Hi, I am facing a error in The Planar Data Classification assignment of week 3 of Neural networks and Deep Learning. So, in the nn_model function I am calling all the functions correctly and with right parameters and the test cases of above functions have passed successfully, still whenever I am running nn_model_test(nn_model)

Wrong Weight value error.

Failing output:

Cost after iteration 0: 0.693395

Cost after iteration 1000: 0.000217

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: 0.000024

W1 = [[-0.73679287 -1.36621711]

[-0.62039407 -1.13347599]

[-0.71454509 -1.31939197]

[ 0.74580119 1.37837548]]

b1 = [[ 0.01230887]

[-0.00176212]

[ 0.00896606]

[-0.01164917]]

W2 = [[-3.04892822 -2.13993848 -2.84526122 3.11015916]]

b2 = [[0.0041659]]

AssertionError Traceback (most recent call last)

in

----> 1 nn_model_test(nn_model)

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

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

293

→ 294 assert np.allclose(output[“W1”], expected_output[“W1”]), “Wrong values for W1”

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

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

AssertionError: Wrong values for W1