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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 5 new columns ({'time_stats.send_recv.median', 'time_stats.send_recv.min', 'time_stats.send_recv.max', 'time_stats.send_recv.mean', 'time_stats.send_recv.std'}) and 5 missing columns ({'time_stats.all_reduce.min', 'time_stats.all_reduce.max', 'time_stats.all_reduce.mean', 'time_stats.all_reduce.std', 'time_stats.all_reduce.median'}).
This happened while the csv dataset builder was generating data using
/tmp/hf-datasets-cache/medium/datasets/91099307809417-config-parquet-and-info-project-vajra-dev-staging-6382ba24/hub/datasets--project-vajra--dev-staging-h100-dgx/snapshots/229812664025961536fe35b67b6dede9a190f16d/send_recv.csv.xz
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 1870, in _prepare_split_single
writer.write_table(table)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 622, 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 2292, in table_cast
return cast_table_to_schema(table, schema)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2240, in cast_table_to_schema
raise CastError(
datasets.table.CastError: Couldn't cast
Unnamed: 0: int64
time_stats.send_recv.min: double
time_stats.send_recv.max: double
time_stats.send_recv.mean: double
time_stats.send_recv.median: double
time_stats.send_recv.std: double
rank: int64
num_workers: int64
size: int64
collective: string
devices_per_node: int64
max_devices_per_node: int64
-- schema metadata --
pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 1847
to
{'Unnamed: 0': Value(dtype='int64', id=None), 'time_stats.all_reduce.min': Value(dtype='float64', id=None), 'time_stats.all_reduce.max': Value(dtype='float64', id=None), 'time_stats.all_reduce.mean': Value(dtype='float64', id=None), 'time_stats.all_reduce.median': Value(dtype='float64', id=None), 'time_stats.all_reduce.std': Value(dtype='float64', id=None), 'rank': Value(dtype='int64', id=None), 'num_workers': Value(dtype='int64', id=None), 'size': Value(dtype='int64', id=None), 'collective': Value(dtype='string', id=None), 'devices_per_node': Value(dtype='int64', id=None), 'max_devices_per_node': 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 1420, 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 1052, in convert_to_parquet
builder.download_and_prepare(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 924, in download_and_prepare
self._download_and_prepare(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1000, 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 1741, 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 1872, 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 5 new columns ({'time_stats.send_recv.median', 'time_stats.send_recv.min', 'time_stats.send_recv.max', 'time_stats.send_recv.mean', 'time_stats.send_recv.std'}) and 5 missing columns ({'time_stats.all_reduce.min', 'time_stats.all_reduce.max', 'time_stats.all_reduce.mean', 'time_stats.all_reduce.std', 'time_stats.all_reduce.median'}).
This happened while the csv dataset builder was generating data using
/tmp/hf-datasets-cache/medium/datasets/91099307809417-config-parquet-and-info-project-vajra-dev-staging-6382ba24/hub/datasets--project-vajra--dev-staging-h100-dgx/snapshots/229812664025961536fe35b67b6dede9a190f16d/send_recv.csv.xz
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.
