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Datasets:
ducido
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icml2027_mg_archive_data

Tags:
robotics
robocasa
lerobot
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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 1400, 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 977, 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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End of preview.

icml2027_mg_archive_data: RoboCasa365 pilot training data (archived 2026-10-23)

This is the training data for the pilot checkpoints in ducido/icml2027_mg_archive. Each folder holds one tar per task, because HF limits API requests per account and a loose upload of ~20k small files hits that limit.

t012_dr_pilot_tar/: visual domain-randomized re-renders (T012)

  • Contents: 12 tars, t012_dr_pilot_<Task>.tar, 1.94 GB in total, 20,884 files.
  • Layout: <Task>/dr1/lerobot/ and <Task>/dr2/lerobot/. Each is a LeRobot dataset in the same format as the source RoboCasa365 demos.
  • How they were made: every human demo of the task (RoboCasa365 pretrain split, 100_demos) was re-rendered from its stored MuJoCo states. Textures, materials, lights and the agent-view camera were randomized with seed 1 (dr1) and seed 2 (dr2). Actions, states and episode boundaries are unchanged.
  • Tool: dr_rerender.py (project scripts). Rendering used NVIDIA EGL.
  • Unpack: tar -xf t012_dr_pilot_<Task>.tar -C /dev/shm/dr_pilot. This is the path that config pi05_atomic65_sd1_aug expects.

sd_pilot_r1_packed_tar/: SimDeploy rollouts (T011)

  • Contents: 12 tars, <Task>.tar, 0.60 GB in total, 3,864 files, plus a README.md.
    • 540 successful self-rollouts of ducido/pi05_atomic65_50k/35000 on the 12 pilot tasks: RoboCasa365 pretrain split, seeds 900000 + ep, 80 attempts per task, 144,103 frames.
    • The roll arm (pi05_atomic65_sd1_roll) was trained on them.
  • Layout: <Task>/lerobot/, a LeRobot v2.1 dataset in the same storage order and schema as the source human demos.
    • extras/episode_XXXXXX/ holds the MuJoCo states.npz, model.xml.gz and ep_meta.json of each episode.
  • How they were made: collected with collect_rollouts.py and packed with pack_rollouts.py (openpi fork). Only successful episodes are kept.
  • Video note: after an accidental deletion on 2026-10-23, the camera videos were re-rendered from the stored states with the collection pipeline (rerender_packed_rollouts.py: llvmpipe, libx264 crf 23, yuv420p, 20 fps, 256x256).
    • 156 videos (52 complete episodes) are originals.
    • The others differ from the lost originals at h264-noise level: mean |diff| about 2 gray levels, under 0.3% of pixels above 30.
    • Actions, states and parquet are original.
    • All 540 episodes were checked: frame counts match the parquet, and the openpi loader reads the data.
  • Unpack: tar -xf <Task>.tar -C IMPLEMENTATION/eval_runs/sd_pilot_r1/packed. This is the path that pi05_atomic65_sd1_roll expects.
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