# Compute and display gradient with w initialized to zeroes

initial_w = 0

initial_b = 0

tmp_dj_dw, tmp_dj_db = compute_gradient(x_train, y_train, initial_w, initial_b)

print(‘Gradient at initial w, b (zeros):’, tmp_dj_dw, tmp_dj_db)

compute_gradient_test(compute_gradient)

##
Gradient at initial w, b (zeros): -566.3960999999998 -0.060197268572643195

Using X with shape (4, 1)

AssertionError Traceback (most recent call last)

in

6 print(‘Gradient at initial w, b (zeros):’, tmp_dj_dw, tmp_dj_db)

7

----> 8 compute_gradient_test(compute_gradient)

~/work/public_tests.py in compute_gradient_test(target)

51 #assert dj_dw.shape == initial_w.shape, f"Wrong shape for dj_dw. {dj_dw} != {initial_w.shape}"

52 assert dj_db == 0.0, f"Case 1: dj_db is wrong: {dj_db} != 0.0"

—> 53 assert np.allclose(dj_dw, 0), f"Case 1: dj_dw is wrong: {dj_dw} != [[0.0]]"

54

55 # Case 2

AssertionError: Case 1: dj_dw is wrong: 2.0 != [[0.0]]

How to rectify the code without the assertion error?