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The dataset generation failed because of a cast error
Error code: DatasetGenerationCastError Exception: DatasetGenerationCastError Message: An error occurred while generating the dataset All the data files must have the same columns, but at some point there are 1 missing columns ({'label'}) This happened while the csv dataset builder was generating data using hf://datasets/VedantPadwal/mnist/test.csv (at revision 23061c5172509304b9891b3ac36a4ea477809dbe) Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations) Traceback: Traceback (most recent call last): File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 2011, in _prepare_split_single writer.write_table(table) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 585, in write_table pa_table = table_cast(pa_table, self._schema) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2302, in table_cast return cast_table_to_schema(table, schema) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2256, in cast_table_to_schema raise CastError( datasets.table.CastError: Couldn't cast pixel0: int64 pixel1: int64 pixel2: int64 pixel3: int64 pixel4: int64 pixel5: int64 pixel6: int64 pixel7: int64 pixel8: int64 pixel9: int64 pixel10: int64 pixel11: int64 pixel12: int64 pixel13: int64 pixel14: int64 pixel15: int64 pixel16: int64 pixel17: int64 pixel18: int64 pixel19: int64 pixel20: int64 pixel21: int64 pixel22: int64 pixel23: int64 pixel24: int64 pixel25: int64 pixel26: int64 pixel27: int64 pixel28: int64 pixel29: int64 pixel30: int64 pixel31: int64 pixel32: int64 pixel33: int64 pixel34: int64 pixel35: int64 pixel36: int64 pixel37: int64 pixel38: int64 pixel39: int64 pixel40: int64 pixel41: int64 pixel42: int64 pixel43: int64 pixel44: int64 pixel45: int64 pixel46: int64 pixel47: int64 pixel48: int64 pixel49: int64 pixel50: int64 pixel51: int64 pixel52: int64 pixel53: int64 pixel54: int64 pixel55: int64 pixel56: int64 pixel57: int64 pixel58: int64 pixel59: int64 pixel60: int64 pixel61: int64 pixel62: int64 pixel63: int64 pixel64: int64 pixel65: int64 pixel66: int64 pixel67: int64 pixel68: int64 pixel69: int64 pixel70: int64 pixel71: int64 pixel72: int64 pixel73: int64 pixel74: int64 pixel75: int64 pixel76: int64 pixel77: int64 pixel78: int64 pixel79: int64 pixel80: int64 pixel81: int64 pixel82: int64 pixel83: int64 pixel84: int64 pixel85: int64 pixel86: int64 pixel87: int64 pixel88: int64 pixel89: int64 pixel90: int64 pixel91: int64 pixel92: int64 pixel93: int64 pixel94: int64 pixel95: int64 pixel96: int64 pixel97: int64 pixel98: int64 pixel99: int64 pixel100: ... t64 pixel697: int64 pixel698: int64 pixel699: int64 pixel700: int64 pixel701: int64 pixel702: int64 pixel703: int64 pixel704: int64 pixel705: int64 pixel706: int64 pixel707: int64 pixel708: int64 pixel709: int64 pixel710: int64 pixel711: int64 pixel712: int64 pixel713: int64 pixel714: int64 pixel715: int64 pixel716: int64 pixel717: int64 pixel718: int64 pixel719: int64 pixel720: int64 pixel721: int64 pixel722: int64 pixel723: int64 pixel724: int64 pixel725: int64 pixel726: int64 pixel727: int64 pixel728: int64 pixel729: int64 pixel730: int64 pixel731: int64 pixel732: int64 pixel733: int64 pixel734: int64 pixel735: int64 pixel736: int64 pixel737: int64 pixel738: int64 pixel739: int64 pixel740: int64 pixel741: int64 pixel742: int64 pixel743: int64 pixel744: int64 pixel745: int64 pixel746: int64 pixel747: int64 pixel748: int64 pixel749: int64 pixel750: int64 pixel751: int64 pixel752: int64 pixel753: int64 pixel754: int64 pixel755: int64 pixel756: int64 pixel757: int64 pixel758: int64 pixel759: int64 pixel760: int64 pixel761: int64 pixel762: int64 pixel763: int64 pixel764: int64 pixel765: int64 pixel766: int64 pixel767: int64 pixel768: int64 pixel769: int64 pixel770: int64 pixel771: int64 pixel772: int64 pixel773: int64 pixel774: int64 pixel775: int64 pixel776: int64 pixel777: int64 pixel778: int64 pixel779: int64 pixel780: int64 pixel781: int64 pixel782: int64 pixel783: int64 -- schema metadata -- pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 88635 to {'label': Value(dtype='int64', id=None), 'pixel0': Value(dtype='int64', id=None), 'pixel1': Value(dtype='int64', id=None), 'pixel2': Value(dtype='int64', id=None), 'pixel3': Value(dtype='int64', id=None), 'pixel4': Value(dtype='int64', id=None), 'pixel5': Value(dtype='int64', id=None), 'pixel6': Value(dtype='int64', id=None), 'pixel7': Value(dtype='int64', id=None), 'pixel8': Value(dtype='int64', id=None), 'pixel9': Value(dtype='int64', id=None), 'pixel10': Value(dtype='int64', id=None), 'pixel11': Value(dtype='int64', id=None), 'pixel12': Value(dtype='int64', id=None), 'pixel13': Value(dtype='int64', id=None), 'pixel14': Value(dtype='int64', id=None), 'pixel15': Value(dtype='int64', id=None), 'pixel16': Value(dtype='int64', id=None), 'pixel17': Value(dtype='int64', id=None), 'pixel18': Value(dtype='int64', id=None), 'pixel19': Value(dtype='int64', id=None), 'pixel20': Value(dtype='int64', id=None), 'pixel21': Value(dtype='int64', id=None), 'pixel22': Value(dtype='int64', id=None), 'pixel23': Value(dtype='int64', id=None), 'pixel24': Value(dtype='int64', id=None), 'pixel25': Value(dtype='int64', id=None), 'pixel26': Value(dtype='int64', id=None), 'pixel27': Value(dtype='int64', id=None), 'pixel28': Value(dtype='int64', id=None), 'pixel29': Value(dtype='int64', id=None), 