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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 ({'recording', 'supervisions', 'start', 'duration', 'channel'}) and 1 missing columns ({'tracks'}).
This happened while the json dataset builder was generating data using
gzip://lsheavymix_cuts_test-clean_2spk_snr_aug_mono.jsonl::hf://datasets/zrjin/LibriheavyMix-test@deab6e9c4ad86f9929497045617e7b555a97791f/test-lhotse/lsheavymix_cuts_test-clean_2spk_snr_aug_mono.jsonl.gz
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
id: string
start: double
duration: double
channel: int64
supervisions: list<item: struct<id: string, recording_id: string, start: double, duration: double, channel: int64, language: string, speaker: string, custom: struct<texts: list<item: string>, pre_texts: list<item: string>, begin_byte: int64, end_byte: int64>>>
child 0, item: struct<id: string, recording_id: string, start: double, duration: double, channel: int64, language: string, speaker: string, custom: struct<texts: list<item: string>, pre_texts: list<item: string>, begin_byte: int64, end_byte: int64>>
child 0, id: string
child 1, recording_id: string
child 2, start: double
child 3, duration: double
child 4, channel: int64
child 5, language: string
child 6, speaker: string
child 7, custom: struct<texts: list<item: string>, pre_texts: list<item: string>, begin_byte: int64, end_byte: int64>
child 0, texts: list<item: string>
child 0, item: string
child 1, pre_texts: list<item: string>
child 0, item: string
child 2, begin_byte: int64
child 3, end_byte: int64
recording: struct<id: string, sources: list<item: struct<type: string, channels: list<item: int64>, source: string>>, sampling_rate: int64, num_samples: int64, duration: double, channel_ids: list<item: int64>>
child 0, id: string
child 1, sources: list<item: struct<type: string, channels: list<item: int64>, source: string>>
child 0, item: struct<type: string, channels: list<item: int64>, source: string>
child 0, type: string
child 1, channels: list<item: int64>
child 0, item: int64
child 2, source: string
child 2, sampling_rate: int64
child 3, num_samples: int64
child 4, duration: double
child 5, channel_ids: list<item: int64>
child 0, item: int64
type: string
to
{'id': Value(dtype='string', id=None), 'tracks': [{'cut': {'id': Value(dtype='string', id=None), 'start': Value(dtype='float64', id=None), 'duration': Value(dtype='float64', id=None), 'channel': Value(dtype='int64', id=None), 'supervisions': [{'id': Value(dtype='string', id=None), 'recording_id': Value(dtype='string', id=None), 'start': Value(dtype='int64', id=None), 'duration': Value(dtype='float64', id=None), 'channel': Value(dtype='int64', id=None), 'language': Value(dtype='string', id=None), 'speaker': Value(dtype='string', id=None), 'custom': {'texts': Sequence(feature=Value(dtype='string', id=None), length=-1, id=None), 'pre_texts': Sequence(feature=Value(dtype='string', id=None), length=-1, id=None), 'begin_byte': Value(dtype='int64', id=None), 'end_byte': Value(dtype='int64', id=None)}}], 'features': {'type': Value(dtype='string', id=None), 'num_frames': Value(dtype='int64', id=None), 'num_features': Value(dtype='int64', id=None), 'frame_shift': Value(dtype='float64', id=None), 'sampling_rate': Value(dtype='int64', id=None), 'start': Value(dtype='float64', id=None), 'duration': Value(dtype='float64', id=None), 'storage_type': Value(dtype='string', id=None), 'storage_path': Value(dtype='string', id=None), 'storage_key': Value(dtype='string', id=None), 'recording_id': Value(dtype='string', id=None), 'channels': Value(dtype='int64', id=None)}, 'recording': {'id': Value(dtype='string', id=None), 'sources': [{'type': Value(dtype='string', id=None), 'channels': Sequence(fea
...
