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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 80 new columns ({'p05_n119', 'p01_n176', 'p05_n155', 'p09_n188', 'p07_n132', 'p09_n168', 'p09_n189', 'p01_n167', 'p05_n179', 'p09_n114', 'p05_n147', 'p05_n121', 'p07_n113', 'p09_n171', 'p05_n154', 'p09_n160', 'p07_n161', 'p05_n126', 'p09_n190', 'p07_n164', 'p05_n156', 'p09_n142', 'p05_n153', 'p05_n174', 'p05_n116', 'p01_n131', 'p07_n158', 'p09_n124', 'p05_n187', 'p09_n172', 'p07_n139', 'p09_n123', 'p09_n150', 'p01_n136', 'p09_n137', 'p05_n178', 'p09_n169', 'p01_n148', 'p07_n127', 'p05_n125', 'p09_n122', 'p05_n166', 'p05_n134', 'p07_n117', 'p09_n177', 'p09_n112', 'p05_n183', 'p05_n157', 'p01_n191', 'p09_n115', 'p01_n135', 'p09_n163', 'p05_n128', 'p07_n165', 'p09_n152', 'p07_n184', 'p05_n130', 'p01_n162', 'p05_n144', 'p05_n146', 'p07_n149', 'p07_n181', 'p09_n180', 'p07_n185', 'p07_n141', 'p09_n133', 'p05_n140', 'p07_n159', 'p07_n151', 'p05_n129', 'p05_n186', 'p01_n182', 'p01_n138', 'p07_n173', 'p09_n143', 'p05_n145', 'p09_n120', 'p09_n175', 'p09_n170', 'p05_n118'}) and 112 missing columns ({'p04_n103', 'p01_n002', 'p01_n060', 'p06_n036', 'p04_n073', 'p05_n083', 'p01_n057', 'p05_n029', 'p05_n006', 'p01_n093', 'p05_n048', 'p01_n063', 'p05_n027', 'p05_n009', 'p04_n030', 'p06_n021', 'p05_n070', 'p04_n068', 'p01_n102', 'p05_n041', 'p06_n015', 'p05_n095', 'p06_n055', 'p01_n010', 'p02_n100', 'p04_n005', 'p01_n081', 'p06_n020', 'p05_n037', 'p04_n011', 'p01_n111', 'p05_n022', 'p04_n046', 'p01_n053', 'p01_n045', 'p02_n097', 'p02_n001', 'p05_n084', 'p05_n043', 'p05_n065', 'p06_n013', 'p02_n072', 'p05_n078', 'p01_n012', 'p01_n023', 'p04_n058', 'p01_n108', 'p06_n054', 'p06_n018', 'p01_n050', 'p01_n099', 'p02_n101', 'p05_n062', 'p01_n110', 'p06_n039', 'p02_n066', 'p01_n028', 'p06_n061', 'p06_n007', 'p01_n107', 'p06_n109', 'p05_n071', 'p01_n040', 'p06_n096', 'p01_n042', 'p05_n031', 'p05_n025', 'p05_n086', 'p02_n088', 'p04_n049', 'p06_n056', 'p04_n032', 'p01_n067', 'p01_n008', 'p01_n087', 'p05_n047', 'p01_n069', 'p01_n052', 'p04_n074', 'p04_n026', 'p06_n033', 'p05_n004', 'p05_n077', 'p01_n085', 'p01_n090', 'p05_n092', 'p04_n003', 'p04_n038', 'p04_n091', 'p04_n034', 'p05_n075', 'p01_n082', 'p01_n000', 'p05_n094', 'p04_n080', 'p04_n106', 'p02_n079', 'p01_n044', 'p05_n017', 'p04_n035', 'p04_n016', 'p02_n051', 'p02_n098', 'p05_n059', 'p05_n076', 'p06_n024', 'p01_n105', 'p04_n089', 'p02_n104', 'p06_n014', 'p06_n019', 'p05_n064'}).
