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From 0645bf8369bf49ca4c23a9b2c19e4742f174addc Mon Sep 17 00:00:00 2001
From: YurenHao0426 <Blackhao0426@gmail.com>
Date: Mon, 27 Jul 2026 13:49:15 -0500
Subject: [PATCH 14/19] experiment: freeze plain CNN P2 registry
---
crossover_grid.py | 177 +++++++++++++++++++++++++++++++++++++++++++++-
1 file changed, 175 insertions(+), 2 deletions(-)
diff --git a/crossover_grid.py b/crossover_grid.py
index 340e174..846a2f1 100644
--- a/crossover_grid.py
+++ b/crossover_grid.py
@@ -13,6 +13,14 @@ import time
ROOT = os.path.dirname(os.path.abspath(__file__))
MAIN_ROOT = "/home/yurenh2/sdil"
PROTOCOL = os.path.join(MAIN_ROOT, "PLAIN_CNN_CROSSOVER.md")
+SELECTOR = os.path.join(
+ MAIN_ROOT, "results", "plain_cnn_p1_selector.json")
+SELECTOR_SHA256 = (
+ "3365f4618e0941de7dd7183f69c1f1bdd596a94b60f58de9e4e60ed05c38918c")
+P2_METHODS = (
+ "bp", "fa", "dfa", "pepita", "ff", "ep", "dualprop", "clean_kp",
+ "sdil")
+P2_ARCHITECTURES = ("minicnn", "vgglike", "vgg16")
def output(*args):
@@ -58,6 +66,18 @@ def rate_tag(rate):
return f"{rate:g}".replace(".", "p")
+def selector_report():
+ if sha256(SELECTOR) != SELECTOR_SHA256:
+ raise RuntimeError("P1 selector artifact hash drift")
+ with open(SELECTOR, encoding="utf-8") as handle:
+ report = json.load(handle)
+ if report["gate"] != "pass" or report["num_audited_records"] != 19:
+ raise RuntimeError("P1 selector gate did not pass")
+ if set(report["selected"]) != set(P2_METHODS):
+ raise RuntimeError("P1 selector method registry drift")
+ return report
+
+
def p1_jobs():
# Expensive jobs are deliberately interleaved across modulo shards.
specifications = [
@@ -84,6 +104,159 @@ def p1_jobs():
return [p1_command(method, rate) for method, rate in specifications]
+def p2_jobs():
+ report = selector_report()
+ # Expensive largest-model cells start first. Modulo-2 assignment places
+ # VGG16 EP and DP on different physical GPUs.
+ schedule = [
+ ("ep", "vgg16"),
+ ("dualprop", "vgg16"),
+ ("ff", "vgg16"),
+ ("pepita", "vgg16"),
+ ("sdil", "vgg16"),
+ ("clean_kp", "vgg16"),
+ ("fa", "vgg16"),
+ ("dfa", "vgg16"),
+ ("bp", "vgg16"),
+ ("ep", "vgglike"),
+ ("dualprop", "vgglike"),
+ ("ff", "vgglike"),
+ ("pepita", "vgglike"),
+ ("sdil", "vgglike"),
+ ("clean_kp", "vgglike"),
+ ("fa", "vgglike"),
+ ("dfa", "vgglike"),
+ ("bp", "vgglike"),
+ ("ep", "minicnn"),
+ ("dualprop", "minicnn"),
+ ("ff", "minicnn"),
+ ("pepita", "minicnn"),
+ ("sdil", "minicnn"),
+ ("clean_kp", "minicnn"),
+ ("fa", "minicnn"),
+ ("dfa", "minicnn"),
+ ("bp", "minicnn"),
+ ]
+ assert len(schedule) == len(P2_METHODS) * len(P2_ARCHITECTURES)
+ assert set(schedule) == {
+ (method, architecture)
+ for method in P2_METHODS for architecture in P2_ARCHITECTURES}
+ return [
+ p2_command(
+ method, architecture, report["selected"][method]["rate"])
+ for method, architecture in schedule
+ ]
+
+
+def p2_command(method, architecture, rate):
+ cli_method = {
+ "bp": "backprop",
+ "dualprop": "dualprop-lagr-ff",
+ "clean_kp": "clean-kp",
+ }.get(method, method)
+ model = {
+ "minicnn": "miniCNN",
+ "vgglike": "VGGlike",
+ "vgg16": "VGG16",
+ }[architecture]
+ runner = "train_ff.py" if method == "ff" else "train.py"
