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fe8202e | 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 | import os
import sys
import torch
sys.path.append(os.path.join(os.path.dirname(__file__), "..", "src"))
from gliomasam3_moe.losses.brats_losses import LossComputer
def test_loss_backward():
logits = torch.randn(2, 3, 8, 32, 32, requires_grad=True)
labels = torch.randint(0, 4, (2, 1, 8, 32, 32))
# map {0,1,2,3} -> {0,1,2,4}
labels = labels.clone()
labels[labels == 3] = 4
aux = {
"pi_et": torch.sigmoid(torch.randn(2)),
"moe_gamma": torch.softmax(torch.randn(2, 5), dim=-1),
}
loss_fn = LossComputer()
loss, _ = loss_fn(logits, aux, labels)
loss.backward()
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