class_docstr: SoftCrossEntropyLoss (useful for label smoothing and mixup).
  Identical to torch.nn.CrossEntropyLoss if used with one-hot labels.
class_docstr_tok: ["SoftCrossEntropyLoss","(","useful","for","label","smoothing","and","mixup",")",".","Identical","to","torch.nn.CrossEntropyLoss","if","used","with","one-hot","labels","."]
code: def __init__(self):
      super(SoftCrossEntropyLoss, self).__init__()
  
file_path: pycls/pycls/core/net.py
imports: import itertools
  import numpy
  import pycls.core.distributed
  import torch
  from pycls.core.config import cfg
label_desc: Use image node_id 1 to create a new SoftCrossEntropyLoss object from inherited base classes: torch.nn with example: obj = SoftCrossEntropyLoss()