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
  
      #
      return conf
  
file_path: annotated_deep_learning_paper_implementations/labml_nn/transformers/fnet/experiment.py
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_classification import NLPClassificationConfigs
  from labml_nn.transformers import Encoder
  from labml_nn.transformers import TransformerConfigs
label_desc: Use image node_id 1 for calling a global function with example usage: _transformer_configs(c) and returns: conf