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
codebase_version: string
robot_type: string
total_episodes: int64
total_frames: int64
total_tasks: int64
chunks_size: int64
data_files_size_in_mb: int64
video_files_size_in_mb: int64
fps: int64
splits: struct<train: string>
child 0, train: string
data_path: string
video_path: string
features: struct<observation.state: struct<dtype: string, shape: list<item: int64>, names: list<item: string>> (... 1124 chars omitted)
child 0, 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 1, 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 2, observation.images.front: struct<dtype: string, shape: list<item: int64>, names: list<item: string>, info: struct<video.height (... 157 chars omitted)
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 3, info: struct<video.height: int64, video.width: int64, video.codec: string, video.pix_fmt: string, video.is (... 75 chars omitted)
child 0, video.height: int64
chil
...
child 1, type: string
child 2, kwargs: struct<sharpness: list<item: double>>
child 0, sharpness: list<item: double>
child 0, item: double
child 5, affine: struct<weight: double, type: string, kwargs: struct<degrees: list<item: double>, translate: list<ite (... 12 chars omitted)
child 0, weight: double
child 1, type: string
child 2, kwargs: struct<degrees: list<item: double>, translate: list<item: double>>
child 0, degrees: list<item: double>
child 0, item: double
child 1, translate: list<item: double>
child 0, item: double
child 6, color_temp: struct<weight: double, type: string, kwargs: struct<temperature: list<item: double>>>
child 0, weight: double
child 1, type: string
child 2, kwargs: struct<temperature: list<item: double>>
child 0, temperature: list<item: double>
child 0, item: double
child 4, revision: null
child 5, use_imagenet_stats: bool
child 6, video_backend: string
child 7, streaming: bool
steps: int64
rabc_head_mode: string
resume: bool
seed: int64
rabc_kappa: double
scheduler: struct<type: string, num_warmup_steps: int64, name: string>
child 0, type: string
child 1, num_warmup_steps: int64
child 2, name: string
rabc_epsilon: double
checkpoint_path: null
tolerance_s: double
to
{'dataset': {'repo_id': Value('string'), 'root': Value('string'), 'episodes': Value('null'), 'image_transforms': {'enable': Value('bool'), 'max_num_transforms': Value('int64'), 'random_order': Value('bool'), 'tfs': {'brightness': {'weight': Value('float64'), 'type': Value('string'), 'kwargs': {'brightness': List(Value('float64'))}}, 'contrast': {'weight': Value('float64'), 'type': Value('string'), 'kwargs': {'contrast': List(Value('float64'))}}, 'saturation': {'weight': Value('float64'), 'type': Value('string'), 'kwargs': {'saturation': List(Value('float64'))}}, 'hue': {'weight': Value('float64'), 'type': Value('string'), 'kwargs': {'hue': List(Value('float64'))}}, 'sharpness': {'weight': Value('float64'), 'type': Value('string'), 'kwargs': {'sharpness': List(Value('float64'))}}, 'affine': {'weight': Value('float64'), 'type': Value('string'), 'kwargs': {'degrees': List(Value('float64')), 'translate': List(Value('float64'))}}, 'color_temp': {'weight': Value('float64'), 'type': Value('string'), 'kwargs': {'temperature': List(Value('float64'))}}}}, 'revision': Value('null'), 'use_imagenet_stats': Value('bool'), 'video_backend': Value('string'), 'streaming': Value('bool')}, 'env': Value('null'), 'policy': {'type': Value('string'), 'n_obs_steps': Value('int64'), 'input_features': {'observation.images.front': {'type': Value('string'), 'shape': List(Value('int64'))}, 'observation.images.right_wrist_top': {'type': Value('string'), 'shape': List(Value('int64'))}, 'observation.state':
...