This happened while the json dataset builder was generating data using
hf://datasets/mvazquez/LSE_eSaude_UVIGO_MSSL/data/val/val.json (at revision d58dec86dc1e680d142ec8e108ed48d06da35188)
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 2011, in _prepare_split_single
writer.write_table(table)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/arrow_writer.py", line 585, 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 2302, in table_cast
return cast_table_to_schema(table, schema)
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2256, in cast_table_to_schema
raise CastError(
datasets.table.CastError: Couldn't cast
p09_n114: list<item: list<item: int64>>
child 0, item: list<item: int64>
child 0, item: int64
p05_n119: list<item: list<item: int64>>
child 0, item: list<item: int64>
child 0, item: int64
p09_n189: list<item: list<item: int64>>
child 0, item: list<item: int64>
child 0, item: int64
p09_n152: list<item: list<item: int64>>
child 0, item: list<item: int64>
child 0, item: int64
p07_n127: list<item: list<item: int64>>
child 0, item: list<item: int64>
child 0, item: int64
p01_n136: list<item: list<item: int64>>
child 0, item: list<item: int64>
child 0, item: int64
p01_n162: list<item: list<item: int64>>
child 0, item: list<item: int64>
child 0, item: int64
p09_n112: list<item: list<item: int64>>
child 0, item: list<item: int64>
child 0, item: int64
p07_n158: list<item: list<item: int64>>
child 0, item: list<item: int64>
child 0, item: int64
p07_n173: list<item: list<item: int64>>
child 0, item: list<item: int64>
child 0, item: int64
p09_n171: list<item: list<item: int64>>
child 0, item: list<item: int64>
child 0, item: int64
p09_n143: list<item: list<item: int64>>
child 0, item: list<item: int64>
child 0, item: int64
p09_n137: list<item: list<item: int64>>
child 0, item: list<item: int64>
child 0, item: int64
p07_n151: list<item: list<item: int64>>
child 0, item: list<item: int64>
child 0, item: int64
p09_n180: list<item: list<item: int64>>
child 0, item: list<item: int6
...
m: int64>>
child 0, item: list<item: int64>
child 0, item: int64
p05_n125: list<item: list<item: int64>>
child 0, item: list<item: int64>
child 0, item: int64
p01_n131: list<item: list<item: int64>>
child 0, item: list<item: int64>
child 0, item: int64
p07_n139: list<item: list<item: int64>>
child 0, item: list<item: int64>
child 0, item: int64
p05_n145: list<item: list<item: int64>>
child 0, item: list<item: int64>
child 0, item: int64
p09_n168: list<item: list<item: int64>>
child 0, item: list<item: int64>
child 0, item: int64
p07_n113: list<item: list<item: int64>>
child 0, item: list<item: int64>
child 0, item: int64
p01_n148: list<item: list<item: int64>>
child 0, item: list<item: int64>
child 0, item: int64
p01_n138: list<item: list<item: int64>>
child 0, item: list<item: int64>
child 0, item: int64
p05_n178: list<item: list<item: int64>>
child 0, item: list<item: int64>
child 0, item: int64
p05_n174: list<item: list<item: int64>>
child 0, item: list<item: int64>
child 0, item: int64
p07_n185: list<item: list<item: int64>>
child 0, item: list<item: int64>
child 0, item: int64
p09_n133: list<item: list<item: int64>>
child 0, item: list<item: int64>
child 0, item: int64
p05_n146: list<item: list<item: int64>>
child 0, item: list<item: int64>
child 0, item: int64
p09_n124: list<item: list<item: int64>>
child 0, item: list<item: int64>
child 0, item: int64
to
{'p01_n002': Sequence(feature=Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), length=-1, id=None), 'p06_n019': Sequence(feature=Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), length=-1, id=None), 'p06_n007': Sequence(feature=Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), length=-1, id=None), 'p01_n053': Sequence(feature=Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), length=-1, id=None), 'p04_n074': Sequence(feature=Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), length=-1, id=None), 'p05_n077': Sequence(feature=Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), length=-1, id=None), 'p05_n027': Sequence(feature=Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), length=-1, id=None), 'p05_n022': Sequence(feature=Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), length=-1, id=None), 'p01_n110': Sequence(feature=Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), length=-1, id=None), 'p06_n036': Sequence(feature=Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), length=-1, id=None), 'p01_n069': Sequence(feature=Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), length=-1, id=None), 'p06_n109': Sequence(feature=Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), length=-1, id=None), 'p04_n089': Sequence(feature=Sequence(feature=Value(dtype='int64', id=N
...
