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#!/usr/bin/env python3
"""Immutable job registry and driver for the ResNet crossover stages."""
import argparse
import hashlib
import json
import os
import subprocess
import sys
import time
ROOT = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
PROTOCOL = os.path.join(ROOT, "RESNET_CROSSOVER.md")
RESULT_ROOT = os.path.join(ROOT, "results", "resnet_crossover")
METHODS = (
"bp", "fa", "dfa", "pepita", "ff", "ep", "dualprop", "clean_kp",
"sdil")
def sha256(path):
digest = hashlib.sha256()
with open(path, "rb") as handle:
for chunk in iter(lambda: handle.read(1024 * 1024), b""):
digest.update(chunk)
return digest.hexdigest()
def git_output(*args):
return subprocess.run(
["git", *args], cwd=ROOT, check=True, capture_output=True,
text=True).stdout.strip()
def source_report():
dirty = git_output(
"status", "--porcelain", "--untracked-files=no")
if dirty:
raise RuntimeError("ResNet crossover requires clean tracked source")
paths = [
PROTOCOL,
os.path.abspath(__file__),
os.path.join(ROOT, "experiments", "resnet_crossover_native.py"),
os.path.join(ROOT, "experiments", "conv_run.py"),
os.path.join(ROOT, "sdil", "conv_crossover.py"),
os.path.join(ROOT, "sdil", "conv.py"),
os.path.join(ROOT, "sdil", "data.py"),
]
for path in paths:
tracked = subprocess.run(
["git", "ls-files", "--error-unmatch",
os.path.relpath(path, ROOT)],
cwd=ROOT, capture_output=True).returncode == 0
if not tracked:
raise RuntimeError(f"untracked crossover source: {path}")
return {
"git_commit": git_output("rev-parse", "HEAD"),
"protocol_path": PROTOCOL,
"protocol_sha256": sha256(PROTOCOL),
"tracked_files": {
os.path.relpath(path, ROOT): sha256(path) for path in paths},
"python": sys.executable,
}
def rate_tag(rate):
return f"{rate:g}".replace(".", "p")
def p1_jobs():
specifications = [
("ep", 0.0003),
("dualprop", 0.01),
("ep", 0.001),
("dualprop", 0.025),
("ep", 0.003),
("dualprop", 0.05),
("pepita", 0.0003),
("fa", 0.01),
("pepita", 0.001),
("dfa", 0.01),
("pepita", 0.003),
("fa", 0.03),
("dfa", 0.03),
("fa", 0.1),
("dfa", 0.1),
("bp", 0.1),
("ff", 0.03),
("clean_kp", 0.1),
("sdil", 0.1),
]
return [p1_command(method, rate) for method, rate in specifications]
def p1_command(method, rate):
name = f"resnet-p1-{method}-d20-lr{rate_tag(rate)}"
output = os.path.join(RESULT_ROOT, "p1", name + ".json")
common = [
"--device", "cuda",
"--depth", "20",
"--width", "16",
"--seed", "0",
"--loader_seed", "0",
"--split_seed", "2027",
"--batch_size", "128",
"--epochs", "10",
"--train_limit", "0",
"--val_examples", "5000",
"--eval_split", "validation",
"--eval_every", "1",
"--augment_train", "1",
"--lr", str(rate),
"--output_lr", "0.1" if method in ("fa", "dfa") else str(rate),
"--lr_schedule", "constant",
"--momentum", "0.9",
"--weight_decay", "1e-4",
]
if method in ("pepita", "ff", "ep", "dualprop"):
command = [
sys.executable, "experiments/resnet_crossover_native.py",
"--method", method,
"--out", output,
"--feedback_seed", "1729",
*common,
]
if method == "pepita":
command.extend(["--pepita_projection_scale", "0.05"])
elif method == "ff":
command.extend([
"--ff_threshold", "2.0",
"--ff_score_from_layer", "1",
])
elif method == "ep":
command.extend([
"--ep_beta", "0.5",
"--ep_dt", "0.5",
"--ep_free_steps", "20",
"--ep_nudge_steps", "4",
])
else:
command.extend([
"--dp_alpha", "0.0",
"--dp_beta", "0.1",
"--dp_inference_passes", "16",
])
else:
modes = {
"bp": "bp",
"fa": "hfa",
"dfa": "dfa",
"clean_kp": "kp",
"sdil": "kp_traffic",
}
command = [
sys.executable, "experiments/conv_run.py",
"--mode", modes[method],
"--out", output,
"--normalization", "batchnorm",
"--a_scale", "1",
"--alignment_probe", "0",
*common,
]
if method == "dfa":
command.extend(["--vectorizer_mode", "spatial_template"])
elif method == "sdil":
command.extend([
"--traffic_rule", "innovation",
"--predictor_mode", "closed_form",
"--neutral_projection", "1",
"--traffic_seed", "5000",
"--traffic_ratio", "4",
"--traffic_calibration_examples", "64",
"--learn_P", "1",
"--eta_P", "0.1",
"--predictor_warmup_steps", "1",
"--predictor_every", "0",
])
return {
"stage": "p1",
"method": method,
"architecture": "resnet20",
"rate": rate,
"experiment_name": name,
"output": output,
"timeout_seconds": 12 * 60 * 60,
"command": command,
}
def run_job(job, source, dry_run):
manifest_path = job["output"] + ".manifest.json"
if os.path.exists(manifest_path):
print(f"preserving {job['experiment_name']}", flush=True)
return
if os.path.exists(job["output"]):
raise RuntimeError(
f"orphaned output requires audit: {job['output']}")
print("RUN", " ".join(job["command"]), flush=True)
if dry_run:
return
os.makedirs(os.path.dirname(job["output"]), exist_ok=True)
started = time.time()
try:
result = subprocess.run(
job["command"], cwd=ROOT, timeout=job["timeout_seconds"])
return_code = result.returncode
status = "completed" if return_code == 0 else "nonzero_exit"
except subprocess.TimeoutExpired:
return_code = None
status = "timeout"
output_exists = os.path.isfile(job["output"])
if status == "completed" and not output_exists:
status = "missing_output"
manifest = {
**job,
"source": source,
"status": status,
"return_code": return_code,
"output_exists": output_exists,
"output_sha256": sha256(job["output"]) if output_exists else None,
"driver_wall_seconds": time.time() - started,
"completed_unix_time": time.time(),
"cuda_visible_devices": os.environ.get("CUDA_VISIBLE_DEVICES"),
}
with open(manifest_path, "w", encoding="utf-8") as handle:
json.dump(manifest, handle, indent=2, sort_keys=True)
handle.write("\n")
print(
f"DONE status={status} {job['experiment_name']}", flush=True)
def main():
parser = argparse.ArgumentParser()
parser.add_argument("--stage", choices=("p1",), default="p1")
parser.add_argument("--shard-index", type=int, default=0)
parser.add_argument("--num-shards", type=int, default=1)
parser.add_argument("--method", choices=METHODS)
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")
source = source_report()
jobs = p1_jobs()
if args.method:
jobs = [job for job in jobs if job["method"] == args.method]
jobs = [
job for index, job in enumerate(jobs)
if index % args.num_shards == args.shard_index]
if not jobs:
raise ValueError("no jobs selected")
for job in jobs:
run_job(job, source, args.dry_run)
if __name__ == "__main__":
main()
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