code: def _mix_mlp_configs(c: Configs):
      """
      The mixing MLP configurations
      """
  
      conf = FeedForwardConfigs()
      # Size of the MLP is the sequence length, because it is applied across tokens
      conf.d_model = c.seq_len
      # The paper suggests $GELU$ activation
      conf.activation = "GELU"
  
      #
      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 1 for calling a global function with example usage: _mix_mlp_configs(c) and returns: conf