feat: experience-guided training with continual learning replay#98
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pearlq12345 wants to merge 6 commits into
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feat: experience-guided training with continual learning replay#98pearlq12345 wants to merge 6 commits into
pearlq12345 wants to merge 6 commits into
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added 6 commits
May 6, 2026 11:17
…checks - Validates checkpoint path exists before inference starts - Checks action_dim in config.json matches manifest follower motor count - Warns on device mismatch between checkpoint and manifest - Warns on dataset repo_id mismatch between checkpoint and current dataset - Warns if dataset codebase_version is older than v2.1 - Hooked into EmbodiedService.start_inference() - 4 new tests covering missing checkpoint, action_dim mismatch, version warning, passing case
…nferenceConfigVerifier Experience replay for continual learning was premature: - lerobot BC models train from scratch, no catastrophic forgetting - no checkpoint-resume support, so replay has no effect - confusing for research users testing different models Kept: - ExperienceStore: records training history, surfaces hints for next run - InferenceConfigVerifier: checkpoint/dataset consistency checks before inference
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What
ExperienceStore: append-only JSONL store that records training outcomes (dataset, policy, result, lesson)get_replay_datasets(): retrieves historically successful datasets for the same policy to mix into new training runsTrainSessionnow records every training submission and completion as a structured experienceTrainSessiongeneratesexperience_hintfrom past terminal-state records (success/failed/error/stopped only, not submitted)continual_learningflag (defaultfalse): when enabled, mixes historical datasets into the current training run to prevent catastrophic forgetting (ref: continual learning survey, arxiv 2302.00487)Testing
tests/test_experience_replay.pyandtests/test_train_experience.pytmp_pathfixtures