code: def pick_probability(x, temp, cos_distance):
      
      f = SNNLCrossEntropy.fits(
          x, x, temp, cos_distance) - tf.eye(tf.shape(x)[0])
      return f / (
          SNNLCrossEntropy.STABILITY_EPS + tf.expand_dims(tf.reduce_sum(f, 1), 1))
docs: Row normalized exponentiated pairwise distance between all the elements
      of x. Conceptualized as the probability of sampling a neighbor point for
      every element of x, proportional to the distance between the points.
      :param x: a matrix
      :param temp: Temperature
      :cos_distance: Boolean for using cosine or euclidean distance
  
      :returns: A tensor for the row normalized exponentiated pairwise distance
                between all the elements of x.