The error:

ValueError Traceback (most recent call last)

in

3 cost, cache = forward_propagation_n(X, Y, parameters)

4 gradients = backward_propagation_n(X, Y, cache)

----> 5 difference = gradient_check_n(parameters, gradients, X, Y, 1e-7, True)

6 expected_values = [0.2850931567761623, 1.1890913024229996e-07]

7 assert not(type(difference) == np.ndarray), “You are not using np.linalg.norm for numerator or denominator”

in gradient_check_n(parameters, gradients, X, Y, epsilon, print_msg)

37 theta_plus = np.copy(parameters_values)

38 theta_plus[i] = theta_plus[i]+epsilon

—> 39 J_plus[i]=forward_propagation_n(X, Y, vector_to_dictionary(theta_plus[i] ))

40 # YOUR CODE ENDS HERE

41

~/work/release/W1A3/gc_utils.py in vector_to_dictionary(theta)

53 “”"

54 parameters = {}

—> 55 parameters[“W1”] = theta[: 20].reshape((5, 4))

56 parameters[“b1”] = theta[20: 25].reshape((5, 1))

57 parameters[“W2”] = theta[25: 40].reshape((3, 5))

ValueError: cannot reshape array of size 1 into shape (5,4)

The code:

*{moderator edit - solution code removed}*