def predict_test(target):
np.random.seed(1)
X = np.random.randn(2, 3)
parameters = {
'W1':
np.array([[-0.00615039, 0.0169021], [-0.02311792, 0.03137121],
[-0.0169217, -0.01752545], [0.00935436, -0.05018221]]),
'W2':
np.array([[-0.0104319, -0.04019007, 0.01607211, 0.04440255]]),
'b1':
np.array([[-8.97523455e-07], [8.15562092e-06], [6.04810633e-07],
[-2.54560700e-06]]),
'b2':
np.array([[9.14954378e-05]])
}
expected_output = np.array([[True, False, True]])
test_cases = [{
"name": "datatype_check",
"input": [parameters, X],
"expected": expected_output,
"error": "Data type mismatch"
}, {
"name": "shape_check",
"input": [parameters, X],
"expected": expected_output,
"error": "Wrong shape"
}, {
"name": "equation_output_check",
"input": [parameters, X],
"expected": expected_output,
"error": "Wrong output"
}]
single_test(test_cases, target)
def compute_cost_with_regularization_test(target):
np.random.seed(1)
Y = np.array([[1, 1, 0, 1, 0]])
W1 = np.random.randn(2, 3)
b1 = np.random.randn(2, 1)
W2 = np.random.randn(3, 2)
b2 = np.random.randn(3, 1)
W3 = np.random.randn(1, 3)
b3 = np.random.randn(1, 1)
parameters = {"W1": W1, "b1": b1, "W2": W2, "b2": b2, "W3": W3, "b3": b3}
A3 = np.array([[ 0.40682402, 0.01629284, 0.16722898, 0.10118111, 0.40682402]])
lambd = 0.1
expected_output = np.float64(1.7864859451590758)
test_cases = [
{
"name": "shape_check",
"input": [A3, Y, parameters, lambd],
"expected": expected_output,
"error": "Wrong shape"
},
{
"name": "equation_output_check",
"input": [A3, Y, parameters, lambd],
"expected": expected_output,
"error": "Wrong output"
}
]
single_test(test_cases, target)
def compute_cost_test(target):
np.random.seed(1)
Y = (np.random.randn(1, 3) > 0)
parameters = {'W1': np.array([[-0.00416758, -0.00056267],
[-0.02136196, 0.01640271],
[-0.01793436, -0.00841747],
[ 0.00502881, -0.01245288]]),
'W2': np.array([[-0.01057952, -0.00909008, 0.00551454, 0.02292208]]),
'b1': np.array([[ 0.],
[ 0.],
[ 0.],
[ 0.]]),
'b2': np.array([[ 0.]])}
A2 = (np.array([[ 0.5002307 , 0.49985831, 0.50023963]]))
expected_output = 0.6930587610394646
test_cases = [
{
"name":"datatype_check",
"input": [A2, Y],
"expected": expected_output,
"error":"Datatype mismatch"
},
{
"name": "equation_output_check",
"input": [A2, Y],
"expected": expected_output,
"error": "Wrong output"
}
]
single_test(test_cases, target)
def gradient_check_n_test(target, parameters, gradients, X, Y):
expected_output_1 = 0.2850931567761623
expected_output_2 = 1.1890913024229996e-07
test_cases = [{
"name": "multiple_equation_output_check",
"input": [parameters, gradients, X, Y],
"expected": [expected_output_1, expected_output_2],
"error": "Wrong output"
}]
single_test(test_cases, target)
def forward_propagation_test(target):
x, theta = 2, 4
expected_output = 8
test_cases = [{
"name": "equation_output_check",
"input": [x, theta],
"expected": expected_output,
"error": "Wrong output"
}]
single_test(test_cases, target)
def gradient_check_test(target):
x, theta = 2, 4
expected_output = 2.919335883291695e-10
test_cases = [{
"name": "equation_output_check",
"input": [x, theta],
"expected": expected_output,
"error": "Wrong output"
}]
single_test(test_cases, target)
def compute_cost_test(target):
Y = np.asarray([[1, 1, 0]])
AL = np.array([[.8, .9, 0.4]])
expected_output = np.array(0.27977656)
test_cases = [{
"name": "equation_output_check",
"input": [AL, Y],
"expected": expected_output,
"error": "Wrong output"
}]
single_test(test_cases, target)
def compute_cost_test(target):
np.random.seed(1)
Y = (np.random.randn(1, 5) > 0)
A2 = (np.array([[0.5002307, 0.49985831, 0.50023963, 0.25, 0.7]]))
expected_output = 0.5447066599017815
test_cases = [{
"name": "datatype_check",
