kOutputTensor)); |
| } |
| |
| template <typename DataType, typename ComparisonType> |
| bool executeLessEqualTyped(IOperationExecutionContext* context) { |
| return compute<DataType, ComparisonType>( |
| std::less_equal<ComparisonType>(), context->getInputBuffer<DataType>(kInputTensor1), |
| context->getInputShape(kInputTensor1), context->getInputBuffer<DataType>(kInputTensor2), |
| context->getInputShape(kInputTensor2), context->getOutputBuffer<bool8>(kOutputTensor), |
| context->getOutputShape(kOutputTensor)); |
| } |
| |
| template <typename DataType, typename ComparisonType> |
| bool executeEqualTyped(IOperationExecutionContext* context) { |
| return compute<DataType, ComparisonType>( |
| std::equal_to<ComparisonType>(), context->getInputBuffer<DataType>(kInputTensor1), |
| context->getInputShape(kInputTensor1), context->getInputBuffer<DataType>(kInputTensor2), |
| context->getInputShape(kInputTensor2), context->getOutputBuffer<bool8>(kOutputTensor), |
| context->getOutputShape(kOutputTensor)); |
| } |
| |
| template <typename DataType, typename ComparisonType> |
| bool executeNotEqualTyped(IOperationExecutionContext* context) { |
| return compute<DataType, ComparisonType>( |
| std::not_equal_to<ComparisonType>(), context->getInputBuffer<DataType>(kInputTensor1), |
| context->getInputShape(kInputTensor1), context->getInputBuffer<DataType>(kInputTensor2), |
| context->getInputShape(kInputTensor2), context->getOutputBuffer<bool8>(kOutputTensor), |
| context->getOutputShape(kOutputTensor)); |
| } |
| |
| template <typename DataType, typename ComparisonType> |
| bool executeGreaterEqualTyped(IOperationExecutionContext* context) { |
| return compute<DataType, ComparisonType>( |
| std::greater_equal<ComparisonType>(), context->getInputBuffer<DataType>(kInputTensor1), |
| context->getInputShape(kInputTensor1), context->getInputBuffer<DataType>(kInputTensor2), |
| context->getInputShape(kInputTensor2), context->getOutputBuffer<bool8>(kOutputTensor), |
| context->getOutputShape(kOutputTensor)); |
| } |
| |
| template <typename DataType, typename ComparisonType> |
| bool executeGreaterTyped(IOperationExecutionContext* context) { |
| return compute<DataType, ComparisonType>( |
| std::greater<ComparisonType>(), context->getInputBuffer<DataType>(kInputTensor1), |
| context->getInputShape(kInputTensor1), context->getInputBuffer<DataType>(kInputTensor2), |
| context->getInputShape(kInputTensor2), context->getOutputBuffer<bool8>(kOutputTensor), |
| context->getOutputShape(kOutputTensor)); |
| } |
| |
| } // namespace |
| |
| bool prepare(IOperationExecutionContext* context) { |
| Shape input1 = context->getInputShape(kInputTensor1); |
| Shape input2 = context->getInputShape(kInputTensor2); |
| Shape output = context->getOutputShape(kOutputTensor); |
| NN_RET_CHECK(calculateBroadcastedShape(input1, input2, &output)); |
| return context->setOutputShape(kOutputTensor, output); |
| } |
| |
| bool executeLess(IOperationExecutionContext* context) { |
| switch (context->getInputType(kInputTensor1)) { |
| case OperandType::TENSOR_FLOAT16: |
| return executeLessTyped<_Float16, _Float16>(context); |
| case OperandType::TENSOR_FLOAT32: |
| return executeLessTyped<float, float>(context); |
| case OperandType::TENSOR_INT32: |
| return executeLessTyped<int32_t, int32_t>(context); |
| case OperandType::TENSOR_QUANT8_ASYMM: |
| return executeLessTyped<uint8_t, float>(context); |
| case OperandType::TENSOR_QUANT8_ASYMM_SIGNED: |
| return executeLessTyped<int8_t, float>(context); |
| case OperandType::TENSOR_BOOL8: |
| return executeLessTyped<bool8, bool8>(context); |
| default: |
| NN_RET_CHECK_FAIL() << "Unsupported tensor type for comparison"; |
| } |
| } |
| |
| bool executeLessEqual(IOperationExecutionContext* context) { |
| switch (context->getInputType(kInputTensor1)) { |
| case OperandType::TENSOR_FLOAT16: |
| return executeLessEqualTyped<_Float16, _Float16>(context); |
| case OperandType::TENSOR_FLOAT32: |
| return executeLessEqualTyped<float, float>(context); |
| case OperandType::TENSOR_INT32: |
| return executeLessEqualTyped<int32_t, int32_t>(context); |
| case OperandType::TENSOR_QUANT8_ASYMM: |
| return executeLessEqualTyped<uint8_t, float>(context); |
