102 lines
3.7 KiB
C++
102 lines
3.7 KiB
C++
/*
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* Copyright (C) 2017 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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// Contains the implementation of the operations.
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#define LOG_TAG "Operations"
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#include "Operations.h"
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#include "OperationsUtils.h"
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#include "internal/optimized/optimized_ops.h"
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namespace android {
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namespace nn {
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bool reshapeGeneric(const void* inputData, const Shape& inputShape,
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void* outputData, const Shape& outputShape) {
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size_t count = sizeOfData(inputShape.type, inputShape.dimensions);
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memcpy(outputData, inputData, count);
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return true;
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}
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bool resizeBilinearFloat32(const float* inputData, const Shape& inputShape,
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float* outputData, const Shape& outputShape) {
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int32_t height = (int32_t) getSizeOfDimension(outputShape, 1);
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int32_t width = (int32_t) getSizeOfDimension(outputShape, 2);
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int32_t outDimData[2] = {height, width};
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// We have to fake a tensor here, to satisfy ResizeBilinear().
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Shape outDimShape;
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outDimShape.dimensions = {1, 1, 1, 2};
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optimized_ops::ResizeBilinear(
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inputData, convertShapeToDims(inputShape),
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outDimData, convertShapeToDims(outDimShape),
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outputData, convertShapeToDims(outputShape));
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return true;
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}
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bool depthToSpaceGeneric(const uint8_t* inputData, const Shape& inputShape,
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int32_t blockSize,
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uint8_t* outputData, const Shape& outputShape) {
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if (inputShape.type == OperandType::TENSOR_FLOAT32) {
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optimized_ops::DepthToSpace(
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reinterpret_cast<const float*>(inputData),
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convertShapeToDims(inputShape),
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blockSize,
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reinterpret_cast<float*>(outputData),
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convertShapeToDims(outputShape));
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} else if (inputShape.type == OperandType::TENSOR_QUANT8_ASYMM) {
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optimized_ops::DepthToSpace(
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reinterpret_cast<const uint8_t*>(inputData),
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convertShapeToDims(inputShape),
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blockSize,
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reinterpret_cast<uint8_t*>(outputData),
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convertShapeToDims(outputShape));
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} else {
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LOG(ERROR) << "Unsupported data type";
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return false;
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}
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return true;
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}
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bool spaceToDepthGeneric(const uint8_t* inputData, const Shape& inputShape,
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int32_t blockSize,
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uint8_t* outputData, const Shape& outputShape) {
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if (inputShape.type == OperandType::TENSOR_FLOAT32) {
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optimized_ops::SpaceToDepth(
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reinterpret_cast<const float*>(inputData),
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convertShapeToDims(inputShape),
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blockSize,
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reinterpret_cast<float*>(outputData),
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convertShapeToDims(outputShape));
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} else if (inputShape.type == OperandType::TENSOR_QUANT8_ASYMM) {
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optimized_ops::SpaceToDepth(
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reinterpret_cast<const uint8_t*>(inputData),
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convertShapeToDims(inputShape),
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blockSize,
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reinterpret_cast<uint8_t*>(outputData),
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convertShapeToDims(outputShape));
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} else {
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LOG(ERROR) << "Unsupported data type";
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return false;
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}
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return true;
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}
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} // namespace nn
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} // namespace android
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