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firestar5683
22a8575199
Keep official openpilot ancestry and dependency licenses. Store resources directly in Git, remove LFS setup requirements, and leave the downloadable big model outside the source tree.
29 lines
1.1 KiB
Python
29 lines
1.1 KiB
Python
from examples.mlperf.metrics import dice_score
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from tinygrad import Tensor
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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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def sigmoid_focal_loss(pred:Tensor, tgt:Tensor, alpha:float=0.25, gamma:float=2.0, reduction:str="none") -> Tensor:
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assert reduction in ["mean", "sum", "none"], f"unsupported reduction {reduction}"
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p, ce_loss = pred.sigmoid(), pred.binary_crossentropy_logits(tgt, reduction="none")
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p_t = p * tgt + (1 - p) * (1 - tgt)
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loss = ce_loss * ((1 - p_t) ** gamma)
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if alpha >= 0:
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alpha_t = alpha * tgt + (1 - alpha) * (1 - tgt)
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loss = loss * alpha_t
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if reduction == "mean": loss = loss.mean()
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elif reduction == "sum": loss = loss.sum()
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return loss
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def l1_loss(pred:Tensor, tgt:Tensor, reduction:str="none") -> Tensor:
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assert reduction in ["mean", "sum", "none"], f"unsupported reduction {reduction}"
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loss = (pred - tgt).abs()
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if reduction == "mean": loss = loss.mean()
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elif reduction == "sum": loss = loss.sum()
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return loss |