Datasets:
The dataset viewer is not available for this split.
Error code: StreamingRowsError
Exception: CastError
Message: Couldn't cast
namespaces: list<item: string>
child 0, item: string
datasets: list<item: string>
child 0, item: string
total_steps: int64
dataset_id: string
total_episodes: int64
description: string
observation_space: string
data_format: string
minari_version: string
env_spec: string
code_permalink: string
dataset_size: double
algorithm_name: string
author: list<item: string>
child 0, item: string
action_space: string
to
{'total_episodes': Value('int64'), 'total_steps': Value('int64'), 'data_format': Value('string'), 'observation_space': Value('string'), 'action_space': Value('string'), 'env_spec': Value('string'), 'dataset_id': Value('string'), 'code_permalink': Value('string'), 'author': List(Value('string')), 'algorithm_name': Value('string'), 'description': Value('string'), 'minari_version': Value('string'), 'dataset_size': Value('float64')}
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 544, 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 3052, in __iter__
for key, example in ex_iterable:
^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2559, in __iter__
for key, pa_table in self._iter_arrow():
~~~~~~~~~~~~~~~~^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 2584, 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 558, in _iter_arrow
for key, pa_table in iterator:
^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/iterable_dataset.py", line 440, 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 361, 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 2381, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2309, in cast_table_to_schema
raise CastError(
...<3 lines>...
)
datasets.table.CastError: Couldn't cast
namespaces: list<item: string>
child 0, item: string
datasets: list<item: string>
child 0, item: string
total_steps: int64
dataset_id: string
total_episodes: int64
description: string
observation_space: string
data_format: string
minari_version: string
env_spec: string
code_permalink: string
dataset_size: double
algorithm_name: string
author: list<item: string>
child 0, item: string
action_space: string
to
{'total_episodes': Value('int64'), 'total_steps': Value('int64'), 'data_format': Value('string'), 'observation_space': Value('string'), 'action_space': Value('string'), 'env_spec': Value('string'), 'dataset_id': Value('string'), 'code_permalink': Value('string'), 'author': List(Value('string')), 'algorithm_name': Value('string'), 'description': Value('string'), 'minari_version': Value('string'), 'dataset_size': Value('float64')}
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.
TeleArms offline RL datasets (state)
30 Minari datasets of human teleoperated demonstrations of 10 bimanual
YAM cube tasks in MuJoCo: each task in three subsets of 1,500 demos, picked at random
(random-1500), by player ELO (elo-1500) and by demo score (score-1500). The ids are
telearms/<Task>/<subset>-v0:
import os
import minari
from huggingface_hub import snapshot_download
root = os.environ.get("MINARI_DATASETS_PATH", os.path.expanduser("~/.minari/datasets"))
snapshot_download("mliu48/telearms", repo_type="dataset", local_dir=os.path.join(root, "telearms"),
allow_patterns="CubePatchPlacement/random-1500-v0/*")
dataset = minari.load_dataset("telearms/CubePatchPlacement/random-1500-v0")
env = dataset.recover_environment() # needs telearms-gym installed
The environment is TeleArmsEnv(task, obs_mode="privileged") in
telearms-gym (gymnasium_env/telearms_env.py). On a machine without EGL, set MUJOCO_GL=disable
before importing it.
Observations are the simulator's state, not images: the robot's 14 joint and gripper values, then each cube's position, orientation and velocity (13 numbers per cube), then each goal patch's position and orientation (7 per patch).
| Task | Observation size |
|---|---|
| CubePatchPlacement | 54 |
| FrontEdgeCubeRow | 53 |
| FrontToBackCubeLine | 53 |
| LCubeArrangement | 66 |
| LetterFaceAlignment | 27 |
| RedCubeInFrontOfBlueCube | 40 |
| RedLeftOfBluePlacement | 40 |
| SemanticCubeOnRedPatchAUp | 34 |
| SequentialPushBlockToTarget | 54 |
| ThreeCubeWallRow | 53 |
Rewards. Every demo was replayed in its task's environment and scored by its rules. rewards
is the sparse reward, 1.0 on the step that reaches success, else 0. infos["reward_dense"] is the
environment's reward_type="dense" reward: 1/N on the first step that reaches each of the task's
N stages (grasp, lift, place, ...) plus 1.0 on success, at most 2 per episode. Each demo ends at
its first success (terminations), as the environment ends an episode. Of the 45,000 demos,
665 (1.5%) were accepted when played but never satisfy the environment's task check; they end with
truncations and no reward.
The same demos with camera images are the offline-rl branch of
mliu48/telearms-yam-cube-v5-exp-<subset>:
LeRobotDataset("mliu48/telearms-yam-cube-v5-exp-random-1500", revision="offline-rl").
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