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Nerlnet

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tiles_sorted

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Nerlnet 6

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 68 new columns ({'0.0.184', '0.0.177', '0.0.182', '0.0.212', '0.0.187', '0.0.204', '0.196078431372549', '0.0.202', '0.0.205', '0.0.186', '0.0.211', '0.0.174', '0.4784313725490196', '0.0.200', '0.0.172', '0.0.183', '0.0.216', '0.0.196', '0.0.214', '0.0.203', '0.0.176', '0.0.207', '0.7411764705882353', '0.0.191', '0.9882352941176472.7', '0.9294117647058824', '0.0.175', '0.6235294117647059', '0.0.181', '0.0.210', '0.0.206', '0.0.190', '0.8901960784313725', '0.9882352941176472.10', '0.0.197', '0.0.218', '0.9882352941176472.12', '0.0.213', '0.0.192', '0.0.193', '0.6235294117647059.1', '0.0.201', '0.0.194', '0.0235294117647058', '0.0.180', '0.0.185', '0.9882352941176472.9', '0.9372549019607844', '0.0.178', '0.9882352941176472.11', '0.3764705882352941', '0.0.189', '0.992156862745098.4', '0.6549019607843137', '0.9882352941176472.8', '0.0.173', '0.0.215', '0.0.188', '0.0.199', '0.792156862745098', '0.992156862745098.3', '0.0.217', '0.0.208', '0.0.195', '0.992156862745098.5', '0.0.198', '0.0.209', '0.0.179'}) and 12 missing columns ({'0.6980392156862745', '0.0274509803921568', '0.8156862745098039', '0.2470588235294117', '0.1490196078431372', '0.2784313725490196', '0.7019607843137254', '0.6470588235294118', '0.9411764705882352', '0.0745098039215686', '0.9333333333333332.1', '0.1098039215686274'}).

This happened while the csv dataset builder was generating data using

hf://datasets/Nerlnet/tiles_sorted/mnist_tiles_sorted.csv (at revision 6e37a49c969dd27c139589492eb2493698827f25)

