File size: 2,254 Bytes
81ae663 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 | """Build, score, train, and evaluate a configured local reaction inventory."""
import argparse
import json
import subprocess
import sys
from pathlib import Path
import yaml
from dooable.chemistry import read_catalog, reactions, build_graph, descriptor_rewards
from dooable.properties import property_rewards
def main():
parser = argparse.ArgumentParser()
parser.add_argument("--config", required=True)
args = parser.parse_args()
cfg = yaml.safe_load(Path(args.config).read_text())
out = Path(cfg["output"])
out.mkdir(parents=True, exist_ok=True)
parents = read_catalog(cfg["parents"], cfg.get("parent_limit"))
reagents = read_catalog(cfg["reagents"], cfg.get("reagent_limit"))
templates = reactions(cfg["reactions"])
for budget in cfg.get("budgets", [0, 1, 2]):
directory = out / f"budget{budget}"
directory.mkdir(parents=True, exist_ok=True)
graph = build_graph(
parents, reagents, templates, budget, cfg.get("max_nodes", 100000)
)
graph.save(directory / "graph.json")
if cfg.get("property_models"):
rewards, scores = property_rewards(graph, cfg["property_models"])
scores.to_csv(directory / "scores.csv", index=False)
else:
rewards = descriptor_rewards(graph)
(directory / "rewards.json").write_text(json.dumps(rewards, indent=2))
run = dict(
graph=str(directory / "graph.json"),
rewards=str(directory / "rewards.json"),
output=str(directory / "benchmark"),
methods=cfg.get("methods", ["dooable", "tb_uniform", "exact"]),
temperature=cfg.get("temperature", 0.7),
steps=cfg.get("steps", 2000),
samples=cfg.get("samples", 1000),
seeds=cfg.get("seeds", [0]),
batch_size=cfg.get("batch_size", 64),
)
run_path = directory / "run.yaml"
run_path.write_text(yaml.safe_dump(run))
subprocess.run(
[
sys.executable,
str(Path(__file__).with_name("run_benchmarks.py")),
"--config",
str(run_path),
],
check=True,
)
if __name__ == "__main__":
main()
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