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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 12 new columns ({'right_sampler', 'domain', 'physics', 'frequency_samples', 'top_samples', 'top_sampler', 'right_samples', 'top_boundary', 'mesh', 'n_observations', 'right_boundary', 'frequency_sampler'}) and 12 missing columns ({'transport_0', 'rank', 'mkdir_mus', 'threads', 'meta_sort_merge_mus', 'minmax_mus', 'bytes', 'start', 'transport_1', 'buffering_mus', 'aggregation_mus', 'memcpy_mus'}).
This happened while the json dataset builder was generating data using
hf://datasets/JakobEWagner/helmholtz_pulsating_sphere_s4096_f400-500_Yre0-1_Yim-1-0/train/properties.json (at revision 87bd9acb3b41ac1cd447848a711de833ff02aa6a)
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
domain: struct<box_lengths: list<item: double>, sphere_radius: double, ndim: int64>
child 0, box_lengths: list<item: double>
child 0, item: double
child 1, sphere_radius: double
child 2, ndim: int64
mesh: struct<elements_per_wavelengths: int64, elements_per_radians: double, excitation_boundary: int64, top_boundary: int64, right_boundary: int64>
child 0, elements_per_wavelengths: int64
child 1, elements_per_radians: double
child 2, excitation_boundary: int64
child 3, top_boundary: int64
child 4, right_boundary: int64
physics: struct<c: double, rho: double>
child 0, c: double
child 1, rho: double
n_observations: int64
frequency_sampler: struct<type: string, x_min: list<item: double>, x_max: list<item: double>>
child 0, type: string
child 1, x_min: list<item: double>
child 0, item: double
child 2, x_max: list<item: double>
child 0, item: double
top_boundary: string
top_sampler: struct<type: string, x_min: list<item: double>, x_max: list<item: double>>
child 0, type: string
child 1, x_min: list<item: double>
child 0, item: double
child 2, x_max: list<item: double>
child 0, item: double
right_boundary: string
right_sampler: struct<type: string, x_min: list<item: double>, x_max: list<item: double>>
child 0, type: string
child 1, x_min: list<item: double>
child 0, item: double
child 2, x_max: list<item: double>
child 0, item: double
frequency_samples: list<item: double>
child 0, item: double
top_samples: list<item: list<item: double>>
child 0, item: list<item: double>
child 0, item: double
right_samples: list<item: list<item: double>>
child 0, item: list<item: double>
child 0, item: double
to
{'transport_0': {'close_mus': Value(dtype='int64', id=None), 'open_mus': Value(dtype='int64', id=None), 'type': Value(dtype='string', id=None), 'write_mus': Value(dtype='int64', id=None)}, 'rank': Value(dtype='int64', id=None), 'mkdir_mus': Value(dtype='int64', id=None), 'threads': Value(dtype='int64', id=None), 'meta_sort_merge_mus': Value(dtype='int64', id=None), 'minmax_mus': Value(dtype='int64', id=None), 'bytes': Value(dtype='int64', id=None), 'start': Value(dtype='string', id=None), 'transport_1': {'close_mus': Value(dtype='int64', id=None), 'open_mus': Value(dtype='int64', id=None), 'type': Value(dtype='string', id=None), 'write_mus': Value(dtype='int64', id=None)}, 'buffering_mus': Value(dtype='int64', id=None), 'aggregation_mus': Value(dtype='int64', id=None), 'memcpy_mus': Value(dtype='int64', 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 1577, 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 1191, in convert_to_parquet
builder.download_and_prepare(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1027, in download_and_prepare
self._download_and_prepare(
File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/builder.py", line 1122, 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 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 12 new columns ({'right_sampler', 'domain', 'physics', 'frequency_samples', 'top_samples', 'top_sampler', 'right_samples', 'top_boundary', 'mesh', 'n_observations', 'right_boundary', 'frequency_sampler'}) and 12 missing columns ({'transport_0', 'rank', 'mkdir_mus', 'threads', 'meta_sort_merge_mus', 'minmax_mus', 'bytes', 'start', 'transport_1', 'buffering_mus', 'aggregation_mus', 'memcpy_mus'}).
This happened while the json dataset builder was generating data using
hf://datasets/JakobEWagner/helmholtz_pulsating_sphere_s4096_f400-500_Yre0-1_Yim-1-0/train/properties.json (at revision 87bd9acb3b41ac1cd447848a711de833ff02aa6a)
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.
transport_0
dict | rank
int64 | mkdir_mus
int64 | threads
int64 | meta_sort_merge_mus
int64 | minmax_mus
int64 | bytes
int64 | start
string | transport_1
dict | buffering_mus
int64 | aggregation_mus
int64 | memcpy_mus
int64 | domain
dict | mesh
dict | physics
dict | n_observations
int64 | frequency_sampler
dict | top_boundary
string | top_sampler
dict | right_boundary
string | right_sampler
dict | frequency_samples
sequence | top_samples
sequence | right_samples
sequence |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
{
"close_mus": 10,
"open_mus": 111,
"type": "File_POSIX",
"write_mus": 695151
} | 0 | 100 | 1 | 163,071 | 225,509 | 762,404,487 | Tue_Jul_09_12:07:07_2024 | {
"close_mus": 0,
"open_mus": 106,
"type": "File_POSIX",
"write_mus": 29679
} | 549,520 | 0 | 45,455 | null | null | null | null | null | null | null | null | null | null | null | null |
null | null | null | null | null | null | null | null | null | null | null | null | {
"box_lengths": [
1,
1
],
"sphere_radius": 0.2,
"ndim": 2
} | {"elements_per_wavelengths":15,"elements_per_radians":30.0,"excitation_boundary":101,"top_boundary":(...TRUNCATED) | {
"c": 343.2,
"rho": 1.2043
} | 4,096 | {
"type": "UniformSampler",
"x_min": [
400
],
"x_max": [
500
]
} | lambda a: lambda x: np.ones(x[0].shape) * a[0] + 1j * a[1] * np.ones(x[0].shape)
| {
"type": "UniformSampler",
"x_min": [
0,
-1
],
"x_max": [
1,
0
]
} | lambda a: lambda x: np.ones(x[1].shape) * a[0] + 1j * a[1] * np.ones(x[1].shape)
| {
"type": "UniformSampler",
"x_min": [
0,
-1
],
"x_max": [
1,
0
]
} | [434.6165019391972,420.4460772608176,405.8112930826629,405.62020055309284,448.8348308228759,466.2431(...TRUNCATED) | [[0.8601686212786032,-0.2786319944558162],[0.791580906537889,-0.7637266205339663],[0.780039091103954(...TRUNCATED) | [[0.7649005505092011,-0.5652698979192223],[0.37385365784649094,-0.5976737086596499],[0.3398699743841(...TRUNCATED) |