code: def create_norm_fn(norm_type: str, dim: int, **kwargs) -> nn.Module:
      """Create normalization module for transformer encoder layer.
  
      Args:
          norm_type (str): Normalization method.
          dim (int): Dimension of the normalized layer.
          **kwargs (dict): Additional parameters for normalization layer.
      Returns:
          nn.Module: Normalization module.
      """
      if norm_type == "layer_norm":
          return nn.LayerNorm(dim, eps=1e-5, **kwargs)
      else:
          raise ValueError(f"Unknown norm type: {norm_type}")
  
imports: import typing
  from einops import rearrange
  import torch
  import torch.nn
  from torch.nn import functional
  from torch.utils.checkpoint import checkpoint
  from xformers import ops
  from .rope import RotaryEmbedding
  from .streaming import StreamingModule
label_desc: Use image node_id 4 for calling a global function with example usage: create_norm_fn(norm_type, dim) and returns: nn