I am testing out airflow, I am running into the below error when implementing the dag.

ERROR [airflow.models.dagbag.DagBag] Failed to import: /Users/sbhardwa/airflow/dags/heart_desease/inference_pipeline.py
Traceback (most recent call last):
  File "/Users/sbhardwa/airflow/airflow_venv/lib/python3.12/site-packages/airflow/models/dagbag.py", line 351, in parse
    loader.exec_module(new_module)
  File "<frozen importlib._bootstrap_external>", line 995, in exec_module
  File "<frozen importlib._bootstrap>", line 488, in _call_with_frames_removed
  File "/Users/sbhardwa/airflow/dags/heart_desease/inference_pipeline.py", line 57, in <module>
    normalise_task.set_downstream(predict_data)
  File "/Users/sbhardwa/airflow/airflow_venv/lib/python3.12/site-packages/airflow/models/taskmixin.py", line 262, in set_downstream
    self._set_relatives(task_or_task_list, upstream=False, edge_modifier=edge_modifier)
  File "/Users/sbhardwa/airflow/airflow_venv/lib/python3.12/site-packages/airflow/models/taskmixin.py", line 214, in _set_relatives
    task_object.update_relative(self, not upstream, edge_modifier=edge_modifier)
    ^^^^^^^^^^^^^^^^^^^^^^^^^^^
AttributeError: 'function' object has no attribute 'update_relative'

Here is the code block –

from airflow import DAG
from airflow.operators.python import PythonOperator

from datetime import datetime, timedelta
from heart_desease.utils import *


default_args = {
    'owner': 'airflow',
    'start_date': datetime(2023,7,30),
    'retries' : 1, 
    'retry_delay' : timedelta(seconds=30)
}


ML_inference_dag = DAG(
                dag_id = 'Heart_dag',
                default_args = default_args,
                description = 'Dag to run inferences on predictions of heart disease patients',
                schedule_interval = '@hourly'
)

load_task = PythonOperator(
            task_id = 'load_task',
            python_callable = get_inference_data,
            dag = ML_inference_dag)

######
#Define task for encoding the categorial variables here
######

encode_task = PythonOperator(
            task_id = 'encode_task',
            python_callable = encode_features,
            dag = ML_inference_dag)

######
#Define task for normalising the variables here
######

normalise_task = PythonOperator(
            task_id = 'normalise_task',
            python_callable = normalize_data,
            dag = ML_inference_dag)

######
#Define task for getting models prediction here
######

prediction_task = PythonOperator(
            task_id = 'prediction_task',
            python_callable = predict_data,
            dag = ML_inference_dag)

load_task.set_downstream(encode_task)
encode_task.set_downstream(normalise_task)
normalise_task.set_downstream(predict_data)

here are the airflow detail –
Providers info
apache-airflow-providers-common-io | 1.3.1
apache-airflow-providers-common-sql | 1.13.0
apache-airflow-providers-fab | 1.1.0
apache-airflow-providers-ftp | 3.9.0
apache-airflow-providers-http | 4.11.0
apache-airflow-providers-imap | 3.6.0
apache-airflow-providers-smtp | 1.7.0
apache-airflow-providers-sqlite | 3.8.0

When I remove the ‘set_downstream’ lines, the Dags runs without error.
I googled, but I couldn’t and response to this error

Please advise