Value(dtype='int64', id=None), 'num_features': Value(dtype='int64', id=None), 'frame_shift': Value(dtype='float64', id=None), 'sampling_rate': Value(dtype='int64', id=None), 'start': Value(dtype='float64', id=None), 'duration': Value(dtype='float64', id=None), 'storage_type': Value(dtype='string', id=None), 'storage_path': Value(dtype='string', id=None), 'storage_key': Value(dtype='string', id=None), 'recording_id': Value(dtype='string', id=None), 'channels': Value(dtype='int64', id=None)}, 'recording': {'id': Value(dtype='string', id=None), 'sources': [{'type': Value(dtype='string', id=None), 'channels': Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None), 'source': Value(dtype='string', id=None)}], 'sampling_rate': Value(dtype='int64', id=None), 'num_samples': Value(dtype='int64', id=None), 'duration': Value(dtype='float64', id=None), 'channel_ids': Sequence(feature=Value(dtype='int64', id=None), length=-1, id=None)}, 'custom': {'text_path': Value(dtype='string', id=None)}, 'sampling_rate': Value(dtype='int64', id=None), 'feat_value': Value(dtype='float64', id=None), 'num_frames': Value(dtype='int64', id=None), 'num_features': Value(dtype='int64', id=None), 'frame_shift': Value(dtype='float64', id=None), 'num_samples': Value(dtype='int64', id=None)}, 'type': Value(dtype='string', id=None), 'offset': Value(dtype='float64', id=None)}]}, 'type': Value(dtype='string', id=None), 'offset': Value(dtype='float64', id=None)}], 'type': 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 1572, in compute_config_parquet_and_info_response
parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1136, 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 5 new columns ({'recording', 'supervisions', 'start', 'duration', 'channel'}) and 1 missing columns ({'tracks'}).
This happened while the json dataset builder was generating data using
gzip://lsheavymix_cuts_test-clean_2spk_snr_aug_mono.jsonl::hf://datasets/zrjin/LibriheavyMix-test@deab6e9c4ad86f9929497045617e7b555a97791f/test-lhotse/lsheavymix_cuts_test-clean_2spk_snr_aug_mono.jsonl.gz
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.
id string | tracks list | type string |
|---|---|---|
8061e165-a91d-47bb-aa2d-0fc561d6eddb | [
{
"cut": {
"id": "medium/92/essays_first_series_0708_librivox_64kb_mp3/essays_first_series_07_emerson_64kb_134_repeat0",
"start": 1193.1600625,
"duration": 23.679,
"channel": 0,
"supervisions": [
{
"id": "medium/92/essays_first_series_0708_librivox_64kb_mp3/essays... | MixedCut |
17b8cea9-49c7-4ae2-aaf1-b101f59ef8b2 | [
{
"cut": {
"id": "medium/110/blackbeauty_librivox_64kb_mp3/blackbeauty_39_sewell_64kb_28_repeat0",
"start": 262.16,
"duration": 30,
"channel": 0,
"supervisions": [
{
"id": "medium/110/blackbeauty_librivox_64kb_mp3/blackbeauty_39_sewell_64kb_28",
"recordi... | MixedCut |
6768fe09-d70f-4e4d-b94a-cd4cfa47d78d | [
{
"cut": {
"id": "medium/1096/essays_first_series_0708_librivox_64kb_mp3/essays_first_series_04_emerson_64kb_180_repeat0",
"start": 1965.0799375,
"duration": 30.84,
"channel": 0,
"supervisions": [
{
"id": "medium/1096/essays_first_series_0708_librivox_64kb_mp3/ess... | MixedCut |
0ac52187-9029-4d8e-884f-d83550c005f5 | [
{
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"start": 30.12,
"duration": 20.199,
"channel": 0,
"supervisions": [
{
"id": "medium/362/blackbeauty_librivox_64kb_mp3/blackbeauty_48_sewell_64kb_39",
"reco... | MixedCut |
c62c6edc-cb38-4411-b73d-18c69d6d6bcf | [
{
"cut": {
"id": "medium/611/blackbeauty_librivox_64kb_mp3/blackbeauty_23_sewell_64kb_29_repeat0",
"start": 146.88,
"duration": 28.479,
"channel": 0,
"supervisions": [
{
"id": "medium/611/blackbeauty_librivox_64kb_mp3/blackbeauty_23_sewell_64kb_29",
"rec... | MixedCut |
728b6b43-8e6a-46a9-b73b-a0590a094da8 | [
{
"cut": {
"id": "medium/1096/essays_first_series_0708_librivox_64kb_mp3/essays_first_series_04_emerson_64kb_77_repeat0",
"start": 527.08,
"duration": 20.719,
"channel": 0,
"supervisions": [
{
"id": "medium/1096/essays_first_series_0708_librivox_64kb_mp3/essays_fi... | MixedCut |
80c58700-cb05-4444-b2ca-ecb30aa31e86 | [
{
"cut": {
"id": "medium/92/essays_first_series_0708_librivox_64kb_mp3/essays_first_series_07_emerson_64kb_114_repeat0",
"start": 557.72,
"duration": 20.6,
"channel": 0,
"supervisions": [
{
"id": "medium/92/essays_first_series_0708_librivox_64kb_mp3/essays_first_s... | MixedCut |
53b45678-4976-42cd-b0e5-5b08e5e4b382 | [
