class_docstr: This is a general transformer module with multiple transformer layers
code: def forward(self, x: torch.Tensor):
      for i, layer in enumerate(self.layers):
          # Get layer output
          x = layer(x)
  
      # Normalize the output
      return self.norm(x)
  
imports: import torch
  from torch import nn
  from labml_helpers.module import Module
  from labml_nn.transformers.feed_forward import FeedForward
  from labml_nn.transformers.mha import PrepareForMultiHeadAttention
  from labml_nn.utils import clone_module_list
label_desc: Use image node_id 2 for calling the FastWeightsAttentionTransformer obj's underlying member method code with example usage: obj.forward(x) and returns: self