pretty_name: PAARBench PushObj Training Data
tags:
- robotics
- world-models
- test-time-adaptation
Optional training dataset
The PAARBench evaluation protocol does not require training trajectories. Its goal
segments are tracked under data/pushobj_eval/, and evaluation reads fixed
normalization metadata without opening the training dataset.
The training release is provided for researchers who want to reproduce base-model or adapter training, or develop methods that explicitly use offline trajectories:
.venv/bin/python scripts/download_data.py
The downloader fetches the immutable benchmark release from the
ThomasWalker1/paarbench-data
dataset repository into data/pushobj_multishape/ and verifies it against
DATASET_MANIFEST.json.
Contents
The release contains only the nonredundant splits used by the training pipeline:
| split | episodes | files | bytes |
|---|---|---|---|
train |
7,200 | 7,206 | 864,106,305 |
val |
800 | 806 | 97,366,292 |
Each split contains states.pth, velocities.pth, rel_actions.pth,
abs_actions.pth, seq_lengths.pkl, shapes.pkl, and one MP4 observation stream per
episode under obses/. Redundant root-level copies and intermediate shards are not
part of the release.
The trajectories were generated in the PushObj simulator across the T, L, Z, and + shapes. No license is asserted here beyond the rights of the repository owner; users should review the dataset repository card and applicable upstream asset licenses before redistribution.