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import time, os, re, glob, math, pickle, subprocess
from pathlib import Path
import torch
import lt_ep_train as L
from lt_ep_train import EQBlock
os.chdir("/home/yurenh2/ept/ep_run")
L.DD=Path('data/tinystories_bpe'); L.vocab=pickle.load(open(L.DD/'meta.pkl','rb'))['vocab_size']
dev='cuda'; eps=0.1; B=8; T=256; N=800; OUT="runs/t2fix_rho.log"
torch.manual_seed(1234); idx,y=L.get_batch('val',B,T); idx=idx.to(dev) if hasattr(idx,'to') else idx
def measure(ckpt):
blk=EQBlock(512,16,256,256,s=1.0,c=1.0,attn_mode='thick'); blk.qknorm=True
ck=torch.load(ckpt,map_location=dev)
with torch.no_grad():
for p,w in zip(blk.allp,ck['allp']): p.copy_(w.to(dev))
xin=blk.embed(idx).detach(); z=xin.clone(); ress=[]
for t in range(N):
z2=z+eps*blk.force(z,xin).detach()
r=(z2-z).norm().item()/(z.norm().item()+1e-9); ress.append(r); z=z2
if not math.isfinite(r) or r>1e2: break
win=[ress[i] for i in range(len(ress)) if 1e-6<ress[i]<1e-1] or ress[-200:]
rats=[win[i+1]/win[i] for i in range(len(win)-1) if win[i]>0]
return (math.exp(sum(math.log(x) for x in rats)/len(rats)) if rats else float('nan')), ress[-1]
def alive(): return subprocess.run(["pgrep","-f","ckpt runs/ep_t2fix.pt"],capture_output=True).returncode==0
def valof(step):
try:
for l in open("runs/ep_t2fix.log"):
if l.startswith("step"):
m=re.search(r"step\s+(\d+)/.*val CE ([\d.]+)", l)
if m and int(m.group(1))==step: return m.group(2)
except Exception: pass
return "?"
open(OUT,"a").write("# ep_t2fix(t2sel=160) rho-tracking | refs: BPTT=0.982 ; redx val3.4->0.988, val2.74->0.998(blew)\n")
seen=set(); fired=None; t0=time.time()
while fired is None and time.time()-t0<24*3600:
time.sleep(60)
for ck in sorted(glob.glob("runs/t2fix_traj/s*.pt"), key=lambda p:int(re.search(r's(\d+)',p).group(1))):
step=int(re.search(r's(\d+)',ck).group(1))
if step in seen: continue
seen.add(step)
try: rho,fr=measure(ck)
except Exception: rho,fr=float('nan'),float('nan')
v=valof(step); line=f"step {step} val {v}: rho={rho:.4f} final_res={fr:.2e}"
open(OUT,"a").write(line+"\n"); print(line,flush=True)
try:
vf=float(v)
if vf<3.3 and isinstance(rho,float) and not math.isnan(rho):
if rho<0.992: fired=f"ep_t2fix val {v}: rho={rho:.4f} STAYS LOW (vs redx ~0.998 here) -> better gradient holds contraction (FIX WORKING)"; break
if rho>0.997: fired=f"ep_t2fix val {v}: rho={rho:.4f} DRIFTED to threshold like redx -> gradient does NOT defend rho (your objection holds)"; break
except Exception: pass
if not alive(): fired=f"ep_t2fix exited; trajectory in {OUT}"; break
print("=== EP_T2FIX RHO VERDICT ==="); print(fired or "24h timeout")
for l in open(OUT): print(l.rstrip())
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