class_docstr: See `tf.keras.losses.CategoricalCrossentropy`.
code: def __init__(self, from_logits=False, lazy_normalization=False):
      self.from_logits = from_logits
      self.lazy_normalization = lazy_normalization
      if from_logits:
          super(CategoricalCrossentropy, self).__init__(
              categorical_crossentropy_from_logits
          )
      else:
          super(CategoricalCrossentropy, self).__init__(
              categorical_crossentropy
          )
  
imports: import tf_encrypted
label_desc: Use image node_id 1 to create a new CategoricalCrossentropy object from inherited base classes: Loss with example: obj = CategoricalCrossentropy(from_logits, lazy_normalization)