File size: 2,037 Bytes
54d2b91 | 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 51 52 53 54 55 56 57 58 59 60 61 | """Top-level evaluation script — runs Protocols 1/2/3/4 on a checkpoint."""
from __future__ import annotations
import argparse
import json
import sys
from pathlib import Path
import torch
from omegaconf import OmegaConf
sys.path.insert(0, str(Path(__file__).resolve().parent.parent))
from src.data import FairTalkingDataModule
from src.methods import build_method
from src.eval import run_protocol_1, run_protocol_2, run_protocol_3, run_protocol_4
def main():
ap = argparse.ArgumentParser()
ap.add_argument("--config", required=True, help="path to the Hydra-composed config saved during training")
ap.add_argument("--ckpt", required=True)
ap.add_argument("--out_dir", required=True)
ap.add_argument("--protocols", default="1,2,3,4",
help="comma-separated list of protocol IDs to run")
args = ap.parse_args()
cfg = OmegaConf.load(args.config)
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
dm = FairTalkingDataModule(data_cfg=cfg.data, return_paired=False)
model = build_method(
method_name=cfg.method.name,
method_cfg=cfg.method,
backbone_cfg=cfg.backbone,
data_cfg=cfg.data,
)
state = torch.load(args.ckpt, map_location="cpu")
model.load_state_dict(state.get("state_dict", state), strict=False)
out = Path(args.out_dir); out.mkdir(parents=True, exist_ok=True)
prots = [p.strip() for p in args.protocols.split(",") if p.strip()]
all_metrics = {}
if "1" in prots:
all_metrics["protocol1"] = run_protocol_1(model, dm, device, out)
if "2" in prots:
all_metrics["protocol2"] = run_protocol_2(model, dm, device, out)
if "3" in prots:
all_metrics["protocol3"] = run_protocol_3(model, dm, device, out)
if "4" in prots:
all_metrics["protocol4"] = run_protocol_4(model, dm, device, out)
(out / "summary.json").write_text(json.dumps(all_metrics, indent=2))
print(json.dumps(all_metrics, indent=2))
if __name__ == "__main__":
main()
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