def set_generator_validation_nb(self, number):
        """
        sets self.nb_val_samples which is used in model.fit if input is a generator
        :param number:
        :return:
        """

        self.nb_val_samples = number
        diff_to_batch = number % self.get_batch_size()
        if diff_to_batch > 0:
            self.nb_val_samples += self.get_batch_size() - diff_to_batch

        import keras
        if '1' != keras.__version__[0]:
            self.nb_val_samples = self.nb_val_samples // self.get_batch_size()
def set_generator_validation_nb ( self , number ) : self . nb_val_samples = number diff_to_batch = number % self . get_batch_size ( ) if diff_to_batch > 0 : self . nb_val_samples += self . get_batch_size ( ) - diff_to_batch import keras if '1' != keras . __version__ [ 0 ] : self . nb_val_samples = self . nb_val_samples // self . get_batch_size ( )
sets self.nb_val_samples which is used in model.fit if input is a generator
        :param number:
        :return: