class_docstr: SoftmaxCrossEntropyLoss2D with Auxiliary Loss
  
  Parameters
  ----------
  aux : bool, default True
      Whether to use auxiliary loss.
  aux_weight : float, default 0.2
      The weight for aux loss.
  ignore_label : int, default -1
      The label to ignore.
class_docstr_tok: ["SoftmaxCrossEntropyLoss2D","with","Auxiliary","Loss","Parameters","--","--","--","--","--","aux",":","bool",",","default","True","Whether","to","use","auxiliary","loss",".","aux_weight",":","float",",","default","0.2","The","weight","for","aux","loss",".","ignore_label",":","int",",","default","-1","The","label","to","ignore","."]
code: def __init__(
      self, aux=True, aux_weight=0.2, ignore_label=-1, **kwargs
  ):
      super(MixSoftmaxCrossEntropyOHEMLoss, self).__init__(
          ignore_label=ignore_label, **kwargs
      )
      self.aux = aux
      self.aux_weight = aux_weight
  
imports: from __future__ import absolute_import
  from mxnet import gluon
  from mxnet import nd
  from mxnet.gluon.loss import Loss, _apply_weighting, _reshape_like
label_desc: Use image node_id 1 to create a new MixSoftmaxCrossEntropyOHEMLoss object from inherited base classes: SoftmaxCrossEntropyOHEMLoss with example: obj = MixSoftmaxCrossEntropyOHEMLoss(aux, aux_weight, ignore_label)