"input": [A2, Y],
"expected": expected_output,
"error": "Datatype mismatch"
}, {
"name": "equation_output_check",
"input": [A2, Y],
"expected": expected_output,
"error": "Wrong output"
}]
single_test(test_cases, target)
def pool_backward_test(target):
test_cases = [{
"name": "datatype_check",
"input": [parameters, X],
"expected": expected_output,
"error": "Data type mismatch"
}, {
"name": "shape_check",
"input": [parameters, X],
"expected": expected_output,
"error": "Wrong shape"
}, {
"name": "equation_output_check",
"input": [parameters, X],
"expected": expected_output,
"error": "Wrong output"
}]
single_test(test_cases, target)
def zero_pad_test(target):
np.random.seed(1)
x = np.random.randn(4, 3, 3, 2)
pad = 2
expected_output = expected_output = np.array(
[[[[0., 0.], [0., 0.], [0., 0.], [0., 0.], [0., 0.], [0., 0.],
[0., 0.]],
[[0., 0.], [0., 0.], [0., 0.], [0., 0.], [0., 0.], [0., 0.],
[0., 0.]],
[[0., 0.], [0., 0.], [1.62434536, -0.61175641],
[-0.52817175, -1.07296862], [0.86540763, -2.3015387], [0., 0.],
[0., 0.]],
[[0., 0.], [0., 0.], [1.74481176, -0.7612069],
[0.3190391, -0.24937038], [1.46210794, -2.06014071], [0., 0.],
[0., 0.]],
[[0., 0.], [0., 0.], [-0.3224172, -0.38405435],
[1.13376944, -1.09989127], [-0.17242821, -0.87785842], [0., 0.],
[0., 0.]],
[[0., 0.], [0., 0.], [0., 0.], [0., 0.], [0., 0.], [0., 0.],
[0., 0.]],
[[0., 0.], [0., 0.], [0., 0.], [0., 0.], [0., 0.], [0., 0.],
[0., 0.]]],
[[[0., 0.], [0., 0.], [0., 0.], [0., 0.], [0., 0.], [0., 0.],
[0., 0.]],
[[0., 0.], [0., 0.], [0., 0.], [0., 0.], [0., 0.], [0., 0.],
[0., 0.]],
[[0., 0.], [0., 0.], [0.04221375, 0.58281521],
[-1.10061918, 1.14472371], [0.90159072, 0.50249434], [0., 0.],
[0., 0.]],
[[0., 0.], [0., 0.], [0.90085595, -0.68372786],
[-0.12289023, -0.93576943], [-0.26788808,
0.53035547], [0., 0.], [0., 0.]],
[[0., 0.], [0., 0.], [-0.69166075, -0.39675353],
[-0.6871727, -0.84520564], [-0.67124613, -0.0126646], [0., 0.],
[0., 0.]],
[[0., 0.], [0., 0.], [0., 0.], [0., 0.], [0., 0.], [0., 0.],
[0., 0.]],
[[0., 0.], [0., 0.], [0., 0.], [0., 0.], [0., 0.], [0., 0.],
[0., 0.]]],
[[[0., 0.], [0., 0.], [0., 0.], [0., 0.], [0., 0.], [0., 0.],
[0., 0.]],
[[0., 0.], [0., 0.], [0., 0.], [0., 0.], [0., 0.], [0., 0.],
[0., 0.]],
[[0., 0.], [0., 0.], [-1.11731035, 0.2344157],
[1.65980218, 0.74204416], [-0.19183555, -0.88762896], [0., 0.],
[0., 0.]],
[[0., 0.], [0., 0.], [-0.74715829, 1.6924546],
[0.05080775, -0.63699565], [0.19091548, 2.10025514], [0., 0.],
[0., 0.]],
[[0., 0.], [0., 0.], [0.12015895, 0.61720311],
[0.30017032, -0.35224985], [-1.1425182, -0.34934272], [0., 0.],
[0., 0.]],
[[0., 0.], [0., 0.], [0., 0.], [0., 0.], [0., 0.], [0., 0.],
[0., 0.]],
[[0., 0.], [0., 0.], [0., 0.], [0., 0.], [0., 0.], [0., 0.],
[0., 0.]]],
[[[0., 0.], [0., 0.], [0., 0.], [0., 0.], [0., 0.], [0., 0.],
[0., 0.]],
[[0., 0.], [0., 0.], [0., 0.], [0., 0.], [0., 0.], [0., 0.],
[0., 0.]],
[[0., 0.], [0., 0.], [-0.20889423, 0.58662319],
[0.83898341, 0.93110208], [0.28558733, 0.88514116], [0., 0.],
[0., 0.]],
[[0., 0.], [0., 0.], [-0.75439794, 1.25286816],
[0.51292982, -0.29809284], [0.48851815, -0.07557171], [0., 0.],
[0., 0.]],
[[0., 0.], [0., 0.], [1.13162939, 1.51981682],
[2.18557541, -1.39649634], [-1.44411381, -0.50446586], [0., 0.],
[0., 0.]],
[[0., 0.], [0., 0.], [0., 0.], [0., 0.], [0., 0.], [0., 0.],
[0., 0.]],
[[0., 0.], [0., 0.], [0., 0.], [0., 0.], [0., 0.], [0., 0.],
[0., 0.]]]])
test_cases = [{
"name": "datatype_check",
"input": [x, pad],
"expected": expected_output,
"error": "Datatype mismatch."
}, {
"name": "equation_output_check",
"input": [x, pad],
"expected": expected_output,
"error": "Wrong output"
}]
single_test(test_cases, target)