Unnamed: 0 int64 | time_stats.all_reduce.min float64 | time_stats.all_reduce.max float64 | time_stats.all_reduce.mean float64 | time_stats.all_reduce.median float64 | time_stats.all_reduce.std float64 | rank int64 | num_workers int64 | size int64 | collective string | devices_per_node int64 | max_devices_per_node int64 |
|---|---|---|---|---|---|---|---|---|---|---|---|
0 | 0.018 | 0.038 | 0.030667 | 0.036 | 0.008994 | 0 | 8 | 2,048 | all_reduce | 8 | 8 |
1 | 0.019 | 0.037 | 0.031 | 0.037 | 0.008485 | 0 | 8 | 10,240 | all_reduce | 8 | 8 |
2 | 0.036 | 0.041 | 0.037667 | 0.036 | 0.002357 | 0 | 8 | 18,432 | all_reduce | 8 | 8 |
3 | 0.019 | 0.038 | 0.031333 | 0.037 | 0.008731 | 0 | 8 | 26,624 | all_reduce | 8 | 8 |
4 | 0.038 | 0.04 | 0.039 | 0.039 | 0.000816 | 0 | 8 | 34,816 | all_reduce | 8 | 8 |
5 | 0.035 | 0.04 | 0.038333 | 0.04 | 0.002357 | 0 | 8 | 43,008 | all_reduce | 8 | 8 |
6 | 0.035 | 0.038 | 0.036667 | 0.037 | 0.001247 | 0 | 8 | 51,200 | all_reduce | 8 | 8 |
7 | 0.037 | 0.045 | 0.04 | 0.038 | 0.003559 | 0 | 8 | 59,392 | all_reduce | 8 | 8 |
8 | 0.04 | 0.042 | 0.041 | 0.041 | 0.000816 | 0 | 8 | 67,584 | all_reduce | 8 | 8 |
9 | 0.033 | 0.039 | 0.036333 | 0.037 | 0.002494 | 0 | 8 | 75,776 | all_reduce | 8 | 8 |
10 | 0.037 | 0.04 | 0.038667 | 0.039 | 0.001247 | 0 | 8 | 83,968 | all_reduce | 8 | 8 |
11 | 0.038 | 0.041 | 0.039 | 0.038 | 0.001414 | 0 | 8 | 92,160 | all_reduce | 8 | 8 |
12 | 0.037 | 0.042 | 0.039 | 0.038 | 0.00216 | 0 | 8 | 100,352 | all_reduce | 8 | 8 |
13 | 0.02 | 0.036 | 0.030667 | 0.036 | 0.007542 | 0 | 8 | 108,544 | all_reduce | 8 | 8 |
14 | 0.037 | 0.04 | 0.038333 | 0.038 | 0.001247 | 0 | 8 | 116,736 | all_reduce | 8 | 8 |
15 | 0.036 | 0.041 | 0.038333 | 0.038 | 0.002055 | 0 | 8 | 124,928 | all_reduce | 8 | 8 |
16 | 0.037 | 0.04 | 0.038667 | 0.039 | 0.001247 | 0 | 8 | 133,120 | all_reduce | 8 | 8 |
17 | 0.034 | 0.039 | 0.037 | 0.038 | 0.00216 | 0 | 8 | 141,312 | all_reduce | 8 | 8 |
18 | 0.038 | 0.038 | 0.038 | 0.038 | 0 | 0 | 8 | 149,504 | all_reduce | 8 | 8 |
19 | 0.026 | 0.04 | 0.034333 | 0.037 | 0.006018 | 0 | 8 | 157,696 | all_reduce | 8 | 8 |
20 | 0.031 | 0.038 | 0.035 | 0.036 | 0.002944 | 0 | 8 | 165,888 | all_reduce | 8 | 8 |
21 | 0.03 | 0.038 | 0.034667 | 0.036 | 0.003399 | 0 | 8 | 174,080 | all_reduce | 8 | 8 |
