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3e77c56 | 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 | """Evaluation: mean test relative-L2 on a split (de-normalized).
Mirrors the eval loop in Transolver ``exp_elas.py``: predictions are decoded with the
(train-fitted) normalizer before the metric; targets are physical.
"""
from __future__ import annotations
import torch
from torch.utils.data import DataLoader
from .losses.relative_l2 import relative_l2
@torch.no_grad()
def evaluate(model, loader: DataLoader, normalizer, device) -> float:
"""Return mean relative-L2 over the loader (physical units)."""
model.eval()
total = 0.0
n = 0
for coords, sigma in loader:
coords = coords.to(device)
sigma = sigma.to(device) # physical (B, N, 1)
out = model(coords, None) # (B, N, 1) normalized
out = normalizer.decode(out) # -> physical
total += relative_l2(out, sigma, reduction="sum").item()
n += coords.shape[0]
return total / max(n, 1)
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