The full dataset viewer is not available (click to read why). Only showing a preview of the rows.
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 454 new columns ({'000198', '000305', '000189', '000433', '000133', '000128', '000335', '000251', '000037', '000456', '000165', '000057', '000290', '000082', '000446', '000353', '000319', '000286', '000348', '000017', '000011', '000415', '000021', '000157', '000106', '000352', '000156', '000100', '000253', '000214', '000206', '000158', '000421', '000155', '000039', '000459', '000299', '000232', '000351', '000209', '000042', '000202', '000383', '000114', '000074', '000168', '000356', '000426', '000391', '000298', '000012', '000287', '000121', '000263', '000476', '000482', '000430', '000048', '000185', '000393', '000022', '000428', '000418', '000420', '000454', '000008', '000447', '000078', '000240', '000041', '000439', '000101', '000408', '000461', '000452', '000252', '000443', '000379', '000413', '000145', '000246', '000429', '000458', '000141', '000062', '000382', '000170', '000280', '000403', '000238', '000303', '000207', '000388', '000258', '000137', '000261', '000409', '000400', '000257', '000025', '000139', '000072', '000424', '000217', '000339', '000256', '000135', '000033', '000438', '000148', '000334', '000201', '000166', '000316', '000054', '000150', '000215', '000275', '000384', '000453', '000386', '000269', '000462', '000120', '000122', '000406', '000001', '000058', '000460', '000398', '000283', '000068', '000323', '000046', '000481', '000203', '000295', '000317', '000364', '000423', '000099', '000056', '000479', '000216', '000071', '000199', '000231', '000065', '000031', '000161',
...
'000197', '000060', '000473', '000328', '000343', '000064', '000250', '000277', '000268', '000040', '000079', '000019', '000076', '000004', '000059', '000276', '000350', '000061', '000226', '000366', '000297', '000211', '000186', '000077', '000378', '000173', '000047', '000337', '000360', '000009', '000417', '000032', '000361', '000027', '000354', '000330', '000045', '000152', '000159', '000248', '000028', '000347', '000416', '000124', '000080', '000116', '000208', '000333', '000394', '000192', '000204', '000363', '000143', '000327', '000311', '000247', '000210', '000466', '000096', '000365', '000195', '000414', '000066', '000110', '000293', '000125', '000044', '000043', '000105', '000169', '000178', '000264', '000271', '000478', '000371', '000067', '000255', '000091', '000262', '000349', '000050', '000397', '000154', '000448', '000358', '000140', '000254', '000144', '000404', '000242', '000003', '000063', '000075', '000108', '000359', '000102', '000304', '000234', '000229', '000392', '000434', '000188', '000221', '000176', '000244', '000126', '000472', '000288', '000480', '000103', '000355', '000132', '000396', '000172', '000399', '000222', '000119', '000084', '000450', '000053', '000142', '000463', '000111', '000194', '000200', '000279', '000088', '000265', '000024', '000338', '000340', '000427', '000016', '000449', '000259', '000073', '000227', '000469', '000055', '000425', '000411', '000451', '000162', '000441', '000010', '000113', '000313', '000272', '000051', '000164'}) and 5 missing columns ({'train_ids', 'num_exemplars', 'count', 'ids', 'val_ids'}).
This happened while the json dataset builder was generating data using
zip://chess4/metadata.json::hf://datasets/xieyizheng/hypernerf_custom_scenes@265589302460bc30d2e62f6ba7ab642ecfa87f4d/chess/chess_dataset.zip
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
000002: struct<warp_id: int64, appearance_id: int64, camera_id: int64>
child 0, warp_id: int64
child 1, appearance_id: int64
child 2, camera_id: int64
000003: struct<warp_id: int64, appearance_id: int64, camera_id: int64>
child 0, warp_id: int64
child 1, appearance_id: int64
child 2, camera_id: int64
000004: struct<warp_id: int64, appearance_id: int64, camera_id: int64>
child 0, warp_id: int64
child 1, appearance_id: int64
child 2, camera_id: int64
000005: struct<warp_id: int64, appearance_id: int64, camera_id: int64>
child 0, warp_id: int64
child 1, appearance_id: int64
child 2, camera_id: int64
000006: struct<warp_id: int64, appearance_id: int64, camera_id: int64>
child 0, warp_id: int64
child 1, appearance_id: int64
child 2, camera_id: int64
000007: struct<warp_id: int64, appearance_id: int64, camera_id: int64>
child 0, warp_id: int64
child 1, appearance_id: int64
child 2, camera_id: int64
000008: struct<warp_id: int64, appearance_id: int64, camera_id: int64>
child 0, warp_id: int64
child 1, appearance_id: int64
child 2, camera_id: int64
000009: struct<warp_id: int64, appearance_id: int64, camera_id: int64>
child 0, warp_id: int64
child 1, appearance_id: int64
child 2, camera_id: int64
000010: struct<warp_id: int64, appearance_id: int64, camera_id: int64>
child 0, warp_id: int64
child 1, appearance_id: int64
child 2, camera_id: int64
000011: struct<warp_id: int64, appearance_id: int64, camera_id: int64>
child 0, warp_
...
