code: def main():
      # Parse command-line arguments
      args = parse_args()
  
      # Enable auto logging
      mlflow.fastai.autolog()
  
      # Create Learner model
      learn = Learner(
          get_data_loaders(),
          Model(),
          loss_func=nn.MSELoss(),
          splitter=splitter,
      )
  
      # Start MLflow session
      with mlflow.start_run():
          # Train and fit with default or supplied command line arguments
          learn.fit_one_cycle(args.epochs, args.lr)
  
file_path: mlflow/examples/fastai/train.py
imports: import argparse
  import numpy
  from fastai.learner import Learner
  from fastai.tabular.all import TabularDataLoaders
  from sklearn.datasets import load_iris
  from torch import nn
  import mlflow
label_desc: Use image node_id 4 for calling a global function with example usage: main() without return types