/* * Copyright (C) 2017 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. */ #include "Operations.h" #include "CpuOperationUtils.h" #include "tensorflow/contrib/lite/kernels/internal/optimized/optimized_ops.h" namespace android { namespace nn { #define ANDROID_NN_POOLING_PARAMETERS \ uint32_t height = getSizeOfDimension(inputShape, 1); \ uint32_t width = getSizeOfDimension(inputShape, 2); \ uint32_t outHeight = getSizeOfDimension(outputShape, 1); \ uint32_t outWidth = getSizeOfDimension(outputShape, 2); \ \ uint32_t paddingHeight = (uint32_t)padding_top; \ uint32_t paddingWidth = (uint32_t)padding_left; bool averagePoolFloat32(const float* inputData, const Shape& inputShape, int32_t padding_left, int32_t padding_right, int32_t padding_top, int32_t padding_bottom, int32_t stride_width, int32_t stride_height, int32_t filter_width, int32_t filter_height, int32_t activation, float* outputData, const Shape& outputShape) { ANDROID_NN_POOLING_PARAMETERS float output_activation_min, output_activation_max; CalculateActivationRangeFloat(activation, &output_activation_min, &output_activation_max); tflite::optimized_ops::AveragePool( inputData, convertShapeToDims(inputShape), stride_width, stride_height, paddingWidth, paddingHeight, filter_width, filter_height, output_activation_min, output_activation_max, outputData, convertShapeToDims(outputShape)); return true; } bool averagePoolQuant8(const uint8_t* inputData, const Shape& inputShape, int32_t padding_left, int32_t padding_right, int32_t padding_top, int32_t padding_bottom, int32_t stride_width, int32_t stride_height, int32_t filter_width, int32_t filter_height, int32_t activation, uint8_t* outputData, const Shape& outputShape) { ANDROID_NN_POOLING_PARAMETERS int32_t output_activation_min = 0; int32_t output_activation_max = 0; CalculateActivationRangeUint8(activation, outputShape, &output_activation_min, &output_activation_max); tflite::optimized_ops::AveragePool( inputData, convertShapeToDims(inputShape), stride_width, stride_height, paddingWidth, paddingHeight, filter_width, filter_height, output_activation_min, output_activation_max, outputData, convertShapeToDims(outputShape)); return true; } bool l2PoolFloat32(const float* inputData, const Shape& inputShape, int32_t padding_left, int32_t padding_right, int32_t padding_top, int32_t padding_bottom, int32_t stride_width, int32_t stride_height, int32_t filter_width, int32_t filter_height, int32_t activation, float* outputData, const Shape& outputShape) { ANDROID_NN_POOLING_PARAMETERS float output_activation_min, output_activation_max; CalculateActivationRangeFloat(activation, &output_activation_min, &output_activation_max); tflite::optimized_ops::L2Pool( inputData, convertShapeToDims(inputShape), stride_width, stride_height, paddingWidth, paddingHeight, filter_width, filter_height, output_activation_min, output_activation_max, outputData, convertShapeToDims(outputShape)); return true; } bool maxPoolFloat32(const float* inputData, const Shape& inputShape, int32_t padding_left, int32_t padding_right, int32_t padding_top, int32_t padding_bottom, int32_t stride_width, int32_t stride_height, int32_t filter_width, int32_t filter_height, int32_t activation, float* outputData, const Shape& outputShape) { ANDROID_NN_POOLING_PARAMETERS float output_activation_min, output_activation_max; CalculateActivationRangeFloat(activation, &output_activation_min, &output_activation_max); tflite::optimized_ops::MaxPool( inputData, convertShapeToDims(inputShape), stride_width, stride_height, paddingWidth, paddingHeight, filter_width, filter_height, output_activation_min, output_activation_max, outputData, convertShapeToDims(outputShape)); return true; } bool maxPoolQuant8(const uint8_t* inputData, const Shape& inputShape, int32_t padding_left, int32_t padding_right, int32_t padding_top, int32_t padding_bottom, int32_t stride_width, int32_t stride_height, int32_t filter_width, int32_t filter_height, int32_t activation, uint8_t* outputData, const Shape& outputShape) { ANDROID_NN_POOLING_PARAMETERS int32_t output_activation_min = 0; int32_t output_activation_max = 0; CalculateActivationRangeUint8(activation, outputShape, &output_activation_min, &output_activation_max); tflite::optimized_ops::MaxPool( inputData, convertShapeToDims(inputShape), stride_width, stride_height, paddingWidth, paddingHeight, filter_width, filter_height, output_activation_min, output_activation_max, outputData, convertShapeToDims(outputShape)); return true; } #undef ANDROID_NN_POOLING_PARAMETERS } // namespace nn } // namespace android