'pixel30': Value(dtype='int64', id=None), 'pixel31': Value(dtype='int64', id=None), 'pixel32': Value(dtype='int64', id=None), 'pixel33': Value(dtype='int64', id=None), 'pixel34': Value(dtype='int64', id=None), ... el749': Value(dtype='int64', id=None), 'pixel750': Value(dtype='int64', id=None), 'pixel751': Value(dtype='int64', id=None), 'pixel752': Value(dtype='int64', id=None), 'pixel753': Value(dtype='int64', id=None), 'pixel754': Value(dtype='int64', id=None), 'pixel755': Value(dtype='int64', id=None), 'pixel756': Value(dtype='int64', id=None), 'pixel757': Value(dtype='int64', id=None), 'pixel758': Value(dtype='int64', id=None), 'pixel759': Value(dtype='int64', id=None), 'pixel760': Value(dtype='int64', id=None), 'pixel761': Value(dtype='int64', id=None), 'pixel762': Value(dtype='int64', id=None), 'pixel763': Value(dtype='int64', id=None), 'pixel764': Value(dtype='int64', id=None), 'pixel765': Value(dtype='int64', id=None), 'pixel766': Value(dtype='int64', id=None), 'pixel767': Value(dtype='int64', id=None), 'pixel768': Value(dtype='int64', id=None), 'pixel769': Value(dtype='int64', id=None), 'pixel770': Value(dtype='int64', id=None), 'pixel771': Value(dtype='int64', id=None), 'pixel772': Value(dtype='int64', id=None), 'pixel773': Value(dtype='int64', id=None), 'pixel774': Value(dtype='int64', id=None), 'pixel775': Value(dtype='int64', id=None), 'pixel776': Value(dtype='int64', id=None), 'pixel777': Value(dtype='int64', id=None), 'pixel778': Value(dtype='int64', id=None), 'pixel779': Value(dtype='int64', id=None), 'pixel780': Value(dtype='int64', id=None), 'pixel781': Value(dtype='int64', id=None), 'pixel782': Value(dtype='int64', id=None), 'pixel783': Value(dtype='int64', id=None)} because column names don't match During handling of the above exception, another exception occurred: Traceback (most recent call last): File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1321, in compute_config_parquet_and_info_response parquet_operations = convert_to_parquet(builder) File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 935, in convert_to_parquet builder.download_and_prepare( File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1027, in download_and_prepare self._download_and_prepare( File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1122, in _download_and_prepare self._prepare_split(split_generator, **prepare_split_kwargs) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1882, in _prepare_split for job_id, done, content in self._prepare_split_single( File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 2013, in _prepare_split_single raise DatasetGenerationCastError.from_cast_error( datasets.exceptions.DatasetGenerationCastError: An error occurred while generating the dataset All the data files must have the same columns, but at some point there are 1 missing columns ({'label'}) This happened while the csv dataset builder was generating data using hf://datasets/VedantPadwal/mnist/test.csv (at revision 23061c5172509304b9891b3ac36a4ea477809dbe) Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)
Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
label
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int64 | pixel719
int64 | pixel720
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int64 | pixel724
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9 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 15 | 48 | 143 | 186 | 244 | 143 | 31 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 83 | 209 | 253 | 252 | 252 | 252 | 252 | 192 | 15 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 5 | 166 | 241 | 252 | 253 | 252 | 170 | 162 | 252 | 252 | 113 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 5 | 61 | 234 | 252 | 252 | 243 | 121 | 44 | 2 | 21 | 245 | 252 | 122 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 80 | 252 | 252 | 243 | 163 | 50 | 0 | 0 | 0 | 5 | 101 | 88 | 8 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 105 | 234 | 252 | 210 | 88 | 0 | 0 | 0 | 0 | 74 | 199 | 240 | 43 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 185 | 252 | 210 | 21 | 0 | 4 | 12 | 41 | 231 | 249 | 252 | 252 | 55 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 242 | 252 | 218 | 154 | 154 | 184 | 252 | 253 | 252 | 252 | 248 | 184 | 22 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 209 | 252 | 252 | 252 | 252 | 252 | 252 | 253 | 252 | 252 | 196 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 17 | 57 | 142 | 95 | 142 | 61 | 81 | 253 | 252 | 209 | 20 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 11 | 177 | 255 | 230 | 86 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 12 | 124 | 252 | 245 | 57 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 135 | 252 | 252 | 86 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 79 | 248 | 252 | 233 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 231 | 252 | 202 | 12 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 20 | 175 | 248 | 252 | 136 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 109 | 252 | 252 | 159 | 6 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 33 | 218 | 252 | 252 | 192 | 141 | 14 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 132 | 252 | 252 | 252 | 205 | 74 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 132 | 252 | 252 | 146 | 13 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
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