I have an error that says ‘wrong values W1 error’, but the result are totally same with the expected output.

Oviously, I didn’t use -= operand in previous function definition. I used ‘W1 = W1 - (learning_rate * dW1)’

What is the problem?

##
Cost after iteration 0: 0.692739

Cost after iteration 1000: 0.000218

Cost after iteration 2000: 0.000107

Cost after iteration 3000: 0.000071

Cost after iteration 4000: 0.000053

Cost after iteration 5000: 0.000042

Cost after iteration 6000: 0.000035

Cost after iteration 7000: 0.000030

Cost after iteration 8000: 0.000026

Cost after iteration 9000: 0.000023

W1 = [[-0.65848169 1.21866811]

[-0.76204273 1.39377573]

[ 0.5792005 -1.10397703]

[ 0.76773391 -1.41477129]]

b1 = [[ 0.287592 ]

[ 0.3511264 ]

[-0.2431246 ]

[-0.35772805]]

W2 = [[-2.45566237 -3.27042274 2.00784958 3.36773273]]

b2 = [[0.20459656]]

AssertionError Traceback (most recent call last)

in

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

8

----> 9 nn_model_test(nn_model)

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

273 assert output[“b2”].shape == expected_output[“b2”].shape, f"Wrong shape for b2."

274

→ 275 assert np.allclose(output[“W1”], expected_output[“W1”]), “Wrong values for W1”

276 assert np.allclose(output[“b1”], expected_output[“b1”]), “Wrong values for b1”

277 assert np.allclose(output[“W2”], expected_output[“W2”]), “Wrong values for W2”

AssertionError: Wrong values for W1

Expected output

Cost after iteration 0: 0.692739

Cost after iteration 1000: 0.000218

Cost after iteration 2000: 0.000107

…

Cost after iteration 8000: 0.000026

Cost after iteration 9000: 0.000023

W1 = [[-0.65848169 1.21866811]

[-0.76204273 1.39377573]

[ 0.5792005 -1.10397703]

[ 0.76773391 -1.41477129]]

b1 = [[ 0.287592 ]

[ 0.3511264 ]

[-0.2431246 ]

[-0.35772805]]

W2 = [[-2.45566237 -3.27042274 2.00784958 3.36773273]]

b2 = [[0.20459656]]