args = parse_args()
if args.openml_apikey:
    openml.config.apikey = args.openml_apikey
if args.openml_server:
    openml.config.server = args.openml_server
else:
    openml.config.server = 'https://test.openml.org/api/v1/'
clf_pipeline=pipeline()
run = openml.runs.run_model_on_task(clf_pipeline, args.task_id)
score = []
evaluations = run.fold_evaluations['mean_absolute_error'][0]
for key in evaluations:
    score.append(evaluations[key])
mae=np.mean(score)
print(np.mean(score))
print(np.mean(run.get_metric_fn(sklearn.metrics.mean_squared_error)))
print(np.mean(run.get_metric_fn(sklearn.metrics.r2_score)))
logging.info('Task %d - %s; Accuracy: %0.2f' % (args.task_id, task.get_dataset().name, mae))

del_outputdir()
run.to_filesystem(directory= 'myrun')
print(args.upload_result)

if args.upload_result:
    run.publish()
    print(run)
    print('Results Uploaded to Openml and stored in local folder myrun')
else:
    print('Results stored in local folder myrun')`