diff options
Diffstat (limited to 'tests/validation/reference/DepthwiseConvolutionLayer.cpp')
| -rw-r--r-- | tests/validation/reference/DepthwiseConvolutionLayer.cpp | 25 |
1 files changed, 16 insertions, 9 deletions
diff --git a/tests/validation/reference/DepthwiseConvolutionLayer.cpp b/tests/validation/reference/DepthwiseConvolutionLayer.cpp index 6ca347f1d4..66e3a4b783 100644 --- a/tests/validation/reference/DepthwiseConvolutionLayer.cpp +++ b/tests/validation/reference/DepthwiseConvolutionLayer.cpp @@ -140,11 +140,18 @@ SimpleTensor<uint8_t> depthwise_convolution(const SimpleTensor<uint8_t> &src, co const int input_depth = src.shape().z(); const int num_batches = src.shape().total_size() / (input_width * input_height * input_depth); - const int filter_half_size = filter_width / 2; - const int pad_x = std::min(filter_half_size, static_cast<int>(conv_info.pad().first)); - const int pad_y = std::min(filter_half_size, static_cast<int>(conv_info.pad().second)); - const int minimum_x = -pad_x + filter_half_size; - const int minimum_y = -pad_y + filter_half_size; + const int filter_half_width = filter_width / 2; + const int filter_half_height = filter_height / 2; + + const int pad_left = std::min(static_cast<int>(conv_info.pad_left()), filter_half_width); + const int pad_top = std::min(static_cast<int>(conv_info.pad_top()), filter_half_height); + const int pad_right = std::min(static_cast<int>(conv_info.pad_right()), filter_half_width); + const int pad_bottom = std::min(static_cast<int>(conv_info.pad_bottom()), filter_half_height); + + const int minimum_x = -pad_left + filter_half_width; + const int minimum_y = -pad_top + filter_half_height; + const int maximum_x = input_width + pad_left - filter_half_width + pad_right - filter_half_width; + const int maximum_y = input_height + pad_top - filter_half_height + pad_bottom - filter_half_height; int out_pos = 0; for(int r = 0; r < num_batches; ++r) @@ -152,17 +159,17 @@ SimpleTensor<uint8_t> depthwise_convolution(const SimpleTensor<uint8_t> &src, co for(int z = 0; z < input_depth; ++z) { int32_t bias_val = *static_cast<const int32_t *>(biases(Coordinates(z))); - for(int y = minimum_y; y < input_height + pad_y - filter_half_size; y += conv_info.stride().second) + for(int y = minimum_y; y < minimum_y + maximum_y; y += conv_info.stride().second) { - for(int x = minimum_x; x < input_width + pad_x - filter_half_size; x += conv_info.stride().first) + for(int x = minimum_x; x < minimum_x + maximum_x; x += conv_info.stride().first) { Coordinates coords(x, y, z, r); int filter_offset = filter_plane * z; int32_t val = 0; - for(int j = y - filter_half_size; j <= (y + filter_half_size); ++j) + for(int j = y - filter_half_height; j <= (y + filter_half_height); ++j) { - for(int i = x - filter_half_size; i <= (x + filter_half_size); ++i) + for(int i = x - filter_half_width; i <= (x + filter_half_width); ++i) { coords.set(0, i); coords.set(1, j); |