Remove nested directory: BitTransformerLM/review_cli.py

BitTransformerLM/review_cli.py

@@ -1,49 +0,0 @@
-import argparse
-import json
-from pathlib import Path
-
-import torch
-from bit_transformer import BitTransformerLM
-
-
-def list_candidates(path: Path):
-    models = sorted(path.glob("*.pt"))
-    for m in models:
-        metrics_file = m.with_suffix(m.suffix + ".json")
-        metrics = {}
-        if metrics_file.exists():
-            with open(metrics_file) as f:
-                metrics = json.load(f)
-        yield m, metrics
-
-
-def main():
-    parser = argparse.ArgumentParser(description="Review distilled submodels")
-    parser.add_argument("directory", type=Path, help="Directory with candidate models")
-    parser.add_argument("--approve-dir", type=Path, default=Path("approved"), help="Directory to store approved models")
-    args = parser.parse_args()
-
-    args.approve_dir.mkdir(exist_ok=True)
-    log_file = args.approve_dir / "review_log.jsonl"
-
-    for model_path, metrics in list_candidates(args.directory):
-        print("Candidate:", model_path.name)
-        for k, v in metrics.items():
-            print(f"  {k}: {v}")
-        ans = input("Approve this model? [y/N] ").strip().lower()
-        if ans == "y":
-            approved_path = args.approve_dir / model_path.name
-            torch.save(torch.load(model_path), approved_path)
-            entry = {"model": approved_path.name, "metrics": metrics, "approved": True}
-            with open(log_file, "a") as lf:
-                lf.write(json.dumps(entry) + "\n")
-            print("Approved and saved to", approved_path)
-        else:
-            entry = {"model": model_path.name, "metrics": metrics, "approved": False}
-            with open(log_file, "a") as lf:
-                lf.write(json.dumps(entry) + "\n")
-            print("Rejected", model_path.name)
-
-
-if __name__ == "__main__":
-    main()