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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 1 new columns ({'stats'}) and 2 missing columns ({'length', 'tasks'}).
This happened while the json dataset builder was generating data using
hf://datasets/csuvla/piperdata/meta/episodes_stats.jsonl (at revision 04e410f89c2c7c7010b85675a061e8aec9a42d6f)
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 1871, in _prepare_split_single
writer.write_table(table)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 643, 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 2293, in table_cast
return cast_table_to_schema(table, schema)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2241, in cast_table_to_schema
raise CastError(
datasets.table.CastError: Couldn't cast
episode_index: int64
stats: struct<observation.state: struct<min: list<item: double>, max: list<item: double>, mean: list<item: double>, std: list<item: double>, count: list<item: int64>>, action: struct<min: list<item: double>, max: list<item: double>, mean: list<item: double>, std: list<item: double>, count: list<item: int64>>, observation.images.cam_high: struct<min: list<item: list<item: list<item: double>>>, max: list<item: list<item: list<item: double>>>, mean: list<item: list<item: list<item: double>>>, std: list<item: list<item: list<item: double>>>, count: list<item: int64>>, observation.images.cam_low: struct<min: list<item: list<item: list<item: double>>>, max: list<item: list<item: list<item: double>>>, mean: list<item: list<item: list<item: double>>>, std: list<item: list<item: list<item: double>>>, count: list<item: int64>>, observation.images.cam_left_wrist: struct<min: list<item: list<item: list<item: double>>>, max: list<item: list<item: list<item: double>>>, mean: list<item: list<item: list<item: double>>>, std: list<item: list<item: list<item: double>>>, count: list<item: int64>>, observation.images.cam_right_wrist: struct<min: list<item: list<item: list<item: double>>>, max: list<item: list<item: list<item: double>>>, mean: list<item: list<item: list<item: double>>>, std: list<item: list<item: list<item: double>>>, count: list<item: int64>>, timestamp: struct<min: list<item: double>, max: list<item: double>, mean: list<item: double>, std: list<item: double
...
index: struct<min: list<item: int64>, max: list<item: int64>, mean: list<item: double>, std: list<item: double>, count: list<item: int64>>
child 0, min: list<item: int64>
child 0, item: int64
child 1, max: list<item: int64>
child 0, item: int64
child 2, mean: list<item: double>
child 0, item: double
child 3, std: list<item: double>
child 0, item: double
child 4, count: list<item: int64>
child 0, item: int64
child 9, index: struct<min: list<item: int64>, max: list<item: int64>, mean: list<item: double>, std: list<item: double>, count: list<item: int64>>
child 0, min: list<item: int64>
child 0, item: int64
child 1, max: list<item: int64>
child 0, item: int64
child 2, mean: list<item: double>
child 0, item: double
child 3, std: list<item: double>
child 0, item: double
child 4, count: list<item: int64>
child 0, item: int64
child 10, task_index: struct<min: list<item: int64>, max: list<item: int64>, mean: list<item: double>, std: list<item: double>, count: list<item: int64>>
child 0, min: list<item: int64>
child 0, item: int64
child 1, max: list<item: int64>
child 0, item: int64
child 2, mean: list<item: double>
child 0, item: double
child 3, std: list<item: double>
child 0, item: double
child 4, count: list<item: int64>
child 0, item: int64
to
{'episode_index': Value(dtype='int64', id=None), 'tasks': Sequence(feature=Value(dtype='string', id=None), length=-1, id=None), 'length': 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 1433, 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 1050, in convert_to_parquet
builder.download_and_prepare(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 925, in download_and_prepare
self._download_and_prepare(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1001, 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 1742, 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 1873, 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 1 new columns ({'stats'}) and 2 missing columns ({'length', 'tasks'}).
This happened while the json dataset builder was generating data using
hf://datasets/csuvla/piperdata/meta/episodes_stats.jsonl (at revision 04e410f89c2c7c7010b85675a061e8aec9a42d6f)
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.
