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 #ifndef ANDROID_ML_NN_COMMON_OPERATIONS_INTERNAL_REFERENCE_DEPTHWISECONV_FLOAT_H_ 18 #define ANDROID_ML_NN_COMMON_OPERATIONS_INTERNAL_REFERENCE_DEPTHWISECONV_FLOAT_H_ 19 20 #include "../common.h" 21 #include "../types.h" 22 23 namespace android { 24 namespace nn { 25 namespace reference_ops { 26 27 template <FusedActivationFunctionType Ac> 28 void DepthwiseConv(const float* input_data, const Dims<4>& input_dims, 29 const float* filter_data, const Dims<4>& filter_dims, 30 const float* bias_data, const Dims<4>& bias_dims, 31 int stride_width, int stride_height, 32 int pad_width, int pad_height, int depth_multiplier, 33 float* output_data, const Dims<4>& output_dims) { 34 const int batches = MatchingArraySize(input_dims, 3, output_dims, 3); 35 const int output_depth = MatchingArraySize(filter_dims, 0, output_dims, 0); 36 const int input_height = ArraySize(input_dims, 2); 37 const int input_width = ArraySize(input_dims, 1); 38 const int input_depth = ArraySize(input_dims, 0); 39 const int filter_height = ArraySize(filter_dims, 2); 40 const int filter_width = ArraySize(filter_dims, 1); 41 const int output_height = ArraySize(output_dims, 2); 42 const int output_width = ArraySize(output_dims, 1); 43 DCHECK(output_depth == input_depth * depth_multiplier); 44 45 for (int b = 0; b < batches; ++b) { 46 for (int out_y = 0; out_y < output_height; ++out_y) { 47 for (int out_x = 0; out_x < output_width; ++out_x) { 48 for (int ic = 0; ic < input_depth; ++ic) { 49 for (int m = 0; m < depth_multiplier; m++) { 50 const int oc = m + ic * depth_multiplier; 51 const int in_x_origin = (out_x * stride_width) - pad_width; 52 const int in_y_origin = (out_y * stride_height) - pad_height; 53 float total = 0.f; 54 for (int filter_y = 0; filter_y < filter_height; ++filter_y) { 55 for (int filter_x = 0; filter_x < filter_width; ++filter_x) { 56 const int in_x = in_x_origin + filter_x; 57 const int in_y = in_y_origin + filter_y; 58 // If the location is outside the bounds of the input image, 59 // use zero as a default value. 60 if ((in_x >= 0) && (in_x < input_width) && (in_y >= 0) && 61 (in_y < input_height)) { 62 float input_value = 63 input_data[Offset(input_dims, ic, in_x, in_y, b)]; 64 float filter_value = filter_data[Offset( 65 filter_dims, oc, filter_x, filter_y, 0)]; 66 total += (input_value * filter_value); 67 } 68 } 69 } 70 float bias_value = 0.0f; 71 if (bias_data) { 72 bias_value = bias_data[Offset(bias_dims, oc, 0, 0, 0)]; 73 } 74 output_data[Offset(output_dims, oc, out_x, out_y, b)] = 75 ActivationFunction<Ac>(total + bias_value); 76 } 77 } 78 } 79 } 80 } 81 } 82 83 } // end namespace reference_ops 84 } // namespace nn 85 } // namespace android 86 87 #endif // ANDROID_ML_NN_COMMON_OPERATIONS_INTERNAL_REFERENCE_DEPTHWISECONV_FLOAT_H_ 88
