code: def _gmlp_configs(c: Configs):
      """
      ### Create a gMLP block
      """
      return GMLPBlock(c.d_model, c.d_ffn, c.seq_len)
  
file_path: annotated_deep_learning_paper_implementations/labml_nn/transformers/gmlp/experiment.py
imports: from labml import experiment
  from labml.configs import option
  from labml_nn.transformers import TransformerConfigs
  from labml_nn.transformers.basic.autoregressive_experiment import Configs
  from labml_nn.transformers.gmlp import GMLPBlock
label_desc: Use image node_id 1 for calling a global function with example usage: _gmlp_configs(c) and returns: GMLPBlock