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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 13 new columns ({'features', 'total_frames', 'fps', 'video_path', 'codebase_version', 'chunks_size', 'data_path', 'total_episodes', 'total_chunks', 'splits', 'total_tasks', 'total_videos', 'robot_type'}) and 2 missing columns ({'stats', 'episode_index'}).
This happened while the json dataset builder was generating data using
hf://datasets/Gukchan/dataset_251205_converted/meta/info.json (at revision 1af19f71e7755536a8fb66057c0c1e22daf9d175)
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 "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1831, in _prepare_split_single
writer.write_table(table)
File "/usr/local/lib/python3.12/site-packages/datasets/arrow_writer.py", line 714, in write_table
pa_table = table_cast(pa_table, self._schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2272, in table_cast
return cast_table_to_schema(table, schema)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/table.py", line 2218, in cast_table_to_schema
raise CastError(
datasets.table.CastError: Couldn't cast
codebase_version: string
robot_type: string
total_episodes: int64
total_frames: int64
total_tasks: int64
total_videos: int64
total_chunks: int64
chunks_size: int64
fps: int64
splits: struct<>
data_path: string
video_path: string
features: struct<action: struct<dtype: string, shape: list<item: int64>, names: list<item: string>>, observati (... 453 chars omitted)
child 0, action: struct<dtype: string, shape: list<item: int64>, names: list<item: string>>
child 0, dtype: string
child 1, shape: list<item: int64>
child 0, item: int64
child 2, names: list<item: string>
child 0, item: string
child 1, observation.state: struct<dtype: string, shape: list<item: int64>, names: list<item: string>>
child 0, dtype: string
child 1, shape: list<item: int64>
child 0, item: int64
child 2, names: list<item: string>
child 0, item: string
child 2, timestamp: struct<dtype: string, shape: list<item: int64>, names: null>
child 0, dtype: string
child 1, shape: list<item: int64>
child 0, item: int64
child 2, names: null
child 3, frame_index: struct<dtype: string, shape: list<item: int64>, names: null>
child 0, dtype: string
child 1, shape: list<item: int64>
child 0, item: int64
child 2, names: null
child 4, episode_index: struct<dtype: string, shape: list<item: int64>, names: null>
child 0, dtype: string
child 1, shape: list<item: int64>
child 0, item: int64
child 2, names: null
child 5, index: struct<dtype: string, shape: list<item: int64>, names: null>
child 0, dtype: string
child 1, shape: list<item: int64>
child 0, item: int64
child 2, names: null
child 6, task_index: struct<dtype: string, shape: list<item: int64>, names: null>
child 0, dtype: string
child 1, shape: list<item: int64>
child 0, item: int64
child 2, names: null
to
{'episode_index': Value('int64'), 'stats': {'annotation.human.action.task_description': {'mean': Value('float64'), 'std': Value('float64'), 'min': Value('float64'), 'max': Value('float64')}, 'annotation.human.validity': {'mean': Value('float64'), 'std': Value('float64'), 'min': Value('float64'), 'max': Value('float64')}, 'next.reward': {'mean': Value('float64'), 'std': Value('float64'), 'min': Value('float64'), 'max': Value('float64')}}}
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 1339, 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 972, in convert_to_parquet
builder.download_and_prepare(
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 894, in download_and_prepare
self._download_and_prepare(
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 970, in _download_and_prepare
self._prepare_split(split_generator, **prepare_split_kwargs)
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1702, in _prepare_split
for job_id, done, content in self._prepare_split_single(
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/builder.py", line 1833, 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 13 new columns ({'features', 'total_frames', 'fps', 'video_path', 'codebase_version', 'chunks_size', 'data_path', 'total_episodes', 'total_chunks', 'splits', 'total_tasks', 'total_videos', 'robot_type'}) and 2 missing columns ({'stats', 'episode_index'}).
