code: def forward(self, inputs: torch.Tensor, **kwargs):
      assert inputs.shape[1:] == self.input_shape
  
      hidden = inputs
      hidden = self.layernorm1(hidden).transpose(1, 2)
      hidden = self.mlp1(hidden).transpose(1, 2)
  
      mid = hidden + inputs
  
      hidden = self.layernorm2(mid)
      hidden = self.mlp2(hidden)
  
      output = hidden + mid
      assert output.shape[1:] == self.output_shape
      return output
  
imports: from typing import Tuple, Union
  import torch
  import torch.nn
  from ludwig.utils.torch_utils import LudwigModule
label_desc: Use image node_id 2 for calling the MixerBlock obj's underlying member method code with example usage: obj.forward(inputs) and returns: output