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Error code: StreamingRowsError Exception: ReadError Message: unexpected end of data Traceback: Traceback (most recent call last): File "/src/services/worker/src/worker/utils.py", line 90, in get_rows_or_raise return get_rows( File "/src/libs/libcommon/src/libcommon/utils.py", line 197, in decorator return func(*args, **kwargs) File "/src/services/worker/src/worker/utils.py", line 68, in get_rows rows_plus_one = list(itertools.islice(ds, rows_max_number + 1)) File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 2012, in __iter__ for key, example in ex_iterable: File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 188, in __iter__ for key_example in islice(self.generate_examples_fn(**gen_kwags), shard_example_idx_start, None): File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 113, in _generate_examples for example_idx, example in enumerate(self._get_pipeline_from_tar(tar_path, tar_iterator)): File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/webdataset/webdataset.py", line 40, in _get_pipeline_from_tar current_example[field_name.lower()] = f.read() File "/usr/local/lib/python3.9/tarfile.py", line 690, in read raise ReadError("unexpected end of data") tarfile.ReadError: unexpected end of data
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Dataset Card
This is the fine-tuning dataset used in the paper RDT-1B: a Diffusion Foundation Model for Bimanual Manipulation.
Source
- Project Page: https://rdt-robotics.github.io/rdt-robotics/
- Paper: https://arxiv.org/pdf/2410.07864
- Code: https://github.com/thu-ml/RoboticsDiffusionTransformer
- Model: https://huggingface.co./robotics-diffusion-transformer/rdt-1b
Uses
Download all archive files and use the following command to extract:
cat rdt_data.tar.gz.* | tar -xzvf -
In the resulting rdt_data
folder, each sub-folder is a task. In each task sub-folder, we have HDF5 files and the instruction JSON file, as illustrated below:
rdt_data/---task_1/---episode_1.hdf5
| |
|-task_2/ |-episode_2.hdf5
| |
|-task_3/ |-...
| |
|-... |-expanded_instruction_gpt-4-turbo.json
Each HDF5 file corresponds to a trajectory/episode of the task, which has the following keys:
observations
:qpos
: joint positions of the two robot arms, (TRAJ_LEN, 14); the seventh and fourteenth joints are gripper joint anglesimages
:cam_high
: RGB images from the exterior camera at each time step, (TRAJ_LEN, 480, 640, 3)cam_left_wrist
: RGB images from the left-wrist camera at each time step, (TRAJ_LEN, 480, 640, 3)cam_right_wrist
: RGB images from the right-wrist camera at each time step, (TRAJ_LEN, 480, 640, 3)
action
: desired joint positions of the two robot arms at the next time step, (TRAJ_LEN, 14); Note that this is slightly different from the actual joint positions at the next time step
Note: The number in episode_<NUMBER>.hdf5
is not necessarily consecutive. TRAJ_LEN
may vary from episode to episode.
Each JSON file corresponds to the annotated language instructions of the task, which has the following keys:
instruction
: original human-annotated instructions; its value is a stringexpanded_instruction
: instructions generated by GPT-4-Turbo by expanding the original one; its value is a list of stringssimplified_instruction
: instructions generated by GPT-4-Turbo by simplifying the original one; its value is a list of strings
Citation
If you find our work helpful, please cite us:
@article{liu2024rdt,
title={RDT-1B: a Diffusion Foundation Model for Bimanual Manipulation},
author={Liu, Songming and Wu, Lingxuan and Li, Bangguo and Tan, Hengkai and Chen, Huayu and Wang, Zhengyi and Xu, Ke and Su, Hang and Zhu, Jun},
journal={arXiv preprint arXiv:2410.07864},
year={2024}
}
Thank you!
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