code: def _transformer_configs(c: Configs):
      """
      ### Transformer configurations
      """
  
      # We use our
      # [configurable transformer implementation](../configs.html#TransformerConfigs)
      conf = TransformerConfigs()
      # Set the vocabulary sizes for embeddings and generating logits
      conf.n_src_vocab = c.n_tokens
      conf.n_tgt_vocab = c.n_tokens
      # GPT uses GELU activation for position wise feedforward
      conf.ffn.activation = "GELU"
  
      #
      return conf
  
imports: import torch
  from torch import nn
  from labml import experiment
  from labml.configs import option
  from labml_helpers.module import Module
  from labml_nn.experiments.nlp_autoregression import NLPAutoRegressionConfigs
  from labml_nn.optimizers.configs import OptimizerConfigs
  from labml_nn.transformers import TransformerConfigs, Encoder
  from labml_nn.transformers.utils import subsequent_mask
label_desc: Use image node_id 1 for calling a global function with example usage: _transformer_configs(c) and returns: conf