Function onednn_sys::dnnl_dilated_convolution_backward_weights_desc_init

pub unsafe extern "C" fn dnnl_dilated_convolution_backward_weights_desc_init(
    conv_desc: *mut dnnl_convolution_desc_t, 
    alg_kind: dnnl_alg_kind_t, 
    src_desc: *const dnnl_memory_desc_t, 
    diff_weights_desc: *const dnnl_memory_desc_t, 
    diff_bias_desc: *const dnnl_memory_desc_t, 
    diff_dst_desc: *const dnnl_memory_desc_t, 
    strides: *mut dnnl_dim_t, 
    dilates: *mut dnnl_dim_t, 
    padding_l: *mut dnnl_dim_t, 
    padding_r: *mut dnnl_dim_t
) -> dnnl_status_t

Initializes a descriptor for a dilated convolution weights gradient primitive.

@note Memory descriptors can be initialized with #dnnl_format_tag_any or with format_kind set to #dnnl_format_kind_any.

Arrays @p strides, @p dilates, @p padding_l, and @p padding_r contain values for spatial dimensions only and hence must have the same number of elements as there are spatial dimensions. The order of values is the same as in the tensor: depth (for 3D tensors), height (for 3D and 2D tensors), and width.

@param conv_desc Output descriptor for a convolution primitive. @param alg_kind Convolution algorithm. Possible values are #dnnl_convolution_direct, #dnnl_convolution_winograd, #dnnl_convolution_auto. @param src_desc Source memory descriptor. @param diff_weights_desc Diff weights memory descriptor. @param diff_bias_desc Diff bias memory descriptor. Passing NULL, a zero memory descriptor, or a memory descriptor with format_kind set to #dnnl_format_kind_undef disables the bias term. @param diff_dst_desc Diff destination memory descriptor. @param strides Array of strides for spatial dimension. @param dilates Array of dilations for spatial dimension. A zero value means no dilation in the corresponding dimension. @param padding_l Array of padding values for low indices for each spatial dimension ([[front,] top,] left). @param padding_r Array of padding values for high indices for each spatial dimension ([[back,] bottom,] right). Can be NULL in which case padding is considered to be symmetrical. @returns #dnnl_success on success and a status describing the error otherwise.