| """Command line entry point: `ptb setup | run | eval`.""" |
|
|
| import argparse |
| import json |
| import time |
| from pathlib import Path |
|
|
| from . import config |
| from .evaluate import evaluate |
| from .provision import setup |
| from .solve import solve |
|
|
|
|
| def run(args: argparse.Namespace) -> None: |
| """Full benchmark run: agent phase, then evaluation of its final model.""" |
| safe = str.maketrans("/:[]", "____") |
| run_dir = (config.RESULTS_DIR |
| / f"{args.agent}_{args.agent_model.translate(safe)}_{args.hours}h{args.experiment_name}" |
| / f"{args.task}_{args.model.translate(safe)}_{time.strftime('%Y%m%d-%H%M%S')}") |
| run_dir.mkdir(parents=True) |
| print(f"Run directory: {run_dir}") |
| solve(run_dir, args.task, args.model, args.agent, args.agent_model, args.hours, args.container) |
| if not (run_dir / "final_model").is_dir(): |
| raise SystemExit("The agent produced no final_model; nothing to evaluate.") |
| report(evaluate(run_dir, args.task, str(run_dir / "final_model"))) |
|
|
|
|
| def report(metrics: dict | None) -> None: |
| if metrics is None: |
| raise SystemExit("Evaluation failed; see the final_eval_*.txt logs.") |
| print(json.dumps(metrics, indent=2)) |
|
|
|
|
| def main() -> None: |
| parser = argparse.ArgumentParser(prog="ptb", description=__doc__) |
| commands = parser.add_subparsers(dest="command", required=True) |
|
|
| p = commands.add_parser("setup", help="build the container images, download models and test data") |
| p.add_argument("--containers", nargs="*", default=[config.AGENT_CONTAINER, config.EVAL_CONTAINER], |
| choices=config.DEFINITIONS, help="upstream container definitions to build") |
| p.add_argument("--full-cache", action="store_true", |
| help="prefill the HF cache with upstream's 14 models and 382 dataset splits") |
| p.add_argument("--models", nargs="*", default=[], help="HF ids of base models to download") |
| p.add_argument("--tasks", nargs="*", default=[], choices=config.TASKS, help="benchmarks to fetch test data for") |
| p.set_defaults(func=lambda a: setup(a.containers, a.models, a.tasks, a.full_cache)) |
|
|
| p = commands.add_parser("run", help="let an agent post-train a model, then evaluate the result") |
| p.add_argument("--task", required=True, choices=config.TASKS) |
| p.add_argument("--model", required=True, help="HF id of the base model to post-train") |
| p.add_argument("--agent", default="claude_non_api", choices=config.AGENTS, help="upstream agent scaffold") |
| p.add_argument("--agent-model", required=True, help="API model driving the agent, e.g. claude-opus-5") |
| p.add_argument("--container", default=config.AGENT_CONTAINER, choices=config.DEFINITIONS, |
| help="container for the agent phase; upstream picks one per cell") |
| p.add_argument("--hours", type=int, default=10, help="time budget of the agent") |
| |
| |
| p.add_argument("--experiment-name", default="", help="suffix for the results directory, e.g. _run1") |
| p.set_defaults(func=run) |
|
|
| p = commands.add_parser("eval", help="evaluate a model only (e.g. a base model as baseline)") |
| p.add_argument("--task", required=True, choices=config.TASKS) |
| p.add_argument("--model", required=True, help="model directory or HF id") |
| p.add_argument("--out-dir", required=True, type=Path) |
| p.add_argument("--limit", type=int, default=-1, help="number of samples; -1 = full benchmark") |
| p.set_defaults(func=lambda a: report(evaluate(a.out_dir, a.task, a.model, a.limit))) |
|
|
| args = parser.parse_args() |
| args.func(args) |
|
|