{
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"id": "medium/170/blackbeauty_librivox_64kb_mp3/blackbeauty_10_sewell_64kb_30_repeat0",
"start": 200.36,
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"channel": 0,
"supervisions": [
{
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"rec... | MixedCut |
b375d39d-736a-493c-89db-e9c05bddea77 | [
{
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"id": "medium/102/essays_first_series_0708_librivox_64kb_mp3/essays_first_series_06_emerson_64kb_45_repeat0",
"start": 1552.4,
"duration": 20.28,
"channel": 0,
"supervisions": [
{
"id": "medium/102/essays_first_series_0708_librivox_64kb_mp3/essays_first... | MixedCut |
9846974a-66b6-4716-a2db-7d58e80550ba | [
{
"cut": {
"id": "medium/102/essays_first_series_0708_librivox_64kb_mp3/essays_first_series_01_emerson_64kb_140_repeat0",
"start": 35.2,
"duration": 20.559,
"channel": 0,
"supervisions": [
{
"id": "medium/102/essays_first_series_0708_librivox_64kb_mp3/essays_first... | MixedCut |
51d459ff-986d-419c-a22d-d82f533cb6d1 | [
{
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"duration": 20.279,
"channel": 0,
"supervisions": [
{
"id": "medium/610/blackbeauty_librivox_64kb_mp3/blackbeauty_15_sewell_64kb_5",
"recor... | MixedCut |
1da3835a-4fc0-4b98-bc35-481875bf5676 | [
{
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"id": "medium/302/blackbeauty_librivox_64kb_mp3/blackbeauty_38_sewell_64kb_13_repeat0",
"start": 406.08,
"duration": 20.08,
"channel": 0,
"supervisions": [
{
"id": "medium/302/blackbeauty_librivox_64kb_mp3/blackbeauty_38_sewell_64kb_13",
"reco... | MixedCut |
e831be42-a6de-493d-8c89-96805a359862 | [
{
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"id": "medium/301/blackbeauty_librivox_64kb_mp3/blackbeauty_45_sewell_64kb_18_repeat0",
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"channel": 0,
"supervisions": [
{
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"rec... | MixedCut |
ea5e82bc-de9b-4747-9ead-4790391b908c | [
{
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"start": 472.88,
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"channel": 0,
"supervisions": [
{
"id": "medium/1096/essays_first_series_0708_librivox_64kb_mp3/essays_fi... | MixedCut |
5484873a-4e53-4454-b572-e88b0246f874 | [
{
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"channel": 0,
"supervisions": [
{
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afdfe13d-de3d-4d13-bedd-21360a0578d0 | [
{
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"start": 582.56,
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"channel": 0,
"supervisions": [
{
"id": "medium/102/essays_first_series_0708_librivox_64kb_mp3/essays_fir... | MixedCut |
da3a4b7e-2b3f-476f-9c1f-572f8b01243a | [
{
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"start": 359.6,
"duration": 28.959,
"channel": 0,
"supervisions": [
{
"id": "medium/302/blackbeauty_librivox_64kb_mp3/blackbeauty_43_sewell_64kb_31",
"reco... | MixedCut |
bde3fc20-61fe-46f1-b40f-f479865fde3e | [
{
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"channel": 0,
"supervisions": [
{
"id": "medium/1096/essays_first_series_0708_librivox_64kb_mp3/ess... | MixedCut |
bd02622b-65e4-4d44-a5de-6a07fce66ff4 | [
{
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"start": 150.48,
"duration": 29,
"channel": 0,
"supervisions": [
{
"id": "medium/337/blackbeauty_librivox_64kb_mp3/blackbeauty_24_sewell_64kb_58",
"recordi... | MixedCut |
e938de95-28c2-462d-b137-5108e3ce63ef | [
{
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"start": 803.36,
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"channel": 0,
"supervisions": [
{
"id": "medium/1096/essays_first_series_0708_librivox_64kb_mp3/essays_fir... | MixedCut |
e201fe1e-7967-4a8f-b63f-9c4b18b021c9 | [
{
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"start": 262.04,
"duration": 28.239,
"channel": 0,
"supervisions": [
{
"id": "medium/611/blackbeauty_librivox_64kb_mp3/blackbeauty_23_sewell_64kb_23",
"rec... | MixedCut |
508df618-624a-4b1b-9af7-9ce6b1ae3e48 | [
{
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"start": 432.12,
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"channel": 0,
"supervisions": [
{
"id": "medium/32/blackbeauty_librivox_64kb_mp3/blackbeauty_08_sewell_64kb_11",
"record... | MixedCut |
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