Assertion error running model function

[12_Zahid]

I have following error, and i think the code is write.

AssertionError Traceback (most recent call last)
in
1 from public_tests import *
2
----> 3 model_test(model)

~/work/release/W2A2/public_tests.py in model_test(target)
121 assert type(d[‘w’]) == np.ndarray, f"Wrong type for d[‘w’]. {type(d[‘w’])} != np.ndarray"
122 assert d[‘w’].shape == (X.shape[0], 1), f"Wrong shape for d[‘w’]. {d[‘w’].shape} != {(X.shape[0], 1)}"
→ 123 assert np.allclose(d[‘w’], expected_output[‘w’]), f"Wrong values for d[‘w’]. {d[‘w’]} != {expected_output[‘w’]}"
124
125 assert np.allclose(d[‘b’], expected_output[‘b’]), f"Wrong values for d[‘b’]. {d[‘b’]} != {expected_output[‘b’]}"

AssertionError: Wrong values for d[‘w’]. [[ 0.14449502]
[-0.1429235 ]
[-0.19867517]
[ 0.21265053]] != [[ 0.08639757]
[-0.08231268]
[-0.11798927]
[ 0.12866053]]

[paulinpaloalto]

If all your previous functions passed their tests, then the bug is in the model logic. One common problem is either “hard-coding” the learning rate and number of iterations when you call optimize from model or just omitting those “optional” arguments. If you do the latter, then you end up with the default values declared in the definition of optimize, but that’s wrong if different values are passed in at the model level.

[12_Zahid]

thank you @paulinpaloalto I found the solution