eps': Value('int64'), 'do_mask_loss_for_padding': Value('bool'), 'optimizer_lr': Value('float64'), 'optimizer_betas': List(Value('float64')), 'optimizer_eps': Value('float64'), 'optimizer_weight_decay': Value('float64'), 'scheduler_name': Value('string'), 'scheduler_warmup_steps': Value('int64')}, 'output_dir': Value('string'), 'job_name': Value('string'), 'resume': Value('bool'), 'seed': Value('int64'), 'num_workers': Value('int64'), 'batch_size': Value('int64'), 'steps': Value('int64'), 'eval_freq': Value('int64'), 'log_freq': Value('int64'), 'tolerance_s': Value('float64'), 'save_checkpoint': Value('bool'), 'save_freq': Value('int64'), 'use_policy_training_preset': Value('bool'), 'optimizer': {'type': Value('string'), 'lr': Value('float64'), 'weight_decay': Value('float64'), 'grad_clip_norm': Value('float64'), 'betas': List(Value('float64')), 'eps': Value('float64')}, 'scheduler': {'type': Value('string'), 'num_warmup_steps': Value('int64'), 'name': Value('string')}, 'eval': {'n_episodes': Value('int64'), 'batch_size': Value('int64'), 'use_async_envs': Value('bool')}, 'wandb': {'enable': Value('bool'), 'disable_artifact': Value('bool'), 'project': Value('string'), 'entity': Value('null'), 'notes': Value('null'), 'run_id': Value('null'), 'mode': Value('null')}, 'use_rabc': Value('bool'), 'rabc_progress_path': Value('null'), 'rabc_kappa': Value('float64'), 'rabc_epsilon': Value('float64'), 'rabc_head_mode': Value('string'), 'rename_map': {}, 'checkpoint_path': Value('null')}
because column names don't match
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/utils.py", line 147, 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 127, 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 483, 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 2951, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2461, in __iter__
for key, pa_table in self._iter_arrow():
~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2486, 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 547, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 430, 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 2378, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2306, in cast_table_to_schema
raise CastError(
...<3 lines>...
)
datasets.table.CastError: Couldn't cast
codebase_version: string
robot_type: string
total_episodes: int64
total_frames: int64
total_tasks: int64
chunks_size: int64
data_files_size_in_mb: int64
video_files_size_in_mb: int64
fps: int64
splits: struct<train: string>
child 0, train: string
data_path: string
video_path: string
features: struct<observation.state: struct<dtype: string, shape: list<item: int64>, names: list<item: string>> (... 1124 chars omitted)
child 0, 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 1, 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 2, observation.images.front: struct<dtype: string, shape: list<item: int64>, names: list<item: string>, info: struct<video.height (... 157 chars omitted)
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 3, info: struct<video.height: int64, video.width: int64, video.codec: string, video.pix_fmt: string, video.is (... 75 chars omitted)
child 0, video.height: int64
chil
...
child 1, type: string
child 2, kwargs: struct<sharpness: list<item: double>>
child 0, sharpness: list<item: double>
child 0, item: double
child 5, affine: struct<weight: double, type: string, kwargs: struct<degrees: list<item: double>, translate: list<ite (... 12 chars omitted)
child 0, weight: double
child 1, type: string
child 2, kwargs: struct<degrees: list<item: double>, translate: list<item: double>>
child 0, degrees: list<item: double>
child 0, item: double
child 1, translate: list<item: double>
child 0, item: double
child 6, color_temp: struct<weight: double, type: string, kwargs: struct<temperature: list<item: double>>>
child 0, weight: double
child 1, type: string
child 2, kwargs: struct<temperature: list<item: double>>
child 0, temperature: list<item: double>
child 0, item: double
child 4, revision: null
