Continuing the discussion from Compute_gradient_test(compute_gradient):
{Moderator Edit: Solution Code Removed}
Compute and display cost and gradient with non-zero w and b
test_w = np.array([ 0.2, -0.5])
test_b = -24
dj_db, dj_dw = compute_gradient(X_train, y_train, test_w, test_b)
print(‘dj_db at test w and b:’, dj_db)
print(‘dj_dw at test w and b:’, dj_dw.tolist())
UNIT TESTS
compute_gradient_test(compute_gradient)
and I am getting this error :
dj_db at test w and b: -0.5999999999991071
dj_dw at test w and b: [-44.831353617873795, -44.37384124953978]
ValueError Traceback (most recent call last)
in
8
9 # UNIT TESTS
—> 10 compute_gradient_test(compute_gradient)
~/work/public_tests.py in compute_gradient_test(target)
49 test_w = np.array([1, 0.5, -0.35])
50 test_b = 1.7
—> 51 dj_db, dj_dw = target(X, y, test_w, test_b)
52
53 assert np.isclose(dj_db, 0.28936094), f"Wrong value for dj_db. Expected: {0.28936094} got: {dj_db}"
in compute_gradient(X_train, y_train, test_w, test_b, *argv)
25 test_b = -24
26 for i in range(m):
—> 27 z = np.dot(X_train[i],test_w) + test_b
28 f_wb_i = sigmoid(z)
29 err_i = f_wb_i - y_train[i]
<array_function internals> in dot(*args, **kwargs)
ValueError: shapes (3,) and (2,) not aligned: 3 (dim 0) != 2 (dim 0)