| case OperandType::TENSOR_QUANT8_ASYMM_SIGNED: |
| return executeLessEqualTyped<int8_t, float>(context); |
| case OperandType::TENSOR_BOOL8: |
| return executeLessEqualTyped<bool8, bool8>(context); |
| default: |
| NN_RET_CHECK_FAIL() << "Unsupported tensor type for comparison"; |
| } |
| } |
| |
| bool executeEqual(IOperationExecutionContext* context) { |
| switch (context->getInputType(kInputTensor1)) { |
| case OperandType::TENSOR_FLOAT16: |
| return executeEqualTyped<_Float16, _Float16>(context); |
| case OperandType::TENSOR_FLOAT32: |
| return executeEqualTyped<float, float>(context); |
| case OperandType::TENSOR_INT32: |
| return executeEqualTyped<int32_t, int32_t>(context); |
| case OperandType::TENSOR_QUANT8_ASYMM: |
| return executeEqualTyped<uint8_t, float>(context); |
| case OperandType::TENSOR_QUANT8_ASYMM_SIGNED: |
| return executeEqualTyped<int8_t, float>(context); |
| case OperandType::TENSOR_BOOL8: |
| return executeEqualTyped<bool8, bool8>(context); |
| default: |
| NN_RET_CHECK_FAIL() << "Unsupported tensor type for comparison"; |
| } |
| } |
| |
| bool executeNotEqual(IOperationExecutionContext* context) { |
| switch (context->getInputType(kInputTensor1)) { |
| case OperandType::TENSOR_FLOAT16: |
| return executeNotEqualTyped<_Float16, _Float16>(context); |
| case OperandType::TENSOR_FLOAT32: |
| return executeNotEqualTyped<float, float>(context); |
| case OperandType::TENSOR_INT32: |
| return executeNotEqualTyped<int32_t, int32_t>(context); |
| case OperandType::TENSOR_QUANT8_ASYMM: |
| return executeNotEqualTyped<uint8_t, float>(context); |
| case OperandType::TENSOR_QUANT8_ASYMM_SIGNED: |
| return executeNotEqualTyped<int8_t, float>(context); |
| case OperandType::TENSOR_BOOL8: |
| return executeNotEqualTyped<bool8, bool8>(context); |
| default: |
| NN_RET_CHECK_FAIL() << "Unsupported tensor type for comparison"; |
| } |
| } |
| |
| bool executeGreaterEqual(IOperationExecutionContext* context) { |
| switch (context->getInputType(kInputTensor1)) { |
| case OperandType::TENSOR_FLOAT16: |
| return executeGreaterEqualTyped<_Float16, _Float16>(context); |
| case OperandType::TENSOR_FLOAT32: |
| return executeGreaterEqualTyped<float, float>(context); |
| case OperandType::TENSOR_INT32: |
| return executeGreaterEqualTyped<int32_t, int32_t>(context); |
| case OperandType::TENSOR_QUANT8_ASYMM: |
| return executeGreaterEqualTyped<uint8_t, float>(context); |
| case OperandType::TENSOR_QUANT8_ASYMM_SIGNED: |
| return executeGreaterEqualTyped<int8_t, float>(context); |
| case OperandType::TENSOR_BOOL8: |
| return executeGreaterEqualTyped<bool8, bool8>(context); |
| default: |
| NN_RET_CHECK_FAIL() << "Unsupported tensor type for comparison"; |
| } |
| } |
| |
| bool executeGreater(IOperationExecutionContext* context) { |
| switch (context->getInputType(kInputTensor1)) { |
| case OperandType::TENSOR_FLOAT16: |
| return executeGreaterTyped<_Float16, _Float16>(context); |
| case OperandType::TENSOR_FLOAT32: |
| return executeGreaterTyped<float, float>(context); |
| case OperandType::TENSOR_INT32: |
| return executeGreaterTyped<int32_t, int32_t>(context); |
| case OperandType::TENSOR_QUANT8_ASYMM: |
| return executeGreaterTyped<uint8_t, float>(context); |
| case OperandType::TENSOR_QUANT8_ASYMM_SIGNED: |
| return executeGreaterTyped<int8_t, float>(context); |
| case OperandType::TENSOR_BOOL8: |
| return executeGreaterTyped<bool8, bool8>(context); |
| default: |
| NN_RET_CHECK_FAIL() << "Unsupported tensor type for comparison"; |
| } |
| } |
| |
| } // namespace comparisons |
| |
| NN_REGISTER_OPERATION_DEFAULT_VALIDATION(LESS, comparisons::prepare, comparisons::executeLess); |
| NN_REGISTER_OPERATION_DEFAULT_VALIDATION(LESS_EQUAL, comparisons::prepare, |
| comparisons::executeLessEqual); |
| NN_REGISTER_OPERATION_DEFAULT_VALIDATION(EQUAL, comparisons::prepare, comparisons::executeEqual); |
| NN_REGISTER_OPERATION_DEFAULT_VALIDATION(NOT_EQUAL, comparisons::prepare, |
| comparisons::executeNotEqual); |
| NN_REGISTER_OPERATION_DEFAULT_VALIDATION(GREATER_EQUAL, comparisons::prepare, |
| comparisons::executeGreaterEqual); |
| NN_REGISTER_OPERATION_DEFAULT_VALIDATION(GREATER, comparisons::prepare, |
| comparisons::executeGreater); |
| |
| } // namespace nn |
| } // namespace android |
