RESULT 10: epoch endpoints (BP 1.2509/1.2750 vs EP 1.4802, +0.22 erosion cost); GENERATION GATE PASSED (casc_gen.py, coherent stories, no-backprop 42.75M); stage1b improved-recipe pair launched (Muon cosine via build_hybrid)

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_014FAPDWQ49M5Ye3NpTndTpn

1 files changed, 11 insertions, 3 deletions

diff --git a/ep_run/muon.py b/ep_run/muon.py
index 5ac6fc6..3116030 100644
--- a/ep_run/muon.py
+++ b/ep_run/muon.py
@@ -52,13 +52,21 @@ class MultiSched:
         for s in self.scheds: s.step()
 
 
-def build_hybrid(blocks, other_params, lr_adamw, lr_muon, warmup):
-    """Muon(2D block matrices) + AdamW(everything else), with linear-warmup scheds for both."""
+def build_hybrid(blocks, other_params, lr_adamw, lr_muon, warmup, total_steps=0, lr_min_ratio=0.1):
+    """Muon(2D block matrices) + AdamW(everything else). Scheds: linear warmup, then cosine decay to
+    lr_min_ratio*peak if total_steps>0 (long runs), else constant after warmup (legacy)."""
+    import math as _m
     mats = [p for p in blocks.parameters() if p.ndim == 2]
     mat_ids = {id(p) for p in mats}
     rest = [p for p in other_params if id(p) not in mat_ids]
     om = Muon(mats, lr=lr_muon)
     oa = torch.optim.AdamW(rest, lr=lr_adamw, weight_decay=1e-4)
-    fn = lambda s: min(1.0, (s + 1) / max(warmup, 1))
+    if total_steps > 0:
+        def fn(s):
+            if s < warmup: return (s + 1) / max(warmup, 1)
+            p = min(1.0, (s - warmup) / max(1, total_steps - warmup))
+            return lr_min_ratio + 0.5 * (1 - lr_min_ratio) * (1 + _m.cos(_m.pi * p))
+    else:
+        fn = lambda s: min(1.0, (s + 1) / max(warmup, 1))
     scheds = [torch.optim.lr_scheduler.LambdaLR(om, fn), torch.optim.lr_scheduler.LambdaLR(oa, fn)]
     return MultiOpt([om, oa]), MultiSched(scheds)