code: def parse_args():
      parser = argparse.ArgumentParser(description="LightGBM example")
      parser.add_argument(
          "--learning-rate",
          type=float,
          default=0.1,
          help="learning rate to update step size at each boosting step (default: 0.3)",
      )
      parser.add_argument(
          "--colsample-bytree",
          type=float,
          default=1.0,
          help="subsample ratio of columns when constructing each tree (default: 1.0)",
      )
      parser.add_argument(
          "--subsample",
          type=float,
          default=1.0,
          help="subsample ratio of the training instances (default: 1.0)",
      )
      return parser.parse_args()
  
file_path: BentoML/examples/mlflow/lightgbm/train.py
imports: import argparse
  import lightgbm
  import matplotlib
  import mlflow
  import mlflow.lightgbm
  from sklearn import datasets
  from sklearn.metrics import accuracy_score
  from sklearn.metrics import log_loss
  from sklearn.model_selection import train_test_split
  import bentoml
label_desc: Use image node_id 1 for calling a global function with example usage: parse_args() and returns: parser