Dataset Viewer
The dataset viewer is not available for this split.
Cannot extract the features (columns) for the split 'train' of the config 'default' of the dataset.
Error code: FeaturesError
Exception: ArrowInvalid
Message: Schema at index 1 was different:
4000: struct<partnet_mobility_id: int64, scale: double>
4001: struct<partnet_mobility_id: int64, scale: double>
4003: struct<partnet_mobility_id: int64, scale: double>
4006: struct<partnet_mobility_id: int64, scale: double>
4008: struct<partnet_mobility_id: int64, scale: double>
4009: struct<partnet_mobility_id: int64, scale: double>
4010: struct<partnet_mobility_id: int64, scale: double>
4011: struct<partnet_mobility_id: int64, scale: double>
4012: struct<partnet_mobility_id: int64, scale: double>
4016: struct<partnet_mobility_id: int64, scale: double>
4017: struct<partnet_mobility_id: int64, scale: double>
4018: struct<partnet_mobility_id: int64, scale: double>
4019: struct<partnet_mobility_id: int64, scale: double>
4020: struct<partnet_mobility_id: int64, scale: double>
4021: struct<partnet_mobility_id: int64, scale: double>
4022: struct<partnet_mobility_id: int64, scale: double>
4023: struct<partnet_mobility_id: int64, scale: double>
4024: struct<partnet_mobility_id: int64, scale: double>
4025: struct<partnet_mobility_id: int64, scale: double>
4031: struct<partnet_mobility_id: int64, scale: double>
4032: struct<partnet_mobility_id: int64, scale: double>
4035: struct<partnet_mobility_id: int64, scale: double>
4043: struct<partnet_mobility_id: int64, scale: double>
4044: struct<partnet_mobility_id: int64, scale: double>
4045: struct<partnet_mobility_id: int64, scale: double>
4051: struct<partnet_mobility_id: int64, scale: double>
4052: struct<partnet_mobility_id: int64, scale: double>
4055: struct<partnet_mobility_id: int64, scale: double>
4056: struct<partnet_mobility_id: int64, scale: double>
vs
1000: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1001: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1002: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1006: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1007: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1014: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1017: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1018: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1025: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1026: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1027: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1028: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1030: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1031: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1034: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1036: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1038: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1039: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1041: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1042: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1044: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1045: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1046: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1047: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1049: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1051: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1052: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1054: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1057: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1060: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1061: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1062: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1063: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1064: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1065: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1067: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1068: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1073: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1075: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1077: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1078: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1081: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
Traceback: Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 228, in compute_first_rows_from_streaming_response
iterable_dataset = iterable_dataset._resolve_features()
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 3496, in _resolve_features
features = _infer_features_from_batch(self.with_format(None)._head())
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2257, in _head
return next(iter(self.iter(batch_size=n)))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 2461, in iter
for key, example in iterator:
^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 1952, in __iter__
for key, pa_table in self._iter_arrow():
^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 1974, in _iter_arrow
yield from self.ex_iterable._iter_arrow()
File "/usr/local/lib/python3.12/site-packages/datasets/iterable_dataset.py", line 531, in _iter_arrow
yield new_key, pa.Table.from_batches(chunks_buffer)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "pyarrow/table.pxi", line 5039, in pyarrow.lib.Table.from_batches
File "pyarrow/error.pxi", line 155, in pyarrow.lib.pyarrow_internal_check_status
File "pyarrow/error.pxi", line 92, in pyarrow.lib.check_status
pyarrow.lib.ArrowInvalid: Schema at index 1 was different:
4000: struct<partnet_mobility_id: int64, scale: double>
4001: struct<partnet_mobility_id: int64, scale: double>
4003: struct<partnet_mobility_id: int64, scale: double>
4006: struct<partnet_mobility_id: int64, scale: double>
4008: struct<partnet_mobility_id: int64, scale: double>
4009: struct<partnet_mobility_id: int64, scale: double>
4010: struct<partnet_mobility_id: int64, scale: double>
4011: struct<partnet_mobility_id: int64, scale: double>
4012: struct<partnet_mobility_id: int64, scale: double>
4016: struct<partnet_mobility_id: int64, scale: double>
4017: struct<partnet_mobility_id: int64, scale: double>
4018: struct<partnet_mobility_id: int64, scale: double>
4019: struct<partnet_mobility_id: int64, scale: double>
4020: struct<partnet_mobility_id: int64, scale: double>
4021: struct<partnet_mobility_id: int64, scale: double>
4022: struct<partnet_mobility_id: int64, scale: double>
4023: struct<partnet_mobility_id: int64, scale: double>
4024: struct<partnet_mobility_id: int64, scale: double>
4025: struct<partnet_mobility_id: int64, scale: double>
4031: struct<partnet_mobility_id: int64, scale: double>
4032: struct<partnet_mobility_id: int64, scale: double>
4035: struct<partnet_mobility_id: int64, scale: double>
4043: struct<partnet_mobility_id: int64, scale: double>
4044: struct<partnet_mobility_id: int64, scale: double>
4045: struct<partnet_mobility_id: int64, scale: double>
4051: struct<partnet_mobility_id: int64, scale: double>
4052: struct<partnet_mobility_id: int64, scale: double>
4055: struct<partnet_mobility_id: int64, scale: double>
4056: struct<partnet_mobility_id: int64, scale: double>
vs
1000: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1001: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1002: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1006: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1007: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1014: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1017: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1018: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1025: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1026: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1027: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1028: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1030: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1031: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1034: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1036: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1038: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1039: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1041: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1042: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1044: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1045: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1046: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1047: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1049: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1051: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1052: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1054: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1057: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1060: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1061: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1062: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1063: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1064: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1065: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1067: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1068: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1073: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1075: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1077: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1078: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>
1081: struct<num_target_links: int64, partnet_mobility_id: int64, scale: double>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.
Asset Download
The assets need to be placed into RLinf's ManiSkill environment folder with the name assets.
# uv pip install huggingface_hub if you don't have it
cd <path_to_RLinf>/rlinf/envs/maniskill
hf download --repo-type dataset RLinf/maniskill_assets --local-dir ./assets
You can also use git to clone the repository:
cd <path_to_RLinf>/rlinf/envs/maniskill
git clone https://hf.co/datasets/RLinf/maniskill_assets ./assets
License
Our assets are attributed to objaverse. We follow the license of Objaverse-XL. The use of the dataset as a whole is licensed under the ODC-By v1.0 license. Individual objects in Objaverse-XL are licensed under different licenses.
- Downloads last month
- 661