>
child 0, warp_id: int64
child 1, appearance_id: int64
child 2, camera_id: int64
000285: struct<warp_id: int64, appearance_id: int64, camera_id: int64>
child 0, warp_id: int64
child 1, appearance_id: int64
child 2, camera_id: int64
000308: struct<warp_id: int64, appearance_id: int64, camera_id: int64>
child 0, warp_id: int64
child 1, appearance_id: int64
child 2, camera_id: int64
000332: struct<warp_id: int64, appearance_id: int64, camera_id: int64>
child 0, warp_id: int64
child 1, appearance_id: int64
child 2, camera_id: int64
000354: struct<warp_id: int64, appearance_id: int64, camera_id: int64>
child 0, warp_id: int64
child 1, appearance_id: int64
child 2, camera_id: int64
000386: struct<warp_id: int64, appearance_id: int64, camera_id: int64>
child 0, warp_id: int64
child 1, appearance_id: int64
child 2, camera_id: int64
000408: struct<warp_id: int64, appearance_id: int64, camera_id: int64>
child 0, warp_id: int64
child 1, appearance_id: int64
child 2, camera_id: int64
000428: struct<warp_id: int64, appearance_id: int64, camera_id: int64>
child 0, warp_id: int64
child 1, appearance_id: int64
child 2, camera_id: int64
000448: struct<warp_id: int64, appearance_id: int64, camera_id: int64>
child 0, warp_id: int64
child 1, appearance_id: int64
child 2, camera_id: int64
000469: struct<warp_id: int64, appearance_id: int64, camera_id: int64>
child 0, warp_id: int64
child 1, appearance_id: int64
child 2, camera_id: int64
to
{'count': Value(dtype='int64', id=None), 'num_exemplars': Value(dtype='int64', id=None), 'ids': Sequence(feature=Value(dtype='string', id=None), length=-1, id=None), 'train_ids': Sequence(feature=Value(dtype='string', id=None), length=-1, id=None), 'val_ids': Sequence(feature=Value(dtype='string', 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 1316, in compute_config_parquet_and_info_response
parquet_operations, partial = stream_convert_to_parquet(
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 909, in stream_convert_to_parquet
builder._prepare_split(
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 454 new columns ({'000198', '000305', '000189', '000433', '000133', '000128', '000335', '000251', '000037', '000456', '000165', '000057', '000290', '000082', '000446', '000353', '000319', '000286', '000348', '000017', '000011', '000415', '000021', '000157', '000106', '000352', '000156', '000100', '000253', '000214', '000206', '000158', '000421', '000155', '000039', '000459', '000299', '000232', '000351', '000209', '000042', '000202', '000383', '000114', '000074', '000168', '000356', '000426', '000391', '000298', '000012', '000287', '000121', '000263', '000476', '000482', '000430', '000048', '000185', '000393', '000022', '000428', '000418', '000420', '000454', '000008', '000447', '000078', '000240', '000041', '000439', '000101', '000408', '000461', '000452', '000252', '000443', '000379', '000413', '000145', '000246', '000429', '000458', '000141', '000062', '000382', '000170', '000280', '000403', '000238', '000303', '000207', '000388', '000258', '000137', '000261', '000409', '000400', '000257', '000025', '000139', '000072', '000424', '000217', '000339', '000256', '000135', '000033', '000438', '000148', '000334', '000201', '000166', '000316', '000054', '000150', '000215', '000275', '000384', '000453', '000386', '000269', '000462', '000120', '000122', '000406', '000001', '000058', '000460', '000398', '000283', '000068', '000323', '000046', '000481', '000203', '000295', '000317', '000364', '000423', '000099', '000056', '000479', '000216', '000071', '000199', '000231', '000065', '000031', '000161',
...