This happened while the json dataset builder was generating data using
hf://datasets/Gukchan/dataset_251205_converted/meta/info.json (at revision 1af19f71e7755536a8fb66057c0c1e22daf9d175)
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.
episode_index int64 | stats dict |
|---|---|
0 | {
"annotation.human.action.task_description": {
"mean": 0,
"std": 0,
"min": 0,
"max": 0
},
"annotation.human.validity": {
"mean": 1,
"std": 0,
"min": 1,
"max": 1
},
"next.reward": {
"mean": 1,
"std": 0,
"min": 1,
"max": 1
}
} |
1 | {
"annotation.human.action.task_description": {
"mean": 0,
"std": 0,
"min": 0,
"max": 0
},
"annotation.human.validity": {
"mean": 1,
"std": 0,
"min": 1,
"max": 1
},
"next.reward": {
"mean": 1,
"std": 0,
"min": 1,
"max": 1
}
} |
2 | {
"annotation.human.action.task_description": {
"mean": 0,
"std": 0,
"min": 0,
"max": 0
},
"annotation.human.validity": {
"mean": 1,
"std": 0,
"min": 1,
"max": 1
},
"next.reward": {
"mean": 1,
"std": 0,
"min": 1,
"max": 1
}
} |
3 | {
"annotation.human.action.task_description": {
"mean": 0,
"std": 0,
"min": 0,
"max": 0
},
"annotation.human.validity": {
"mean": 1,
"std": 0,
"min": 1,
"max": 1
},
"next.reward": {
"mean": 1,
"std": 0,
"min": 1,
"max": 1
}
} |
4 | {
"annotation.human.action.task_description": {
"mean": 0,
"std": 0,
"min": 0,
"max": 0
},
"annotation.human.validity": {
"mean": 1,
"std": 0,
"min": 1,
"max": 1
},
"next.reward": {
"mean": 1,
"std": 0,
"min": 1,
"max": 1
}
} |
5 | {
"annotation.human.action.task_description": {
"mean": 0,
"std": 0,
"min": 0,
"max": 0
},
"annotation.human.validity": {
"mean": 1,
"std": 0,
"min": 1,
"max": 1
},
"next.reward": {
"mean": 1,
"std": 0,
"min": 1,
"max": 1
}
} |
6 | {
"annotation.human.action.task_description": {
"mean": 0,
"std": 0,
"min": 0,
"max": 0
},
"annotation.human.validity": {
"mean": 1,
"std": 0,
"min": 1,
"max": 1
},
"next.reward": {
"mean": 1,
"std": 0,
"min": 1,
"max": 1
}
} |
7 | {
"annotation.human.action.task_description": {
"mean": 0,
"std": 0,
"min": 0,
"max": 0
},
"annotation.human.validity": {
"mean": 1,
"std": 0,
"min": 1,
"max": 1
},
"next.reward": {
"mean": 1,
"std": 0,
"min": 1,
"max": 1
}
} |
8 | {
"annotation.human.action.task_description": {
"mean": 0,
"std": 0,
"min": 0,
"max": 0
},
"annotation.human.validity": {
"mean": 1,
"std": 0,
"min": 1,
"max": 1
},
"next.reward": {
"mean": 1,
"std": 0,
"min": 1,
"max": 1
}
} |
9 | {
"annotation.human.action.task_description": {
"mean": 0,
"std": 0,
"min": 0,
"max": 0
},
"annotation.human.validity": {
"mean": 1,
"std": 0,
"min": 1,
"max": 1
},
"next.reward": {
"mean": 1,
"std": 0,
"min": 1,
"max": 1
}
} |
10 | {
"annotation.human.action.task_description": {
"mean": 0,
"std": 0,
"min": 0,
"max": 0
},
"annotation.human.validity": {
"mean": 1,
"std": 0,
"min": 1,
"max": 1
},
"next.reward": {
"mean": 1,
"std": 0,
