From b83947778e2c776f757a07d4719b7ce961d7ed55 Mon Sep 17 00:00:00 2001 From: Yuren Hao Date: Fri, 3 Jul 2026 05:56:50 -0500 Subject: =?UTF-8?q?Initial=20commit:=20ept=20=E2=80=94=20backprop-free=20e?= =?UTF-8?q?quilibrium=20transformer=20(EP)?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Code (ep_run/), organized docs (docs/{method,campaign,hardware,outreach,paper}), analysis scripts (scripts/), ONBOARDING.md entry point. Large data/checkpoints git-ignored (share separately). Co-Authored-By: Claude Opus 4.8 Claude-Session: https://claude.ai/code/session_014FAPDWQ49M5Ye3NpTndTpn --- ep_run/eval_relax_s3200.py | 23 +++++++++++++++++++++++ 1 file changed, 23 insertions(+) create mode 100644 ep_run/eval_relax_s3200.py (limited to 'ep_run/eval_relax_s3200.py') diff --git a/ep_run/eval_relax_s3200.py b/ep_run/eval_relax_s3200.py new file mode 100644 index 0000000..49a8316 --- /dev/null +++ b/ep_run/eval_relax_s3200.py @@ -0,0 +1,23 @@ +import torch, pickle, math +from pathlib import Path +import lt_ep_train as L +from lt_ep_train import EQBlock +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=6000 +torch.manual_seed(1234); idx,y=L.get_batch('val',B,T); idx=idx.to(dev) if hasattr(idx,'to') else idx +blk=EQBlock(512,16,256,256,s=1.0,c=1.0,attn_mode='thick'); blk.qknorm=True +ck=torch.load('runs/redx_traj/s3200.pt',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>1e3: print(f"DIVERGED at t={t} r={r:.2e}"); break +print("=== eval_relax redx s3200 (marginal, val 2.74) : CONVERGE-slow (rho<1) or LIMIT-CYCLE (floor/oscillate)? ===") +for t in [50,150,500,1000,2000,4000,5999]: + if t=1000 else ress +mono=all(tail[i]>=tail[i+1]-1e-12 for i in range(len(tail)-1)) +print(f" tail(last1000): min={min(tail):.2e} max={max(tail):.2e} last={ress[-1]:.2e} monotone_decreasing={mono}") +print(" VERDICT: res->~1e-5 monotone => SLOW CONVERGENCE (rho<1, finite-horizon budget); floored ~1e-2 + non-monotone => LIMIT CYCLE (forward non-convergence)") -- cgit v1.2.3