'000197', '000060', '000473', '000328', '000343', '000064', '000250', '000277', '000268', '000040', '000079', '000019', '000076', '000004', '000059', '000276', '000350', '000061', '000226', '000366', '000297', '000211', '000186', '000077', '000378', '000173', '000047', '000337', '000360', '000009', '000417', '000032', '000361', '000027', '000354', '000330', '000045', '000152', '000159', '000248', '000028', '000347', '000416', '000124', '000080', '000116', '000208', '000333', '000394', '000192', '000204', '000363', '000143', '000327', '000311', '000247', '000210', '000466', '000096', '000365', '000195', '000414', '000066', '000110', '000293', '000125', '000044', '000043', '000105', '000169', '000178', '000264', '000271', '000478', '000371', '000067', '000255', '000091', '000262', '000349', '000050', '000397', '000154', '000448', '000358', '000140', '000254', '000144', '000404', '000242', '000003', '000063', '000075', '000108', '000359', '000102', '000304', '000234', '000229', '000392', '000434', '000188', '000221', '000176', '000244', '000126', '000472', '000288', '000480', '000103', '000355', '000132', '000396', '000172', '000399', '000222', '000119', '000084', '000450', '000053', '000142', '000463', '000111', '000194', '000200', '000279', '000088', '000265', '000024', '000338', '000340', '000427', '000016', '000449', '000259', '000073', '000227', '000469', '000055', '000425', '000411', '000451', '000162', '000441', '000010', '000113', '000313', '000272', '000051', '000164'}) and 5 missing columns ({'train_ids', 'num_exemplars', 'count', 'ids', 'val_ids'}).
This happened while the json dataset builder was generating data using
zip://chess4/metadata.json::hf://datasets/xieyizheng/hypernerf_custom_scenes@265589302460bc30d2e62f6ba7ab642ecfa87f4d/chess/chess_dataset.zip
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.
count
int64 | num_exemplars
int64 | ids
sequence | train_ids
sequence | val_ids
sequence | 000002
dict | 000003
dict | 000004
dict | 000005
dict | 000006
dict | 000007
dict | 000008
dict | 000009
dict | 000010
dict | 000011
dict | 000012
dict | 000013
dict | 000014
dict | 000015
dict | 000016
dict | 000017
dict | 000018
dict | 000019
dict | 000020
dict | 000022
dict | 000023
dict | 000024
dict | 000025
dict | 000026
dict | 000027
dict | 000028
dict | 000029
dict | 000030
dict | 000031
dict | 000032
dict | 000033
dict | 000034
dict | 000035
dict | 000036
dict | 000037
dict | 000038
dict | 000039
dict | 000040
dict | 000042
dict | 000043
dict | 000044
dict | 000045
dict | 000046
dict | 000047
dict | 000048
dict | 000049
dict | 000050
dict | 000051
dict | 000052
dict | 000053
dict | 000054
dict | 000055
dict | 000056
dict | 000057
dict | 000058
dict | 000059
dict | 000060
dict | 000062
dict | 000063
dict | 000064
dict | 000065
dict | 000066
dict | 000067
dict | 000068
dict | 000069
dict | 000070
dict | 000071
dict | 000072
dict | 000073
dict | 000074
dict | 000075
dict | 000076
dict | 000077
dict | 000078
dict | 000079
dict | 000080
dict | 000082
dict | 000083
dict | 000084
dict | 000085
dict | 000086
dict | 000087
dict | 000088
dict | 000089
dict | 000090
dict | 000091
dict | 000092
dict | 000093
dict | 000094
dict | 000095
dict | 000096
dict | 000097
dict | 000098
dict | 000099
dict | 000100
dict | 000102
dict | 000103
dict | 000104
dict | 000105
dict | 000106
dict | 000107
dict | 000108
dict | 000109
dict | 000110
dict | 000111
dict | 000112
dict | 000113
dict | 000114
dict | 000115
dict | 000116
dict | 000117
dict | 000118
dict | 000119
dict | 000120
dict | 000122
dict | 000123
dict | 000124
dict | 000125
dict | 000126
dict | 000127
dict | 000128
dict | 000129
dict | 000130
dict | 000131
dict | 000132
dict | 000133
dict | 000134
dict | 000135
dict | 000136
dict | 000137
dict | 000138
dict | 000139
dict | 000140
dict | 000142
dict | 000143
dict | 000144
dict | 000145
dict | 000146
dict | 000147
dict | 000148
dict | 000149
dict | 000150
dict | 000151
dict | 000152
dict | 000154
dict | 000155
dict | 000156
dict | 000157
dict | 000158
dict | 000159
dict | 000160
dict | 000161
dict | 000163
dict | 000164
dict | 000165
dict | 000166
dict | 000167
dict | 000168
dict | 000169
dict | 000170
dict | 000171
dict | 000172
dict | 000173
dict | 000174
dict | 000175
dict | 000176
dict | 000177
dict | 000178
dict | 000179
dict | 000180
dict | 000181