+ if method in ("bp", "fa", "dfa", "dualprop", "clean_kp", "sdil"):
+ epochs = 130
+ final_rate = 2e-6
+ warmup_rate = 0.001
+ warmup_epochs = 10
+ decay_epochs = 120
+ optimizer_schedule = "author"
+ elif method == "pepita":
+ epochs = 100
+ final_rate = warmup_rate = rate
+ warmup_epochs = 0
+ decay_epochs = epochs
+ optimizer_schedule = "pepita"
+ elif method == "ff":
+ epochs = 40
+ final_rate = warmup_rate = rate
+ warmup_epochs = 0
+ decay_epochs = epochs
+ optimizer_schedule = "author"
+ elif method == "ep":
+ epochs = 100
+ final_rate = warmup_rate = rate
+ warmup_epochs = 0
+ decay_epochs = epochs
+ optimizer_schedule = "author"
+ else:
+ raise ValueError(method)
+ name = f"plain-p2-{method}-{architecture}"
+ command = [
+ sys.executable, runner,
+ "--model", model,
+ "--dataset", "cifar10",
+ "--num-epochs", str(epochs),
+ "--batch-size", "100",
+ "--learning-rate", str(rate),
+ "--learning-rate-final", str(final_rate),
+ "--warmup-learning-rate", str(warmup_rate),
+ "--warmup-epochs", str(warmup_epochs),
+ "--decay-epochs", str(decay_epochs),
+ "--momentum", "0.9",
+ "--weight-decay", "5e-4",
+ "--dtype", "float32",
+ "--param-dtype", "float32",
+ "--percent-train", "90",
+ "--percent-val", "10",
+ "--seeds", "0",
+ "--feedback-seed", "1729",
+ "--gradient-diagnostics", "none",
+ "--spectral-diagnostics", "none",
+ "--test-policy", "none",
+ "--early-stop-policy", "none",
+ "--learning-algorithm", cli_method,
+ "--experiment-name", name,
+ "--optimizer-schedule", optimizer_schedule,
+ ]
+ if method == "pepita":
+ command.extend(["--pepita-projection-scale", "0.05"])
+ if method == "ff":
+ command.extend([
+ "--ff-threshold", "2.0",
+ "--ff-score-from-layer", "1",
+ ])
+ if method == "ep":
+ command.extend([
+ "--ep-beta", "0.5",
+ "--ep-dt", "0.5",
+ "--ep-free-steps", "20",
+ "--ep-nudge-steps", "4",
+ ])
+ if method == "dualprop":
+ command.extend([
+ "--loss", "sce",
+ "--alpha", "0.0",
+ "--beta", "0.1",
+ "--inference-sequence", "fwK",
+ "--inference-passes-nudged", "16",
+ ])
+ if method == "sdil":
+ command.extend([
+ "--sdil-traffic-ratio", "4",
+ "--sdil-traffic-seed", "4000",
+ "--sdil-calibration-examples", "64",
+ ])
+ return {
+ "stage": "p2",
+ "method": method,
+ "architecture": architecture,
+ "rate": rate,
+ "expected_epochs": epochs,
+ "experiment_name": name,
+ "selector_path": SELECTOR,
+ "selector_sha256": SELECTOR_SHA256,
+ "timeout_seconds": 48 * 60 * 60,
+ "command": command,
+ }
+
+
def p1_command(method, rate):
cli_method = {
"bp": "backprop",
@@ -203,7 +376,7 @@ def run_job(job, source, dry_run):
def main():
parser = argparse.ArgumentParser()
- parser.add_argument("--stage", choices=("p1",), default="p1")
+ parser.add_argument("--stage", choices=("p1", "p2"), default="p1")
parser.add_argument("--shard-index", type=int, default=0)
parser.add_argument("--num-shards", type=int, default=1)
parser.add_argument("--method")
@@ -212,7 +385,7 @@ def main():
if not 0 <= args.shard_index < args.num_shards:
raise ValueError("invalid shard")
source = source_report()
- jobs = p1_jobs()
+ jobs = p1_jobs() if args.stage == "p1" else p2_jobs()
if args.method:
jobs = [job for job in jobs if job["method"] == args.method]
jobs = [
--
2.54.0
|
