| import argparse |
| import json |
| import os |
| import sys |
| from pathlib import Path |
|
|
| import torch |
|
|
|
|
| PROJECT_ROOT = Path(__file__).resolve().parents[1] |
| sys.path.insert(0, str(PROJECT_ROOT)) |
|
|
| from onescience.utils.YParams import YParams |
| from model import infer_task_type |
|
|
|
|
| def resolve_path(path_value): |
| path = Path(path_value) |
| return path if path.is_absolute() else PROJECT_ROOT / path |
|
|
|
|
| def output_path(cfg): |
| task_type = infer_task_type(cfg.model.name) |
| output_dir = resolve_path(cfg.inference.output_dir) |
| if cfg.inference.get("group_by_model", False): |
| output_dir = output_dir / task_type / cfg.model.name |
| return output_dir |
|
|
|
|
| def parse_args(): |
| parser = argparse.ArgumentParser(description="Summarize CFDBench inference outputs.") |
| parser.add_argument("--model", default=None, help="Override root.model.name and read that model's inference outputs.") |
| return parser.parse_args() |
|
|
|
|
| def main(): |
| args = parse_args() |
| cfg = YParams(str(PROJECT_ROOT / "conf" / "config.yaml"), "root") |
| if args.model: |
| cfg.model.name = args.model |
| elif os.environ.get("CFDBENCH_MODEL_NAME"): |
| cfg.model.name = os.environ["CFDBENCH_MODEL_NAME"] |
| output_dir = output_path(cfg) |
| pred_path = output_dir / "preds.pt" |
| score_path = output_dir / "scores.json" |
|
|
| if not pred_path.is_file() or not score_path.is_file(): |
| raise FileNotFoundError("Missing inference outputs. Run scripts/inference.py first.") |
|
|
| preds = torch.load(pred_path, map_location="cpu", weights_only=True) |
| scores = json.loads(score_path.read_text(encoding="utf-8")) |
| print(f"Prediction tensor: shape={tuple(preds.shape)}, dtype={preds.dtype}") |
| print(f"Prediction range: min={float(preds.min()):.4e}, max={float(preds.max()):.4e}") |
| print(f"Scores: {scores['mean']}") |
|
|
|
|
| if __name__ == "__main__": |
| main() |
|
|
