Spaces:
Sleeping
Sleeping
File size: 1,251 Bytes
f559cc0 | 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 | """
Train all models in the AnemiaLens ensemble pipeline.
Currently delegates to train_archive_model. As the ensemble grows
(deep-stack, legacy CNN, etc.) this script will orchestrate each
training job in dependency order and produce a combined manifest.
Usage::
python scripts/train_ensemble.py [--dataset PATH] [--output-dir PATH] [--quiet]
"""
from __future__ import annotations
import sys
from pathlib import Path
# Ensure the scripts directory is on the path so we can import sibling scripts.
sys.path.insert(0, str(Path(__file__).resolve().parent))
from train_archive_model import main as train_archive
def main(argv: list[str] | None = None) -> int:
"""
Orchestrate all training jobs.
Returns the exit code of the last failing job, or 0 if all succeeded.
"""
exit_code = 0
print("=== Step 1/1: archive screening model ===")
rc = train_archive(argv)
if rc != 0:
print(f" FAILED (exit {rc})", file=sys.stderr)
exit_code = rc
else:
print(" Done.")
# Future steps (uncomment when models are ready):
# print("=== Step 2/N: deep-stack model ===")
# rc = train_deep_stack(argv)
# ...
return exit_code
if __name__ == "__main__":
sys.exit(main())
|