when I used the new JO api to submit my notebook, it can bug free run, but once I submited it, I got Notebook Threw Exception, the following is my code, did you have the same issue?
\n**** code ****
\nlimits = {'0-4':(1,4), '5-12':(4,14), '13-22':(14,19)}\ncount = 0\nfor (test,sample_submission) in iter_test:\n grps = ['0-4', '5-12', '13-22']\n total_test = []\n for grp in grps:\n a,b = limits[grp]\n sub_test = test[test['level_group']==grp]\n session_ids = sub_test.session_id.unique()\n # ------------------- level 0-4 ---------------------------------\n if a == 1:\n FEATURES = FEATURES1\n sub_test = (pl.from_pandas(sub_test)\n .drop([\"fullscreen\", \"hq\", \"music\"])\n .with_columns(columns))\n sub_test = feature_engineer_pl(sub_test, grp, use_extra=True, feature_suffix='')\n sub_test = sub_test[FEATURES]\n # ------------------- level 5-12 ---------------------------------\n elif a == 4:\n FEATURES = FEATURES2\n sub_test = (pl.from_pandas(sub_test)\n .drop([\"fullscreen\", \"hq\", \"music\"])\n .with_columns(columns))\n sub_test = feature_engineer_pl(sub_test, grp, use_extra=True, feature_suffix='')\n sub_test = sub_test[FEATURES]\n # ------------------- level 13-22 --------------------------------- \n elif a == 14:\n FEATURES = FEATURES3\n sub_test = (pl.from_pandas(sub_test)\n .drop([\"fullscreen\", \"hq\", \"music\"])\n .with_columns(columns))\n sub_test = feature_engineer_pl(sub_test, grp, use_extra=True, feature_suffix='')\n sub_test = sub_test[FEATURES]\n for t in range(a,b):\n clf = xgb_dict[t]\n mask = sample_submission.session_id.apply(lambda x:x.split('_')[1]).isin([f'q{t}']) & sample_submission.session_id.apply(lambda x:int(x.split('_')[0])).isin(session_ids)\n p = clf.predict_proba(sub_test.astype('float32'))[:,1] \n sample_submission.loc[mask,'correct'] = np.where(p>0.625,1,0) \n env.predict(sample_submission)\nwhen I used the new JO api to submit my notebook, it can bug free run, but once I submited it, I got Notebook Threw Exception, the following is my code, did you have the same issue?
\n**** code ****
\nlimits = {'0-4':(1,4), '5-12':(4,14), '13-22':(14,19)}\ncount = 0\nfor (test,sample_submission) in iter_test:\n grps = ['0-4', '5-12', '13-22']\n total_test = []\n for grp in grps:\n a,b = limits[grp]\n sub_test = test[test['level_group']==grp]\n session_ids = sub_test.session_id.unique()\n # ------------------- level 0-4 ---------------------------------\n if a == 1:\n FEATURES = FEATURES1\n sub_test = (pl.from_pandas(sub_test)\n .drop([\"fullscreen\", \"hq\", \"music\"])\n .with_columns(columns))\n sub_test = feature_engineer_pl(sub_test, grp, use_extra=True, feature_suffix='')\n sub_test = sub_test[FEATURES]\n # ------------------- level 5-12 ---------------------------------\n elif a == 4:\n FEATURES = FEATURES2\n sub_test = (pl.from_pandas(sub_test)\n .drop([\"fullscreen\", \"hq\", \"music\"])\n .with_columns(columns))\n sub_test = feature_engineer_pl(sub_test, grp, use_extra=True, feature_suffix='')\n sub_test = sub_test[FEATURES]\n # ------------------- level 13-22 --------------------------------- \n elif a == 14:\n FEATURES = FEATURES3\n sub_test = (pl.from_pandas(sub_test)\n .drop([\"fullscreen\", \"hq\", \"music\"])\n .with_columns(columns))\n sub_test = feature_engineer_pl(sub_test, grp, use_extra=True, feature_suffix='')\n sub_test = sub_test[FEATURES]\n for t in range(a,b):\n clf = xgb_dict[t]\n mask = sample_submission.session_id.apply(lambda x:x.split('_')[1]).isin([f'q{t}']) & sample_submission.session_id.apply(lambda x:int(x.split('_')[0])).isin(session_ids)\n p = clf.predict_proba(sub_test.astype('float32'))[:,1] \n sample_submission.loc[mask,'correct'] = np.where(p>0.625,1,0) \n env.predict(sample_submission)\nSame here , maybe lot of bugs were introduced in the last update
", "rawMarkdown": "Same here , maybe lot of bugs were introduced in the last update ", "votes": 1 }, { "id": 2190863, "postDate": "2023-03-21T14:37:06.410Z", "content": "@leehann, the Kaggle team have been quiet for hours. I would rather wait until they answer all the questions raised here before making any more submission.
