Label Smoothing in PyTorch

I'm building a ResNet-18 classification model for the Stanford Cars dataset using transfer learning. I would like to implement label smoothing to penalize overconfident predictions and improve generalization.

TensorFlow has a simple keyword argument in CrossEntropyLoss. Has anyone built a similar function for PyTorch that I could plug-and-play with?

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