class_docstr: A class for Tensorflow specific optimizer logic.
  
  The major behavior change for this class is for tf.distribute.
  
  It will override methods from base Keras core Optimizer,
  which provide distribute specific functionality, e.g. variable
  creation, loss reduction, etc.
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code: def _clip_by_norm(self, values, axes=None):
      # We need to use TF-specific OP to support the case,
      # when `values` are `tf.IndexedSlices`.
      return tf.clip_by_norm(values, self.clipnorm, axes)
  
file_path: keras/keras/backend/tensorflow/optimizer.py
imports: import tensorflow
  from keras import backend
  from keras.backend.common import KerasVariable
  from keras.optimizers import base_optimizer
label_desc: Use image node_id 12 for calling the TFOptimizer obj's underlying member method code with example usage: obj._clip_by_norm(values, axes) and returns: tf