Datasets:

YujieZhao
/

VoLoAgent-V12

Tasks:

Robotics

Languages:

English

Size:

1K<n<10K

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xet

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The dataset generation failed

Error code:   DatasetGenerationError
Exception:    TypeError
Message:      int() argument must be a string, a bytes-like object or a real number, not 'NoneType'
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1531, in _prepare_split_single
                  for key, record in generator:
                                     ^^^^^^^^^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 613, in wrapped
                  for item in generator(*args, **kwargs):
                              ~~~~~~~~~^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 127, in _generate_examples
                  for example_idx, example in enumerate(self._get_pipeline_from_tar(tar_path, tar_iterator)):
                                              ~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 32, in _get_pipeline_from_tar
                  for filename, f in tar_iterator:
                                     ^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/utils/track.py", line 49, in __iter__
                  for x in self.generator(*self.args):
                           ~~~~~~~~~~~~~~^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/utils/file_utils.py", line 1405, in _iter_from_urlpath
                  with xopen(urlpath, "rb", download_config=download_config, block_size=0) as f:
                       ~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/utils/file_utils.py", line 982, in xopen
                  file_obj = fs.open(paths[0], mode)
                File "<string>", line 3, in open
                File "/usr/local/lib/python3.14/unittest/mock.py", line 1176, in __call__
                  return self._mock_call(*args, **kwargs)
                         ~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/unittest/mock.py", line 1180, in _mock_call
                  return self._execute_mock_call(*args, **kwargs)
                         ~~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/unittest/mock.py", line 1247, in _execute_mock_call
                  result = effect(*args, **kwargs)
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 786, in wrapped
                  tracker.files[urlpath] = {"read": 0, "size": int(f.size)}
                                                               ~~~^^^^^^^^
              TypeError: int() argument must be a string, a bytes-like object or a real number, not 'NoneType'
              
              The above exception was the direct cause of the following exception:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1369, in compute_config_parquet_and_info_response
                  parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
                                                                        ~~~~~~~~~~~~~~~~~~~~~~~~~^
                      builder, max_dataset_size_bytes=max_dataset_size_bytes
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  )
                  ^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 948, in stream_convert_to_parquet
                  builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
                  ~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1393, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                                               ~~~~~~~~~~~~~~~~~~~~~~~~~~^
                      gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  ):
                  ^
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1571, in _prepare_split_single
                  raise DatasetGenerationError("An error occurred while generating the dataset") from e
              datasets.exceptions.DatasetGenerationError: An error occurred while generating the dataset

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	assets/v12_0016940_0/00454_wrist	hf://datasets/YujieZhao/VoLoAgent-V12@edd595857ca1036f80b7beda62713fec60164b52/shards/v12-train-00000-of-00080.tar
	assets/v12_0016940_0/00482_front	hf://datasets/YujieZhao/VoLoAgent-V12@edd595857ca1036f80b7beda62713fec60164b52/shards/v12-train-00000-of-00080.tar
	assets/v12_0016940_0/00482_wrist	hf://datasets/YujieZhao/VoLoAgent-V12@edd595857ca1036f80b7beda62713fec60164b52/shards/v12-train-00000-of-00080.tar
	assets/v12_0016940_0/00511_front	hf://datasets/YujieZhao/VoLoAgent-V12@edd595857ca1036f80b7beda62713fec60164b52/shards/v12-train-00000-of-00080.tar
	assets/v12_0016940_0/00511_wrist	hf://datasets/YujieZhao/VoLoAgent-V12@edd595857ca1036f80b7beda62713fec60164b52/shards/v12-train-00000-of-00080.tar
	assets/v12_0016940_0/00539_front	hf://datasets/YujieZhao/VoLoAgent-V12@edd595857ca1036f80b7beda62713fec60164b52/shards/v12-train-00000-of-00080.tar
	assets/v12_0016940_0/00539_wrist	hf://datasets/YujieZhao/VoLoAgent-V12@edd595857ca1036f80b7beda62713fec60164b52/shards/v12-train-00000-of-00080.tar
	assets/v12_0016940_0/00567_front	hf://datasets/YujieZhao/VoLoAgent-V12@edd595857ca1036f80b7beda62713fec60164b52/shards/v12-train-00000-of-00080.tar
	assets/v12_0016940_0/00567_wrist	hf://datasets/YujieZhao/VoLoAgent-V12@edd595857ca1036f80b7beda62713fec60164b52/shards/v12-train-00000-of-00080.tar
	assets/v12_0016940_0/00596_front	hf://datasets/YujieZhao/VoLoAgent-V12@edd595857ca1036f80b7beda62713fec60164b52/shards/v12-train-00000-of-00080.tar
	assets/v12_0016940_0/00596_wrist	hf://datasets/YujieZhao/VoLoAgent-V12@edd595857ca1036f80b7beda62713fec60164b52/shards/v12-train-00000-of-00080.tar

End of preview.

LIBERO V12 RGB-D-grounded atomic dataset

This is the exact 4,000-episode train release used by VoLoAgent V12. It contains 96,000 sampled observations (24 per episode), raw front/wrist RGB images, robot state, 20-step action targets, and natural-language atomic commands whose XYZ surface points are expressed in the robot-base frame.

Composition

Atomic action	Episodes
GRASP	1,200
PLACE	2,000
ARTICULATE	600
PUSH	200

Object/fixture starts and reachable destinations are perturbed. PLACE examples vary held-object/destination pairings, destination family, relation, approach, and coordinate-region size. Images contain no bounding-box overlay. XYZ text is derived from observable metric depth, camera calibration, and predicted masks.

The source trajectories are standard LIBERO demonstrations. Selected training episodes use demo IDs 0-39; LIBERO-PRO actions are not used for supervision. Offline simulator state is used only as an acceptance/rejection audit, never as policy input. This release is train-only; validation and PRO evaluation are kept separate.

Layout and use

manifests/train_episodes.jsonl has one row per episode and manifests/train_samples.jsonl has one row per sampled observation. Paths in both files are relative to the extracted dataset root. Extract every archive:

for shard in shards/v12-train-*.tar; do tar -xf "$shard"; done

The XML snapshots retain upstream simulator asset paths for provenance. Replay requires a compatible LIBERO/robosuite installation and may require remapping those asset paths. Training from RGB, text, state, and actions does not require the XML files.

fresh_model_audit.json records the final fresh-model replay audit. Per-shard SHA-256 values and episode membership are in shards.json.

Generation and loading code is in VoLoAgent at 4d2d665e9b44. Use of upstream LIBERO demonstrations and assets remains subject to their original terms.

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Total file size:

11 GB