class_docstr: ## Auto regressive model
class_docstr_tok: ["#","#","Auto","regressive","model"]
code: def __init__(self, n_vocab: int, d_model: int, rnn_model: Module):
      super().__init__()
      # Token embedding module
      self.src_embed = nn.Embedding(n_vocab, d_model)
      self.lstm = rnn_model
      self.generator = nn.Linear(d_model, n_vocab)
  
file_path: annotated_deep_learning_paper_implementations/labml_nn/hypernetworks/experiment.py
imports: import torch
  import torch.nn
  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.hypernetworks.hyper_lstm import HyperLSTM
  from labml_nn.lstm import LSTM
label_desc: Use image node_id 1 to create a new AutoregressiveModel object from inherited base classes: Module with example: obj = AutoregressiveModel(n_vocab, d_model, rnn_model)