code: def load_adult_model(**context):
      from deepchecks.tabular.datasets.classification.adult import (
          load_fitted_model,
      )
  
      model = load_fitted_model()
      with open(
          os.path.join(data_path, "adult_model.joblib"), "wb"
      ) as f:
          joblib.dump(model, f)
  
      context["ti"].xcom_push(
          key="adult_model",
          value=os.path.join(data_path, "adult_model.joblib"),
      )
  
file_path: deepchecks/examples/integrations/airflow/deepchecks_airflow_tutorial.py
imports: from datetime import datetime, timedelta
  import os
  from airflow import DAG
  from airflow.operators.python import PythonOperator
  import joblib
  import pandas
  from deepchecks.tabular.datasets.classification import adult
label_desc: Use image node_id 2 for calling a global function with example usage: load_adult_model() without return types