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[Auto] Support weight and label_smoothing in fixed_cross_entropy (cluster-43240-3): merged 1 of 2 PRs #16

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[Auto] Support weight and label_smoothing in fixed_cross_entropy (cluster-43240-3): merged 1 of 2 PRs #16

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7c722ba
Add supported kwargs to fixed_cross_entropy
Rocketknight1 Jan 13, 2026
afb3f23
make style
Rocketknight1 Jan 13, 2026
5e6cba7
Merge branch 'pr-43254' into merge-cluster-cluster-43240-3-2026042322…
evalstate Apr 23, 2026
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6 changes: 5 additions & 1 deletion src/transformers/loss/loss_utils.py
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Expand Up @@ -30,10 +30,14 @@ def fixed_cross_entropy(
target: torch.Tensor,
num_items_in_batch: torch.Tensor | None = None,
ignore_index: int = -100,
weight: torch.Tensor | None = None,
label_smoothing: float = 0.0,
**kwargs,
) -> torch.Tensor:
reduction = "sum" if num_items_in_batch is not None else "mean"
loss = nn.functional.cross_entropy(source, target, ignore_index=ignore_index, reduction=reduction)
loss = nn.functional.cross_entropy(
source, target, ignore_index=ignore_index, weight=weight, reduction=reduction, label_smoothing=label_smoothing
)
if reduction == "sum":
# just in case users pass an int for num_items_in_batch, which could be the case for custom trainer
if torch.is_tensor(num_items_in_batch):
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