def do_inference_on_local_endpoint()

in scikit_learn_script_mode_local_training_and_serving/scikit_learn_script_mode_local_training_and_serving.py [0:0]

• 11 lines of code
• 4 McCabe index (conditional complexity)

def do_inference_on_local_endpoint(predictor):
    print(f'\nStarting Inference on endpoint (local).')
    shape = pd.read_csv("data/iris.csv", header=None)

    a = [50 * i for i in range(3)]
    b = [40 + i for i in range(10)]
    indices = [i + j for i, j in itertools.product(a, b)]

    test_data = shape.iloc[indices[:-1]]
    test_X = test_data.iloc[:, 1:]
    test_y = test_data.iloc[:, 0]
    print("Predictions: {}".format(predictor.predict(test_X.values)))
    print("Actual: {}".format(test_y.values))