My code does not return the expected result. I return [[0. 0. 0.]] instead of [[1.0, 0.0, 1.0]]. So some silly format error.

But also I have inserted print statements to debug this. But I return only two values, and both A[i] are classified correctly .

Please advise.

Thank you!

See output:

Shape of A[0] (3,)

Shape of A[1] (3,)

Debug: Value of A 0 0.4532514150014657

Debug: Value of Prediction 0 0.0

predictions = [[0. 0. 0.]]

Shape of A[0] (3,)

Shape of A[1] (3,)

Debug: Value of A 0 0.4916682712877986

Debug: Value of Prediction 0 0.0

AssertionError Traceback (most recent call last)

in

4 print ("predictions = " + str(predict(w, b, X)))

5

----> 6 predict_test(predict)

~/work/release/W2A2/public_tests.py in predict_test(target)

100 assert pred.shape == (1, X.shape[1]), f"Wrong shape for pred. {pred.shape} != {(1, X.shape[1])}"

101 assert np.bitwise_not(np.allclose(pred, [[1., 1., 1]])), f"Perhaps you forget to add b in the calculation of A"

β 102 assert np.allclose(pred, [[1., 0., 1]]), f"Wrong values for pred. {pred} != {[[1., 0., 1.]]}"

103

104 print(β\033[92mAll tests passed!β)

**AssertionError: Wrong values for pred. [[0. 0. 0.]] != [[1.0, 0.0, 1.0]]**