22 | 0.022 | 0.043 | 0.035 | 0.04 | 0.009274 | 0 | 8 | 182,272 | all_reduce | 8 | 8 |
23 | 0.02 | 0.038 | 0.026 | 0.02 | 0.008485 | 0 | 8 | 190,464 | all_reduce | 8 | 8 |
24 | 0.037 | 0.039 | 0.038333 | 0.039 | 0.000943 | 0 | 8 | 198,656 | all_reduce | 8 | 8 |
25 | 0.026 | 0.038 | 0.033333 | 0.036 | 0.005249 | 0 | 8 | 206,848 | all_reduce | 8 | 8 |
26 | 0.027 | 0.041 | 0.035333 | 0.038 | 0.006018 | 0 | 8 | 215,040 | all_reduce | 8 | 8 |
27 | 0.038 | 0.04 | 0.038667 | 0.038 | 0.000943 | 0 | 8 | 223,232 | all_reduce | 8 | 8 |
28 | 0.037 | 0.04 | 0.038667 | 0.039 | 0.001247 | 0 | 8 | 231,424 | all_reduce | 8 | 8 |
29 | 0.033 | 0.039 | 0.035667 | 0.035 | 0.002494 | 0 | 8 | 239,616 | all_reduce | 8 | 8 |
30 | 0.036 | 0.04 | 0.038333 | 0.039 | 0.0017 | 0 | 8 | 247,808 | all_reduce | 8 | 8 |
31 | 0.038 | 0.039 | 0.038667 | 0.039 | 0.000471 | 0 | 8 | 256,000 | all_reduce | 8 | 8 |
32 | 0.033 | 0.042 | 0.039 | 0.042 | 0.004243 | 0 | 8 | 264,192 | all_reduce | 8 | 8 |
33 | 0.02 | 0.051 | 0.030333 | 0.02 | 0.014614 | 0 | 8 | 272,384 | all_reduce | 8 | 8 |
34 | 0.035 | 0.043 | 0.038667 | 0.038 | 0.0033 | 0 | 8 | 280,576 | all_reduce | 8 | 8 |
35 | 0.037 | 0.038 | 0.037333 | 0.037 | 0.000471 | 0 | 8 | 288,768 | all_reduce | 8 | 8 |
36 | 0.036 | 0.042 | 0.038333 | 0.037 | 0.002625 | 0 | 8 | 296,960 | all_reduce | 8 | 8 |
37 | 0.036 | 0.038 | 0.037 | 0.037 | 0.000816 | 0 | 8 | 305,152 | all_reduce | 8 | 8 |
38 | 0.038 | 0.041 | 0.039 | 0.038 | 0.001414 | 0 | 8 | 313,344 | all_reduce | 8 | 8 |
39 | 0.036 | 0.039 | 0.037333 | 0.037 | 0.001247 | 0 | 8 | 321,536 | all_reduce | 8 | 8 |
40 | 0.03 | 0.044 | 0.037 | 0.037 | 0.005715 | 0 | 8 | 329,728 | all_reduce | 8 | 8 |
41 | 0.039 | 0.041 | 0.04 | 0.04 | 0.000816 | 0 | 8 | 337,920 | all_reduce | 8 | 8 |
42 | 0.04 | 0.053 | 0.046333 | 0.046 | 0.005312 | 0 | 8 | 346,112 | all_reduce | 8 | 8 |
43 | 0.037 | 0.041 | 0.038667 | 0.038 | 0.0017 | 0 | 8 | 354,304 | all_reduce | 8 | 8 |
44 | 0.04 | 0.043 | 0.041667 | 0.042 | 0.001247 | 0 | 8 | 362,496 | all_reduce | 8 | 8 |
45 | 0.036 | 0.039 | 0.037667 | 0.038 | 0.001247 | 0 | 8 | 370,688 | all_reduce | 8 | 8 |
46 | 0.04 | 0.042 | 0.041 | 0.041 | 0.000816 | 0 | 8 | 378,880 | all_reduce | 8 | 8 |
47 | 0.037 | 0.039 | 0.038333 | 0.039 | 0.000943 | 0 | 8 | 387,072 | all_reduce | 8 | 8 |
