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author | Giorgio Arena <giorgio.arena@arm.com> | 2019-08-02 16:00:41 +0100 |
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committer | Giorgio Arena <giorgio.arena@arm.com> | 2019-08-08 10:20:13 +0000 |
commit | 172035864c8eb73fc46aeec1075423526a768e83 (patch) | |
tree | 620fc0f0c8ae69146fe577dc67ae3dbe95d8bc46 /src/core | |
parent | fed275d76d8322d51872845378adc0058c02bfc1 (diff) | |
download | ComputeLibrary-172035864c8eb73fc46aeec1075423526a768e83.tar.gz |
COMPMID-2336 Extend validation for depthwise native and fix same pad calculator
Change-Id: I9f5cc95bc0cbd94869ac13064ffa0aa0f52a7a61
Signed-off-by: Giorgio Arena <giorgio.arena@arm.com>
Reviewed-on: https://review.mlplatform.org/c/1684
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Michele Di Giorgio <michele.digiorgio@arm.com>
Reviewed-by: Gian Marco Iodice <gianmarco.iodice@arm.com>
Diffstat (limited to 'src/core')
-rw-r--r-- | src/core/Utils.cpp | 51 |
1 files changed, 29 insertions, 22 deletions
diff --git a/src/core/Utils.cpp b/src/core/Utils.cpp index 5d32750f0d..d0bffdf660 100644 --- a/src/core/Utils.cpp +++ b/src/core/Utils.cpp @@ -331,37 +331,44 @@ std::string arm_compute::lower_string(const std::string &val) return res; } -PadStrideInfo arm_compute::calculate_same_pad(TensorShape input_shape, TensorShape weights_shape, PadStrideInfo conv_info, DataLayout data_layout, const Size2D &dilation) +PadStrideInfo arm_compute::calculate_same_pad(TensorShape input_shape, TensorShape weights_shape, PadStrideInfo conv_info, DataLayout data_layout, const Size2D &dilation, + const DimensionRoundingType &rounding_type) { - const unsigned int width_idx = arm_compute::get_data_layout_dimension_index(data_layout, DataLayoutDimension::WIDTH); - const unsigned int height_idx = arm_compute::get_data_layout_dimension_index(data_layout, DataLayoutDimension::HEIGHT); - const auto &strides = conv_info.stride(); + const unsigned int width_idx = arm_compute::get_data_layout_dimension_index(data_layout, DataLayoutDimension::WIDTH); + const unsigned int height_idx = arm_compute::get_data_layout_dimension_index(data_layout, DataLayoutDimension::HEIGHT); + const unsigned int in_width = input_shape[width_idx]; + const unsigned int in_height = input_shape[height_idx]; + const unsigned int kernel_width = weights_shape[width_idx]; + const unsigned int kernel_height = weights_shape[height_idx]; + const auto &strides = conv_info.stride(); // Calculate output dimensions - const int out_width = (input_shape[width_idx] + strides.first - 1) / strides.first; - const int out_height = (input_shape[height_idx] + strides.second - 1) / strides.second; + const auto is_ceil = static_cast<unsigned int>(rounding_type == DimensionRoundingType::CEIL); + const unsigned int out_width = ((in_width - is_ceil) + strides.first - 1) / strides.first + is_ceil; + const unsigned int out_height = ((in_height - is_ceil) + strides.second - 1) / strides.second + is_ceil; // Calculate effective weights sizes - const int real_weight_width = (weights_shape[width_idx] - 1) * dilation.x() + 1; - const int real_weight_height = (weights_shape[height_idx] - 1) * dilation.y() + 1; + const int real_weight_width = (kernel_width - 1) * dilation.x() + 1; + const int real_weight_height = (kernel_height - 1) * dilation.y() + 1; // Calculate total pad - const int pad_width = (out_width - 1) * strides.first + real_weight_width - input_shape[width_idx]; - const int pad_height = (out_height - 1) * strides.second + real_weight_height - input_shape[height_idx]; + const int pad_width = std::max(0, static_cast<int>((out_width - 1) * strides.first + real_weight_width - in_width)); + const int pad_height = std::max(0, static_cast<int>((out_height - 1) * strides.second + real_weight_height - in_height)); // Calculate individual paddings - const int same_pad_left = pad_width / 2; - const int same_pad_top = pad_height / 2; - const int same_pad_right = pad_width - same_pad_left; - const int same_pad_bottom = pad_height - same_pad_top; - - return { static_cast<unsigned int>(strides.first), - static_cast<unsigned int>(strides.second), - static_cast<unsigned int>(same_pad_left), - static_cast<unsigned int>(same_pad_right), - static_cast<unsigned int>(same_pad_top), - static_cast<unsigned int>(same_pad_bottom), - DimensionRoundingType::CEIL }; + const unsigned int pad_left = pad_width / 2; + const unsigned int pad_top = pad_height / 2; + const unsigned int pad_right = pad_width - pad_left; + const unsigned int pad_bottom = pad_height - pad_top; + + PadStrideInfo same_info(strides.first, strides.second, pad_left, pad_right, pad_top, pad_bottom, rounding_type); + + // Check for correctness of predicted output shape against the one calculated using the generated info + const auto out_dims = scaled_dimensions(in_width, in_height, kernel_width, kernel_height, same_info, dilation); + ARM_COMPUTE_ERROR_ON(out_dims.first != out_width || out_dims.second != out_height); + ARM_COMPUTE_UNUSED(out_dims); + + return same_info; } std::pair<unsigned int, unsigned int> arm_compute::deconvolution_output_dimensions( |