From b11d9c6da6ce32471e1c25a6f1b5e7a0a568774d Mon Sep 17 00:00:00 2001 From: Yuren Hao Date: Sat, 4 Jul 2026 22:35:16 -0500 Subject: magic-s2000 study: reg_delay/noadaptc flags, 4-arm queue v2, redx trajectory audit MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit - lt_ep_train: --reg_delay N (reg-free early phase: resreg/jr/floss/adaptc off for first N steps) + --noadaptc (kill hidden jacreg==0 damping feedback that would pollute single-reg ablation arms) - queue v2: 4 arms delay-first (abl_delay = reg-free 2k -> proven pair) - eig_traj/2/3: ARPACK audit of redx_traj — the run crossed the edge EARLY and oscillated (s1000 rotating-unstable, s1400 excursion mu=+2.1 self-recovered, s2000 the ONLY stable snapshot mu=-0.02, s2100/s2200 already back out) => s2000 is a post-excursion STABILITY-DIP capture, dip width <100 steps; learning survives mild instability (val fell through unstable stretches). lead_rho cold-40 under-reads clusters — NOT a classifier; ARPACK for audits. Co-Authored-By: Claude Opus 4.8 Claude-Session: https://claude.ai/code/session_014FAPDWQ49M5Ye3NpTndTpn --- ep_run/eig_traj3.py | 39 +++++++++++++++++++++++++++++++++++++++ 1 file changed, 39 insertions(+) create mode 100644 ep_run/eig_traj3.py (limited to 'ep_run/eig_traj3.py') diff --git a/ep_run/eig_traj3.py b/ep_run/eig_traj3.py new file mode 100644 index 0000000..1d864b6 --- /dev/null +++ b/ep_run/eig_traj3.py @@ -0,0 +1,39 @@ +"""E1b: ARPACK gold-standard re-measurement of the redx trajectory at 6 key ckpts (lead_rho's cold 2-D +iteration under-reads near-unity clusters by ~0.02-0.03, so absolute mu from eig_traj.py is suspect). +Top-3 |lam| of the forward map M = I + eps*J_F at the 400-step deep state, same seed-42 batch.""" +import numpy as np, torch, scipy.sparse.linalg as sla +from torch.autograd.functional import jvp +import lt_ep_train as L + +EPS, B, C = 0.1, 6, 1.0 +KEY = [2100, 2200, 2300] + +for s in KEY: + torch.manual_seed(0) + blk = L.EQBlock(512, 16, 256, 256, c=C, attn_mode='thick'); blk.qknorm = True + ck = torch.load(f'runs/redx_traj/s{s}.pt', map_location=L.dev) + with torch.no_grad(): + for p, w in zip(blk.allp, ck['allp']): + p.copy_(w.to(L.dev)) + torch.manual_seed(42) + idx, _ = L.get_batch('train', B, 256) + xin = blk.embed(idx).detach() + z = L.relax(blk, xin.clone(), xin, 400, EPS) + sh, n = z.shape, z.numel() + kk = 1.0 - EPS * (1.0 + C) + + def mv(x, z=z, sh=sh): + v = torch.from_numpy(np.asarray(x, dtype=np.float32)).to(L.dev).view(sh) + with torch.no_grad(): + Mv = kk * v + EPS * jvp(blk.nc_force, z, v)[1] + return Mv.reshape(-1).double().cpu().numpy() + + A = sla.LinearOperator((n, n), matvec=mv, dtype=np.float64) + try: + vals = sorted(sla.eigs(A, k=3, which='LM', return_eigenvectors=False, maxiter=2000, tol=1e-4), + key=lambda x: -abs(x)) + out = " ".join(f"|l|={abs(l):.5f}(mu={(l.real-1)/EPS:+.4f}{l.imag/EPS:+.3f}j)" for l in vals) + except Exception as e: + out = f"ARPACK-fail {type(e).__name__}" + print(f"s{s:<5} {out}", flush=True) +print("EIG_TRAJ2_DONE", flush=True) -- cgit v1.2.3