DeepCFD / scripts /result.py
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import sys
from pathlib import Path
import numpy as np
import torch
PROJECT_ROOT = Path(__file__).resolve().parents[1]
sys.path.insert(0, str(PROJECT_ROOT))
from onescience.utils.YParams import YParams
def resolve_path(path_value):
path = Path(path_value)
return path if path.is_absolute() else PROJECT_ROOT / path
def main():
cfg = YParams(str(PROJECT_ROOT / "config" / "config.yaml"), "root")
checkpoint_path = resolve_path(cfg.inference.checkpoint_path)
pred_dir = resolve_path(cfg.inference.result_dir) / "predictions"
if checkpoint_path.exists():
ckpt = torch.load(checkpoint_path, map_location="cpu")
print(f"Checkpoint: {checkpoint_path}")
print(f"Epoch: {ckpt.get('epoch')}, val_loss: {ckpt.get('val_loss')}")
print(f"Model config: {ckpt.get('config')}")
else:
print(f"Checkpoint not found: {checkpoint_path}")
pred_path = pred_dir / "prediction_batch.npy"
if pred_path.exists():
pred = np.load(pred_path)
print(f"Prediction batch: shape={pred.shape}, dtype={pred.dtype}, mean={pred.mean():.6f}")
else:
print(f"Prediction batch not found: {pred_path}")
if __name__ == "__main__":
main()