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
              0.0: double
              0.0.1: double
              0.0.2: double
              0.0.3: double
              0.0.4: double
              0.0.5: double
              0.0.6: double
              0.0.7: double
              0.0.8: double
              0.0.9: double
              0.0.10: double
              0.0.11: double
              0.0.12: double
              0.0.13: double
              0.0.14: double
              0.0.15: double
              0.0.16: double
              0.0.17: double
              0.0.18: double
              0.0.19: double
              0.0.20: double
              0.0.21: double
              0.0.22: double
              0.0.23: double
              0.0.24: double
              0.0.25: double
              0.0.26: double
              0.0.27: double
              0.0.28: double
              0.0.29: double
              0.0.30: double
              0.0.31: double
              0.0.32: double
              0.0.33: double
              0.0.34: double
              0.0.35: double
              0.0.36: double
              0.0.37: double
              0.0.38: double
              0.0.39: double
              0.0.40: double
              0.0.41: double
              0.0.42: double
              0.0.43: double
              0.0.44: double
              0.0.45: double
              0.0.46: double
              0.0.47: double
              0.0.48: double
              0.0.49: double
              0.0.50: double
              0.0.51: double
              0.0.52: double
              0.0.53: double
              0.0.54: double
              0.0.55: double
              0.0.56: double
              0.0.57: double
              0.0.58: double
              0.0.59: double
              0.0.60: double
              0.0.61: double
              0.0.62: double
              0.0.63: double
              0.0.64: double
              0.0.65: double
              0.0.66: double
              0.0.67: double
              0.0.68: double
              0.0.69: double
              0.0.70: double
              0.0.71: double
              0.0.72: double
              0.0.73: double
              0.0.74: double
              0.0.75: double
              0.0.76: double
              0.0.77: double
              0.0.78: double
              0.0.79: double
              0.0.80: double
              0.0.81: double
              0.0.82: double
              0.0.83: double
              0.0.84: double
              0.0.85: double
              0.0.86: double
              0.0.87: double
              0.0.88: double
              0.0.89: double
              0.0.90: double
              0.0.91: double
              0.0.92: double
              0.0.93: double
              0.0.94: double
              0.0.95: double
              0.0.96: double
              0.0.97: double
              0.0.98: double
              0.0.99: double
              0.0.100: dou
              ...
              0.0.171: double
              0.0.172: double
              0.0.173: double
              0.0.174: double
              0.0.175: double
              0.0.176: double
              0.0.177: double
              0.0.178: double
              0.0.179: double
              0.0.180: double
              0.0.181: double
              0.0.182: double
              0.0.183: double
              0.0.184: double
              0.0.185: double
              0.0.186: double
              0.0392156862745098: double
              0.2352941176470588: double
              0.8784313725490196: double
              0.9882352941176472.5: double
              0.992156862745098.2: double
              0.9882352941176472.6: double
              0.792156862745098: double
              0.3294117647058823: double
              0.9882352941176472.7: double
              0.992156862745098.3: double
              0.4784313725490196: double
              0.0.187: double
              0.0.188: double
              0.0.189: double
              0.0.190: double
              0.0.191: double
              0.0.192: double
              0.0.193: double
              0.0.194: double
              0.0.195: double
              0.0.196: double
              0.0.197: double
              0.0.198: double
              0.0.199: double
              0.0.200: double
              0.0.201: double
              0.0.202: double
              0.0.203: double
              0.6392156862745098: double
              0.9882352941176472.8: double
              0.9882352941176472.9: double
              0.9882352941176472.10: double
              0.992156862745098.4: double
              0.9882352941176472.11: double
              0.9882352941176472.12: double
              0.3764705882352941: double
              0.7411764705882353: double
              0.992156862745098.5: double
              0.6549019607843137: double
              0.0.204: double
              0.0.205: double
              0.0.206: double
              0.0.207: double
              0.0.208: double
              0.0.209: double
              1.0: double
              0.0.210: double
              0.0.211: double