dict | 000183
dict | 000184
dict | 000185
dict | 000186
dict | 000187
dict | 000188
dict | 000189
dict | 000190
dict | 000191
dict | 000192
dict | 000193
dict | 000194
dict | 000195
dict | 000196
dict | 000197
dict | 000198
dict | 000199
dict | 000200
dict | 000201
dict | 000203
dict | 000204
dict | 000205
dict | 000206
dict | 000207
dict | 000208
dict | 000209
dict | 000210
dict | 000211
dict | 000212
dict | 000213
dict | 000214
dict | 000215
dict | 000216
dict | 000217
dict | 000218
dict | 000219
dict | 000220
dict | 000221
dict | 000223
dict | 000224
dict | 000225
dict | 000226
dict | 000227
dict | 000228
dict | 000229
dict | 000230
dict | 000231
dict | 000232
dict | 000233
dict | 000234
dict | 000235
dict | 000236
dict | 000237
dict | 000238
dict | 000239
dict | 000240
dict | 000241
dict | 000243
dict | 000244
dict | 000245
dict | 000246
dict | 000247
dict | 000248
dict | 000249
dict | 000250
dict | 000251
dict | 000252
dict | 000253
dict | 000254
dict | 000255
dict | 000256
dict | 000257
dict | 000258
dict | 000259
dict | 000260
dict | 000261
dict | 000263
dict | 000264
dict | 000265
dict | 000266
dict | 000268
dict | 000269
dict | 000270
dict | 000271
dict | 000272
dict | 000273
dict | 000274
dict | 000275
dict | 000276
dict | 000277
dict | 000278
dict | 000279
dict | 000280
dict | 000281
dict | 000283
dict | 000286
dict | 000287
dict | 000288
dict | 000290
dict | 000291
dict | 000292
dict | 000293
dict | 000294
dict | 000295
dict | 000297
dict | 000298
dict | 000299
dict | 000300
dict | 000302
dict | 000303
dict | 000304
dict | 000305
dict | 000306
dict | 000307
dict | 000309
dict | 000310
dict | 000311
dict | 000313
dict | 000314
dict | 000315
dict | 000316
dict | 000317
dict | 000319
dict | 000321
dict | 000322
dict | 000323
dict | 000324
dict | 000325
dict | 000326
dict | 000327
dict | 000328
dict | 000330
dict | 000331
dict | 000333
dict | 000334
dict | 000335
dict | 000336
dict | 000337
dict | 000338
dict | 000339
dict | 000340
dict | 000343
dict | 000344
dict | 000345
dict | 000346
dict | 000347
dict | 000348
dict | 000349
dict | 000350
dict | 000351
dict | 000352
dict | 000353
dict | 000355
dict | 000356
dict | 000357
dict | 000358
dict | 000359
dict | 000360
dict | 000361
dict | 000362
dict | 000363
dict | 000364
dict | 000365
dict | 000366
dict | 000371
dict | 000378
dict | 000379
dict | 000381
dict | 000382
dict | 000383
dict | 000384
dict | 000387
dict | 000388
dict | 000390
dict | 000391
dict | 000392
dict | 000393
dict | 000394
dict | 000396
dict | 000397
dict | 000398
dict | 000399
dict | 000400
dict | 000401
dict | 000402
dict | 000403
dict | 000404
dict | 000405
dict | 000406
dict | 000407
dict | 000409
dict | 000410
dict | 000411
dict | 000412
dict | 000413
dict | 000414
dict | 000415
dict | 000416
dict | 000417
dict | 000418
dict | 000419
dict | 000420
dict | 000421
dict | 000422
dict | 000423
dict | 000424
dict | 000425
dict | 000426
dict | 000427
dict | 000429
dict | 000430
dict | 000431
dict | 000432
dict | 000433
dict | 000434
dict | 000435
dict | 000436
dict | 000437
dict | 000438
dict | 000439
dict | 000440
dict | 000441
dict | 000442
dict | 000443
dict | 000444
dict | 000445
dict | 000446
dict | 000447
dict | 000449
dict | 000450
dict | 000451
dict | 000452
dict | 000453
dict | 000454
dict | 000455
dict | 000456
dict | 000457
dict | 000458
dict | 000459
dict | 000460
dict | 000461
dict | 000462
dict | 000463
dict | 000465
dict | 000466
dict | 000467
dict | 000468
dict | 000470
dict | 000471
dict | 000472
dict | 000473
dict | 000474
dict | 000475
dict | 000476
dict | 000477
dict | 000478
dict | 000479
dict | 000480
dict | 000481
dict | 000482
dict | 000001
dict | 000021
dict | 000041
dict | 000061
dict | 000081
dict | 000101
dict | 000121
dict | 000141
dict | 000162
dict | 000182
dict | 000202
dict | 000222
dict | 000242
dict | 000262
dict | 000285
dict | 000308
dict | 000332
dict | 000354
dict | 000386
dict | 000408
dict | 000428
dict | 000448
dict | 000469
dict | scale
float64 | center
sequence | bbox
sequence | near
float64 | far
float64 | orientation
sequence | position
sequence | focal_length
float64 | principal_point
sequence | skew
float64 | pixel_aspect_ratio
float64 | radial_distortion
sequence | tangential_distortion
sequence | image_size
sequence |
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