Value(dtype='int64', id=None), length=-1, id=None), length=-1, id=None), 'p06_n056': Sequence(feature=Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), length=-1, id=None), 'p04_n080': Sequence(feature=Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), length=-1, id=None), 'p05_n062': Sequence(feature=Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), length=-1, id=None), 'p04_n034': Sequence(feature=Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), length=-1, id=None), 'p04_n049': Sequence(feature=Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), length=-1, id=None), 'p06_n033': Sequence(feature=Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), length=-1, id=None), 'p02_n100': Sequence(feature=Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), length=-1, id=None), 'p04_n030': Sequence(feature=Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), length=-1, id=None), 'p06_n054': Sequence(feature=Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), length=-1, id=None), 'p05_n047': Sequence(feature=Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), length=-1, id=None), 'p06_n021': Sequence(feature=Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), length=-1, id=None), 'p01_n081': Sequence(feature=Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), length=-1, 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 1321, 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 935, in convert_to_parquet
builder.download_and_prepare(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1027, in download_and_prepare
self._download_and_prepare(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1122, 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 1882, 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 2013, 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 80 new columns ({'p05_n119', 'p01_n176', 'p05_n155', 'p09_n188', 'p07_n132', 'p09_n168', 'p09_n189', 'p01_n167', 'p05_n179', 'p09_n114', 'p05_n147', 'p05_n121', 'p07_n113', 'p09_n171', 'p05_n154', 'p09_n160', 'p07_n161', 'p05_n126', 'p09_n190', 'p07_n164', 'p05_n156', 'p09_n142', 'p05_n153', 'p05_n174', 'p05_n116', 'p01_n131', 'p07_n158', 'p09_n124', 'p05_n187', 'p09_n172', 'p07_n139', 'p09_n123', 'p09_n150', 'p01_n136', 'p09_n137', 'p05_n178', 'p09_n169', 'p01_n148', 'p07_n127', 'p05_n125', 'p09_n122', 'p05_n166', 'p05_n134', 'p07_n117', 'p09_n177', 'p09_n112', 'p05_n183', 'p05_n157', 'p01_n191', 'p09_n115', 'p01_n135', 'p09_n163', 'p05_n128', 'p07_n165', 'p09_n152', 'p07_n184', 'p05_n130', 'p01_n162', 'p05_n144', 'p05_n146', 'p07_n149', 'p07_n181', 'p09_n180', 'p07_n185', 'p07_n141', 'p09_n133', 'p05_n140', 'p07_n159', 'p07_n151', 'p05_n129', 'p05_n186', 'p01_n182', 'p01_n138', 'p07_n173', 'p09_n143', 'p05_n145', 'p09_n120', 'p09_n175', 'p09_n170', 'p05_n118'}) and 112 missing columns ({'p04_n103', 'p01_n002', 'p01_n060', 'p06_n036', 'p04_n073', 'p05_n083', 'p01_n057', 'p05_n029', 'p05_n006', 'p01_n093', 'p05_n048', 'p01_n063', 'p05_n027', 'p05_n009', 'p04_n030', 'p06_n021', 'p05_n070', 'p04_n068', 'p01_n102', 'p05_n041', 'p06_n015', 'p05_n095', 'p06_n055', 'p01_n010', 'p02_n100', 'p04_n005', 