C2W1 Assignment - grader output showed error

I’ve tried submitted 3 times the assignment.

For result on Visualize Training Statistics:
1st time :
We encountered the following warnings when grading this part:

  • Grader timed out while grading your submission. Please try submitting an optimized solution. If you think your solution is correct, please visit the Discussion forum to see if your peers are experiencing similar errors. If the issue isn’t resolved in 24 hours, please reach out to Coursera through our Help Center.

2nd time and 3rd time:
There was a problem grading your submission. Check stderr for more details.

For result on Compare Training and Evaluation Statistics:
1st and 2nd time:
Failed rhs_name correctly set.
Expected:
True,
but got:
False.

Failed lhs_name correctly set.
Expected:
True,
but got:
False.

3rd time:
There was a problem grading your submission. Check stderr for more details.

I got all answers correct matching the reference given with no errors when running cell by cell till the end of the notebook but yet still couldn’t get full marks. Submitted the same codes for 3 times and each round it returned somewhat different grader output remarks… Any advise on this?

2 Likes

Hi SLin! Can you double check if you used the name provided in the hint for rhs_statistics in that exercise (i.e. TRAIN_DATASET)? That happened to me before but I found out that I had a typo in that section. If it’s correct and you’re still getting errors, please check your inbox. We may need a copy of your notebook to see if there is an issue with the grader. Thanks!

2 Likes

Hi Chris, Thanks for your reply. I used the suggested name as lhs_name='EVAL_DATASET', rhs_name='TRAIN_DATASET' but still can’t get through with it at the grader stage. Have replied you with a link to my notebook. Thanks!

1 Like

For reference to other learners who may run into the same issue: There is nothing wrong with the solutions. The issue is with the notebook metadata (it was missing). Problem is resolved with these steps:

  1. Rename your current notebook from within the Coursera jupyter workspace. Any filename will do (e.g. C2W1_Assignment_1.ipynb ).

  2. Click the Help button at the upper right.

Screen Shot 2021-05-19 at 10.00.57 PM

  1. Click Get latest version .

  1. This should grab you a fresh copy of the notebook named C2W1_Assignment.ipynb . Please copy your solutions into this new notebook and click Submit Assignment again. Hopefully, you’ll get the correct grade then.
8 Likes

Thank You Chris! This technique helped to resolve the issue.

2 Likes

Hi @pradyumna @SLin ! Please check your inbox. Thank you!

1 Like

Thanks chris for solving problem.
I got raise score from 53 to 63.
That method is helped to “Ex7. Check anomalies in the serving set”, but still under-scored.

I think my solution of Ex1 need to mofify.
train_stats = tfdv.generate_statistics_from_dataframe (train_df, stats_options=tfdv.​StatsOptions (), n_jobs=1)

1 Like

Glad to hear that! If it helps, you can also use the ungraded labs before the assignments as reference for most of the commands you’ll be running. If you get stuck and you cant find any similar threads, you can post a new topic with the details so mentors can assist. Thank you!

1 Like
  1. I retry a few times. There is no change at 63 points.

-. my solution of Ex1 :
train_stats = tfdv.generate_statistics_from_dataframe (train_df, stats_options=tfdv.​StatsOptions (), n_jobs=1)

Number of features used: 50
Number of examples used: 71236
First feature: encounter_id
Last feature: readmitted

Expected Output:
Number of features used: 48
Number of examples used: 71236
First feature: race
Last feature: readmitted

If my solution of Ex1 is wrong to be considered 2).
2) When solving the first problem, it seems that the metadata was saved in a twisted state. Can’t it be set to a completely initial state of education?

1 Like

Hi @jschoi , it could be due to the stats_options=tfdv.​StatsOptions () isn’t right. You can either just pass in the stats_options that has already been defined earlier or just add feature_whitelist=approved_cols as parameter into tfdv.​StatsOptions ()

1 Like

Hi @ SLin , thanks for solving that problem.

Exercise 4: Compare Training and Evaluation Statistics
It’s the same as the expected result, but I don’t understand why it’s 3/10.

3/10 Score: 3 of 10

Hide grader output
Number of features: 48
Number of examples: 15265
First feature: race
Last feature: readmitted

Expected Output:

Number of features: 48
Number of examples: 15265
First feature: race
Last feature: readmitted
1 Like

Thanks!

Updating the lab to the latest version fixed the issue for me.

/Mattias

3 Likes

Thanks Chris, It helped me a lot.

3 Likes

Hi Mahendra! Welcome to Discourse! Glad you found the post useful. By any chance, did you delete or add any cell (even outside the graded exercise cells) in your old notebook when you were getting the grader error? We’re trying to troubleshoot this bug and this info will definitely help. Thank you!

1 Like

Hi Mattias! Welcome to Discourse! Glad you found the post useful. By any chance, did you delete or add any cell (even outside the graded exercise cells) in your old notebook when you were getting the grader error? We’re trying to troubleshoot this bug and this info will definitely help. Thank you!

1 Like

Hi Chris,
Sorry for the late response, but as far as I can remember I only upgraded the notebook, and it worked after that.

1 Like

Exercise 7 C2W1

Response is no anomalies after using defined statsoptions

1 Like

Great! It worked pretty good!

2 Likes

Hi I have noted all the steps and copy all the existing solutions to the C2W1_Assignment.ipynb.` However, still grader output showed an error. Can you assist in this?

1 Like

Following error
There was a problem compiling the code from your notebook. Details:
‘NoneType’ object is not iterable

1 Like