diff options
Diffstat (limited to 'tests/validation/CPP/DepthwiseConvolution.cpp')
| -rw-r--r-- | tests/validation/CPP/DepthwiseConvolution.cpp | 38 |
1 files changed, 22 insertions, 16 deletions
diff --git a/tests/validation/CPP/DepthwiseConvolution.cpp b/tests/validation/CPP/DepthwiseConvolution.cpp index ae54494c03..b57c2686f6 100644 --- a/tests/validation/CPP/DepthwiseConvolution.cpp +++ b/tests/validation/CPP/DepthwiseConvolution.cpp @@ -51,29 +51,35 @@ SimpleTensor<T> depthwise_convolution(const SimpleTensor<T> &src, const SimpleTe SimpleTensor<T> dst{ dst_shape, src.data_type(), 1, src.fixed_point_position() }; // Compute reference - const size_t filter_width = weights.shape().x(); - const size_t filter_height = weights.shape().y(); - const size_t filter_plane = filter_width * filter_height; - const size_t input_width = src.shape().x(); - const size_t input_height = src.shape().y(); - const size_t input_depth = src.shape().z(); - const int num_batches = src.shape().total_size() / (input_width * input_height * input_depth); + const int filter_width = weights.shape().x(); + const int filter_height = weights.shape().y(); + const int filter_plane = filter_width * filter_height; + const int input_width = src.shape().x(); + const int input_height = src.shape().y(); + const int input_depth = src.shape().z(); + const int num_batches = src.shape().total_size() / (input_width * input_height * input_depth); - const size_t filter_half_width = filter_width / 2; - const size_t filter_half_height = filter_height / 2; - const size_t pad_x = std::min(filter_half_width, static_cast<size_t>(conv_info.pad().first)); - const size_t pad_y = std::min(filter_half_height, static_cast<size_t>(conv_info.pad().second)); - const size_t minimum_x = -pad_x + filter_half_width; - const size_t minimum_y = -pad_y + filter_half_height; + 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) { - for(size_t z = 0; z < input_depth; ++z) + for(int z = 0; z < input_depth; ++z) { - for(size_t y = minimum_y; y < input_height - minimum_y; y += conv_info.stride().second) + for(int y = minimum_y; y < minimum_y + maximum_y; y += conv_info.stride().second) { - for(size_t x = minimum_x; x < input_width - minimum_x; x += conv_info.stride().first) + for(int x = minimum_x; x < minimum_x + maximum_x; x += conv_info.stride().first) { Coordinates coords(static_cast<int>(x), static_cast<int>(y), static_cast<int>(z), static_cast<int>(r)); size_t filter_offset = filter_plane * z; |