Function onednn_sys::dnnl_lbr_gru_forward_desc_init

pub unsafe extern "C" fn dnnl_lbr_gru_forward_desc_init(
    rnn_desc: *mut dnnl_rnn_desc_t, 
    prop_kind: dnnl_prop_kind_t, 
    direction: dnnl_rnn_direction_t, 
    src_layer_desc: *const dnnl_memory_desc_t, 
    src_iter_desc: *const dnnl_memory_desc_t, 
    weights_layer_desc: *const dnnl_memory_desc_t, 
    weights_iter_desc: *const dnnl_memory_desc_t, 
    bias_desc: *const dnnl_memory_desc_t, 
    dst_layer_desc: *const dnnl_memory_desc_t, 
    dst_iter_desc: *const dnnl_memory_desc_t, 
    flags: c_uint
) -> dnnl_status_t

Initializes a descriptor for LBR GRU forward propagation primitive.

The following arguments may either be @c NULL or point to a zero memory descriptor:

• @p src_iter_desc,
• @p bias_desc,
• @p dst_iter_desc.

This would then indicate that the LBR GRU forward propagation primitive should not use them and should default to zero values instead.

@param rnn_desc Output descriptor for LBR GRU primitive. @param prop_kind Propagation kind. Possible values are #dnnl_forward_training and #dnnl_forward_inference. @param direction RNN direction. See @ref dnnl_rnn_direction_t for more info. @param src_layer_desc Memory descriptor for the input vector. @param src_iter_desc Memory descriptor for the input recurrent hidden state vector. @param weights_layer_desc Memory descriptor for the weights applied to the layer input. @param weights_iter_desc Memory descriptor for the weights applied to the recurrent input. @param bias_desc Bias memory descriptor. @param dst_layer_desc Memory descriptor for the output vector. @param dst_iter_desc Memory descriptor for the output recurrent hidden state vector. @param flags Unused. @returns #dnnl_success on success and a status describing the error otherwise.