code: def split_coupling(
      x, x_mask, split_dim, identity_first, decoder_self_attention_bias
  ):
      """Split function used in coupling flows."""
      n_channels = common_layers.shape_list(x)[-1]
      if split_dim == "c":
          n_transform = n_identity = n_channels // 2
          x_id = (
              x[..., :n_identity]
              if identity_first
              else x[..., n_transform:]
          )
          x_tr = (
              x[..., n_identity:]
              if identity_first
              else x[..., :n_transform]
          )
          bias, mask = decoder_self_attention_bias, x_mask
  
      elif split_dim == "a":
          n_transform = n_identity = n_channels // 2
          x_id = x[..., 0::2] if identity_first else x[..., 1::2]
          x_tr = x[..., 1::2] if identity_first else x[..., 0::2]
          bias, mask = decoder_self_attention_bias, x_mask
  
      elif split_dim == "t":
          n_transform = n_identity = n_channels
          x_id = x[:, 0::2, :] if identity_first else x[:, 1::2, :]
          x_tr = x[:, 1::2, :] if identity_first else x[:, 0::2, :]
          bias, mask = (
              decoder_self_attention_bias[..., 0::2],
              x_mask[..., 0::2],
          )
  
      return x_id, x_tr, n_identity, n_transform, bias, mask
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import copy
  import math
  from tensor2tensor.layers import common_attention
  from tensor2tensor.layers import common_layers
  from tensor2tensor.models.transformer import transformer_decoder_layer
  import tensorflow.compat.v1
  import tensorflow_probability
label_desc: Use image node_id 14 for calling a global function with example usage: split_coupling(x, x_mask, split_dim, identity_first, decoder__attention_bias) and returns: x_id,  x_tr,  n_identity,  n_transform,  bias,  mask