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
      # Embedding size
      conf.d_model = c.d_model
      # Change attention module to [MLPMixer](index.html)
      from labml_nn.transformers.mlp_mixer import MLPMixer
  
      conf.encoder_attn = MLPMixer(c.mix_mlp.ffn)
  
      #
      return conf
  
file_path: annotated_deep_learning_paper_implementations/labml_nn/transformers/mlp_mixer/experiment.py
imports: from labml import experiment
  from labml.configs import option
  from labml_nn.transformers import TransformerConfigs
  from labml_nn.transformers.configs import FeedForwardConfigs
  from labml_nn.transformers.mlm.experiment import TransformerMLM, Configs
label_desc: Use image node_id 2 for calling a global function with example usage: _transformer_configs(c) and returns: conf