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Datasets:
lzqlzzq
/
midiset

Size:
100K<n<1M
Tags:
music
art
License:
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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 ({'track_id', 'polyphony_rate', 'program', 'end_time', 'num_notes'}) 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 e2cd65669eb14047f082ca40874972f8b25edfac)

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 ({'track_id', 'polyphony_rate', 'program', 'end_time', 'num_notes'}) 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 e2cd65669eb14047f082ca40874972f8b25edfac)
              
              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

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