"min": 1,
"max": 1
}
} |
11 | {
"annotation.human.action.task_description": {
"mean": 0,
"std": 0,
"min": 0,
"max": 0
},
"annotation.human.validity": {
"mean": 1,
"std": 0,
"min": 1,
"max": 1
},
"next.reward": {
"mean": 1,
"std": 0,
"min": 1,
"max": 1
}
} |
12 | {
"annotation.human.action.task_description": {
"mean": 0,
"std": 0,
"min": 0,
"max": 0
},
"annotation.human.validity": {
"mean": 1,
"std": 0,
"min": 1,
"max": 1
},
"next.reward": {
"mean": 1,
"std": 0,
"min": 1,
"max": 1
}
} |
13 | {
"annotation.human.action.task_description": {
"mean": 0,
"std": 0,
"min": 0,
"max": 0
},
"annotation.human.validity": {
"mean": 1,
"std": 0,
"min": 1,
"max": 1
},
"next.reward": {
"mean": 1,
"std": 0,
"min": 1,
"max": 1
}
} |
14 | {
"annotation.human.action.task_description": {
"mean": 0,
"std": 0,
"min": 0,
"max": 0
},
"annotation.human.validity": {
"mean": 1,
"std": 0,
"min": 1,
"max": 1
},
"next.reward": {
"mean": 1,
"std": 0,
"min": 1,
"max": 1
}
} |
15 | {
"annotation.human.action.task_description": {
"mean": 0,
"std": 0,
"min": 0,
"max": 0
},
"annotation.human.validity": {
"mean": 1,
"std": 0,
"min": 1,
"max": 1
},
"next.reward": {
"mean": 1,
"std": 0,
"min": 1,
"max": 1
}
} |
16 | {
"annotation.human.action.task_description": {
"mean": 0,
"std": 0,
"min": 0,
"max": 0
},
"annotation.human.validity": {
"mean": 1,
"std": 0,
"min": 1,
"max": 1
},
"next.reward": {
"mean": 1,
"std": 0,
"min": 1,
"max": 1
}
} |
17 | {
"annotation.human.action.task_description": {
"mean": 0,
"std": 0,
"min": 0,
"max": 0
},
"annotation.human.validity": {
"mean": 1,
"std": 0,
"min": 1,
"max": 1
},
"next.reward": {
"mean": 1,
"std": 0,
"min": 1,
"max": 1
}
} |
18 | {
"annotation.human.action.task_description": {
"mean": 0,
"std": 0,
"min": 0,
"max": 0
},
"annotation.human.validity": {
"mean": 1,
"std": 0,
"min": 1,
"max": 1
},
"next.reward": {
"mean": 1,
"std": 0,
"min": 1,
"max": 1
}
} |
19 | {
"annotation.human.action.task_description": {
"mean": 0,
"std": 0,
"min": 0,
"max": 0
},
"annotation.human.validity": {
"mean": 1,
"std": 0,
"min": 1,
"max": 1
},
"next.reward": {
"mean": 1,
"std": 0,
"min": 1,
"max": 1
}
} |
20 | {
"annotation.human.action.task_description": {
"mean": 0,
"std": 0,
"min": 0,
"max": 0
},
"annotation.human.validity": {
"mean": 1,
"std": 0,
"min": 1,
"max": 1
},
"next.reward": {
"mean": 1,
"std": 0,
"min": 1,
"max": 1
}
} |
21 | {
"annotation.human.action.task_description": {
"mean": 0,
"std": 0,
"min": 0,
"max": 0
},
"annotation.human.validity": {
"mean": 1,
"std": 0,
"min": 1,
"max": 1
},
"next.reward": {
"mean": 1,
"std": 0,
"min": 1,
"max": 1
}
} |
22 | {
"annotation.human.action.task_description": {
"mean": 0,
"std": 0,
"min": 0,
"max": 0
},
"annotation.human.validity": {
"mean": 1,
"std": 0,
"min": 1,
"max": 1
},
"next.reward": {
"mean": 1,
"std": 0,
"min": 1,
"max": 1
}
} |