child 5, use_imagenet_stats: bool
child 6, video_backend: string
child 7, streaming: bool
steps: int64
rabc_head_mode: string
resume: bool
seed: int64
rabc_kappa: double
scheduler: struct<type: string, num_warmup_steps: int64, name: string>
child 0, type: string
child 1, num_warmup_steps: int64
child 2, name: string
rabc_epsilon: double
checkpoint_path: null
tolerance_s: double
to
{'dataset': {'repo_id': Value('string'), 'root': Value('string'), 'episodes': Value('null'), 'image_transforms': {'enable': Value('bool'), 'max_num_transforms': Value('int64'), 'random_order': Value('bool'), 'tfs': {'brightness': {'weight': Value('float64'), 'type': Value('string'), 'kwargs': {'brightness': List(Value('float64'))}}, 'contrast': {'weight': Value('float64'), 'type': Value('string'), 'kwargs': {'contrast': List(Value('float64'))}}, 'saturation': {'weight': Value('float64'), 'type': Value('string'), 'kwargs': {'saturation': List(Value('float64'))}}, 'hue': {'weight': Value('float64'), 'type': Value('string'), 'kwargs': {'hue': List(Value('float64'))}}, 'sharpness': {'weight': Value('float64'), 'type': Value('string'), 'kwargs': {'sharpness': List(Value('float64'))}}, 'affine': {'weight': Value('float64'), 'type': Value('string'), 'kwargs': {'degrees': List(Value('float64')), 'translate': List(Value('float64'))}}, 'color_temp': {'weight': Value('float64'), 'type': Value('string'), 'kwargs': {'temperature': List(Value('float64'))}}}}, 'revision': Value('null'), 'use_imagenet_stats': Value('bool'), 'video_backend': Value('string'), 'streaming': Value('bool')}, 'env': Value('null'), 'policy': {'type': Value('string'), 'n_obs_steps': Value('int64'), 'input_features': {'observation.images.front': {'type': Value('string'), 'shape': List(Value('int64'))}, 'observation.images.right_wrist_top': {'type': Value('string'), 'shape': List(Value('int64'))}, 'observation.state':
...
eps': Value('int64'), 'do_mask_loss_for_padding': Value('bool'), 'optimizer_lr': Value('float64'), 'optimizer_betas': List(Value('float64')), 'optimizer_eps': Value('float64'), 'optimizer_weight_decay': Value('float64'), 'scheduler_name': Value('string'), 'scheduler_warmup_steps': Value('int64')}, 'output_dir': Value('string'), 'job_name': Value('string'), 'resume': Value('bool'), 'seed': Value('int64'), 'num_workers': Value('int64'), 'batch_size': Value('int64'), 'steps': Value('int64'), 'eval_freq': Value('int64'), 'log_freq': Value('int64'), 'tolerance_s': Value('float64'), 'save_checkpoint': Value('bool'), 'save_freq': Value('int64'), 'use_policy_training_preset': Value('bool'), 'optimizer': {'type': Value('string'), 'lr': Value('float64'), 'weight_decay': Value('float64'), 'grad_clip_norm': Value('float64'), 'betas': List(Value('float64')), 'eps': Value('float64')}, 'scheduler': {'type': Value('string'), 'num_warmup_steps': Value('int64'), 'name': Value('string')}, 'eval': {'n_episodes': Value('int64'), 'batch_size': Value('int64'), 'use_async_envs': Value('bool')}, 'wandb': {'enable': Value('bool'), 'disable_artifact': Value('bool'), 'project': Value('string'), 'entity': Value('null'), 'notes': Value('null'), 'run_id': Value('null'), 'mode': Value('null')}, 'use_rabc': Value('bool'), 'rabc_progress_path': Value('null'), 'rabc_kappa': Value('float64'), 'rabc_epsilon': Value('float64'), 'rabc_head_mode': Value('string'), 'rename_map': {}, 'checkpoint_path': Value('null')}
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.
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Archived: WetLabRoboData/lerobot-data-pick_vial_20260524
This repo has been reorganized. All of its previous contents are preserved
in the old/ subfolder of this same repo (nothing was deleted).
Please use the dedicated split repos going forward:
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- See the WetLabRoboData collections for the task-grouped landing pages.
The old/ subfolder here is a safety net during migration and will be deleted
at a later date.
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