Files
lerobot/tests
pepijn 3d0e8681f3 refactor(datasets): make EpisodeAwareSampler always deterministic
With Feistel gone, deterministic and legacy modes were both just torch.randperm and the
deterministic path strictly dominated (reproducible across ranks via the (seed, epoch) seed,
no accelerate generator sync, resumable). Collapse to a single path and drop the redundant
flag:

- remove the `deterministic` and `generator` constructor args, `_iter_default`, and
  `_require_deterministic`; `set_epoch` / `state_dict` / `load_state_dict` are now unconditional
- remove the `deterministic_sampler` train config field and the legacy generator branch in
  lerobot_train.py (non-streaming map datasets always use the sampler)
- drop the now-obsolete generator/legacy tests

Note: removes the `generator` kwarg from EpisodeAwareSampler (back-compat break vs main); the
order is now a pure function of (seed, epoch), so no cross-rank RNG sync is needed.

Co-authored-by: Cursor <cursoragent@cursor.com>
2026-06-11 15:31:15 +00:00
..
2026-05-12 15:49:54 +02:00