'p01_n081', 'p06_n020', 'p05_n037', 'p04_n011', 'p01_n111', 'p05_n022', 'p04_n046', 'p01_n053', 'p01_n045', 'p02_n097', 'p02_n001', 'p05_n084', 'p05_n043', 'p05_n065', 'p06_n013', 'p02_n072', 'p05_n078', 'p01_n012', 'p01_n023', 'p04_n058', 'p01_n108', 'p06_n054', 'p06_n018', 'p01_n050', 'p01_n099', 'p02_n101', 'p05_n062', 'p01_n110', 'p06_n039', 'p02_n066', 'p01_n028', 'p06_n061', 'p06_n007', 'p01_n107', 'p06_n109', 'p05_n071', 'p01_n040', 'p06_n096', 'p01_n042', 'p05_n031', 'p05_n025', 'p05_n086', 'p02_n088', 'p04_n049', 'p06_n056', 'p04_n032', 'p01_n067', 'p01_n008', 'p01_n087', 'p05_n047', 'p01_n069', 'p01_n052', 'p04_n074', 'p04_n026', 'p06_n033', 'p05_n004', 'p05_n077', 'p01_n085', 'p01_n090', 'p05_n092', 'p04_n003', 'p04_n038', 'p04_n091', 'p04_n034', 'p05_n075', 'p01_n082', 'p01_n000', 'p05_n094', 'p04_n080', 'p04_n106', 'p02_n079', 'p01_n044', 'p05_n017', 'p04_n035', 'p04_n016', 'p02_n051', 'p02_n098', 'p05_n059', 'p05_n076', 'p06_n024', 'p01_n105', 'p04_n089', 'p02_n104', 'p06_n014', 'p06_n019', 'p05_n064'}).
This happened while the json dataset builder was generating data using
hf://datasets/mvazquez/LSE_eSaude_UVIGO_MSSL/data/val/val.json (at revision d58dec86dc1e680d142ec8e108ed48d06da35188)
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.
p01_n002
sequence | p06_n019
sequence | p06_n007
sequence | p01_n053
sequence | p04_n074
sequence | p05_n077
sequence | p05_n027
sequence | p05_n022
sequence | p01_n110
sequence | p06_n036
sequence | p01_n069
sequence | p06_n109
sequence | p04_n089
sequence | p01_n044
sequence | p05_n037
sequence | p04_n038
sequence | p06_n055
sequence | p01_n099
sequence | p02_n066
sequence | p04_n035
sequence | p01_n057
sequence | p01_n105
sequence | p04_n058
sequence | p05_n043
sequence | p06_n020
sequence | p02_n001
sequence | p04_n032
sequence | p05_n084
sequence | p01_n102
sequence | p06_n096
sequence | p02_n104
sequence | p01_n090
sequence | p01_n040
sequence | p04_n073
sequence | p01_n067
sequence | p05_n004
sequence | p06_n061
sequence | p05_n092
sequence | p06_n015
sequence | p04_n106
sequence | p05_n095
sequence | p02_n072
sequence | p05_n031
sequence | p01_n060
sequence | p05_n048
sequence | p05_n029
sequence | p01_n000
sequence | p01_n050
sequence | p05_n025
sequence | p04_n011
sequence | p01_n023
sequence | p01_n042
sequence | p01_n111
sequence | p05_n083
sequence | p05_n094
sequence | p04_n103
sequence | p01_n093
sequence | p04_n003
sequence | p05_n078
sequence | p01_n052
sequence | p02_n098
sequence | p06_n013
sequence | p05_n006
sequence | p01_n063
sequence | p02_n097
sequence | p05_n065
sequence | p01_n108
sequence | p06_n018
sequence | p05_n009
sequence | p05_n071
sequence | p04_n091
sequence | p05_n075
sequence | p01_n012
sequence | p05_n076
sequence | p04_n005
sequence | p04_n046
sequence | p01_n045
sequence | p05_n041
sequence | p01_n008
sequence | p02_n101
sequence | p01_n085
sequence | p05_n064
sequence | p05_n017
sequence | p01_n028
sequence | p02_n079
sequence | p01_n010
sequence | p01_n082
sequence | p01_n107
sequence | p02_n088
sequence | p01_n087
sequence | p05_n086
sequence | p06_n024
sequence | p05_n070
sequence | p04_n016
sequence | p04_n068
