Function onednn_sys::dnnl_convolution_backward_data_desc_init

pub unsafe extern "C" fn dnnl_convolution_backward_data_desc_init(
    conv_desc: *mut dnnl_convolution_desc_t, 
    alg_kind: dnnl_alg_kind_t, 
    diff_src_desc: *const dnnl_memory_desc_t, 
    weights_desc: *const dnnl_memory_desc_t, 
    diff_dst_desc: *const dnnl_memory_desc_t, 
    strides: *mut dnnl_dim_t, 
    padding_l: *mut dnnl_dim_t, 
    padding_r: *mut dnnl_dim_t
) -> dnnl_status_t

Initializes a descriptor for a convolution backward propagation 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 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 diff_src_desc Diff source memory descriptor. @param weights_desc Weights memory descriptor. @param diff_dst_desc Diff destination memory descriptor. @param strides Array of strides for spatial 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 assumed to be symmetrical. @returns #dnnl_success on success and a status describing the error otherwise.