Commit History
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Wave 3: integration architecture + spike-005 trainer skeleton (16 tests pass)
baladithyabUser asked: can RLVR + Composer-SDPO + N-teacher-replay all integrate complementarily with the PyTorch agentic-RL stack (Monarch / TorchForge / OpenEnv / VeRL / TRL)? Answer (verified, not extrapolated): YES, with concrete extension points: 1. Verified ground-truth integration surfaces via DeepWiki audits: - TRL: subclass GRPOTrainer, override _compute_loss(model, inputs); plug OpenEnv via environment_factory= kwarg. - VeRL: register a new advantage estimator via @register_adv_est(name); attach extra fields to DataProto.batch / non_tensor_batch (precedent exists — distillation already uses 'teacher_log_probs' the same way). - OPSD: generalized_jsd_loss is a self-contained static method, MIT, directly liftable. FlashAttention-2 compatible, standard PyTorch. 2. NEW docs/INTEGRATION_ARCHITECTURE.md (30KB): - Per-framework integration matrix (TRL / VeRL / TorchForge / Monarch / OpenEnv) × per-channel (RLVR / SDPO / N-teacher-replay). - Sequence di…fd77f74