parameters: (self, observation_transition_tradeoff_log=None)
docstring: Define extra model-specific parameters.
  
      Models should wrap any variables defined here in the model's variable scope.
  
      Args:
        observation_transition_tradeoff_log: An ensemble-global parameter
          controlling the tradeoff between observation noise and transition
          noise. If its value is not None, component transition noise should scale
          with e^-observation_transition_tradeoff_log.
docstring_summary: Define extra model-specific parameters.
docstring_tokens: Define extra model - specific parameters .
function: def _define_parameters(self, observation_transition_tradeoff_log=None):
      """Define extra model-specific parameters.
  
      Models should wrap any variables defined here in the model's variable scope.
  
      Args:
        observation_transition_tradeoff_log: An ensemble-global parameter
          controlling the tradeoff between observation noise and transition
          noise. If its value is not None, component transition noise should scale
          with e^-observation_transition_tradeoff_log.
      """
      with variable_scope.variable_scope(self._variable_scope):
        # A scalar which allows the optimizer to quickly shift from observation
        # noise to transition noise (this value is subtracted from log transition
        # noise and added to log observation noise).
        if observation_transition_tradeoff_log is None:
          self._observation_transition_tradeoff_log_scale = (
              self._variable_observation_transition_tradeoff_log())
        else:
          self._observation_transition_tradeoff_log_scale = (
              observation_transition_tradeoff_log)
        self.state_transition_noise_covariance = (
            self.get_state_transition_noise_covariance())
function_tokens: def _define_parameters ( self , observation_transition_tradeoff_log = None ) : with variable_scope . variable_scope ( self . _variable_scope ) : # A scalar which allows the optimizer to quickly shift from observation # noise to transition noise (this value is subtracted from log transition # noise and added to log observation noise). if observation_transition_tradeoff_log is None : self . _observation_transition_tradeoff_log_scale = ( self . _variable_observation_transition_tradeoff_log ( ) ) else : self . _observation_transition_tradeoff_log_scale = ( observation_transition_tradeoff_log ) self . state_transition_noise_covariance = ( self . get_state_transition_noise_covariance ( ) )