code: def get_exome_config(
      config: ml_collections.ConfigDict,
  ) -> ml_collections.ConfigDict:
      """Config parameters for exome training."""
  
      # Exome Dataset
      config.train_dataset_pbtxt = (
          "/path/to/your/train.dataset_config.pbtxt"
      )
      config.tune_dataset_pbtxt = (
          "/path/to/your/tune.dataset_config.pbtxt"
      )
      # If set to 0, use full validation dataset.
      config.num_validation_examples = 0
  
      config.num_epochs = 80
      config.learning_rate = 0.01
      config.learning_rate_num_epochs_per_decay = 2.0
      config.learning_rate_decay_rate = 0.9999
      config.rho = 0.9763046740422171
      config.momentum = 0.9848544529312561
      config.epsilon = 0.8696723762650027
      config.warmup_steps = 718
      config.weight_decay = 0.1
      config.backbone_dropout_rate = 0.22517227651098964
  
      config.init_checkpoint = ""
  
      return config
  
label_desc: Use image node_id 1 for calling a global function with example usage: get_exome_config(config) and returns: config