code: def __init__(self, config):
      super(Transformer, self).__init__()
  
      # self.xxx = config.xxx
      self.num_hidden_layers = config.num_hidden_layers
      self.output_attentions = config.output_attentions
      self.output_hidden_states = config.output_hidden_states
  
      self.layer = nn.ModuleList(
          [
              TransformerLayer(config)
              for _ in range(self.num_hidden_layers)
          ]
      )
  
imports: import math
  import torch
  import torch.nn
  import torch.nn.functional
  from .Attention import MultiHeadAttention
label_desc: Use image node_id 1 to create a new Transformer object from inherited base classes: nn with example: obj = Transformer(config)