Hello,

for this exercise, we had:

```
The size of the input layer is: n_x = 5
The size of the hidden layer is: n_h = 4
The size of the output layer is: n_y = 2
```

Then in 4.2, we had to initialize the parameters. Here is my initialization:

*{moderator edit - solution code removed}*

which follows this geometry described in the code:

W1 – weight matrix of shape (n_h, n_x)

b1 – bias vector of shape (n_h, 1)

W2 – weight matrix of shape (n_y, n_h)

b2 – bias vector of shape (n_y, 1)

However, running the code I get this output:

##
W1 = [[-4.16757847e-03 -5.62668272e-04 -2.13619610e-02 1.64027081e-02

-1.79343559e-02]

[-8.41747366e-03 5.02881417e-03 -1.24528809e-02 -1.05795222e-02

-9.09007615e-03]

[ 5.51454045e-03 2.29220801e-02 4.15393930e-04 -1.11792545e-02

5.39058321e-03]

[-5.96159700e-03 -1.91304965e-04 1.17500122e-02 -7.47870949e-03

9.02525097e-05]]

b1 = [[0.]

[0.]

[0.]

[0.]]

W2 = [[-0.00878108 -0.00156434 0.0025657 -0.00988779]

[-0.00338822 -0.00236184 -0.00637655 -0.01187612]]

b2 = [[0.]

[0.]]

AssertionError Traceback (most recent call last)

in

8 print("b2 = " + str(parameters[“b2”]))

9

—> 10 initialize_parameters_test(initialize_parameters)

~/work/release/W3A1/public_tests.py in initialize_parameters_test(target)

52 assert type(parameters[“b2”]) == np.ndarray, f"Wrong type for b2. Expected: {np.ndarray}"

53

—> 54 assert parameters[“W1”].shape == expected_output[“W1”].shape, f"Wrong shape for W1."

55 assert parameters[“b1”].shape == expected_output[“b1”].shape, f"Wrong shape for b1."

56 assert parameters[“W2”].shape == expected_output[“W2”].shape, f"Wrong shape for W2."

AssertionError: Wrong shape for W1.

…

…

…

which is completely different from the expected output. I would appreciate any help to realize what it’s happening here.