Hi all,
\nnew to kaggle, I've been trying to submit my notebook for well over a week but I keep on running into an exception error. On the test dataset it works fine, no errors, the samplesubmission.csv is created as expected, when I submit it always throwback an error:
\ns / [==============================] - ETA: 0s\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b/ [==============================] - 0s 26ms/step\ns /opt/conda/lib/python3/site-packages/traitlets/traitlets.py:: FutureWarning: --Exporter.preprocessors=[] containers deprecated traitlets . You can `--Exporter.preprocessors item` ... multiple times to add items to a .\ns FutureWarning,\ns [NbConvertApp] Converting notebook __notebook__.ipynb to notebook\ns [NbConvertApp] Writing to __notebook__.ipynb\ns /opt/conda/lib/python3/site-packages/traitlets/traitlets.py:: FutureWarning: --Exporter.preprocessors=[] containers deprecated traitlets . You can `--Exporter.preprocessors item` ... multiple times to add items to a .\ns FutureWarning,\ns [NbConvertApp] Converting notebook __notebook__.ipynb to html\ns [NbConvertApp] Writing to __results__.html\nWhat does it mean? This is very difficult to debug. This is my submission loop:
\nlimits = {:(,), :(,), :(,)}\n\n (test, sample_submission) iter_test:\n\n \n df = concat_features(test)\n\n \n grp = test.level_group.values[]\n a,b = limits[grp]\n t (a,b):\n clf = MODELS[]\n p = clf.predict(df)[][]\n mask = sample_submission.session_id..contains()\n sample_submission.loc[mask,] = ( p > )\n\n env.predict(sample_submission)\nHi all,
\nnew to kaggle, I've been trying to submit my notebook for well over a week but I keep on running into an exception error. On the test dataset it works fine, no errors, the samplesubmission.csv is created as expected, when I submit it always throwback an error:
\ns / [==============================] - ETA: 0s\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b/ [==============================] - 0s 26ms/step\ns /opt/conda/lib/python3/site-packages/traitlets/traitlets.py:: FutureWarning: --Exporter.preprocessors=[] containers deprecated traitlets . You can `--Exporter.preprocessors item` ... multiple times to add items to a .\ns FutureWarning,\ns [NbConvertApp] Converting notebook __notebook__.ipynb to notebook\ns [NbConvertApp] Writing to __notebook__.ipynb\ns /opt/conda/lib/python3/site-packages/traitlets/traitlets.py:: FutureWarning: --Exporter.preprocessors=[] containers deprecated traitlets . You can `--Exporter.preprocessors item` ... multiple times to add items to a .\ns FutureWarning,\ns [NbConvertApp] Converting notebook __notebook__.ipynb to html\ns [NbConvertApp] Writing to __results__.html\nWhat does it mean? This is very difficult to debug. This is my submission loop:
\nlimits = {:(,), :(,), :(,)}\n\n (test, sample_submission) iter_test:\n\n \n df = concat_features(test)\n\n \n grp = test.level_group.values[]\n a,b = limits[grp]\n t (a,b):\n clf = MODELS[]\n p = clf.predict(df)[][]\n mask = sample_submission.session_id..contains()\n sample_submission.loc[mask,] = ( p > )\n\n env.predict(sample_submission)\nHi @joseviteri , if it works on the test dataset, it may come from your concat_features function. It may run into something that didn't happen in the test dataset. One way to test that is to simplify your concat_features to the minimum and add features until it errors again.
", "rawMarkdown": "Hi @joseviteri , if it works on the test dataset, it may come from your concat_features function. It may run into something that didn't happen in the test dataset. One way to test that is to simplify your concat_features to the minimum and add features until it errors again.", "votes": null }, { "id": "2241535", "postDate": "05/01/2023 15:29:13", "content": "This is just warning. And in fact, it is too difficult to inspect the bug for the limited code you published.
", "rawMarkdown": "This is just warning. And in fact, it is too difficult to inspect the bug for the limited code you published.", "votes": null }, { "id": "2241639", "postDate": "05/01/2023 17:07:19", "content": " ():\n dfs = []\n temp = df.groupby(by = [])[].() - df.groupby(by = [])[].()\n temp = temp.rename()\n dfs.append(temp)\n dfs = dfs.fillna(-)\n dfs = dfs.reset_index()\n dfs = dfs.set_index()\n\n dfs\n@littlstar123 nothing special as you can see, the concat function is only looking at elapsed time.
", "rawMarkdown": "```python\ndef concat_features(df):\n dfs = []\n temp = df.groupby(by = [\"session_id\"])[\"elapsed_time\"].max() - df.groupby(by = [\"session_id\"])[\"elapsed_time\"].min()\n temp = temp.rename(\"elapsed_duration\")\n dfs.append(temp)\n dfs = dfs.fillna(-1)\n dfs = dfs.reset_index()\n dfs = dfs.set_index('session_id')\n \n return dfs\n```\n@littlstar123 nothing special as you can see, the concat function is only looking at elapsed time.", "votes": null }, { "id": "2241640", "postDate": "05/01/2023 17:08:02", "content": "Thanks for the guidance! I'll try it, at the current status I'm only viewing the elapsed_time feature.
