ViperEkura 2c7a71a9c0 refactor: separate old policy and ref model in GRPO strategy ... - Split single ref_model into old_model (importance sampling ratio) and ref_model (frozen KL regularizer) - Move ref_model/old_model creation from strategy __init__ to TrainContextBuilder, pass as explicit parameters - Remove periodic sync_ref_model + sync_interval; add sync_old_model for external rollout loop to call - DPOStrategy also receives ref_model from builder - Fix std to use unbiased=False (population std per GRPO paper) - Remove redundant tests (test_grpo_kl_zero_at_init, test_grpo_no_sync_interval_param) - Remove --grpo_sync_interval CLI arg		2026-07-14 20:03:45 +08:00
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__init__.py	chore : 升级 torch 2.11.0+cu128，移除自定义 Muon，修复 gloo device_id	2026-06-27 16:10:37 +08:00
metric_util.py	refactor : grad_norm 指标简化，clip_grad_norm 移至 executor	2026-06-30 14:59:43 +08:00
schedule.py	fix: scheduler division-by-zero, loss_mask bool	2026-07-03 22:04:55 +08:00
strategy.py	refactor: separate old policy and ref model in GRPO strategy	2026-07-14 20:03:45 +08:00
train_callback.py	feat : add distributed checkpoint via executor checkpoint_context	2026-07-13 12:27:09 +08:00
train_context.py	refactor: separate old policy and ref model in GRPO strategy	2026-07-14 20:03:45 +08:00
trainer.py	refactor: merge validation into MetricCallback, simplify progress bar to optimizer steps	2026-07-03 21:43:08 +08:00