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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 15 new columns ({'MU_juv', 'G_center', 'MU_min', 'MU_r_juv', 'MU_sen', 'G_sigma', 'K_base', 'K_sigma', 'K_amp', 'MU_p_sen', 'R0', 'G_offset', 'K_center', 'G_amp', 'family_id'}) and 9 missing columns ({'u_star', 'rollout_id', 'plant_zeta2', 'time_index', 'species', 'plant_zeta1', 'sample_id', 'snapshot_order', 'time'}).

This happened while the csv dataset builder was generating data using

hf://datasets/lukebhan/NeuralOperatorsLotkaSharpePredatoryPrey/simple_parametric_summary.csv (at revision 09527b0ca84dda96995b0146fc60ffddc191aa6b), [/tmp/hf-datasets-cache/medium/datasets/34891475826601-config-parquet-and-info-lukebhan-NeuralOperatorsL-a7239f9d/hub/datasets--lukebhan--NeuralOperatorsLotkaSharpePredatoryPrey/snapshots/09527b0ca84dda96995b0146fc60ffddc191aa6b/adaptive_estimator_summary.csv (origin=hf://datasets/lukebhan/NeuralOperatorsLotkaSharpePredatoryPrey@09527b0ca84dda96995b0146fc60ffddc191aa6b/adaptive_estimator_summary.csv), /tmp/hf-datasets-cache/medium/datasets/34891475826601-config-parquet-and-info-lukebhan-NeuralOperatorsL-a7239f9d/hub/datasets--lukebhan--NeuralOperatorsLotkaSharpePredatoryPrey/snapshots/09527b0ca84dda96995b0146fc60ffddc191aa6b/simple_parametric_summary.csv (origin=hf://datasets/lukebhan/NeuralOperatorsLotkaSharpePredatoryPrey@09527b0ca84dda96995b0146fc60ffddc191aa6b/simple_parametric_summary.csv)]

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 "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1890, in _prepare_split_single
                  writer.write_table(table)
                File "/usr/local/lib/python3.12/site-packages/datasets/arrow_writer.py", line 760, in write_table
                  pa_table = table_cast(pa_table, self._schema)
                             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2272, in table_cast
                  return cast_table_to_schema(table, schema)
                         ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2218, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              family_id: int64
              R0: double
              zeta: double
              K_base: double
              K_amp: double
              K_center: double
              K_sigma: double
              MU_min: double
              MU_juv: double
              MU_r_juv: double
              MU_sen: double
              MU_p_sen: double
              G_offset: double
              G_amp: double
              G_center: double
              G_sigma: double
              -- schema metadata --
              pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 2080
              to
              {'rollout_id': Value('int64'), 'snapshot_order': Value('int64'), 'time_index': Value('int64'), 'time': Value('float64'), 'species': Value('int64'), 'zeta': Value('float64'), 'u_star': Value('float64'), 'plant_zeta1': Value('float64'), 'plant_zeta2': Value('float64'), 'sample_id': Value('int64')}
              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 1347, 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 980, in convert_to_parquet
                  builder.download_and_prepare(
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 884, in download_and_prepare
                  self._download_and_prepare(
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 947, in _download_and_prepare
                  self._prepare_split(split_generator, **prepare_split_kwargs)
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1739, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                                               ^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1892, 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 15 new columns ({'MU_juv', 'G_center', 'MU_min', 'MU_r_juv', 'MU_sen', 'G_sigma', 'K_base', 'K_sigma', 'K_amp', 'MU_p_sen', 'R0', 'G_offset', 'K_center', 'G_amp', 'family_id'}) and 9 missing columns ({'u_star', 'rollout_id', 'plant_zeta2', 'time_index', 'species', 'plant_zeta1', 'sample_id', 'snapshot_order', 'time'}).
              
              This happened while the csv dataset builder was generating data using
              
              hf://datasets/lukebhan/NeuralOperatorsLotkaSharpePredatoryPrey/simple_parametric_summary.csv (at revision 09527b0ca84dda96995b0146fc60ffddc191aa6b), [/tmp/hf-datasets-cache/medium/datasets/34891475826601-config-parquet-and-info-lukebhan-NeuralOperatorsL-a7239f9d/hub/datasets--lukebhan--NeuralOperatorsLotkaSharpePredatoryPrey/snapshots/09527b0ca84dda96995b0146fc60ffddc191aa6b/adaptive_estimator_summary.csv (origin=hf://datasets/lukebhan/NeuralOperatorsLotkaSharpePredatoryPrey@09527b0ca84dda96995b0146fc60ffddc191aa6b/adaptive_estimator_summary.csv), /tmp/hf-datasets-cache/medium/datasets/34891475826601-config-parquet-and-info-lukebhan-NeuralOperatorsL-a7239f9d/hub/datasets--lukebhan--NeuralOperatorsLotkaSharpePredatoryPrey/snapshots/09527b0ca84dda96995b0146fc60ffddc191aa6b/simple_parametric_summary.csv (origin=hf://datasets/lukebhan/NeuralOperatorsLotkaSharpePredatoryPrey@09527b0ca84dda96995b0146fc60ffddc191aa6b/simple_parametric_summary.csv)]
              
