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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 4 new columns ({'std', 'mean', 'max', 'min'}) and 7 missing columns ({'time_stats.bandwidth.median', 'dtype', 'time_stats.bandwidth.max', 'time_stats.bandwidth.std', 'time_stats.bandwidth.mean', 'bandwidth_gbps', 'time_stats.bandwidth.min'}).

This happened while the csv dataset builder was generating data using

hf://datasets/project-vajra/dev-staging-bandwidth-a40-pairwise-nvlink/bandwidth_profile.csv (at revision 03e4929b6364cad428c56b1f0eadc61b5850914d)

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 1831, in _prepare_split_single
                  writer.write_table(table)
                File "/usr/local/lib/python3.12/site-packages/datasets/arrow_writer.py", line 714, 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
              direction: string
              data_size: int64
              mean: double
              std: double
              min: double
              max: double
              -- schema metadata --
              pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 923
              to
              {'time_stats.bandwidth.min': Value('float64'), 'time_stats.bandwidth.max': Value('float64'), 'time_stats.bandwidth.mean': Value('float64'), 'time_stats.bandwidth.median': Value('float64'), 'time_stats.bandwidth.std': Value('float64'), 'data_size': Value('int64'), 'direction': Value('string'), 'dtype': Value('string'), 'bandwidth_gbps': Value('float64')}
              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 1339, 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 972, in convert_to_parquet
                  builder.download_and_prepare(
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 894, in download_and_prepare
                  self._download_and_prepare(
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 970, in _download_and_prepare
                  self._prepare_split(split_generator, **prepare_split_kwargs)
                File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1702, 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 1833, 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 4 new columns ({'std', 'mean', 'max', 'min'}) and 7 missing columns ({'time_stats.bandwidth.median', 'dtype', 'time_stats.bandwidth.max', 'time_stats.bandwidth.std', 'time_stats.bandwidth.mean', 'bandwidth_gbps', 'time_stats.bandwidth.min'}).
              
              This happened while the csv dataset builder was generating data using
              
              hf://datasets/project-vajra/dev-staging-bandwidth-a40-pairwise-nvlink/bandwidth_profile.csv (at revision 03e4929b6364cad428c56b1f0eadc61b5850914d)
              
              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)

