7 lines
265 B
7 lines
265 B
2 months ago
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from examples.mlperf.metrics import dice_score
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def dice_ce_loss(pred, tgt):
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ce = pred.permute(0, 2, 3, 4, 1).sparse_categorical_crossentropy(tgt.squeeze(1))
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dice = (1.0 - dice_score(pred, tgt, argmax=False, to_one_hot_x=False)).mean()
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return (dice + ce) / 2
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