              0.0.212: double
              0.0.213: double
              0.0.214: double
              0.0.215: double
              0.0.216: double
              0.0.217: double
              0.0.218: double
              -- schema metadata --
              pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 31115
              to
              {'0.0': Value(dtype='float64', id=None), '0.0.1': Value(dtype='float64', id=None), '0.0.2': Value(dtype='float64', id=None), '0.0.3': Value(dtype='float64', id=None), '0.0.4': Value(dtype='float64', id=None), '0.0.5': Value(dtype='float64', id=None), '0.0.6': Value(dtype='float64', id=None), '0.0.7': Value(dtype='float64', id=None), '0.0.8': Value(dtype='float64', id=None), '0.0.9': Value(dtype='float64', id=None), '0.0.10': Value(dtype='float64', id=None), '0.0.11': Value(dtype='float64', id=None), '0.0.12': Value(dtype='float64', id=None), '0.0.13': Value(dtype='float64', id=None), '0.0.14': Value(dtype='float64', id=None), '0.0.15': Value(dtype='float64', id=None), '0.0.16': Value(dtype='float64', id=None), '0.0.17': Value(dtype='float64', id=None), '0.0.18': Value(dtype='float64', id=None), '0.0.19': Value(dtype='float64', id=None), '0.0.20': Value(dtype='float64', id=None), '0.0.21': Value(dtype='float64', id=None), '0.0.22': Value(dtype='float64', id=None), '0.0.23': Value(dtype='float64', id=None), '0.0.24': Value(dtype='float64', id=None), '0.0.25': Value(dtype='float64', id=None), '0.0.26': Value(dtype='float64', id=None), '0.0.27': Value(dtype='float64', id=None), '0.0.28': Value(dtype='float64', id=None), '0.0.29': Value(dtype='float64', id=None), '0.0.30': Value(dtype='float64', id=None), '0.0.31': Value(dtype='float64', id=None), '0.0.32': Value(dtype='float64', id=None), '0.0.33': Value(dtype='float64', id=None), '0.0.34': Value(dtype='float64', id=None), '0.0.3
              ...
              4', id=None), '0.0274509803921568': Value(dtype='float64', id=None), '0.6980392156862745': Value(dtype='float64', id=None), '0.9882352941176472.4': Value(dtype='float64', id=None), '0.9411764705882352': Value(dtype='float64', id=None), '0.2784313725490196': Value(dtype='float64', id=None), '0.0745098039215686': Value(dtype='float64', id=None), '0.1098039215686274': Value(dtype='float64', id=None), '0.0.153': Value(dtype='float64', id=None), '0.0.154': Value(dtype='float64', id=None), '0.0.155': Value(dtype='float64', id=None), '0.0.156': Value(dtype='float64', id=None), '0.0.157': Value(dtype='float64', id=None), '0.0.158': Value(dtype='float64', id=None), '0.0.159': Value(dtype='float64', id=None), '0.2235294117647059': Value(dtype='float64', id=None), '0.9882352941176472.5': Value(dtype='float64', id=None), '0.9882352941176472.6': Value(dtype='float64', id=None), '0.2470588235294117': Value(dtype='float64', id=None), '0.0.160': Value(dtype='float64', id=None), '0.0.161': Value(dtype='float64', id=None), '0.0.162': Value(dtype='float64', id=None), '1.0': Value(dtype='float64', id=None), '0.0.163': Value(dtype='float64', id=None), '0.0.164': Value(dtype='float64', id=None), '0.0.165': Value(dtype='float64', id=None), '0.0.166': Value(dtype='float64', id=None), '0.0.167': Value(dtype='float64', id=None), '0.0.168': Value(dtype='float64', id=None), '0.0.169': Value(dtype='float64', id=None), '0.0.170': Value(dtype='float64', id=None), '0.0.171': Value(dtype='float64', 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 1577, 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 1191, 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 68 new columns ({'0.0.184', '0.0.177', '0.0.182', '0.0.212', '0.0.187', '0.0.204', '0.196078431372549', '0.0.202', '0.0.205', '0.0.186', '0.0.211', '0.0.174', '0.4784313725490196', '0.0.200', '0.0.172', '0.0.183', '0.0.216', '0.0.196', '0.0.214', '0.0.203', '0.0.176', '0.0.207', '0.7411764705882353', '0.0.191', '0.9882352941176472.7', '0.9294117647058824', '0.0.175', '0.6235294117647059', '0.0.181', '0.0.210', '0.0.206', '0.0.190', '0.8901960784313725', '0.9882352941176472.10', '0.0.197', '0.0.218', '0.9882352941176472.12', '0.0.213', '0.0.192', '0.0.193', '0.6235294117647059.1', '0.0.201', '0.0.194', '0.0235294117647058', '0.0.180', '0.0.185', '0.9882352941176472.9', '0.9372549019607844', '0.0.178', '0.9882352941176472.11', '0.3764705882352941', '0.0.189', '0.992156862745098.4', '0.6549019607843137', '0.9882352941176472.8', '0.0.173', '0.0.215', '0.0.188', '0.0.199', '0.792156862745098', '0.992156862745098.3', '0.0.217', '0.0.208', '0.0.195', '0.992156862745098.5', '0.0.198', '0.0.209', '0.0.179'}) and 12 missing columns ({'0.6980392156862745', '0.0274509803921568', '0.8156862745098039', '0.2470588235294117', '0.1490196078431372', '0.2784313725490196', '0.7019607843137254', '0.6470588235294118', '0.9411764705882352', '0.0745098039215686', '0.9333333333333332.1', '0.1098039215686274'}).
              
              This happened while the csv dataset builder was generating data using
              
              hf://datasets/Nerlnet/tiles_sorted/mnist_tiles_sorted.csv (at revision 6e37a49c969dd27c139589492eb2493698827f25)
              
              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)