code: def transformer_c(c: Configs):
      """
      Initialize the [configurable transformer](../configs.html) encoder for our autoregressive model.
      """
      tc = TransformerConfigs()
      tc.n_src_vocab = c.n_tokens
      tc.n_tgt_vocab = c.n_tokens
  
      return tc
  
file_path: annotated_deep_learning_paper_implementations/labml_nn/transformers/glu_variants/experiment.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 2 for calling a global function with example usage: transformer_c(c) and returns: tc