48 | 0.037 | 0.041 | 0.039333 | 0.04 | 0.0017 | 0 | 8 | 395,264 | all_reduce | 8 | 8 |
49 | 0.039 | 0.041 | 0.04 | 0.04 | 0.000816 | 0 | 8 | 403,456 | all_reduce | 8 | 8 |
50 | 0.037 | 0.042 | 0.039667 | 0.04 | 0.002055 | 0 | 8 | 411,648 | all_reduce | 8 | 8 |
51 | 0.038 | 0.042 | 0.039667 | 0.039 | 0.0017 | 0 | 8 | 419,840 | all_reduce | 8 | 8 |
52 | 0.041 | 0.043 | 0.042 | 0.042 | 0.000816 | 0 | 8 | 428,032 | all_reduce | 8 | 8 |
53 | 0.039 | 0.043 | 0.040333 | 0.039 | 0.001886 | 0 | 8 | 436,224 | all_reduce | 8 | 8 |
54 | 0.038 | 0.039 | 0.038667 | 0.039 | 0.000471 | 0 | 8 | 444,416 | all_reduce | 8 | 8 |
55 | 0.041 | 0.041 | 0.041 | 0.041 | 0 | 0 | 8 | 452,608 | all_reduce | 8 | 8 |
56 | 0.04 | 0.042 | 0.041 | 0.041 | 0.000816 | 0 | 8 | 460,800 | all_reduce | 8 | 8 |
57 | 0.031 | 0.056 | 0.042 | 0.039 | 0.010424 | 0 | 8 | 468,992 | all_reduce | 8 | 8 |
58 | 0.039 | 0.04 | 0.039667 | 0.04 | 0.000471 | 0 | 8 | 477,184 | all_reduce | 8 | 8 |
59 | 0.042 | 0.043 | 0.042667 | 0.043 | 0.000471 | 0 | 8 | 485,376 | all_reduce | 8 | 8 |
60 | 0.041 | 0.046 | 0.043333 | 0.043 | 0.002055 | 0 | 8 | 493,568 | all_reduce | 8 | 8 |
61 | 0.029 | 0.031 | 0.03 | 0.03 | 0.000816 | 0 | 8 | 501,760 | all_reduce | 8 | 8 |
62 | 0.03 | 0.03 | 0.03 | 0.03 | 0 | 0 | 8 | 509,952 | all_reduce | 8 | 8 |
63 | 0.03 | 0.031 | 0.030333 | 0.03 | 0.000471 | 0 | 8 | 518,144 | all_reduce | 8 | 8 |
64 | 0.027 | 0.029 | 0.028 | 0.028 | 0.000816 | 0 | 8 | 526,336 | all_reduce | 8 | 8 |
65 | 0.027 | 0.028 | 0.027667 | 0.028 | 0.000471 | 0 | 8 | 534,528 | all_reduce | 8 | 8 |
66 | 0.028 | 0.03 | 0.029 | 0.029 | 0.000816 | 0 | 8 | 542,720 | all_reduce | 8 | 8 |
67 | 0.028 | 0.029 | 0.028333 | 0.028 | 0.000471 | 0 | 8 | 550,912 | all_reduce | 8 | 8 |
68 | 0.027 | 0.03 | 0.028333 | 0.028 | 0.001247 | 0 | 8 | 559,104 | all_reduce | 8 | 8 |
69 | 0.027 | 0.03 | 0.028667 | 0.029 | 0.001247 | 0 | 8 | 567,296 | all_reduce | 8 | 8 |
70 | 0.028 | 0.029 | 0.028667 | 0.029 | 0.000471 | 0 | 8 | 575,488 | all_reduce | 8 | 8 |
71 | 0.029 | 0.03 | 0.029333 | 0.029 | 0.000471 | 0 | 8 | 583,680 | all_reduce | 8 | 8 |
72 | 0.028 | 0.029 | 0.028333 | 0.028 | 0.000471 | 0 | 8 | 591,872 | all_reduce | 8 | 8 |
73 | 0.028 | 0.03 | 0.028667 | 0.028 | 0.000943 | 0 | 8 | 600,064 | all_reduce | 8 | 8 |