              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.

rollout_id int64	snapshot_order int64	time_index int64	time float64	species int64	zeta float64	u_star float64	plant_zeta1 float64	plant_zeta2 float64	sample_id int64
6	0	0	0	1	1.382618	0.831322	1.662645	2.230461	0
6	0	0	0	2	1.456696	0.831322	1.662645	2.230461	1
6	1	25	0.125	1	1.401675	0.831322	1.662645	2.230461	2
6	1	25	0.125	2	1.49988	0.831322	1.662645	2.230461	3
6	2	50	0.25	1	1.417333	0.831322	1.662645	2.230461	4
6	2	50	0.25	2	1.540684	0.831322	1.662645	2.230461	5
6	3	75	0.375	1	1.431995	0.831322	1.662645	2.230461	6
6	3	75	0.375	2	1.579892	0.831322	1.662645	2.230461	7
6	4	101	0.505	1	1.446632	0.831322	1.662645	2.230461	8
6	4	101	0.505	2	1.618906	0.831322	1.662645	2.230461	9
6	5	126	0.63	1	1.459863	0.831322	1.662645	2.230461	10
6	5	126	0.63	2	1.654635	0.831322	1.662645	2.230461	11
6	6	151	0.755	1	1.472239	0.831322	1.662645	2.230461	12
6	6	151	0.755	2	1.688543	0.831322	1.662645	2.230461	13
6	7	176	0.88	1	1.483848	0.831322	1.662645	2.230461	14
6	7	176	0.88	2	1.720619	0.831322	1.662645	2.230461	15
6	8	201	1.005	1	1.494739	0.831322	1.662645	2.230461	16
6	8	201	1.005	2	1.750898	0.831322	1.662645	2.230461	17
6	9	226	1.13	1	1.504921	0.831322	1.662645	2.230461	18
6	9	226	1.13	2	1.779462	0.831322	1.662645	2.230461	19
6	10	251	1.255	1	1.51442	0.831322	1.662645	2.230461	20
6	10	251	1.255	2	1.806393	0.831322	1.662645	2.230461	21
6	11	276	1.38	1	1.523297	0.831322	1.662645	2.230461	22
6	11	276	1.38	2	1.83177	0.831322	1.662645	2.230461	23
6	12	302	1.51	1	1.531917	0.831322	1.662645	2.230461	24
6	12	302	1.51	2	1.8566	0.831322	1.662645	2.230461	25
6	13	327	1.635	1	1.539659	0.831322	1.662645	2.230461	26
6	13	327	1.635	2	1.879051	0.831322	1.662645	2.230461	27
6	14	352	1.76	1	1.546906	0.831322	1.662645	2.230461	28
6	14	352	1.76	2	1.900182	0.831322	1.662645	2.230461	29
6	15	377	1.885	1	1.553697	0.831322	1.662645	2.230461	30
6	15	377	1.885	2	1.920066	0.831322	1.662645	2.230461	31
6	16	402	2.01	1	1.560063	0.831322	1.662645	2.230461	32
6	16	402	2.01	2	1.938771	0.831322	1.662645	2.230461	33
6	17	427	2.135	1	1.566035	0.831322	1.662645	2.230461	34
6	17	427	2.135	2	1.956364	0.831322	1.662645	2.230461	35
6	18	452	2.26	1	1.57164	0.831322	1.662645	2.230461	36
6	18	452	2.26	2	1.972909	0.831322	1.662645	2.230461	37
6	19	477	2.385	1	1.576904	0.831322	1.662645	2.230461	38
6	19	477	2.385	2	1.988465	0.831322	1.662645	2.230461	39
6	20	503	2.515	1	1.582041	0.831322	1.662645	2.230461	40
6	20	503	2.515	2	2.003657	0.831322	1.662645	2.230461	41
6	21	528	2.64	1	1.586676	0.831322	1.662645	2.230461	42
6	21	528	2.64	2	2.017371	0.831322	1.662645	2.230461	43
6	22	553	2.765	1	1.591033	0.831322	1.662645	2.230461	44
6	22	553	2.765	2	2.030262	0.831322	1.662645	2.230461	45
6	23	578	2.89	1	1.595131	0.831322	1.662645	2.230461	46
6	23	578	2.89	2	2.042377	0.831322	1.662645	2.230461	47
6	24	603	3.015	1	1.598984	0.831322	1.662645	2.230461	48
