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      1 /*
      2  * Copyright (C) 2017 The Android Open Source Project
      3  *
      4  * Licensed under the Apache License, Version 2.0 (the "License");
      5  * you may not use this file except in compliance with the License.
      6  * You may obtain a copy of the License at
      7  *
      8  *      http://www.apache.org/licenses/LICENSE-2.0
      9  *
     10  * Unless required by applicable law or agreed to in writing, software
     11  * distributed under the License is distributed on an "AS IS" BASIS,
     12  * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
     13  * See the License for the specific language governing permissions and
     14  * limitations under the License.
     15  */
     16 
     17 #include "Operations.h"
     18 #include "CpuOperationUtils.h"
     19 
     20 #include "tensorflow/contrib/lite/kernels/internal/optimized/depthwiseconv_float.h"
     21 #include "tensorflow/contrib/lite/kernels/internal/optimized/depthwiseconv_uint8.h"
     22 
     23 namespace android {
     24 namespace nn {
     25 
     26 #define ANDROID_NN_DEPTHWISE_CONV_PARAMETERS                                    \
     27     uint32_t height       = getSizeOfDimension(inputShape, 1);                  \
     28     uint32_t width        = getSizeOfDimension(inputShape, 2);                  \
     29     uint32_t filterHeight = getSizeOfDimension(filterShape, 1);                 \
     30     uint32_t filterWidth  = getSizeOfDimension(filterShape, 2);                 \
     31     uint32_t outHeight    = getSizeOfDimension(outputShape, 1);                 \
     32     uint32_t outWidth     = getSizeOfDimension(outputShape, 2);                 \
     33                                                                                 \
     34     uint32_t paddingHeight = (uint32_t)padding_top;                             \
     35     uint32_t paddingWidth = (uint32_t)padding_left;
     36 
     37 bool depthwiseConvFloat32(const float* inputData, const Shape& inputShape,
     38                           const float* filterData, const Shape& filterShape,
     39                           const float* biasData, const Shape& biasShape,
     40                           int32_t padding_left, int32_t padding_right,
     41                           int32_t padding_top, int32_t padding_bottom,
     42                           int32_t stride_width, int32_t stride_height,
     43                           int32_t depth_multiplier, int32_t activation,
     44                           float* outputData, const Shape& outputShape) {
     45 
     46     ANDROID_NN_DEPTHWISE_CONV_PARAMETERS
     47 
     48     float output_activation_min, output_activation_max;
     49     CalculateActivationRangeFloat(activation, &output_activation_min,
     50                                   &output_activation_max);
     51 
     52     tflite::optimized_ops::DepthwiseConv(
     53             inputData, convertShapeToDims(inputShape),
     54             filterData, convertShapeToDims(filterShape),
     55             biasData, convertShapeToDims(biasShape),
     56             stride_width, stride_height,
     57             paddingWidth, paddingHeight, depth_multiplier,
     58             output_activation_min, output_activation_max,
     59             outputData, convertShapeToDims(outputShape));
     60 
     61     return true;
     62 }
     63 
     64 
     65 bool depthwiseConvQuant8(const uint8_t* inputData, const Shape& inputShape,
     66                          const uint8_t* filterData, const Shape& filterShape,
     67                          const int32_t* biasData, const Shape& biasShape,
     68                          int32_t padding_left, int32_t padding_right,
     69                          int32_t padding_top, int32_t padding_bottom,
     70                          int32_t stride_width, int32_t stride_height,
     71                          int32_t depth_multiplier, int32_t activation,
     72                          uint8_t* outputData, const Shape& outputShape) {
     73 
     74     ANDROID_NN_DEPTHWISE_CONV_PARAMETERS
     75 
     76     float real_multiplier = 0.0;
     77     int32_t output_multiplier = 0;
     78     int32_t output_shift = 0;
     79     int32_t output_activation_min = 0;
     80     int32_t output_activation_max = 0;
     81 
     82 
     83     if (!GetQuantizedConvolutionMultipler(inputShape, filterShape, biasShape,
     84                                           outputShape, &real_multiplier) ||
     85             !QuantizeMultiplierSmallerThanOne(real_multiplier, &output_multiplier,
     86                                               &output_shift)) {
     87         return false;
     88     }
     89     CalculateActivationRangeUint8(activation, outputShape,
     90                                   &output_activation_min,
     91                                   &output_activation_max);
     92 
     93     uint32_t inputOffset = -inputShape.offset;
     94     uint32_t filterOffset = -filterShape.offset;
     95     uint32_t outputOffset = outputShape.offset;
     96 
     97     tflite::optimized_ops::DepthwiseConv(
     98             inputData, convertShapeToDims(inputShape), inputOffset,
     99             filterData, convertShapeToDims(filterShape), filterOffset,
    100             biasData, convertShapeToDims(biasShape),
    101             stride_width, stride_height,
    102             paddingWidth, paddingHeight, depth_multiplier,
    103             outputOffset, output_multiplier, output_shift,
    104             output_activation_min, output_activation_max,
    105             outputData, convertShapeToDims(outputShape));
    106 
    107     return true;
    108 }
    109 
    110 #undef ANDROID_NN_DEPTHWISE_CONV_PARAMETERS
    111 }  // namespace nn
    112 }  // namespace android
    113