class_docstr: TensorBoard plugin interface.
  
  Every plugin must extend from this class.
  
  Subclasses should have a trivial constructor that takes a TBContext
  argument. Any operation that might throw an exception should either be
  done lazily or made safe with a TBLoader subclass, so the plugin won't
  negatively impact the rest of TensorBoard.
  
  Fields:
    plugin_name: The plugin_name will also be a prefix in the http
      handlers, e.g. `data/plugins/$PLUGIN_NAME/$HANDLER` The plugin
      name must be unique for each registered plugin, or a ValueError
      will be thrown when the application is constructed. The plugin
      name must only contain characters among [A-Za-z0-9_.-], and must
      be nonempty, or a ValueError will similarly be thrown.
docstr: Determines whether this plugin is active.
  
  A plugin may not be active for instance if it lacks relevant data. If a
  plugin is inactive, the frontend may avoid issuing requests to its routes.
  
  Returns:
    A boolean value. Whether this plugin is active.
docstr_tok: ["Determines","whether","this","plugin","is","active",".","A","plugin","may","not","be","active","for","instance","if","it","lacks","relevant","data",".","If","a","plugin","is","inactive",",","the","frontend","may","avoid","issuing","requests","to","its","routes",".","Returns",":","A","boolean","value",".","Whether","this","plugin","is","active","."]
code: def is_active(self):
      """Determines whether this plugin is active.
  
      A plugin may not be active for instance if it lacks relevant data. If a
      plugin is inactive, the frontend may avoid issuing requests to its routes.
  
      Returns:
        A boolean value. Whether this plugin is active.
      """
      raise NotImplementedError()
  
imports: from abc import ABCMeta
  from abc import abstractmethod
label_desc: Use image node_id 3 for calling the TBPlugin obj's underlying member method code with example usage: obj.is_active() without return types