Check implementation. If you see many functions being marked as incorrect, try to trace back your steps & identify if there is an incorrect function that is being used in other steps. This dependency may be the cause of the errors.
Code Cell UNQ_C1: Function āconv_blockā is correct.
Code Cell UNQ_C2: Function āupsampling_blockā is correct.
Code Cell UNQ_C3: Function āunet_modelā is incorrect. Check implementation.
If you see many functions being marked as incorrect, try to trace back your steps & identify if there is an incorrect function that is being used in other steps.
This dependency may be the cause of the errors.
Please click on my name to start a private message. Then, attach your notebook as a .ipynb file. Please note that mentors cannot access your Coursera Jupyter workspace, so sending the notebook in a .ipynb format is essential.
The classic way this can happen is if you āhard-codeā the parameters to be the default values, instead of using the actual values passed. E.g. using 23 instead of n_classes or likewise for n_filters.
@anas_azeez
I got full score upon submitting the notebook you gave me via direct message. Itās possible that you didnāt save the changes or something odd did happen with the grader.
Upon refreshing my workspace and pasting your code only where required between ### START CODE HERE and ### END CODE HERE for submission, the grader gave full score as well.