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#!/usr/bin/env python3
"""Run one cell of the frozen oral-B temporal-difference confirmation."""
import argparse
import hashlib
import json
import math
import os
import platform
import resource
import subprocess
import sys
import time
import torch
sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
from experiments.bci_td_run import (CONDITIONS, build_config, evaluate,
neutral_warmup, train)
from sdil.bci import BCISDIL, generate_trajectories
from sdil.bci_metrics import signature_metrics
ROOT = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
PROTOCOL_PATH = os.path.join(ROOT, "ORAL_B_RECOVERY.md")
TASK_SEEDS = tuple(range(10, 16))
MODEL_SEEDS = tuple(range(5))
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 finite_tree(value):
if isinstance(value, dict):
return all(finite_tree(item) for item in value.values())
if isinstance(value, (list, tuple)):
return all(finite_tree(item) for item in value)
if isinstance(value, (int, float)):
return math.isfinite(value)
return True
def provenance(d4_gate, r1_gate):
def run(command):
return subprocess.run(
command, cwd=ROOT, check=True, capture_output=True,
text=True).stdout.strip()
paths = {
"runner": os.path.abspath(__file__),
"development_runner": os.path.join(ROOT, "experiments", "bci_td_run.py"),
"protocol": PROTOCOL_PATH,
"d4_gate": os.path.abspath(d4_gate),
"r1_gate": os.path.abspath(r1_gate),
}
relative = {name: os.path.relpath(path, ROOT)
for name, path in paths.items()}
tracked = {
name: subprocess.run(
["git", "ls-files", "--error-unmatch", path], cwd=ROOT,
capture_output=True).returncode == 0
for name, path in relative.items()
}
return {
"git_commit": run(["git", "rev-parse", "HEAD"]),
"git_tracked_dirty": bool(run(
["git", "status", "--porcelain", "--untracked-files=no"])),
"tracked_inputs": tracked,
"input_sha256": {name: sha256(path) for name, path in paths.items()},
}
def require_gate(d4, r1, d4_digest):
if not (d4.get("protocol") ==
"kp_dynamic_neutral_projection_confirmation_v1"
and d4.get("status") == "passed"
and d4.get("review_score_after") == 7):
raise ValueError("oral-B R2 requires the complete audited D4 pass")
if not (r1.get("protocol") == "oral_b_td_development_v1"
and r1.get("status") == "passed"
and r1.get("complete_grid") is True
and r1.get("confirmation_seeds_touched") is False
and r1.get("oral_b_confirmation_opened") is True
and r1.get("review_score_after") == 7
and r1.get("d4_gate_sha256") == d4_digest
and r1.get("selected", {}).get("eta") in (0.03, 0.1)):
raise ValueError("oral-B R2 requires the complete eligible R1 gate")
def main():
parser = argparse.ArgumentParser()
parser.add_argument(
"--d4_gate",
default="results/kp_dynamic_projection_confirmation_gate.json")
parser.add_argument(
"--r1_gate", default="results/bci_td_dev_gate.json")
parser.add_argument("--task-seed", type=int, choices=TASK_SEEDS, required=True)
parser.add_argument("--model-seed", type=int, choices=MODEL_SEEDS, required=True)
parser.add_argument("--outdir", default="results/bci_td_confirmation")
args = parser.parse_args()
with open(args.d4_gate) as handle:
d4 = json.load(handle)
with open(args.r1_gate) as handle:
r1 = json.load(handle)
d4_digest = sha256(args.d4_gate)
require_gate(d4, r1, d4_digest)
eta = float(r1["selected"]["eta"])
source = provenance(args.d4_gate, args.r1_gate)
if (source["git_tracked_dirty"]
or not all(source["tracked_inputs"].values())):
raise RuntimeError(
"R2 requires clean tracked code, protocol, D4 gate, and R1 gate")
cfg = build_config(eta)
trajectories = generate_trajectories(cfg, args.task_seed)
evaluation_seed = args.task_seed + 300_000
evaluation = generate_trajectories(
cfg, evaluation_seed, days=1, episodes=256)
initial = BCISDIL(cfg, args.model_seed)
conditions = {}
trained = {}
warmups = {}
training_events = None
started = time.perf_counter()
for name in CONDITIONS:
model, warmup = neutral_warmup(
initial, args.task_seed, args.model_seed, name)
events, report = train(
model, trajectories, name, collect=name == "intact")
warmups[name] = warmup
trained[name] = model
conditions[name] = report
if name == "intact":
training_events = events
evaluation_events = None
for name in CONDITIONS:
report = evaluate(
trained[name], evaluation, collect=name == "intact")
conditions[name]["final_success"] = report["success_rate"]
if name == "intact":
evaluation_events = report["events"]
signatures = signature_metrics(
training_events, evaluation_events, cfg, trained["intact"].role)
result = {
"schema_version": 1,
"protocol": {
"name": "oral_b_td_confirmation_v1",
"split": "untouched_confirmation",
"training_task_seed": args.task_seed,
"evaluation_task_seed": evaluation_seed,
"selected_eta": eta,
"no_further_selection": True,
"confirmation_grid_size": len(TASK_SEEDS) * len(MODEL_SEEDS),
"d4_gate_sha256": source["input_sha256"]["d4_gate"],
"r1_gate_sha256": source["input_sha256"]["r1_gate"],
"protocol_sha256": source["input_sha256"]["protocol"],
},
"args": vars(args),
"config": vars(cfg),
"provenance": source,
"warmup": warmups,
"conditions": conditions,
"signatures": signatures,
"wall_s": time.perf_counter() - started,
"peak_rss_mib": resource.getrusage(resource.RUSAGE_SELF).ru_maxrss / 1024,
"hardware": {
"device": "cpu", "platform": platform.platform(),
"torch_version": torch.__version__, "threads": torch.get_num_threads(),
},
}
result["finite"] = finite_tree(result)
if not result["finite"]:
raise RuntimeError("non-finite oral-B R2 record")
os.makedirs(args.outdir, exist_ok=True)
path = os.path.join(
args.outdir,
f"bci_td_confirm_t{args.task_seed}_m{args.model_seed}.json")
if os.path.exists(path):
raise FileExistsError(f"refusing to overwrite {path}")
with open(path, "w") as handle:
json.dump(result, handle, indent=2, sort_keys=True)
handle.write("\n")
print(json.dumps({
"path": path,
"finite": result["finite"],
"intact_final": conditions["intact"]["final_success"],
"sign_inversion": signatures["causal_role_sign_inversion_index"],
}, indent=2))
if __name__ == "__main__":
main()
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