protocol: freeze hierarchical causal-capture funnel

1 files changed, 54 insertions, 0 deletions

diff --git a/experiments/oral_a_v4_calibration_screen.py b/experiments/oral_a_v4_calibration_screen.py
new file mode 100644
index 0000000..2e29bb6
--- /dev/null
+++ b/experiments/oral_a_v4_calibration_screen.py
@@ -0,0 +1,54 @@
+#!/usr/bin/env python3
+"""Run a shard of the frozen hierarchical-feedback causal-capture screen."""
+import argparse
+import os
+import subprocess
+import sys
+
+
+def main():
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--device", default="cuda")
+    parser.add_argument("--shard_index", type=int, default=0)
+    parser.add_argument("--num_shards", type=int, default=1)
+    parser.add_argument("--dry_run", action="store_true")
+    args = parser.parse_args()
+    if not 0 <= args.shard_index < args.num_shards:
+        raise ValueError("invalid shard index")
+    common = [
+        sys.executable, "experiments/conv_run.py", "--device", args.device,
+        "--depth", "20", "--width", "16", "--seed", "0",
+        "--loader_seed", "0", "--batch_size", "128", "--epochs", "0",
+        "--train_limit", "10000", "--val_examples", "5000",
+        "--split_seed", "2027", "--eval_split", "validation",
+        "--eval_every", "0", "--augment_train", "1", "--lr", "0.1",
+        "--output_lr", "0.1", "--lr_schedule", "constant",
+        "--warmup_epochs", "0", "--momentum", "0.9",
+        "--weight_decay", "1e-4", "--normalization", "batchnorm",
+        "--a_scale", "1", "--pert_sigma", "0.01",
+        "--pert_directions", "1", "--pert_every", "4",
+        "--perturb_seed", "1000", "--alignment_probe", "64",
+    ]
+    jobs = [("fixed_hfa", common + [
+        "--mode", "hfa", "--out",
+        "results/oral_a_v4_calibration/fixed_hfa.json",
+    ])]
+    for rate in (0.1, 1.0, 10.0):
+        tag = f"learned_hfa_etaA{rate}"
+        jobs.append((tag, common + [
+            "--mode", "lhfa", "--eta_A", str(rate),
+            "--a_warmup_steps", "400", "--out",
+            f"results/oral_a_v4_calibration/{tag}.json",
+        ]))
+    os.makedirs("results/oral_a_v4_calibration", exist_ok=True)
+    for index, (tag, command) in enumerate(jobs):
+        if index % args.num_shards != args.shard_index:
+            continue
+        print(tag, " ".join(command), flush=True)
+        if not args.dry_run:
+            subprocess.run(command, check=True)
+
+
+if __name__ == "__main__":
+    main()
+