def get_default_state(self, _):
    '\n        Gather state description\n\n        Returns\n        -------\n        dict\n            Environment state\n\n        '
    gradients = self._get_gradients()
    (self.firstOrderMomentum, self.secondOrderMomentum) = self._get_momentum(gradients)
    (predictiveChangeVarDiscountedAverage, predictiveChangeVarUncertainty) = self._get_predictive_change_features(self.current_lr, self.firstOrderMomentum, self.secondOrderMomentum)
    (lossVarDiscountedAverage, lossVarUncertainty) = self._get_loss_features()
    state = {'predictiveChangeVarDiscountedAverage': predictiveChangeVarDiscountedAverage, 'predictiveChangeVarUncertainty': predictiveChangeVarUncertainty, 'lossVarDiscountedAverage': lossVarDiscountedAverage, 'lossVarUncertainty': lossVarUncertainty, 'currentLR': self.current_lr, 'trainingLoss': self.current_training_loss, 'validationLoss': self.current_validation_loss}
    return state
Gather state description

Returns
-------
dict
    Environment state
def get_default_state(self, _):
    '\n        Gather state description\n\n        Returns\n        -------\n        dict\n            Environment state\n\n        '
    gradients = self._get_gradients()
    (self.firstOrderMomentum, self.secondOrderMomentum) = self._get_momentum(gradients)
    (predictiveChangeVarDiscountedAverage, predictiveChangeVarUncertainty) = self._get_predictive_change_features(self.current_lr, self.firstOrderMomentum, self.secondOrderMomentum)
    (lossVarDiscountedAverage, lossVarUncertainty) = self._get_loss_features()
    state = {'predictiveChangeVarDiscountedAverage': predictiveChangeVarDiscountedAverage, 'predictiveChangeVarUncertainty': predictiveChangeVarUncertainty, 'lossVarDiscountedAverage': lossVarDiscountedAverage, 'lossVarUncertainty': lossVarUncertainty, 'currentLR': self.current_lr, 'trainingLoss': self.current_training_loss, 'validationLoss': self.current_validation_loss}
    return state