class_docstr: Manages dependencies on other objects with Keras tracking.
  
  Similar to TF AutoTrackable, but disabling tracking is based
  on tracking within Keras.
  
  This serves as an interface between Keras tracking and TF tracking.
class_docstr_tok: ["Manages","dependencies","on","other","objects","with","Keras","tracking",".","Similar","to","TF","AutoTrackable",",","but","disabling","tracking","is","based","on","tracking","within","Keras",".","This","serves","as","an","interface","between","Keras","tracking","and","TF","tracking","."]
docstr: Support self.foo = trackable syntax.
docstr_tok: ["Support","self.foo","=","trackable","syntax","."]
code: def __setattr__(self, name, value):
      """Support self.foo = trackable syntax."""
      try:
          if getattr(self, name) is value:
              # Short circuit for `self.$x = self.$x`.
              return
      except AttributeError:
          pass
  
      if getattr(self, "_self_setattr_tracking", True):
          value = sticky_attribute_assignment(
              trackable=self, value=value, name=name
          )
      super().__setattr__(name, value)
  
imports: import tensorflow
  from keras.utils import tracking
label_desc: Use image node_id 1 for calling the KerasAutoTrackable obj's underlying member method code with example usage: obj.__setattr__(name, value) without return types