Week 3 Exercise 8 Wrong Value of W1

Cost Value is not changing. I have checked for hard code but not found any.
None of the values of W1, W2, b1 etc matching
please help

Cost after iteration 0: 0.689099
Cost after iteration 1000: 0.689099
Cost after iteration 2000: 0.689099
Cost after iteration 3000: 0.689099
Cost after iteration 4000: 0.689099
Cost after iteration 5000: 0.689099
Cost after iteration 6000: 0.689099
Cost after iteration 7000: 0.689099
Cost after iteration 8000: 0.689099
Cost after iteration 9000: 0.689099
W1 = [[-0.00643025  0.01936718]
 [-0.02410458  0.03978052]
 [-0.01653973 -0.02096177]
 [ 0.01046864 -0.05990141]]
b1 = [[-1.02420756e-06]
 [ 1.27373948e-05]
 [ 8.32996807e-07]
W2 = [[-0.01041081 -0.04463285  0.01758031  0.04747113]]
b2 = [[0.00010457]]
AssertionError                            Traceback (most recent call last)
<ipython-input-55-6d3d4c22ad68> in <module>
      7 print("b2 = " + str(parameters["b2"]))
----> 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."
--> 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

Inside the loop in nn_model, are you calling update_parameters after computing gradients?

Yes, I am calling update_parameters after computing gradients.

Are you calling optimize inside the model function?

There is no optimize function in the Exercise

Sorry. Wrong window. Please message me your code. Click on my name and Message to attach your code.

The problem was fixed. There was a minor bug wrt assignment.

Facing the same issue at my end. Tried many different things, but all steps above seem to work. It simply fails at the nn_model with the attached error.

Welcome to the community.

If none of the above solves your case, it is better to create a new thread.
In you case, bias is always 0. So, most likely update_parameters() is not called or failed.
This should be the starting point. Please double check.

Created a new thread and was able to resolve it after a few suggestions from Paul. Thanks @anon57530071 for responding!