class_docstr: Jensen-Shannon Divergence + Cross-Entropy Loss
  
  Based on impl here: https://github.com/google-research/augmix/blob/master/imagenet.py
  From paper: 'AugMix: A Simple Data Processing Method to Improve Robustness and Uncertainty -
  https://arxiv.org/abs/1912.02781
  
  Hacked together by / Copyright 2020 Ross Wightman
code: def __init__(self, num_splits=3, alpha=12, smoothing=0.1):
      super().__init__()
      self.num_splits = num_splits
      self.alpha = alpha
      if smoothing is not None and smoothing > 0:
          self.cross_entropy_loss = LabelSmoothingCrossEntropy(
              smoothing
          )
      else:
          self.cross_entropy_loss = torch.nn.CrossEntropyLoss()
  
file_path: pytorch-image-models/timm/loss/jsd.py
imports: import torch
  import torch.nn
  import torch.nn.functional
  from .cross_entropy import LabelSmoothingCrossEntropy
label_desc: Use image node_id 1 to create a new JsdCrossEntropy object from inherited base classes: nn with example: obj = JsdCrossEntropy(num_splits, alpha, smoothing)