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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 ({'polyphony_rate', 'track_id', 'program', 'num_notes', 'end_time'}) and 2 missing columns ({'time_signature', 'global_tempo'}).
This happened while the csv dataset builder was generating data using
hf://datasets/lzqlzzq/midiset/track_features.csv (at revision df2e0ececaf73d5de534c211a985ff953f87cc1d)
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
midi_id: string
track_id: int64
program: int64
num_notes: int64
end_time: double
polyphony_rate: double
-- schema metadata --
pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 962
to
{'midi_id': Value(dtype='string', id=None), 'global_tempo': Value(dtype='float64', id=None), 'time_signature': Value(dtype='string', 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 ({'polyphony_rate', 'track_id', 'program', 'num_notes', 'end_time'}) and 2 missing columns ({'time_signature', 'global_tempo'}).
This happened while the csv dataset builder was generating data using
hf://datasets/lzqlzzq/midiset/track_features.csv (at revision df2e0ececaf73d5de534c211a985ff953f87cc1d)
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.
midi_id
string | global_tempo
float64 | time_signature
string |
|---|---|---|
000000/6819561392665023488
| 138
| null |
000000/2082347145784761397
| 118
|
(4, 4)
|
000000/1710301504502468975
| 90
|
(4, 4)
|
000000/8447082837283840882
| null | null |
000000/9747101262370999714
| 120
|
(4, 4)
|
000000/14289236458061141112
| 120
|
(4, 2)
|
000000/1939154233717887883
| 112
|
(3, 2)
|
000000/9222765079466901230
| 130
|
(4, 4)
|
000000/10423517713641539983
| 132
|
(4, 4)
|
000000/3672234968391614075
| 112
|
(4, 4)
|
000000/5826149401124392126
| 72
|
(4, 4)
|
000000/3722725725407270218
| 164
|
(2, 4)
|
000000/430561863398445019
| 168
|
(4, 4)
|
000000/16791727662655930059
| 200
|
(4, 4)
|
000000/7969815293962456708
| 160
|
(4, 4)
|
000000/4287804287229987715
| 90
|
(4, 4)
|
000000/8079641048619876776
| 100
|
(3, 4)
|
000000/7089709603546667478
| 81
|
(3, 4)
|
000000/783604498143419463
| 150
| null |
000000/7325716987695433964
| 160
|
(4, 4)
|
000000/1706480402320366821
| 165
|
(4, 4)
|
000000/7730776832025307577
| 130
|
(4, 4)
|
000000/17540898942732843977
| 107
|
(3, 4)
|
000000/17758353612807823622
| 120
|
(4, 4)
|
000000/12887664479836818744
| 110
|
(4, 4)
|
000000/17877660433880837652
| 92
|
(4, 4)
|
000000/9705442813380667911
| 140
| null |
000000/15223234699189320076
| 143
|
(4, 4)
|
000000/2280323122759672540
| 164
|
(4, 4)
|
000000/14588097100310184779
| 100
|
(4, 4)
|
000000/8387733265033280753
| 296
|
(4, 4)
|
000000/11934027031232880709
| null | null |
000000/4485084663858539115
| 134
|
(4, 4)
|
000000/9969263920803281742
| 140
|
(4, 4)
|
000000/8901984271038381845
| 138
|
(4, 4)
|
000000/6362095606332304029
| 92
|
(4, 4)
|
000000/9724993332930166167
| 120
|
(4, 4)
|
000000/11116243485040695983
| 100
|
(4, 4)
|
000000/11416798984713677446
| 65
|
(4, 4)
|
000000/11152259876051115505
| 140
|
(4, 4)
|
000000/7556929243083351250
| 64
|
(6, 4)
|
000000/8619823004194199884
