code: def _model(c: Configs):
      """
      Create an autoregressive model and initialize weights
      """
      m = AutoregressiveTransformer(
          c.transformer.encoder,
          c.transformer.src_embed,
          c.transformer.generator,
      ).to(c.device)
  
      return m
  
imports: from labml import experiment
  from labml.configs import option, calculate
  from labml_nn.transformers import TransformerConfigs
  from labml_nn.transformers.basic.autoregressive_experiment import AutoregressiveTransformer, Configs
label_desc: Use image node_id 2 for calling a global function with example usage: _model(c) and returns: m