code: def BinaryCrossEntropyLoss():
      """Returns a layer that outputs binary prediction-target cross-entropy.
  
      DEPRECATED; refactor to use ``BinaryCrossEntropy`` instead. (The newer
      ``BinaryCrossEntropy`` does not use weights, so refactor accordingly. Unless
      and until clear motivating use cases arise, the library will not include a
      binary cross-entropy function with weights.)
      """
      return cb.Serial(
          _BinaryCrossEntropy(),
          _WeightedMean(),
          name="BinaryCrossEntropyLoss",
          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 15 for calling a global function with example usage: BinaryCrossEntropyLoss() and returns: cb