code: def _model(c: Configs):
      """
      Create GPT model and initialize weights
      """
      m = AutoregressiveTransformer(
          c.transformer.encoder,
          c.transformer.src_embed,
          c.transformer.generator,
      ).to(c.device)
  
      return m
  
file_path: annotated_deep_learning_paper_implementations/labml_nn/transformers/basic/autoregressive_experiment.py
imports: import torch
  from torch import nn
  from labml import experiment
  from labml.configs import option
  from labml_nn.experiments.nlp_autoregression import NLPAutoRegressionConfigs
  from labml_nn.transformers import TransformerConfigs, Encoder
  from labml_nn.transformers.utils import subsequent_mask
label_desc: Use image node_id 2 for calling a global function with example usage: _model(c) and returns: m