A problem with the Programming Assignment: Transformers Architecture with TensorFlow

Course Q&A Deep Learning Specialization Sequence Models
1

Having a problem with the Programming Assignment: Transformers Architecture with TensorFlow. This project is in week four from the Sequence Models DeepLearning.AI class.
Although I get positive indication of the successful completion of every other exercise in the Transformers Architecture with TensorFlow, I get a zero grade for the entire unit. This is preventing me from finishing the class Sequence Models DeepLearning.AI class, as I have successfully completed every other lab and quiz in the four-week Sequence Models program. I did try to download a fresh copy of the week 4 transformers lab, but I consistently get the same error results for the one section on transformer networks. (see below)

AssertionError Traceback (most recent call last)
in
1 # UNIT TEST
----> 2 scaled_dot_product_attention_test(scaled_dot_product_attention)

~/work/W4A1/public_tests.py in scaled_dot_product_attention_test(target)
73 assert np.allclose(weights, [[0.30719590187072754, 0.5064803957939148, 0.0, 0.18632373213768005],
74 [0.3836517333984375, 0.3836517333984375, 0.0, 0.2326965481042862],
—> 75 [0.3836517333984375, 0.3836517333984375, 0.0, 0.2326965481042862]]), “Wrong masked weights”
76 assert np.allclose(attention, [[0.6928040981292725, 0.18632373213768005],
77 [0.6163482666015625, 0.2326965481042862],

AssertionError: Wrong masked weights

Here is a link to the lab.

Can anyone help to resolve this time sensitive matter?

2

@fred_feisullin

as this is your first post, I have moved your query to the category as per you described from which specialisation and course it is. From next time, please choose right category to get response from course related mentors.

Also just a heads sharing link to graded assignment, sharing codes correct or incorrect, sharing assignment notebook is against community guidelines. So refrain from posting grade cell codes.

Keep Learning!

Also refer below post comment to do the correct to your code

regards
DP