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3.08 kB
| #!/usr/bin/env python3 | |
| """Run the bounded learned continuous-latent continuation pilot.""" | |
| from __future__ import annotations | |
| import argparse | |
| import json | |
| from pathlib import Path | |
| from typing import Sequence | |
| from music3lab.editing.learned_audio_continuation_data import ( | |
| load_learned_continuation_config, | |
| load_pair_records, | |
| ) | |
| from music3lab.editing.learned_audio_continuation_runner import ( | |
| run_learned_audio_continuation, | |
| ) | |
| def _parser() -> argparse.ArgumentParser: | |
| parser = argparse.ArgumentParser() | |
| commands = parser.add_subparsers(dest="command", required=True) | |
| check = commands.add_parser("check") | |
| check.add_argument("--config", type=Path, required=True) | |
| check.add_argument("--corpus-root", type=Path, required=True) | |
| run = commands.add_parser("run") | |
| run.add_argument("--config", type=Path, required=True) | |
| run.add_argument("--flow-config", type=Path, required=True) | |
| run.add_argument("--corpus-root", type=Path, required=True) | |
| run.add_argument("--encoder-checkpoint", type=Path, required=True) | |
| run.add_argument("--audio", type=Path, required=True) | |
| run.add_argument("--snapshot", type=Path, required=True) | |
| run.add_argument("--base-manifest", type=Path, required=True) | |
| run.add_argument("--diffusers-root", type=Path, required=True) | |
| run.add_argument("--output-root", type=Path, required=True) | |
| return parser | |
| def main(argv: Sequence[str] | None = None) -> int: | |
| arguments = _parser().parse_args(argv) | |
| if arguments.command == "check": | |
| loaded = load_learned_continuation_config(arguments.config) | |
| records = load_pair_records(arguments.corpus_root, loaded) | |
| result = { | |
| "schema_version": loaded.config.schema_version, | |
| "config_file_sha256": loaded.file_sha256, | |
| "split_counts": {key: len(value) for key, value in records.items()}, | |
| "target_visible_to_conditioner": False, | |
| "specialist_champion_eligible": False, | |
| } | |
| status = 0 | |
| elif arguments.command == "run": | |
| metrics = run_learned_audio_continuation( | |
| config_path=arguments.config, | |
| flow_config_path=arguments.flow_config, | |
| corpus_root=arguments.corpus_root, | |
| encoder_checkpoint=arguments.encoder_checkpoint, | |
| demonstration_audio=arguments.audio, | |
| snapshot=arguments.snapshot, | |
| base_manifest=arguments.base_manifest, | |
| diffusers_root=arguments.diffusers_root, | |
| output_root=arguments.output_root, | |
| ) | |
| result = { | |
| "output_root": metrics["output_root"], | |
| "status": metrics["status"], | |
| "best_step": metrics["best_step"], | |
| "heldout_gate": metrics["heldout"]["passes"], | |
| "specialist_promoted": False, | |
| } | |
| status = 0 if metrics["status"] == "FUNCTIONAL_PASS" else 1 | |
| else: | |
| raise AssertionError("unreachable") | |
| print(json.dumps(result, sort_keys=True, separators=(",", ":"))) | |
| return status | |
| if __name__ == "__main__": | |
| raise SystemExit(main()) | |