hanapasta/skygrip-smolvla-v4
Robotics • 0.5B • Updated • 13
Dataset Viewer
The dataset viewer is not available for this split.
Cannot load the dataset split (in streaming mode) to extract the first rows.
Error code: StreamingRowsError
Exception: CastError
Message: Couldn't cast
checkpoint: string
revision: null
task_template: string
hook_side: string
grip_latch: bool
split: string
summary: struct<act: struct<n: int64, outcomes: struct<false_refusal: int64, no_engagement: int64, wrong_obje (... 126 chars omitted)
child 0, act: struct<n: int64, outcomes: struct<false_refusal: int64, no_engagement: int64, wrong_object_engagemen (... 113 chars omitted)
child 0, n: int64
child 1, outcomes: struct<false_refusal: int64, no_engagement: int64, wrong_object_engagement: int64>
child 0, false_refusal: int64
child 1, no_engagement: int64
child 2, wrong_object_engagement: int64
child 2, mean_disturbance_mm: double
child 3, median_max_tilt_deg: double
child 4, crash_rate: double
child 5, level_touchdowns: int64
episodes: list<item: struct<outcome: string, disturbance_mm: double, wrong_object_disturbance_mm: double, succ (... 406 chars omitted)
child 0, item: struct<outcome: string, disturbance_mm: double, wrong_object_disturbance_mm: double, success: bool, (... 394 chars omitted)
child 0, outcome: string
child 1, disturbance_mm: double
child 2, wrong_object_disturbance_mm: double
child 3, success: bool
child 4, why: string
child 5, episode: int64
child 6, mode: string
child 7, sector: int64
child 8, relation: string
child 9, band: string
child 10, distractor_dist_m: double
child 11, tag_condition: string
child 12, bys
...
ouble
child 3, null_auroc: double
child 4, colour_auroc: double
best: struct<trunk.last: struct<layout_auroc: double, layout_layer: int64, null_max: double, colour_auroc: (... 404 chars omitted)
child 0, trunk.last: struct<layout_auroc: double, layout_layer: int64, null_max: double, colour_auroc: double, colour_lay (... 10 chars omitted)
child 0, layout_auroc: double
child 1, layout_layer: int64
child 2, null_max: double
child 3, colour_auroc: double
child 4, colour_layer: int64
child 1, trunk.mean: struct<layout_auroc: double, layout_layer: int64, null_max: double, colour_auroc: double, colour_lay (... 10 chars omitted)
child 0, layout_auroc: double
child 1, layout_layer: int64
child 2, null_max: double
child 3, colour_auroc: double
child 4, colour_layer: int64
child 2, expert.last: struct<layout_auroc: double, layout_layer: int64, null_max: double, colour_auroc: double, colour_lay (... 10 chars omitted)
child 0, layout_auroc: double
child 1, layout_layer: int64
child 2, null_max: double
child 3, colour_auroc: double
child 4, colour_layer: int64
child 3, expert.mean: struct<layout_auroc: double, layout_layer: int64, null_max: double, colour_auroc: double, colour_lay (... 10 chars omitted)
child 0, layout_auroc: double
child 1, layout_layer: int64
child 2, null_max: double
child 3, colour_auroc: double
child 4, colour_layer: int64
to
{'n': Value('int64'), 'checkpoint': Value('string'), 'spawn_baseline_auroc': Value('float64'), 'layers': {'trunk.last': List({'layer': Value('int64'), 'layout_auroc': Value('float64'), 'layout_std': Value('float64'), 'null_auroc': Value('float64'), 'colour_auroc': Value('float64')}), 'trunk.mean': List({'layer': Value('int64'), 'layout_auroc': Value('float64'), 'layout_std': Value('float64'), 'null_auroc': Value('float64'), 'colour_auroc': Value('float64')}), 'expert.last': List({'layer': Value('int64'), 'layout_auroc': Value('float64'), 'layout_std': Value('float64'), 'null_auroc': Value('float64'), 'colour_auroc': Value('float64')}), 'expert.mean': List({'layer': Value('int64'), 'layout_auroc': Value('float64'), 'layout_std': Value('float64'), 'null_auroc': Value('float64'), 'colour_auroc': Value('float64')})}, 'best': {'trunk.last': {'layout_auroc': Value('float64'), 'layout_layer': Value('int64'), 'null_max': Value('float64'), 'colour_auroc': Value('float64'), 'colour_layer': Value('int64')}, 'trunk.mean': {'layout_auroc': Value('float64'), 'layout_layer': Value('int64'), 'null_max': Value('float64'), 'colour_auroc': Value('float64'), 'colour_layer': Value('int64')}, 'expert.last': {'layout_auroc': Value('float64'), 'layout_layer': Value('int64'), 'null_max': Value('float64'), 'colour_auroc': Value('float64'), 'colour_layer': Value('int64')}, 'expert.mean': {'layout_auroc': Value('float64'), 'layout_layer': Value('int64'), 'null_max': Value('float64'), 'colour_auroc': Value('float64'), 'colour_layer': Value('int64')}}}
because column names don't match
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 149, in get_rows_or_raise
return get_rows(
dataset=dataset,
...<4 lines>...
column_names=column_names,
)
File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
return func(*args, **kwargs)
File "/src/services/worker/src/worker/utils.py", line 129, in get_rows
rows_plus_one = list(itertools.islice(safe_iter(ds, dataset=dataset), rows_max_number + 1))
File "/src/services/worker/src/worker/utils.py", line 489, in safe_iter
yield from ds.decode(False) if ds.features else ds
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2818, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2355, in __iter__
for key, pa_table in self._iter_arrow():
~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2380, in _iter_arrow
for key, pa_table in self.ex_iterable._iter_arrow():
~~~~~~~~~~~~~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 536, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 419, in _iter_arrow
for key, pa_table in self.generate_tables_fn(**gen_kwags):
~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 343, in _generate_tables
self._cast_table(pa_table, json_field_paths=json_field_paths),
~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
pa_table = table_cast(pa_table, self.info.features.arrow_schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2369, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2297, in cast_table_to_schema
raise CastError(
...<3 lines>...
