162 lines
7.1 KiB
C++
162 lines
7.1 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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#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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#define ANDROID_NN_POOLING_PARAMETERS \
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uint32_t height = getSizeOfDimension(inputShape, 1); \
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uint32_t width = getSizeOfDimension(inputShape, 2); \
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uint32_t outHeight = getSizeOfDimension(outputShape, 1); \
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uint32_t outWidth = getSizeOfDimension(outputShape, 2); \
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\
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uint32_t paddingHeight = (uint32_t)padding_top; \
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uint32_t paddingWidth = (uint32_t)padding_left;
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bool averagePoolFloat32(const float* inputData, const Shape& inputShape,
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int32_t padding_left, int32_t padding_right,
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int32_t padding_top, int32_t padding_bottom,
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int32_t stride_width, int32_t stride_height,
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int32_t filter_width, int32_t filter_height, int32_t activation,
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float* outputData, const Shape& outputShape) {
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ANDROID_NN_POOLING_PARAMETERS
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#define ANDROID_NN_AVERAGE_POOL(activation) \
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optimized_ops::AveragePool<FusedActivationFunctionType::activation>( \
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inputData, convertShapeToDims(inputShape), \
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stride_width, stride_height, paddingWidth, paddingHeight, \
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filter_width, filter_height, \
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outputData, convertShapeToDims(outputShape))
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ANDROID_NN_MACRO_DISPATCH(ANDROID_NN_AVERAGE_POOL)
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#undef ANDROID_NN_AVERAGE_POOL
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return true;
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}
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bool averagePoolQuant8(const uint8_t* inputData, const Shape& inputShape,
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int32_t padding_left, int32_t padding_right,
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int32_t padding_top, int32_t padding_bottom,
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int32_t stride_width, int32_t stride_height,
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int32_t filter_width, int32_t filter_height, int32_t activation,
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uint8_t* outputData, const Shape& outputShape) {
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ANDROID_NN_POOLING_PARAMETERS
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int32_t output_activation_min = 0;
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int32_t output_activation_max = 0;
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CalculateActivationRangeUint8(activation, outputShape,
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&output_activation_min,
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&output_activation_max);
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#define ANDROID_NN_AVERAGE_POOL(activation) \
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optimized_ops::AveragePool<FusedActivationFunctionType::activation>( \
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inputData, convertShapeToDims(inputShape), \
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stride_width, stride_height, paddingWidth, paddingHeight, \
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filter_width, filter_height, \
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output_activation_min, output_activation_max, \
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outputData, convertShapeToDims(outputShape))
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ANDROID_NN_MACRO_DISPATCH(ANDROID_NN_AVERAGE_POOL)
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#undef ANDROID_NN_AVERAGE_POOL
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return true;
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}
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bool l2PoolFloat32(const float* inputData, const Shape& inputShape,
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int32_t padding_left, int32_t padding_right,
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int32_t padding_top, int32_t padding_bottom,
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int32_t stride_width, int32_t stride_height,
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int32_t filter_width, int32_t filter_height, int32_t activation,
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float* outputData, const Shape& outputShape) {
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ANDROID_NN_POOLING_PARAMETERS
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#define ANDROID_NN_L2_POOL(activation) \
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optimized_ops::L2Pool<FusedActivationFunctionType::activation>( \
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inputData, convertShapeToDims(inputShape), \
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stride_width, stride_height, paddingWidth, paddingHeight, \
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filter_width, filter_height, \
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outputData, convertShapeToDims(outputShape))
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ANDROID_NN_MACRO_DISPATCH(ANDROID_NN_L2_POOL)
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#undef ANDROID_NN_L2_POOL
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return true;
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}
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bool maxPoolFloat32(const float* inputData, const Shape& inputShape,
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int32_t padding_left, int32_t padding_right,
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int32_t padding_top, int32_t padding_bottom,
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int32_t stride_width, int32_t stride_height,
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int32_t filter_width, int32_t filter_height, int32_t activation,
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float* outputData, const Shape& outputShape) {
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ANDROID_NN_POOLING_PARAMETERS
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#define ANDROID_NN_MAX_POOL(activation) \
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optimized_ops::MaxPool<FusedActivationFunctionType::activation>( \
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inputData, convertShapeToDims(inputShape), \
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stride_width, stride_height, paddingWidth, paddingHeight, \
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filter_width, filter_height, \
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outputData, convertShapeToDims(outputShape))
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ANDROID_NN_MACRO_DISPATCH(ANDROID_NN_MAX_POOL)
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#undef ANDROID_NN_MAX_POOL
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return true;
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}
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bool maxPoolQuant8(const uint8_t* inputData, const Shape& inputShape,
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int32_t padding_left, int32_t padding_right,
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int32_t padding_top, int32_t padding_bottom,
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int32_t stride_width, int32_t stride_height,
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int32_t filter_width, int32_t filter_height, int32_t activation,
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uint8_t* outputData, const Shape& outputShape) {
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ANDROID_NN_POOLING_PARAMETERS
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int32_t output_activation_min = 0;
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int32_t output_activation_max = 0;
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CalculateActivationRangeUint8(activation, outputShape,
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&output_activation_min,
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&output_activation_max);
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#define ANDROID_NN_MAX_POOL(activation) \
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optimized_ops::MaxPool<FusedActivationFunctionType::activation>( \
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inputData, convertShapeToDims(inputShape), \
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stride_width, stride_height, paddingWidth, paddingHeight, \
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filter_width, filter_height, \
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output_activation_min, output_activation_max, \
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outputData, convertShapeToDims(outputShape))
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ANDROID_NN_MACRO_DISPATCH(ANDROID_NN_MAX_POOL)
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#undef ANDROID_NN_MAX_POOL
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return true;
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}
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#undef ANDROID_NN_POOLING_PARAMETERS
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} // namespace nn
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} // namespace android
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