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

This happened while the csv dataset builder was generating data using

hf://datasets/project-vajra/dev-staging-bandwidth-h200-pci/bandwidth_profile.csv (at revision adddd8b04554e77e1b8bfd0a5a8ee0538fe4a89d)

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 1455, 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 1054, 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', 'max', 'mean', 'min'}) and 7 missing columns ({'bandwidth_gbps', 'time_stats.bandwidth.median', 'dtype', 'time_stats.bandwidth.min', 'time_stats.bandwidth.std', 'time_stats.bandwidth.max', 'time_stats.bandwidth.mean'}).
              
              This happened while the csv dataset builder was generating data using
              
              hf://datasets/project-vajra/dev-staging-bandwidth-h200-pci/bandwidth_profile.csv (at revision adddd8b04554e77e1b8bfd0a5a8ee0538fe4a89d)
              
              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
0.000018
0.000025
0.00002
0.000019
0.000002
1,024
h2d
torch.float16
0.047185
0.000021
0.000025
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0.000021
0.000001
1,024
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torch.float16
0.043469
0.000018
0.000022
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0.000018
0.000001
2,048
h2d
torch.float16
0.099176
0.00002
0.000025
0.000022
0.000021
0.000002
2,048
d2h
torch.float16
0.087397
0.000018
0.000028
0.000021
0.000019
0.000003
4,096
h2d
torch.float16
0.179208
0.000021
0.000024
0.000022
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0.000001
4,096
d2h
torch.float16
0.176137
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0.000022
0.00002
0.00002
0.000001
8,192
h2d
torch.float16
0.377723
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0.000022
0.000022
0.000001
8,192
d2h
torch.float16
0.341476
0.000019
0.000023
0.000021
0.00002
0.000001
16,384
h2d
torch.float16
0.74066
0.000022
0.000025
0.000023
0.000023
0.000001
16,384
d2h
torch.float16
0.673119
0.000021
0.000025
0.000023
0.000022
0.000001
32,768
h2d
torch.float16
1.345098
0.000023
0.00003
0.000025
0.000025
0.000003
32,768
d2h
torch.float16
1.206267
0.000025
0.00003
0.000027
0.000026
0.000002
65,536
h2d
torch.float16
2.285892
0.000024
0.000028
0.000026
0.000026
0.000001
65,536
d2h
torch.float16
2.359412
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0.000029
0.000027
0.000026
0.000001
131,072
h2d
torch.float16
4.542388
0.000028
0.000033
0.00003
0.00003
0.000002
131,072
d2h
torch.float16
4.054738
0.000031
0.000036
0.000033
0.000032
0.000002
262,144
h2d
torch.float16
7.438957
0.000037
0.000041
0.000039
0.000039
0.000001
262,144
d2h
torch.float16
6.244389
0.000042
0.000049
0.000044
0.000043
0.000003
524,288
h2d
torch.float16
11.015586
0.000055
0.00006
0.000057
0.000057
0.000002
524,288
d2h
torch.float16
8.495985
0.000062
0.00007
0.000065
0.000064
0.000003
1,048,576
h2d
torch.float16
14.928861
0.000092
0.000104
0.000096
0.000095
0.000004
1,048,576
d2h
torch.float16
10.14952
0.00009
0.000094
0.000092
0.000091
0.000002
2,097,152
h2d
torch.float16
21.318601
0.000142
0.000156
0.000148
0.000147
0.000005
2,097,152
d2h
torch.float16
13.180831
0.000146
0.000159
0.00015
0.000147
0.000005
4,194,304
h2d
torch.float16
25.988996
0.000246
0.000266
0.000254
0.00025
0.000008
4,194,304
d2h
torch.float16
15.362099
0.000257
0.000283
0.000268
0.000264
0.00001
8,388,608
h2d
torch.float16
29.187364
0.00046
0.000504
0.000471
0.000463
0.000016
8,388,608
d2h
torch.float16
16.569881
0.000554
0.00058
0.000564
0.00056
0.00001
16,777,216
h2d
torch.float16
27.719943
0.000889
0.000947
0.000912
0.000915
0.000021
16,777,216
d2h
torch.float16
17.125705
0.001344
0.001427
0.001365
0.001347
0.000032
33,554,432
h2d
torch.float16
22.891868
0.001866
0.001908
0.001887
0.001893
0.000015
33,554,432
d2h
torch.float16
16.561619
0.002242
0.002692
0.002448
0.002438
0.000143
67,108,864
h2d
torch.float16
25.536053
0.003115
0.003223
0.003145
0.003123
0.00004
67,108,864
d2h
torch.float16
19.872824
0.004593
0.004699
0.00465
0.004663
0.000037
134,217,728
h2d
torch.float16
26.884477
0.006351
0.006478
0.006407
0.006402
0.000046
134,217,728
d2h
torch.float16
19.511407
0.009214
0.009262
0.009239
0.009244
0.000017
268,435,456
h2d
torch.float16
27.059951
0.013024
0.013187
0.013109
0.013117
0.000055
268,435,456
d2h
torch.float16
19.070721
0.018672
0.01886
0.018748
0.018754
0.000067
536,870,912
h2d
torch.float16
26.669392
0.026022
0.026185
0.02612
0.026167
0.000066
536,870,912
d2h
torch.float16
19.142162
0.035515
0.035889
0.035722
0.035737
0.00012
1,073,741,824
h2d
torch.float16
27.994237
0.052033
0.053091
0.052359
0.05219
0.00039
1,073,741,824
d2h
torch.float16
19.099034
0.070362
0.070952
0.070705
0.070704
0.000211
2,147,483,648
h2d
torch.float16
28.28641
0.113271
0.114164
0.113669
0.11361
0.000359
2,147,483,648
d2h
torch.float16
17.594899
0.144806
0.147492
0.145702
0.145119
0.001033
4,294,967,296
h2d
torch.float16
27.45332
0.197894
0.198621
0.198352
0.198467
0.000263
4,294,967,296
d2h
torch.float16
20.16622
0.28958
0.291023
0.290267
0.290179
0.000507
8,589,934,592
h2d
torch.float16
27.560816
0.44575
0.448243
0.446592
0.446125
0.000897
8,589,934,592
d2h
torch.float16
17.913429
0.583846
0.652117
0.621882
0.644052
0.030658
17,179,869,184
h2d
torch.float16
25.728362
0.903096
0.954482
0.925125
0.90891
0.023419
17,179,869,184
d2h
torch.float16
17.294952
null
null
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null
1,024
d2h
null
null
null
null
null
null
null
2,048
d2h
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4,096
d2h
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null
null
8,192
d2h
null
null
null
null
null
null
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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
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262,144
d2h
null
null
null
null
null
null
null
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d2h
null
null
null
null
null
null
null
1,048,576
d2h
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null
null
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null
null
2,097,152
d2h
null
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null
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null
null
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4,194,304
d2h
null
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null
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null
null
null
8,388,608
d2h
null
null
null
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null
null
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d2h
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null
null
null
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null
null
33,554,432
d2h
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null
null
67,108,864
d2h
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null
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134,217,728
d2h
null
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null
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null
null
268,435,456
d2h
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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
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1,024
h2d
null
null
null
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null
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2,048
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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
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null
null
134,217,728
h2d
null
null
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null
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268,435,456
h2d
null
null
null
null
null
null
null
536,870,912
h2d
null
null
null
null
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null
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h2d
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h2d
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4,294,967,296
h2d
null
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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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