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GitHub Repository: y33-j3T/Coursera-Deep-Learning
 Path: blob/master/Custom Models, Layers, and Loss Functions with TensorFlow/Week 2 - Custom Loss Functions/utils.py
Views: 13373
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import numpy as np

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from sklearn.model_selection import train_test_split

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from tensorflow.python.framework.ops import EagerTensor

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from numpy import int64

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def test_loop(test_cases):

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    success = 0

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    fails = 0

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    for test_case in test_cases:

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        try:

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            assert test_case["result"] == test_case["expected"]

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            success += 1

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        except:

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            fails += 1

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            print(f'{test_case["name"]}: {test_case["error_message"]}\nExpected: {test_case["expected"]}\nResult: {test_case["result"]}\n')

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    if fails == 0:

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        print("\033[92m All public tests passed")

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    else:

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        print('\033[92m', success," Tests passed")

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        print('\033[91m', fails, " Tests failed")

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        raise Exception(test_case["error_message"])

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def test_my_rmse(my_rmse):

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    test_y_true = np.array([-1.0,  0.0, 1.0, 2.0, 3.0, 4.0], dtype=float)

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    test_y_pred = np.array([-3.0, -1.0, 1.0, 3.0, 5.0, 7.0], dtype=float)

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    expected = 1.7795130420052185

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    result = my_rmse(test_y_true, test_y_pred)

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    test_cases = [

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        {

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            "name": "type_check",

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            "result": type(result),

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            "expected": EagerTensor,

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            "error_message": f'output has an incorrect type.'

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        },

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        {

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            "name": "output_check",

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            "result": result,

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            "expected": expected,

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            "error_message": "Output is incorrect. Please check the equation."

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        }

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    ]

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    test_loop(test_cases)

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def test_model_loss(model_loss):

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    test_y_true = np.array([-1.0,  0.0, 1.0, 2.0, 3.0, 4.0], dtype=float)

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    test_y_pred = np.array([-3.0, -1.0, 1.0, 3.0, 5.0, 7.0], dtype=float)

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    expected = 1.7795130420052185

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    result = model_loss(test_y_true, test_y_pred)

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    test_cases = [

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        {

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            "name": "type_check",

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            "result": type(result),

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            "expected": EagerTensor,

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            "error_message": f'output has an incorrect type.'

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        },

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        {

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            "name": "output_check",

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            "result": result,

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            "expected": expected,

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            "error_message": "Output is incorrect. Please check the equation."

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        }

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    ]

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    test_loop(test_cases)

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