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time_stats.bandwidth.min float64	time_stats.bandwidth.max float64	time_stats.bandwidth.mean float64	time_stats.bandwidth.median float64	time_stats.bandwidth.std float64	data_size int64	direction string	dtype string	bandwidth_gbps float64
0.000022	0.000031	0.000024	0.000022	0.000004	1,024	h2d	torch.float16	0.039359
0.000019	0.00003	0.000022	0.000019	0.000004	1,024	d2h	torch.float16	0.043368
0.000022	0.000039	0.000026	0.000023	0.000006	2,048	h2d	torch.float16	0.072494
0.000021	0.00003	0.000024	0.000022	0.000003	2,048	d2h	torch.float16	0.080941
0.000022	0.000034	0.000026	0.000023	0.000004	4,096	h2d	torch.float16	0.148049
0.000019	0.000028	0.000022	0.000021	0.000003	4,096	d2h	torch.float16	0.170396
0.000021	0.00003	0.000024	0.000022	0.000004	8,192	h2d	torch.float16	0.319939
0.00002	0.00003	0.000023	0.000022	0.000004	8,192	d2h	torch.float16	0.326601
0.000046	0.000059	0.000051	0.00005	0.000004	16,384	h2d	torch.float16	0.296947
0.000041	0.000078	0.000057	0.000058	0.000014	16,384	d2h	torch.float16	0.268308
0.000053	0.000087	0.000063	0.000057	0.000013	32,768	h2d	torch.float16	0.487763
0.000075	0.000088	0.00008	0.00008	0.000005	32,768	d2h	torch.float16	0.379315
0.000114	0.000137	0.000124	0.000122	0.000009	65,536	h2d	torch.float16	0.493876
0.000043	0.000059	0.000049	0.000049	0.000005	65,536	d2h	torch.float16	1.24031
0.000033	0.00004	0.000035	0.000033	0.000002	131,072	h2d	torch.float16	3.46287
0.000019	0.000025	0.000021	0.00002	0.000002	131,072	d2h	torch.float16	5.822188
0.000086	0.000095	0.00009	0.000087	0.000004	262,144	h2d	torch.float16	2.727511
0.000042	0.000081	0.000055	0.000053	0.000014	262,144	d2h	torch.float16	4.434663
0.00033	0.000408	0.000363	0.000353	0.000026	524,288	h2d	torch.float16	1.345335
0.000065	0.000072	0.000069	0.000069	0.000002	524,288	d2h	torch.float16	7.090515
0.000294	0.000305	0.000299	0.000299	0.000004	1,048,576	h2d	torch.float16	3.261192
0.000057	0.000061	0.000059	0.000059	0.000001	1,048,576	d2h	torch.float16	16.542486
0.000139	0.000152	0.000143	0.000141	0.000005	2,097,152	h2d	torch.float16	13.691152
0.000089	0.00009	0.00009	0.00009	0	2,097,152	d2h	torch.float16	21.745459
0.000293	0.000298	0.000295	0.000295	0.000002	4,194,304	h2d	torch.float16	13.223953
0.000176	0.000196	0.000182	0.000179	0.000007	4,194,304	d2h	torch.float16	21.475372
0.0007	0.00099	0.000923	0.000976	0.000112	8,388,608	h2d	torch.float16	8.462941
0.000345	0.00035	0.000348	0.000348	0.000002	8,388,608	d2h	torch.float16	22.481135
0.000763	0.000861	0.000787	0.000768	0.000037	16,777,216	h2d	torch.float16	19.856257
0.000636	0.000642	0.000639	0.00064	0.000002	16,777,216	d2h	torch.float16	24.435077
0.001578	0.001715	0.001635	0.001613	0.000051	33,554,432	h2d	torch.float16	19.117995
0.001283	0.003913	0.001891	0.001447	0.001014	33,554,432	d2h	torch.float16	16.525354
0.003946	0.003991	0.003965	0.003967	0.000017	67,108,864	h2d	torch.float16	15.763543
0.002556	0.002566	0.00256	0.002558	0.000003	67,108,864	d2h	torch.float16	24.418275
0.009505	0.009601	0.009535	0.009528	0.000035	134,217,728	h2d	torch.float16	13.110017
0.005099	0.005108	0.005104	0.005104	0.000003	134,217,728	d2h	torch.float16	24.489276
0.016118	0.016199	0.016161	0.016167	0.000028	268,435,456	h2d	torch.float16	15.469678
0.009909	0.009981	0.00993	0.00992	0.000027	268,435,456	d2h	torch.float16	25.174993
0.026664	0.026773	0.026733	0.026742	0.000036	536,870,912	h2d	torch.float16	18.703584
0.020341	0.020497	0.02038	0.020352	0.000059	536,870,912	d2h	torch.float16	24.534434
0.070321	0.071089	0.070601	0.070528	0.000266	1,073,741,824	h2d	torch.float16	14.164111
0.040676	0.040754	0.040708	0.04068	0.000036	1,073,741,824	d2h	torch.float16	24.56532
0.109811	0.110338	0.110179	0.110317	0.000205	2,147,483,648	h2d	torch.float16	18.152212
0.081416	0.081721	0.081603	0.081652	0.000104	2,147,483,648	d2h	torch.float16	24.508912
0.2263	0.240714	0.233636	0.234344	0.005366	4,294,967,296	h2d	torch.float16	17.120676
0.16285	0.163494	0.16314	0.163087	0.000212	4,294,967,296	d2h	torch.float16	24.518881
0.435061	0.462773	0.442524	0.437189	0.010295	8,589,934,592	h2d	torch.float16	18.0781
0.334177	0.334687	0.334363	0.334287	0.000185	8,589,934,592	d2h	torch.float16	23.926071
1.023805	1.1343	1.063919	1.065276	0.039725	17,179,869,184	h2d	torch.float16	15.038739
0.682743	0.684485	0.68357	0.683481	0.000686	17,179,869,184	d2h	torch.float16	23.406532
null	null	null	null	null	1,024	d2h	null	null
null	null	null	null	null	2,048	d2h	null	null
null	null	null	null	null	4,096	d2h	null	null
null	null	null	null	null	8,192	d2h	null	null
null	null	null	null	null	16,384	d2h	null	null
null	null	null	null	null	32,768	d2h	null	null
null	null	null	null	null	65,536	d2h	null	null
null	null	null	null	null	131,072	d2h	null	null
null	null	null	null	null	262,144	d2h	null	null
null	null	null	null	null	524,288	d2h	null	null
null	null	null	null	null	1,048,576	d2h	null	null
null	null	null	null	null	2,097,152	d2h	null	null
null	null	null	null	null	4,194,304	d2h	null	null
null	null	null	null	null	8,388,608	d2h	null	null
null	null	null	null	null	16,777,216	d2h	null	null
null	null	null	null	null	33,554,432	d2h	null	null
null	null	null	null	null	67,108,864	d2h	null	null
null	null	null	null	null	134,217,728	d2h	null	null
null	null	null	null	null	268,435,456	d2h	null	null
null	null	null	null	null	536,870,912	d2h	null	null
null	null	null	null	null	1,073,741,824	d2h	null	null
null	null	null	null	null	2,147,483,648	d2h	null	null
null	null	null	null	null	4,294,967,296	d2h	null	null
null	null	null	null	null	8,589,934,592	d2h	null	null
null	null	null	null	null	17,179,869,184	d2h	null	null
null	null	null	null	null	1,024	h2d	null	null
null	null	null	null	null	2,048	h2d	null	null
null	null	null	null	null	4,096	h2d	null	null
null	null	null	null	null	8,192	h2d	null	null
null	null	null	null	null	16,384	h2d	null	null
null	null	null	null	null	32,768	h2d	null	null
null	null	null	null	null	65,536	h2d	null	null
null	null	null	null	null	131,072	h2d	null	null
null	null	null	null	null	262,144	h2d	null	null
null	null	null	null	null	524,288	h2d	null	null
null	null	null	null	null	1,048,576	h2d	null	null
null	null	null	null	null	2,097,152	h2d	null	null
null	null	null	null	null	4,194,304	h2d	null	null
null	null	null	null	null	8,388,608	h2d	null	null
null	null	null	null	null	16,777,216	h2d	null	null
null	null	null	null	null	33,554,432	h2d	null	null
null	null	null	null	null	67,108,864	h2d	null	null
null	null	null	null	null	134,217,728	h2d	null	null
null	null	null	null	null	268,435,456	h2d	null	null
null	null	null	null	null	536,870,912	h2d	null	null
null	null	null	null	null	1,073,741,824	h2d	null	null
null	null	null	null	null	2,147,483,648	h2d	null	null
null	null	null	null	null	4,294,967,296	h2d	null	null
null	null	null	null	null	8,589,934,592	h2d	null	null
null	null	null	null	null	17,179,869,184	h2d	null	null

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