23 | {
"annotation.human.action.task_description": {
"mean": 0,
"std": 0,
"min": 0,
"max": 0
},
"annotation.human.validity": {
"mean": 1,
"std": 0,
"min": 1,
"max": 1
},
"next.reward": {
"mean": 1,
"std": 0,
"min": 1,
"max": 1
}
} |
24 | {
"annotation.human.action.task_description": {
"mean": 0,
"std": 0,
"min": 0,
"max": 0
},
"annotation.human.validity": {
"mean": 1,
"std": 0,
"min": 1,
"max": 1
},
"next.reward": {
"mean": 1,
"std": 0,
"min": 1,
"max": 1
}
} |
25 | {
"annotation.human.action.task_description": {
"mean": 0,
"std": 0,
"min": 0,
"max": 0
},
"annotation.human.validity": {
"mean": 1,
"std": 0,
"min": 1,
"max": 1
},
"next.reward": {
"mean": 1,
"std": 0,
"min": 1,
"max": 1
}
} |
26 | {
"annotation.human.action.task_description": {
"mean": 0,
"std": 0,
"min": 0,
"max": 0
},
"annotation.human.validity": {
"mean": 1,
"std": 0,
"min": 1,
"max": 1
},
"next.reward": {
"mean": 1,
"std": 0,
"min": 1,
"max": 1
}
} |
27 | {
"annotation.human.action.task_description": {
"mean": 0,
"std": 0,
"min": 0,
"max": 0
},
"annotation.human.validity": {
"mean": 1,
"std": 0,
"min": 1,
"max": 1
},
"next.reward": {
"mean": 1,
"std": 0,
"min": 1,
"max": 1
}
} |
28 | {
"annotation.human.action.task_description": {
"mean": 0,
"std": 0,
"min": 0,
"max": 0
},
"annotation.human.validity": {
"mean": 1,
"std": 0,
"min": 1,
"max": 1
},
"next.reward": {
"mean": 1,
"std": 0,
"min": 1,
"max": 1
}
} |
29 | {
"annotation.human.action.task_description": {
"mean": 0,
"std": 0,
"min": 0,
"max": 0
},
"annotation.human.validity": {
"mean": 1,
"std": 0,
"min": 1,
"max": 1
},
"next.reward": {
"mean": 1,
"std": 0,
"min": 1,
"max": 1
}
} |
30 | {
"annotation.human.action.task_description": {
"mean": 0,
"std": 0,
"min": 0,
"max": 0
},
"annotation.human.validity": {
"mean": 1,
"std": 0,
"min": 1,
"max": 1
},
"next.reward": {
"mean": 1,
"std": 0,
"min": 1,
"max": 1
}
} |
31 | {
"annotation.human.action.task_description": {
"mean": 0,
"std": 0,
"min": 0,
"max": 0
},
"annotation.human.validity": {
"mean": 1,
"std": 0,
"min": 1,
"max": 1
},
"next.reward": {
"mean": 1,
"std": 0,
"min": 1,
"max": 1
}
} |
32 | {
"annotation.human.action.task_description": {
"mean": 0,
"std": 0,
"min": 0,
"max": 0
},
"annotation.human.validity": {
"mean": 1,
"std": 0,
"min": 1,
"max": 1
},
"next.reward": {
"mean": 1,
"std": 0,
"min": 1,
"max": 1
}
} |
33 | {
"annotation.human.action.task_description": {
"mean": 0,
"std": 0,
"min": 0,
"max": 0
},
"annotation.human.validity": {
"mean": 1,
"std": 0,
"min": 1,
"max": 1
},
"next.reward": {
"mean": 1,
"std": 0,
"min": 1,
"max": 1
}
} |
34 | {
"annotation.human.action.task_description": {
"mean": 0,
"std": 0,
"min": 0,
"max": 0
},
"annotation.human.validity": {
"mean": 1,
"std": 0,
"min": 1,
"max": 1
},
"next.reward": {
"mean": 1,
"std": 0,
"min": 1,
"max": 1
}
} |
35 | {
