| /* |
| * 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 "OperationsUtils.h" |
| |
| #include "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 |
| |
| #define ANDROID_NN_AVERAGE_POOL(activation) \ |
| optimized_ops::AveragePool<FusedActivationFunctionType::activation>( \ |
| inputData, convertShapeToDims(inputShape), \ |
| stride_width, paddingWidth, paddingHeight, \ |
| filter_width, filter_height, \ |
| outputData, convertShapeToDims(outputShape)) |
| |
| ANDROID_NN_MACRO_DISPATCH(ANDROID_NN_AVERAGE_POOL) |
| #undef ANDROID_NN_AVERAGE_POOL |
| |
| 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); |
| |
| #define ANDROID_NN_AVERAGE_POOL(activation) \ |
| optimized_ops::AveragePool<FusedActivationFunctionType::activation>( \ |
| inputData, convertShapeToDims(inputShape), \ |
| stride_width, paddingWidth, paddingHeight, \ |
| filter_width, filter_height, \ |
| output_activation_min, output_activation_max, \ |
| outputData, convertShapeToDims(outputShape)) |
| |
| ANDROID_NN_MACRO_DISPATCH(ANDROID_NN_AVERAGE_POOL) |
| #undef ANDROID_NN_AVERAGE_POOL |
| |
| 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 |
| |
| #define ANDROID_NN_L2_POOL(activation) \ |
| optimized_ops::L2Pool<FusedActivationFunctionType::activation>( \ |
| inputData, convertShapeToDims(inputShape), \ |
| stride_width, paddingWidth, paddingHeight, \ |
| filter_width, filter_height, \ |
| outputData, convertShapeToDims(outputShape)) |
| |
| ANDROID_NN_MACRO_DISPATCH(ANDROID_NN_L2_POOL) |
| #undef ANDROID_NN_L2_POOL |
| |
| 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 |
| |
| #define ANDROID_NN_MAX_POOL(activation) \ |
| optimized_ops::MaxPool<FusedActivationFunctionType::activation>( \ |
| inputData, convertShapeToDims(inputShape), \ |
| stride_width, paddingWidth, paddingHeight, \ |
| filter_width, filter_height, \ |
| outputData, convertShapeToDims(outputShape)) |
| |
| ANDROID_NN_MACRO_DISPATCH(ANDROID_NN_MAX_POOL) |
| #undef ANDROID_NN_MAX_POOL |
| |
| 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); |
| |
| #define ANDROID_NN_MAX_POOL(activation) \ |
| optimized_ops::MaxPool<FusedActivationFunctionType::activation>( \ |
| inputData, convertShapeToDims(inputShape), \ |
| stride_width, paddingWidth, paddingHeight, \ |
| filter_width, filter_height, \ |
| output_activation_min, output_activation_max, \ |
| outputData, convertShapeToDims(outputShape)) |
| |
| ANDROID_NN_MACRO_DISPATCH(ANDROID_NN_MAX_POOL) |
| #undef ANDROID_NN_MAX_POOL |
| |
| return true; |
| } |
| |
| #undef ANDROID_NN_POOLING_PARAMETERS |
| } // namespace nn |
| } // namespace android |