74 | 0.028 | 0.028 | 0.028 | 0.028 | 0 | 0 | 8 | 608,256 | all_reduce | 8 | 8 |
75 | 0.028 | 0.029 | 0.028333 | 0.028 | 0.000471 | 0 | 8 | 616,448 | all_reduce | 8 | 8 |
76 | 0.028 | 0.031 | 0.029 | 0.028 | 0.001414 | 0 | 8 | 624,640 | all_reduce | 8 | 8 |
77 | 0.028 | 0.028 | 0.028 | 0.028 | 0 | 0 | 8 | 632,832 | all_reduce | 8 | 8 |
78 | 0.029 | 0.03 | 0.029333 | 0.029 | 0.000471 | 0 | 8 | 641,024 | all_reduce | 8 | 8 |
79 | 0.029 | 0.03 | 0.029333 | 0.029 | 0.000471 | 0 | 8 | 649,216 | all_reduce | 8 | 8 |
80 | 0.029 | 0.029 | 0.029 | 0.029 | 0 | 0 | 8 | 657,408 | all_reduce | 8 | 8 |
81 | 0.028 | 0.03 | 0.029 | 0.029 | 0.000816 | 0 | 8 | 665,600 | all_reduce | 8 | 8 |
82 | 0.029 | 0.03 | 0.029333 | 0.029 | 0.000471 | 0 | 8 | 673,792 | all_reduce | 8 | 8 |
83 | 0.029 | 0.032 | 0.03 | 0.029 | 0.001414 | 0 | 8 | 681,984 | all_reduce | 8 | 8 |
84 | 0.029 | 0.029 | 0.029 | 0.029 | 0 | 0 | 8 | 690,176 | all_reduce | 8 | 8 |
85 | 0.029 | 0.03 | 0.029333 | 0.029 | 0.000471 | 0 | 8 | 698,368 | all_reduce | 8 | 8 |
86 | 0.03 | 0.03 | 0.03 | 0.03 | 0 | 0 | 8 | 706,560 | all_reduce | 8 | 8 |
87 | 0.029 | 0.029 | 0.029 | 0.029 | 0 | 0 | 8 | 714,752 | all_reduce | 8 | 8 |
88 | 0.029 | 0.029 | 0.029 | 0.029 | 0 | 0 | 8 | 722,944 | all_reduce | 8 | 8 |
89 | 0.029 | 0.03 | 0.029667 | 0.03 | 0.000471 | 0 | 8 | 731,136 | all_reduce | 8 | 8 |
90 | 0.029 | 0.031 | 0.029667 | 0.029 | 0.000943 | 0 | 8 | 739,328 | all_reduce | 8 | 8 |
91 | 0.029 | 0.03 | 0.029333 | 0.029 | 0.000471 | 0 | 8 | 747,520 | all_reduce | 8 | 8 |
92 | 0.029 | 0.029 | 0.029 | 0.029 | 0 | 0 | 8 | 755,712 | all_reduce | 8 | 8 |
93 | 0.03 | 0.03 | 0.03 | 0.03 | 0 | 0 | 8 | 763,904 | all_reduce | 8 | 8 |
94 | 0.029 | 0.03 | 0.029667 | 0.03 | 0.000471 | 0 | 8 | 772,096 | all_reduce | 8 | 8 |
95 | 0.029 | 0.03 | 0.029667 | 0.03 | 0.000471 | 0 | 8 | 780,288 | all_reduce | 8 | 8 |
96 | 0.03 | 0.03 | 0.03 | 0.03 | 0 | 0 | 8 | 788,480 | all_reduce | 8 | 8 |
97 | 0.03 | 0.031 | 0.030333 | 0.03 | 0.000471 | 0 | 8 | 796,672 | all_reduce | 8 | 8 |
98 | 0.03 | 0.031 | 0.030333 | 0.03 | 0.000471 | 0 | 8 | 804,864 | all_reduce | 8 | 8 |
99 | 0.03 | 0.031 | 0.030333 | 0.03 | 0.000471 | 0 | 8 | 813,056 | all_reduce | 8 | 8 |
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