deepaugment/controller.py
def tell(self, trial_hyperparams, f_val):
        """Tells the controller result of previous tried hyperparameters

        If Bayesian Optimizer, records this results and updates its internal statistical model. If Random Search does nothing, since it will not affect future (random) samples.

        Args:
            trial_hyperparams (list): list of tried hyperparamters
            f_val (float): trial cost
        """
        if self.method == "bayesian_optimization":
            self.opt.tell(trial_hyperparams, f_val)
        elif self.method == "random_search":
            pass
Tells the controller result of previous tried hyperparameters

        If Bayesian Optimizer, records this results and updates its internal statistical model. If Random Search does nothing, since it will not affect future (random) samples.

        Args:
            trial_hyperparams (list): list of tried hyperparamters
            f_val (float): trial cost
        
Tells the controller result of previous tried hyperparameters
If Bayesian Optimizer, records this results and updates its internal statistical model. If Random Search does nothing, since it will not affect future (random) samples.
Tells the controller result of previous tried hyperparameters If Bayesian Optimizer records this results and updates its internal statistical model . If Random Search does nothing since it will not affect future ( random ) samples .
def tell(self, trial_hyperparams, f_val):
        if self.method == "bayesian_optimization":
            self.opt.tell(trial_hyperparams, f_val)
        elif self.method == "random_search":
            pass
def tell ( self , trial_hyperparams , f_val ) : if self . method == "bayesian_optimization" : self . opt . tell ( trial_hyperparams , f_val ) elif self . method == "random_search" : pass
Tells the controller result of previous tried hyperparameters
If Bayesian Optimizer, records this results and updates its internal statistical model.
Tells the controller result of previous tried hyperparameters If Bayesian Optimizer records this results and updates its internal statistical model .
"""Tells the controller result of previous tried hyperparameters

        If Bayesian Optimizer, records this results and updates its internal statistical model. If Random Search does nothing, since it will not affect future (random) samples.

        Args:
            trial_hyperparams (list): list of tried hyperparamters
            f_val (float): trial cost
        """
self
trial_hyperparams
list of tried hyperparamters
list of tried hyperparamters
f_val
None