summaryrefslogtreecommitdiff
path: root/ep_run/fix_probe.py
diff options
context:
space:
mode:
Diffstat (limited to 'ep_run/fix_probe.py')
-rw-r--r--ep_run/fix_probe.py42
1 files changed, 42 insertions, 0 deletions
diff --git a/ep_run/fix_probe.py b/ep_run/fix_probe.py
new file mode 100644
index 0000000..611cf85
--- /dev/null
+++ b/ep_run/fix_probe.py
@@ -0,0 +1,42 @@
+"""The two measurement-side fixes, judged by cos(EP,BPTT) on the near-edge s2000 operator:
+(1) DEEP ANCHOR — relax 400 instead of 150 before measuring (anchor res 2.65 -> 0.046: if the
+ anchor error is the dominant amplified delta, cos jumps). Matched BPTT reference at same T1.
+(2) KAPPA BRAKE — nbrake Tikhonov leak on the nudged dynamics only (shifts the measurement
+ spectrum left by kappa, clips the non-normal transient): cos vs kappa at T1=150.
+bsub kept small for the BPTT unroll memory."""
+import torch
+import lt_ep_train as L
+from diag_cos import cos_ep_bptt
+
+torch.manual_seed(0)
+blk = L.EQBlock(512, 16, 256, 256, c=1.0, attn_mode='thick'); blk.qknorm = True
+ck = torch.load('runs/redx_traj/s2000.pt', map_location=L.dev)
+with torch.no_grad():
+ for p, w in zip(blk.allp, ck['allp']):
+ p.copy_(w.to(L.dev))
+blk.track = True
+torch.manual_seed(11)
+batches = [L.get_batch('train', 24, 256) for _ in range(2)]
+
+print("(1) deep anchor: cos at matched T1", flush=True)
+for T1, bs in ((150, 4), (400, 3)):
+ cs = []
+ for idx, y in batches:
+ try:
+ c, r = cos_ep_bptt(blk, idx, y, T1, 20, 0.1, 0.02, holo=2, hr=0.02, t2sel=40, bsub=bs)
+ except torch.cuda.OutOfMemoryError:
+ torch.cuda.empty_cache()
+ c, r = cos_ep_bptt(blk, idx, y, T1, 20, 0.1, 0.02, holo=2, hr=0.02, t2sel=40, bsub=2)
+ cs.append(c)
+ print(f" T1={T1:<4} cos={' '.join(f'{c:.4f}' for c in cs)} mean={sum(cs)/len(cs):.4f} (res~{r:.1e})", flush=True)
+
+print("(2) kappa brake at T1=150:", flush=True)
+for kap in (0.0, 0.02, 0.05, 0.1, 0.2):
+ blk.nbrake = kap
+ cs = []
+ for idx, y in batches:
+ c, _ = cos_ep_bptt(blk, idx, y, 150, 20, 0.1, 0.02, holo=2, hr=0.02, t2sel=40, bsub=4)
+ cs.append(c)
+ print(f" kappa={kap:<5} cos={' '.join(f'{c:.4f}' for c in cs)} mean={sum(cs)/len(cs):.4f}", flush=True)
+blk.nbrake = 0.0
+print("FIX_PROBE_DONE", flush=True)