", "rawMarkdown": "Thanks for the guidance! I'll try it, at the current status I'm only viewing the elapsed_time feature.", "votes": null } ], "comments": [ { "id": 2241241, "author_name": "gehallak", "author_url": "", "post_date": "05/01/2023 10:23:14", "content": "Hi @joseviteri , if it works on the test dataset, it may come from your concat_features function. It may run into something that didn't happen in the test dataset. One way to test that is to simplify your concat_features to the minimum and add features until it errors again.
", "votes": null, "replies": [ { "id": 2241640, "author_name": "joseviteri", "author_url": "", "post_date": "05/01/2023 17:08:02", "content": "Thanks for the guidance! I'll try it, at the current status I'm only viewing the elapsed_time feature.
", "votes": null, "replies": [] } ] }, { "id": 2241535, "author_name": "littlstar123", "author_url": "", "post_date": "05/01/2023 15:29:13", "content": "This is just warning. And in fact, it is too difficult to inspect the bug for the limited code you published.
", "votes": null, "replies": [ { "id": 2241639, "author_name": "joseviteri", "author_url": "", "post_date": "05/01/2023 17:07:19", "content": " ():\n dfs = []\n temp = df.groupby(by = [])[].() - df.groupby(by = [])[].()\n temp = temp.rename()\n dfs.append(temp)\n dfs = dfs.fillna(-)\n dfs = dfs.reset_index()\n dfs = dfs.set_index()\n\n dfs\n@littlstar123 nothing special as you can see, the concat function is only looking at elapsed time.
", "votes": null, "replies": [] } ] } ], "raw_markdown_by_id": { "2239518": "Hi all, \n\nnew to kaggle, I've been trying to submit my notebook for well over a week but I keep on running into an exception error. On the test dataset it works fine, no errors, the samplesubmission.csv is created as expected, when I submit it always throwback an error:\n\n```python\n235.5s\t201\t1/1 [==============================] - ETA: 0s\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b1/1 [==============================] - 0s 26ms/step\n241.2s\t202\t/opt/conda/lib/python3.7/site-packages/traitlets/traitlets.py:2935: FutureWarning: --Exporter.preprocessors=[\"remove_papermill_header.RemovePapermillHeader\"] for containers is deprecated in traitlets 5.0. You can pass `--Exporter.preprocessors item` ... multiple times to add items to a list.\n241.2s\t203\t FutureWarning,\n241.2s\t204\t[NbConvertApp] Converting notebook __notebook__.ipynb to notebook\n241.9s\t205\t[NbConvertApp] Writing 98100 bytes to __notebook__.ipynb\n243.6s\t206\t/opt/conda/lib/python3.7/site-packages/traitlets/traitlets.py:2935: FutureWarning: --Exporter.preprocessors=[\"nbconvert.preprocessors.ExtractOutputPreprocessor\"] for containers is deprecated in traitlets 5.0. You can pass `--Exporter.preprocessors item` ... multiple times to add items to a list.\n243.6s\t207\t FutureWarning,\n243.6s\t208\t[NbConvertApp] Converting notebook __notebook__.ipynb to html\n244.8s\t209\t[NbConvertApp] Writing 379881 bytes to __results__.html\n```\n\nWhat does it mean? This is very difficult to debug. This is my submission loop:\n\n```python\nlimits = {'0-4':(1,4), '5-12':(4,14), '13-22':(14,19)}\n\nfor (test, sample_submission) in iter_test:\n \n # FEATURE ENGINEER TEST DATA\n df = concat_features(test)\n \n # INFER TEST DATA\n grp = test.level_group.values[0]\n a,b = limits[grp]\n for t in range(a,b):\n clf = MODELS[f\"question {t} model\"]\n p = clf.predict(df)[0][0]\n mask = sample_submission.session_id.str.contains(f'q{t}')\n sample_submission.loc[mask,'correct'] = int( p > 0.65 )\n \n env.predict(sample_submission)\n```\n\n@philculliton", "2241241": "Hi @joseviteri , if it works on the test dataset, it may come from your concat_features function. It may run into something that didn't happen in the test dataset. One way to test that is to simplify your concat_features to the minimum and add features until it errors again.", "2241535": "This is just warning. And in fact, it is too difficult to inspect the bug for the limited code you published.", "2241639": "```python\ndef concat_features(df):\n dfs = []\n temp = df.groupby(by = [\"session_id\"])[\"elapsed_time\"].max() - df.groupby(by = [\"session_id\"])[\"elapsed_time\"].min()\n temp = temp.rename(\"elapsed_duration\")\n dfs.append(temp)\n dfs = dfs.fillna(-1)\n dfs = dfs.reset_index()\n dfs = dfs.set_index('session_id')\n \n return dfs\n```\n@littlstar123 nothing special as you can see, the concat function is only looking at elapsed time.", "2241640": "Thanks for the guidance! I'll try it, at the current status I'm only viewing the elapsed_time feature." }, "source": "meta" }