episode_index int64 | tasks sequence | length int64 |
|---|---|---|
0 | [
"五合一数字5-517mm"
] | 752 |
1 | [
"五合一数字5-517mm"
] | 1,009 |
2 | [
"五合一数字5-517mm"
] | 849 |
3 | [
"五合一数字5-517mm"
] | 1,103 |
4 | [
"五合一数字5-517mm"
] | 745 |
5 | [
"五合一数字5-517mm"
] | 623 |
6 | [
"五合一数字5-517mm"
] | 562 |
7 | [
"五合一数字5-517mm"
] | 741 |
8 | [
"五合一数字5-517mm"
] | 609 |
9 | [
"五合一数字5-517mm"
] | 757 |
10 | [
"五合一数字5-517mm"
] | 725 |
11 | [
"五合一数字5-517mm"
] | 880 |
12 | [
"五合一数字5-517mm"
] | 782 |
13 | [
"五合一数字5-517mm"
] | 753 |
14 | [
"五合一数字5-517mm"
] | 653 |
15 | [
"五合一数字5-517mm"
] | 630 |
16 | [
"五合一数字5-517mm"
] | 705 |
17 | [
"五合一数字5-517mm"
] | 851 |
18 | [
"五合一数字5-517mm"
] | 522 |
19 | [
"五合一数字5-517mm"
] | 770 |
20 | [
"五合一数字5-517mm"
] | 584 |
21 | [
"五合一数字5-517mm"
] | 646 |
22 | [
"五合一数字5-517mm"
] | 761 |
23 | [
"五合一数字5-517mm"
] | 510 |
24 | [
"五合一数字5-517mm"
] | 868 |
25 | [
"五合一数字5-517mm"
] | 588 |
26 | [
"五合一数字5-517mm"
] | 661 |
27 | [
"五合一数字5-517mm"
] | 562 |
28 | [
"五合一数字5-517mm"
] | 613 |
29 | [
"五合一数字5-517mm"
] | 581 |
30 | [
"五合一数字5-517mm"
] | 516 |
31 | [
"五合一数字5-517mm"
] | 668 |
32 | [
"五合一数字5-517mm"
] | 696 |
33 | [
"五合一数字5-517mm"
] | 938 |
34 | [
"五合一数字5-517mm"
] | 547 |
35 | [
"五合一数字5-517mm"
] | 877 |
36 | [
"五合一数字5-517mm"
] | 592 |
37 | [
"五合一数字5-517mm"
] | 590 |
38 | [
"五合一数字5-517mm"
] | 674 |
39 | [
"五合一数字5-517mm"
] | 588 |
40 | [
"五合一数字5-517mm"
] | 658 |
41 | [
"五合一数字5-517mm"
] | 667 |
42 | [
"五合一数字5-517mm"
] | 768 |
43 | [
"五合一数字5-517mm"
] | 803 |
44 | [
"五合一数字5-517mm"
] | 933 |
45 | [
"五合一数字5-517mm"
] | 843 |
46 | [
"五合一数字5-517mm"
] | 498 |
47 | [
"五合一数字5-517mm"
] | 765 |
48 | [
"五合一数字5-517mm"
] | 616 |
49 | [
"五合一数字5-517mm"
] | 545 |
50 | [
"五合一数字6-517mm"
] | 637 |
51 | [
"五合一数字6-517mm"
] | 1,322 |
52 | [
"五合一数字6-517mm"
] | 864 |
53 | [
"五合一数字6-517mm"
] | 492 |
54 | [
"五合一数字6-517mm"
] | 854 |
55 | [
"五合一数字6-517mm"
] | 845 |
56 | [
"五合一数字6-517mm"
] | 771 |
57 | [
"五合一数字6-517mm"
] | 1,003 |
58 | [
"五合一数字6-517mm"
] | 751 |
59 | [
"五合一数字6-517mm"
] | 671 |
60 | [
"五合一数字6-517mm"
] | 602 |
61 | [
"五合一数字6-517mm"
] | 735 |
62 | [
"五合一数字6-517mm"
] | 614 |
63 | [
"五合一数字6-517mm"
] | 673 |
64 | [
"五合一数字6-517mm"
] | 706 |
65 | [
"五合一数字6-517mm"
] | 591 |
66 | [
"五合一数字6-517mm"
] | 725 |
67 | [
"五合一数字6-517mm"
] | 591 |
68 | [
"五合一数字6-517mm"
] | 688 |
69 | [
"五合一数字6-517mm"
] | 572 |
70 | [
"五合一数字6-517mm"
] | 841 |
0 | null | null |
1 | null | null |
2 | null | null |
3 | null | null |
4 | null | null |
5 | null | null |
6 | null | null |
7 | null | null |
8 | null | null |
9 | null | null |
10 | null | null |
11 | null | null |
12 | null | null |
13 | null | null |
14 | null | null |
15 | null | null |
16 | null | null |
17 | null | null |
18 | null | null |
19 | null | null |
20 | null | null |
21 | null | null |
22 | null | null |
23 | null | null |
24 | null | null |
25 | null | null |
26 | null | null |
27 | null | null |
28 | null | null |
End of preview.