Language

Resume And Checkpoints¶

Checkpoint selection is controlled by algorithm-level fields. Use algo.load_run, not training.load_run.

Resume Training¶

Use a run id or -1 for the latest run in the relevant log directory:

uv run train --algo ppo --task go2_joystick_flat --sim mujoco \
  algo.load_run=-1 \
  training.no_play=true

uv run train --algo sac --task g1_walk_flat --sim mujoco \
  algo.load_run=2026-03-16_01-35-12_mujoco \
  training.no_play=true

Replay A Checkpoint¶

uv run eval --algo ppo --task go2_joystick_flat --sim mujoco --load-run -1
uv run eval --algo sac --task g1_walk_flat --sim mujoco --load-run -1

uv run eval maps --load-run to the underlying checkpoint selector and sets playback mode:

uv run eval --algo ppo --task go2_joystick_flat --sim mujoco --load-run -1

Some script paths accept a checkpoint path through algo.load_run; the unified CLI validates --load-run as a run id and does not accept path separators.

Seeds¶

Training seed resolution is implemented in src/unilab/training/seed.py. Algorithm configs currently carry algo.seed, and the helper records seed metadata when experiment tracking is active.