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| import os | |
| import torch | |
| path = "alphazero/training/alphanet_latest.pt" | |
| if not os.path.exists(path): | |
| print(f"File not found: {path}") | |
| else: | |
| sd = torch.load(path, map_location="cpu") | |
| print(f"--- Model Weights Statistics ({path}) ---") | |
| for k, v in list(sd.items())[:10]: | |
| if isinstance(v, torch.Tensor): | |
| print(f"{k:40s}: mean={v.mean():.4f}, std={v.std():.4f}, range=({v.min():.4f}, {v.max():.4f})") | |