)
datasets.table.CastError: Couldn't cast
checkpoint: string
revision: null
task_template: string
hook_side: string
grip_latch: bool
split: string
summary: struct<act: struct<n: int64, outcomes: struct<false_refusal: int64, no_engagement: int64, wrong_obje (... 126 chars omitted)
child 0, act: struct<n: int64, outcomes: struct<false_refusal: int64, no_engagement: int64, wrong_object_engagemen (... 113 chars omitted)
child 0, n: int64
child 1, outcomes: struct<false_refusal: int64, no_engagement: int64, wrong_object_engagement: int64>
child 0, false_refusal: int64
child 1, no_engagement: int64
child 2, wrong_object_engagement: int64
child 2, mean_disturbance_mm: double
child 3, median_max_tilt_deg: double
child 4, crash_rate: double
child 5, level_touchdowns: int64
episodes: list<item: struct<outcome: string, disturbance_mm: double, wrong_object_disturbance_mm: double, succ (... 406 chars omitted)
child 0, item: struct<outcome: string, disturbance_mm: double, wrong_object_disturbance_mm: double, success: bool, (... 394 chars omitted)
child 0, outcome: string
child 1, disturbance_mm: double
child 2, wrong_object_disturbance_mm: double
child 3, success: bool
child 4, why: string
child 5, episode: int64
child 6, mode: string
child 7, sector: int64
child 8, relation: string
child 9, band: string
child 10, distractor_dist_m: double
child 11, tag_condition: string
child 12, bys
...
ouble
child 3, null_auroc: double
child 4, colour_auroc: double
best: struct<trunk.last: struct<layout_auroc: double, layout_layer: int64, null_max: double, colour_auroc: (... 404 chars omitted)
child 0, trunk.last: struct<layout_auroc: double, layout_layer: int64, null_max: double, colour_auroc: double, colour_lay (... 10 chars omitted)
child 0, layout_auroc: double
child 1, layout_layer: int64
child 2, null_max: double
child 3, colour_auroc: double
child 4, colour_layer: int64
child 1, trunk.mean: struct<layout_auroc: double, layout_layer: int64, null_max: double, colour_auroc: double, colour_lay (... 10 chars omitted)
child 0, layout_auroc: double
child 1, layout_layer: int64
child 2, null_max: double
child 3, colour_auroc: double
child 4, colour_layer: int64
child 2, expert.last: struct<layout_auroc: double, layout_layer: int64, null_max: double, colour_auroc: double, colour_lay (... 10 chars omitted)
child 0, layout_auroc: double
child 1, layout_layer: int64
child 2, null_max: double
child 3, colour_auroc: double
child 4, colour_layer: int64
child 3, expert.mean: struct<layout_auroc: double, layout_layer: int64, null_max: double, colour_auroc: double, colour_lay (... 10 chars omitted)
child 0, layout_auroc: double
child 1, layout_layer: int64
child 2, null_max: double
child 3, colour_auroc: double
child 4, colour_layer: int64
to
{'n': Value('int64'), 'checkpoint': Value('string'), 'spawn_baseline_auroc': Value('float64'), 'layers': {'trunk.last': List({'layer': Value('int64'), 'layout_auroc': Value('float64'), 'layout_std': Value('float64'), 'null_auroc': Value('float64'), 'colour_auroc': Value('float64')}), 'trunk.mean': List({'layer': Value('int64'), 'layout_auroc': Value('float64'), 'layout_std': Value('float64'), 'null_auroc': Value('float64'), 'colour_auroc': Value('float64')}), 'expert.last': List({'layer': Value('int64'), 'layout_auroc': Value('float64'), 'layout_std': Value('float64'), 'null_auroc': Value('float64'), 'colour_auroc': Value('float64')}), 'expert.mean': List({'layer': Value('int64'), 'layout_auroc': Value('float64'), 'layout_std': Value('float64'), 'null_auroc': Value('float64'), 'colour_auroc': Value('float64')})}, 'best': {'trunk.last': {'layout_auroc': Value('float64'), 'layout_layer': Value('int64'), 'null_max': Value('float64'), 'colour_auroc': Value('float64'), 'colour_layer': Value('int64')}, 'trunk.mean': {'layout_auroc': Value('float64'), 'layout_layer': Value('int64'), 'null_max': Value('float64'), 'colour_auroc': Value('float64'), 'colour_layer': Value('int64')}, 'expert.last': {'layout_auroc': Value('float64'), 'layout_layer': Value('int64'), 'null_max': Value('float64'), 'colour_auroc': Value('float64'), 'colour_layer': Value('int64')}, 'expert.mean': {'layout_auroc': Value('float64'), 'layout_layer': Value('int64'), 'null_max': Value('float64'), 'colour_auroc': Value('float64'), 'colour_layer': Value('int64')}}}
because column names don't matchNeed help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
No dataset card yet
- Downloads last month
- 95