class_docstr: ## Transformer XL Model
  
  This consists of multiple transformer XL layers
class_docstr_tok: ["#","#","Transformer","XL","Model","This","consists","of","multiple","transformer","XL","layers"]
code: def __init__(self, layer: TransformerXLLayer, n_layers: int):
      super().__init__()
      # Make copies of the transformer layer
      self.layers = clone_module_list(layer, n_layers)
      # Final normalization layer
      self.norm = nn.LayerNorm([layer.size])
  
file_path: annotated_deep_learning_paper_implementations/labml_nn/transformers/xl/__init__.py
imports: from typing import List, Optional
  import torch
  import torch.nn
  from labml_helpers.module import Module
  from labml_nn.utils import clone_module_list
  from .relative_mha import RelativeMultiHeadAttention
  from ..feed_forward import FeedForward
label_desc: Use image node_id 1 to create a new TransformerXL object from inherited base classes: Module with example: obj = TransformerXL(layer, n_layers)