| 112
|
(4, 4)
|
000000/3615665356732674088
| 83
|
(4, 4)
|
000000/16342772138895109533
| 132
|
(4, 4)
|
000000/14352743388944112965
| 106
|
(4, 4)
|
000000/7494069819465512622
| 160
|
(4, 4)
|
000000/15968724663664137104
| 73
|
(4, 4)
|
000000/8308222138553276243
| 120
|
(4, 4)
|
000000/17274016859033413838
| 78
|
(4, 4)
|
000000/17504430192638926915
| 100
|
(4, 4)
|
000000/2089205162626765932
| 73
|
(3, 4)
|
000000/3260999254265525344
| 120
| null |
000000/15928796547859029722
| 191
|
(4, 4)
|
000000/9243850495388933994
| 130
|
(4, 4)
|
000000/12500174283468008691
| 132
|
(4, 4)
|
000000/9696733752079304956
| 98
|
(4, 4)
|
000000/7849426830866122137
| 105
|
(2, 4)
|
000000/12122146461722365984
| 54
| null |
000000/15797973377661935525
| 122
|
(2, 2)
|
000000/16124529735598744983
| 79
|
(4, 4)
|
000000/14611009458517799325
| 184
|
(4, 4)
|
000000/2201149999883778546
| 108
|
(2, 4)
|
000000/15574387847323042309
| 105
|
(4, 4)
|
000000/3899221371840072780
| 100
|
(6, 4)
|
000000/9650890036491462535
| 100
|
(4, 4)
|
000000/13924054423613685049
| 72
|
(4, 4)
|
000000/15356196827961402903
| 84
|
(4, 4)
|
000000/4954665775114799650
| 130
|
(4, 4)
|
000000/14859685871824653911
| 120
|
(1, 8)
|
000000/5755224701096652472
| 90
|
(4, 4)
|
000000/6582789927737577925
| 107
|
(4, 4)
|
000000/3322038266994031002
| 199
|
(4, 4)
|
000000/8670867528785451582
| 150
|
(1, 8)
|
000000/2584160358588604368
| 145
|
(4, 4)
|
000000/5408828988890655856
| 120
| null |
000000/2405162134673870186
| 120
|
(1, 8)
|
000000/13374542789429492145
| 86
|
(4, 4)
|
000000/5610087951202724158
| 100
| null |
000000/11535324247959457517
| 120
|
(4, 4)
|
000000/13281110275131532495
| 75
|
(4, 4)
|
000000/16281745970956204592
| 218
|
(1, 4)
|
000000/6071994167816901300
| 170
|
(4, 4)
|
000000/6490692050125673212
| 112
|
(4, 4)
|
000000/2186671676279339751
| 120
|
(1, 4)
|
000000/8597386406904632346
| 230
|
(6, 8)
|
000000/12066717189116497969
| 110
|
(4, 4)
|
000000/14101547644971895573
| 190
|
(2, 2)
|
000000/16896877671599026629
| 64
|
(4, 4)
|
000000/6765995032493287325
| 113
| null |
000000/7347481392432806788
| 100
|
(4, 4)
|
000000/11808233957481483393
| 71
|
(2, 4)
|
000000/16091553737212263093
| 100
|
(4, 4)
|
000000/17463273681826534231
| 136
| null |
000000/3453908653469936778
| 113
|
(4, 4)
|
000000/11373827843149954981
| 95
|
(4, 4)
|
000000/8131737523854279471
| 100
|
(4, 4)
|
000000/1646831218421748436
| 120
|
(4, 4)
|
000000/1800721839658225684
| 94
|
(4, 4)
|
000000/2957007943516234922
| 80
|
(4, 4)
|
000000/9741182030631859449
| 105
|
(4, 4)
|
End of preview.
midiset
A clean and large scale MIDI dataset curated by professional composer and algorithm.
Feature
- Large-scale: 384696 unique MIDIs
- Clean: No invalid MIDI, and filtered by pitch class entropy
Acknowledgments
- Los Angeles MIDI Dataset: https://github.com/asigalov61/Los-Angeles-MIDI-Dataset
- Bread MIDI Dataset: https://huggingface.co/datasets/breadlicker45/bread-midi-dataset
- MetaMIDI Dataset: https://github.com/jeffreyjohnens/MetaMIDIDataset
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