code: def autoregressive_model(c: Configs):
      """
      Initialize the auto-regressive model
      """
      m = AutoregressiveModel(
          # Get the source token embedding layer, encoder and
          # final token generator from configurable transformer
          src_embed=c.transformer.src_embed,
          encoder=c.transformer.encoder,
          generator=c.transformer.generator,
          # Whether to save $f(c_t)$
          is_save_ff_input=c.is_save_ff_input,
      )
      return m.to(c.device)
  
file_path: annotated_deep_learning_paper_implementations/labml_nn/transformers/knn/train_model.py
imports: import torch
  from labml import experiment
  from labml.configs import option
  from labml.utils.pytorch import get_modules
  from labml_helpers.module import Module
  from labml_nn.experiments.nlp_autoregression import NLPAutoRegressionConfigs
  from labml_nn.transformers import Encoder, Generator, TransformerConfigs
  from labml_nn.transformers.utils import subsequent_mask
label_desc: Use image node_id 1 for calling a global function with example usage: autoregressive_model(c) and returns: m