", "rawMarkdown": "@leehann, the Kaggle team have been quiet for hours. I would rather wait until they answer all the questions raised [here](https://www.kaggle.com/competitions/predict-student-performance-from-game-play/discussion/396202#2190090) before making any more submission." }, { "id": 2190517, "postDate": "2023-03-21T09:42:09.050Z", "content": "can Kaggle staff, help us ?
", "rawMarkdown": "can Kaggle staff, help us ?" }, { "id": 2190507, "postDate": "2023-03-21T09:23:38.277Z", "content": "Same issue here, already submit three notebooks but all fail!
", "rawMarkdown": "Same issue here, already submit three notebooks but all fail! " }, { "id": 2190542, "postDate": "2023-03-21T10:30:21.050Z", "rawMarkdown": "", "votes": 1, "isDeleted": true } ], "comments": [ { "id": 2190453, "author_name": "Reacher", "author_url": "", "post_date": "2023-03-21T08:45:02.457000", "content": "Same here , maybe lot of bugs were introduced in the last update
", "votes": 1, "replies": [] }, { "id": 2190863, "author_name": "YaGana Sheriff-Hussaini", "author_url": "", "post_date": "2023-03-21T14:37:06.410000", "content": "@leehann, the Kaggle team have been quiet for hours. I would rather wait until they answer all the questions raised here before making any more submission.
", "votes": 0, "replies": [] }, { "id": 2190517, "author_name": "HZM", "author_url": "", "post_date": "2023-03-21T09:42:09.050000", "content": "can Kaggle staff, help us ?
", "votes": 0, "replies": [] }, { "id": 2190507, "author_name": "AbaoJiang", "author_url": "", "post_date": "2023-03-21T09:23:38.277000", "content": "Same issue here, already submit three notebooks but all fail!
", "votes": 0, "replies": [] }, { "id": 2190542, "author_name": "", "author_url": "", "post_date": "2023-03-21T10:30:21.050000", "content": "", "votes": 1, "replies": [] } ], "raw_markdown_by_id": { "2190438": "when I used the new JO api to submit my notebook, it can bug free run, but once I submited it, I got Notebook Threw Exception, the following is my code, did you have the same issue?\n\n**** code ****\n\n````\nlimits = {'0-4':(1,4), '5-12':(4,14), '13-22':(14,19)}\ncount = 0\nfor (test,sample_submission) in iter_test:\n grps = ['0-4', '5-12', '13-22']\n total_test = []\n for grp in grps:\n a,b = limits[grp]\n sub_test = test[test['level_group']==grp]\n session_ids = sub_test.session_id.unique()\n # ------------------- level 0-4 ---------------------------------\n if a == 1:\n FEATURES = FEATURES1\n sub_test = (pl.from_pandas(sub_test)\n .drop([\"fullscreen\", \"hq\", \"music\"])\n .with_columns(columns))\n sub_test = feature_engineer_pl(sub_test, grp, use_extra=True, feature_suffix='')\n sub_test = sub_test[FEATURES]\n # ------------------- level 5-12 ---------------------------------\n elif a == 4:\n FEATURES = FEATURES2\n sub_test = (pl.from_pandas(sub_test)\n .drop([\"fullscreen\", \"hq\", \"music\"])\n .with_columns(columns))\n sub_test = feature_engineer_pl(sub_test, grp, use_extra=True, feature_suffix='')\n sub_test = sub_test[FEATURES]\n # ------------------- level 13-22 --------------------------------- \n elif a == 14:\n FEATURES = FEATURES3\n sub_test = (pl.from_pandas(sub_test)\n .drop([\"fullscreen\", \"hq\", \"music\"])\n .with_columns(columns))\n sub_test = feature_engineer_pl(sub_test, grp, use_extra=True, feature_suffix='')\n sub_test = sub_test[FEATURES]\n for t in range(a,b):\n clf = xgb_dict[t]\n mask = sample_submission.session_id.apply(lambda x:x.split('_')[1]).isin([f'q{t}']) & sample_submission.session_id.apply(lambda x:int(x.split('_')[0])).isin(session_ids)\n p = clf.predict_proba(sub_test.astype('float32'))[:,1] \n sample_submission.loc[mask,'correct'] = np.where(p>0.625,1,0) \n env.predict(sample_submission)\n\n````\n", "2190453": "Same here , maybe lot of bugs were introduced in the last update ", "2190863": "@leehann, the Kaggle team have been quiet for hours. I would rather wait until they answer all the questions raised [here](https://www.kaggle.com/competitions/predict-student-performance-from-game-play/discussion/396202#2190090) before making any more submission.", "2190517": "can Kaggle staff, help us ?", "2190507": "Same issue here, already submit three notebooks but all fail! ", "2190542": "" } }