def test_execute(self, mock_hook): op = AutoMLPredictOperator( model_id=MODEL_ID, location=GCP_LOCATION, project_id=GCP_PROJECT_ID, payload=PAYLOAD, task_id=TASK_ID, ) op.execute(context=None) mock_hook.return_value.predict.assert_called_once_with( location=GCP_LOCATION, metadata=None, model_id=MODEL_ID, params={}, payload=PAYLOAD, project_id=GCP_PROJECT_ID, retry=None, timeout=None, )
location=GCP_AUTOML_LOCATION, project_id=GCP_PROJECT_ID, ) # [END howto_operator_deploy_model] with models.DAG( "example_gcp_predict", schedule_interval=None, # Override to match your needs start_date=days_ago(1), tags=["example"], ) as predict_dag: # [START howto_operator_prediction] predict_task = AutoMLPredictOperator( task_id="predict_task", model_id=MODEL_ID, payload={}, # Add your own payload, the used model_id must be deployed location=GCP_AUTOML_LOCATION, project_id=GCP_PROJECT_ID, ) # [END howto_operator_prediction] # [START howto_operator_batch_prediction] batch_predict_task = AutoMLBatchPredictOperator( task_id="batch_predict_task", model_id=MODEL_ID, input_config={}, # Add your config output_config={}, # Add your config location=GCP_AUTOML_LOCATION, project_id=GCP_PROJECT_ID, ) # [END howto_operator_batch_prediction]