6	24	603	3.015	2	2.053762	0.831322	1.662645	2.230461	49
6	25	628	3.14	1	1.602608	0.831322	1.662645	2.230461	50
6	25	628	3.14	2	2.064461	0.831322	1.662645	2.230461	51
6	26	653	3.265	1	1.606017	0.831322	1.662645	2.230461	52
6	26	653	3.265	2	2.074514	0.831322	1.662645	2.230461	53
6	27	678	3.39	1	1.609225	0.831322	1.662645	2.230461	54
6	27	678	3.39	2	2.083959	0.831322	1.662645	2.230461	55
6	28	704	3.52	1	1.612361	0.831322	1.662645	2.230461	56
6	28	704	3.52	2	2.093177	0.831322	1.662645	2.230461	57
6	29	729	3.645	1	1.615195	0.831322	1.662645	2.230461	58
6	29	729	3.645	2	2.101493	0.831322	1.662645	2.230461	59
6	30	754	3.77	1	1.617862	0.831322	1.662645	2.230461	60
6	30	754	3.77	2	2.109306	0.831322	1.662645	2.230461	61
6	31	779	3.895	1	1.620373	0.831322	1.662645	2.230461	62
6	31	779	3.895	2	2.116644	0.831322	1.662645	2.230461	63
6	32	804	4.02	1	1.622736	0.831322	1.662645	2.230461	64
6	32	804	4.02	2	2.123538	0.831322	1.662645	2.230461	65
6	33	829	4.145	1	1.624962	0.831322	1.662645	2.230461	66
6	33	829	4.145	2	2.130013	0.831322	1.662645	2.230461	67
6	34	854	4.27	1	1.627057	0.831322	1.662645	2.230461	68
6	34	854	4.27	2	2.136094	0.831322	1.662645	2.230461	69
6	35	879	4.395	1	1.62903	0.831322	1.662645	2.230461	70
6	35	879	4.395	2	2.141806	0.831322	1.662645	2.230461	71
6	36	905	4.525	1	1.630961	0.831322	1.662645	2.230461	72
6	36	905	4.525	2	2.147378	0.831322	1.662645	2.230461	73
6	37	930	4.65	1	1.632707	0.831322	1.662645	2.230461	74
6	37	930	4.65	2	2.152404	0.831322	1.662645	2.230461	75
6	38	955	4.775	1	1.634352	0.831322	1.662645	2.230461	76
6	38	955	4.775	2	2.157123	0.831322	1.662645	2.230461	77
6	39	980	4.9	1	1.635901	0.831322	1.662645	2.230461	78
6	39	980	4.9	2	2.161555	0.831322	1.662645	2.230461	79
6	40	1,005	5.025	1	1.637361	0.831322	1.662645	2.230461	80
6	40	1,005	5.025	2	2.165717	0.831322	1.662645	2.230461	81
6	41	1,030	5.15	1	1.638736	0.831322	1.662645	2.230461	82
6	41	1,030	5.15	2	2.169625	0.831322	1.662645	2.230461	83
6	42	1,055	5.275	1	1.640033	0.831322	1.662645	2.230461	84
6	42	1,055	5.275	2	2.173294	0.831322	1.662645	2.230461	85
6	43	1,080	5.4	1	1.641254	0.831322	1.662645	2.230461	86
6	43	1,080	5.4	2	2.176739	0.831322	1.662645	2.230461	87
6	44	1,106	5.53	1	1.64245	0.831322	1.662645	2.230461	88
6	44	1,106	5.53	2	2.1801	0.831322	1.662645	2.230461	89
6	45	1,131	5.655	1	1.643533	0.831322	1.662645	2.230461	90
6	45	1,131	5.655	2	2.183129	0.831322	1.662645	2.230461	91
6	46	1,156	5.78	1	1.644553	0.831322	1.662645	2.230461	92
6	46	1,156	5.78	2	2.185974	0.831322	1.662645	2.230461	93
6	47	1,181	5.905	1	1.645516	0.831322	1.662645	2.230461	94
6	47	1,181	5.905	2	2.188644	0.831322	1.662645	2.230461	95
6	48	1,206	6.03	1	1.646423	0.831322	1.662645	2.230461	96
6	48	1,206	6.03	2	2.191151	0.831322	1.662645	2.230461	97
6	49	1,231	6.155	1	1.647278	0.831322	1.662645	2.230461	98
6	49	1,231	6.155	2	2.193505	0.831322	1.662645	2.230461	99

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