Checkpoint on final step of training even when it doesn't coincide wi…

…th `save_freq`. (#284)

lerobot/configs/default.yaml

@@ -39,9 +39,10 @@ training:
   # `online_env_seed` is used for environments for online training data rollouts.
   online_env_seed: ???
   eval_freq: ???
-  save_freq: ???
   log_freq: 250
   save_checkpoint: true
+  # Checkpoint is saved every `save_freq` training iterations and after the last training step.
+  save_freq: ???
   num_workers: 4
   batch_size: ???
   image_transforms:

lerobot/scripts/train.py

@@ -351,7 +351,10 @@ def evaluate_and_checkpoint_if_needed(step):
                 logger.log_video(eval_info["video_paths"][0], step, mode="eval")
             logging.info("Resume training")
 
-        if cfg.training.save_checkpoint and step % cfg.training.save_freq == 0:
+        if cfg.training.save_checkpoint and (
+            step % cfg.training.save_freq == 0
+            or step == cfg.training.offline_steps + cfg.training.online_steps
+        ):
             logging.info(f"Checkpoint policy after step {step}")
             # Note: Save with step as the identifier, and format it to have at least 6 digits but more if
             # needed (choose 6 as a minimum for consistency without being overkill).