class_docstr: 2D Cross Entropy Loss with Multi-Loss
class_docstr_tok: ["2D","Cross","Entropy","Loss","with","Multi-Loss"]
code: def __init__(self, size_average=True, ignore_label=-1, **kwargs):
      super(SegmentationMultiLosses, self).__init__(
          size_average, ignore_label, **kwargs
      )
  
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 SegmentationMultiLosses object from inherited base classes: SoftmaxCrossEntropyLoss with example: obj = SegmentationMultiLosses(size_average, ignore_label)