code: def CrossEntropyLoss():
      """Returns a layer that outputs multiclass prediction-target cross-entropy.
  
      DEPRECATED; refactor to use ``WeightedCategoryCrossEntropy`` or
      ``CategoryCrossEntropy`` instead.
  
      (``CrossEntropyLoss`` by itself does not compute cross-entropy. In older
      code, this layer had to be preceded by ``LogSoftmax``, and the two layers
      together did the work of converting category information to probability
      distributions and computing the cross-entropy between those distributions.
      All this is now done by ``WeightedCategoryCrossEntropy``.)
      """
      return cb.Serial(
          _CrossEntropy(),
          _WeightedMean(),
          name="CrossEntropyLoss",
          sublayers_to_print=[],
      )
  
imports: from trax import fastmath
  from trax import shapes
  from trax.fastmath import numpy
  from trax.layers import base
  from trax.layers import combinators
  from trax.layers import core
label_desc: Use image node_id 13 for calling a global function with example usage: CrossEntropyLoss() and returns: cb