code: def __init__(
      self,
      eps: float = 0.1,  # The weight for the interpolation formula
      weight: Tensor = None,  # Manual rescaling weight given to each class passed to `F.nll_loss`
      reduction: str = "mean",  # PyTorch reduction to apply to the output
  ):
      store_attr()
  
imports: from __future__ import annotations
  from .imports import *
  from .torch_imports import *
  from .torch_core import *
  from .layers import *
label_desc: Use image node_id 1 to create a new LabelSmoothingCrossEntropy object from inherited base classes: Module with example: obj = LabelSmoothingCrossEntropy(eps, weight, reduction)