code: def forward(self, x):
      """Apply layer normalization.
  
      Args:
          x (torch.Tensor): Input tensor.
  
      Returns:
          torch.Tensor: Normalized tensor.
  
      """
      if self.dim == -1:
          return super(LayerNorm, self).forward(x)
      return (
          super(LayerNorm, self)
          .forward(x.transpose(self.dim, -1))
          .transpose(self.dim, -1)
      )
  
imports: import torch
label_desc: Use image node_id 2 for calling the LayerNorm obj's underlying member method code with example usage: obj.forward(x) and returns: super, super