Assignments not getting submitted


As per directed by support team , i am facing issue for below course in MLops specialization

" Machine Learning Data Lifecycle in Production "

My assignments are not getting summited for week 2 and week 3 , although my code output results are matching with expected result .

Please help i already completed rest 3 courses and this course is cloaked at 97% due to this bug.

i am attaching all required code files and snips here for reference

C2W3_Assignment.ipynb (486.7 KB)
C2_W2_Lab_2_Feature_Engineering_Pipeline.ipynb (30.6 KB)

Please do not post your code on the forum. That’s not allowed by the Code of Conduct.

I will move this thread to the appropriate course forum. Hopefully a mentor for that course will reply.

Hi @Prasad_Sonar ,

In your C2_W3_assignment, it appears you tried to edit non-graded code before passing the assignment. This could affect the auto grader code on Coursera and the notebook. Important Note: Please only do this when you’ve already passed the assignment to avoid problems with the autograder. (i.e, after submitting the assignment successfully

  1. On the notebook’s menu, click “View” > “Cell Toolbar” > “Edit Metadata”
  2. Hit the “Edit Metadata” button next to the code cell which you want to lock/unlock
  3. Set the attribute value for “editable” to:
  • “true” if you want to unlock it
  • “false” if you want to lock it
  1. On the notebook’s menu, click “View” > “Cell Toolbar” > “None”

Also, in the Excercise 7, you have duplicated graded cells ### START CODE HERE ### which might also affect the autograder

Please check notebook metadata and refresh the workspace . Also, 1. Remove any cells you may have manually added (even outside the graded cells), restart the notebook, and check if all cells still run.

See more common troubleshooting tips for Courses 2 Assignment here

I tried to retrospect the issue by following steps , but still it is showing zero grades

Please send me the notebook that you submitted

Sure ,

Please see attachments

{moderator edit: code removed}

Hi This one is latest one i what i just tried . apart from that i am facing type error in exercise 6 for

“TypeError: bucketize() got an unexpected keyword argument ‘always_return_num_quantiles’”

i am attaching notebook. i still got zero grade
{moderator edit: code removed}

Hi @Prasad_Sonar,
I checked your notebook. Here’s what I’ve found.

  1. In C2W2 Assignment:
    Exercise 1 is missing #grader-required-cell at several exercises (1, 2, 3, 4, 5).
    At exercise 5, you don’t need to import every module again. Please don’t add any new cells and only edit within ### START CODE HERE
    At exercise 6, remove always_return_num_quantiles=False as that option doesn’t exist in tft.bucketize(). For traffic_volume, there’s no such _fill_in_missing module. You can use normal tf.cast(). The outputs also have IndexError and TypeError. Please double check tft.mean(tf.cast(input, dtype))
    For exercise 7, I believe you accidentally created some new cells and forget to fill out exercise 7. There’s also an extra cell with # grade-up-to-here. This may be why your assignment is not getting graded properly.

  2. In C2W3 Assignment:
    Missing #grader-required-cell at several exercises. There are also extra cells and there’s a duplicate metadata ### START CODE HERE ###

    Also, you used ImporterNode instead of the suggested functionImportSchemaGen.
    The variable of user_schema_importer.outputs is incorrect. The default should have been
    as it’s written for in the notebook['schema'])

In Exercise 8, when stats_options.schema is set, it will be used instead of the schema channel input. Since you add both schema and stats_options, an error will be raised. See more. In excercise 11, you used the original schema artifact instead of the curated schema (user_schema_importer)

Follow these steps to grab the fresh notebook. Only put your solutions in between the ### START CODE HERE and ### END CODE HERE code comments, and also refrain from adding any new cells.

Please be mindful that if you delete/add/edit any cell that has this # tag during your work, you may mistakenly delete important metadata that will be used for the submission and grading process at the end.

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