class_docstr: Calculates a pn variant of the softmax ratio between anchor, positive
  and negative examples in a triplet based on euclidean distance.
class_docstr_tok: ["Calculates","a","pn","variant","of","the","softmax","ratio","between","anchor",",","positive","and","negative","examples","in","a","triplet","based","on","euclidean","distance","."]
code: def __init__(self, name=None):
      name = name or self.__class__.__name__
      self.__name__ = name
  
imports: import functools
  from tensorflow.keras import backend
  import tensorflow
  from tensorflow import keras
  import numpy
  from .distances import euclidean_distance, manhattan_distance, chebyshev_distance, cosine_distance
label_desc: Use image node_id 1 to create a new EuclideanSoftmaxRatioPnLoss object  with example: obj = EuclideanSoftmaxRatioPnLoss(name)