| """Independent V2 deployment stages; preserve all experiment directories.""" |
| import argparse |
| import json |
| import sys |
| from pathlib import Path |
|
|
| ROOT = Path(__file__).resolve().parents[2] |
| sys.path.insert(0, str(ROOT / "src")) |
|
|
| import torch |
| from vimeml.deployment import v2 |
|
|
|
|
| def main(): |
| parser = argparse.ArgumentParser(description=__doc__) |
| parser.add_argument("--threads", type=int, default=4) |
| stages = parser.add_subparsers(dest="stage", required=True) |
| export = stages.add_parser("export") |
| export.add_argument("--checkpoint", type=Path, required=True) |
| export.add_argument("--tokenizer", type=Path, required=True) |
| export.add_argument("--token-manifest", type=Path, required=True) |
| convert = stages.add_parser("convert") |
| convert.add_argument("--bundle", type=Path, required=True) |
| compress = stages.add_parser("compress") |
| compress.add_argument("--source", type=Path, required=True) |
| compress.add_argument("--alignment", type=Path, required=True) |
| align = stages.add_parser("align") |
| align.add_argument("--reference", type=Path, required=True) |
| evaluate = stages.add_parser("evaluate") |
| evaluate.add_argument("--benchmark", type=Path, required=True) |
| evaluate.add_argument("--baseline", type=Path, required=True) |
| samples = stages.add_parser("samples") |
| samples.add_argument("--baseline", type=Path, required=True) |
| fixtures = stages.add_parser("device-fixtures") |
| for command in (align, evaluate, samples, fixtures): |
| command.add_argument("--bundle", type=Path, required=True) |
| command.add_argument("--model", type=Path) |
| for command in (export, convert, compress, align, evaluate, samples, fixtures): |
| command.add_argument("--output", type=Path, required=True) |
| args = parser.parse_args() |
| if args.threads < 1 or args.output.exists(): |
| parser.error("Positive threads and a fresh output path are required.") |
| torch.set_num_threads(args.threads) |
| if args.stage == "export": |
| v2.export_bundle(args.checkpoint, args.tokenizer, args.token_manifest, args.output) |
| elif args.stage == "convert": |
| v2.convert(args.bundle, args.output) |
| elif args.stage == "compress": |
| v2.compress(args.source, args.output, args.alignment) |
| else: |
| lm = v2.CoreMLLM(args.bundle, args.model) if args.model else v2.BundleLM(args.bundle) |
| if args.stage == "align": |
| report = v2.align(lm, args.reference, args.output) |
| print(json.dumps(report, ensure_ascii=False, indent=2)) |
| if not report["passed"]: |
| raise SystemExit("Strict alignment failed; report preserved. Review ranking quality separately.") |
| elif args.stage == "evaluate": |
| report = v2.evaluate(lm, args.benchmark, args.baseline, args.output) |
| print(json.dumps({"metrics": report["metrics"]["all"], |
| "comparison": {k: v for k, v in report["comparison"].items() if k != "changes"}}, indent=2)) |
| elif args.stage == "samples": |
| v2.samples(lm, args.baseline, args.output) |
| else: |
| v2.device_fixtures(lm, args.output) |
| print(f"Output: {args.output.resolve()}") |
|
|
|
|
| if __name__ == "__main__": |
| main() |
|
|