"annotation.human.action.task_description": {
"mean": 0,
"std": 0,
"min": 0,
"max": 0
},
"annotation.human.validity": {
"mean": 1,
"std": 0,
"min": 1,
"max": 1
},
"next.reward": {
"mean": 1,
"std": 0,
"min": 1,
"max": 1
}
} |
36 | {
"annotation.human.action.task_description": {
"mean": 0,
"std": 0,
"min": 0,
"max": 0
},
"annotation.human.validity": {
"mean": 1,
"std": 0,
"min": 1,
"max": 1
},
"next.reward": {
"mean": 1,
"std": 0,
"min": 1,
"max": 1
}
} |
37 | {
"annotation.human.action.task_description": {
"mean": 0,
"std": 0,
"min": 0,
"max": 0
},
"annotation.human.validity": {
"mean": 1,
"std": 0,
"min": 1,
"max": 1
},
"next.reward": {
"mean": 1,
"std": 0,
"min": 1,
"max": 1
}
} |
38 | {
"annotation.human.action.task_description": {
"mean": 0,
"std": 0,
"min": 0,
"max": 0
},
"annotation.human.validity": {
"mean": 1,
"std": 0,
"min": 1,
"max": 1
},
"next.reward": {
"mean": 1,
"std": 0,
"min": 1,
"max": 1
}
} |
39 | {
"annotation.human.action.task_description": {
"mean": 0,
"std": 0,
"min": 0,
"max": 0
},
"annotation.human.validity": {
"mean": 1,
"std": 0,
"min": 1,
"max": 1
},
"next.reward": {
"mean": 1,
"std": 0,
"min": 1,
"max": 1
}
} |
40 | {
"annotation.human.action.task_description": {
"mean": 0,
"std": 0,
"min": 0,
"max": 0
},
"annotation.human.validity": {
"mean": 1,
"std": 0,
"min": 1,
"max": 1
},
"next.reward": {
"mean": 1,
"std": 0,
"min": 1,
"max": 1
}
} |
41 | {
"annotation.human.action.task_description": {
"mean": 0,
"std": 0,
"min": 0,
"max": 0
},
"annotation.human.validity": {
"mean": 1,
"std": 0,
"min": 1,
"max": 1
},
"next.reward": {
"mean": 1,
"std": 0,
"min": 1,
"max": 1
}
} |
42 | {
"annotation.human.action.task_description": {
"mean": 0,
"std": 0,
"min": 0,
"max": 0
},
"annotation.human.validity": {
"mean": 1,
"std": 0,
"min": 1,
"max": 1
},
"next.reward": {
"mean": 1,
"std": 0,
"min": 1,
"max": 1
}
} |
43 | {
"annotation.human.action.task_description": {
"mean": 0,
"std": 0,
"min": 0,
"max": 0
},
"annotation.human.validity": {
"mean": 1,
"std": 0,
"min": 1,
"max": 1
},
"next.reward": {
"mean": 1,
"std": 0,
"min": 1,
"max": 1
}
} |
44 | {
"annotation.human.action.task_description": {
"mean": 0,
"std": 0,
"min": 0,
"max": 0
},
"annotation.human.validity": {
"mean": 1,
"std": 0,
"min": 1,
"max": 1
},
"next.reward": {
"mean": 1,
"std": 0,
"min": 1,
"max": 1
}
} |
45 | {
"annotation.human.action.task_description": {
"mean": 0,
"std": 0,
"min": 0,
"max": 0
},
"annotation.human.validity": {
"mean": 1,
"std": 0,
"min": 1,
"max": 1
},
"next.reward": {
"mean": 1,
"std": 0,
"min": 1,
"max": 1
}
} |
46 | {
"annotation.human.action.task_description": {
"mean": 0,
"std": 0,
"min": 0,
"max": 0
},
"annotation.human.validity": {
"mean": 1,
"std": 0,
"min": 1,
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null | null |
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