sequence | p04_n026
sequence | p06_n039
sequence | p06_n014
sequence | p05_n059
sequence | p02_n051
sequence | p06_n056
sequence | p04_n080
sequence | p05_n062
sequence | p04_n034
sequence | p04_n049
sequence | p06_n033
sequence | p02_n100
sequence | p04_n030
sequence | p06_n054
sequence | p05_n047
sequence | p06_n021
sequence | p01_n081
sequence |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
[
[
17,
640,
1200
],
[
8,
11000,
12000
],
[
36,
18960,
19320
],
[
39,
19800,
20080
],
[
39,
20400,
20760
],
[
1,
25360,
26360
],
[
41,
30600,
30920
],
[
37,
32960,
33320
],
[
50,
34680,
35040
],
[
12,
38800,
39120
],
[
25,
44640,
45120
],
[
59,
48160,
48480
],
[
45,
49840,
50040
],
[
12,
50400,
50760
],
[
7,
52600,
52880
],
[
13,
53200,
53640
],
[
10,
56320,
56560
],
[
7,
57640,
57760
]
] | [
[
21,
1000,
1480
],
[
46,
6120,
6720
],
[
17,
7120,
7760
],
[
51,
10880,
11960
],
[
22,
14600,
15200
],
[
14,
15360,
16040
],
[
33,
19360,
20080
],
[
40,
23400,
23920
],
[
17,
24400,
25320
],
[
17,
28680,
29400
],
[
37,
32720,
32960
],
[
42,
39520,
40080
],
[
50,
40240,
40680
],
[
50,
43360,
43600
],
[
17,
48160,
48760
],
[
37,
48920,
49200
],
[
42,
51720,
52280
],
[
10,
53440,
53960
],
[
18,
54880,
56040
],
[
31,
57000,
57680
],
[
17,
59680,
60000
],
[
53,
60160,
60760
],
[
42,
66280,
66760
],
[
42,
67320,
67960
],
[
17,
71560,
72120
],
[
41,
73720,
74320
],
[
44,
77120,
78000
]
] | [
[
17,
840,
1360
],
[
22,
3040,
3360
],
[
18,
3480,
4000
],
[
25,
4480,
4720
],
[
18,
5600,
5800
],
[
31,
6160,
7160
],
[
13,
8280,
8440
],
[
7,
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YAML Metadata
Warning:
empty or missing yaml metadata in repo card
(https://huggingface.co/docs/hub/datasets-cards)
annotations_creators:
- expert-generated language:
- lse language_creators:
- expert-generated license:
- mit multilinguality:
- monolingual pretty_name:
- LSE_eSaude_UVIGO_MSSL size_categories:
- n<1K source_datasets:
- original tags:
- sign spotting
- sign language recognition
- lse task_categories:
- other task_ids: []
Dataset Card for LSE_eSaude_UVIGO_MSSL
Dataset Summary
[More Information Needed]
Supported Tasks and Leaderboards
[More Information Needed]
Languages
[More Information Needed]
Dataset Structure
Data Instances
[More Information Needed]
Data Fields
[More Information Needed]
Data Splits
[More Information Needed]
Dataset Creation
Curation Rationale
[More Information Needed]
Source Data
Initial Data Collection and Normalization
[More Information Needed]
Who are the source language producers?
[More Information Needed]
Annotations
Annotation process
[More Information Needed]
Who are the annotators?
[More Information Needed]
Personal and Sensitive Information
[More Information Needed]
Considerations for Using the Data
Social Impact of Dataset
[More Information Needed]
Discussion of Biases
[More Information Needed]
Other Known Limitations
[More Information Needed]
Additional Information
Dataset Curators
[More Information Needed]
Licensing Information
[More Information Needed]
Citation Information
[More Information Needed]
Contributions
Thanks to @github-username for adding this dataset.
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