Function calculate_same_pad

src/core/Utils.cpp:218–264

}

PadStrideInfo calculate_same_pad(TensorShape                  input_shape,
                                 TensorShape                  weights_shape,
                                 PadStrideInfo                conv_info,
                                 DataLayout                   data_layout,
                                 const Size2D                &dilation,
                                 const DimensionRoundingType &rounding_type)
{
    const auto &strides = conv_info.stride();
    ARM_COMPUTE_ERROR_ON_MSG((strides.first < 1 || strides.second < 1),
                             "Stride values should be greater than or equal to 1.");

    const unsigned int width_idx     = get_data_layout_dimension_index(data_layout, DataLayoutDimension::WIDTH);
    const unsigned int height_idx    = 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];

    // Calculate output dimensions
    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  = (kernel_width - 1) * dilation.x() + 1;
    const int real_weight_height = (kernel_height - 1) * dilation.y() + 1;

    // Calculate total pad
    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 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> deconvolution_output_dimensions(unsigned int         in_width,
                                                                      unsigned int         in_height,