code: def read_defaults(self)->None:
          "Read the values inside the optimizer for the hyper-parameters."
          self._beta = None
          if 'lr' in self.opt_keys: self._lr = self.read_val('lr')
          if 'momentum' in self.opt_keys: self._mom = self.read_val('momentum')
          if 'alpha' in self.opt_keys: self._beta = self.read_val('alpha')
          if 'betas' in self.opt_keys: self._mom,self._beta = self.read_val('betas')
          if 'weight_decay' in self.opt_keys: self._wd = self.read_val('weight_decay')
          reserved_names = ['params', 'lr', 'momentum', 'alpha', 'betas', 'weight_decay']
          stat_names = [n for n in self.opt_keys if n not in reserved_names]
          self._stats = {n:self.read_val(n) for n in stat_namesf read_defaults(self)->None:
          "Read the values inside the optimizer for the hyper-parameters."
          self._beta = None
          if 'lr' in self.opt_keys: self._lr = self.read_val('lr')
          if 'momentum' in self.opt_keys: self._mom = self.read_val('momentum')
          if 'alpha' in self.opt_keys: self._beta = self.read_val('alpha')
          if 'betas' in self.opt_keys: self._mom,self._beta = self.read_val('betas')
          if 'weight_decay' in self.opt_keys: self._wd = self.read_val('weight_decay')
          reserved_names = ['params', 'lr', 'momentum', 'alpha', 'betas', 'weight_decay']
          stat_names = [n for n in self.opt_keys if n not in reserved_names]
          self._stats = {n:self.read_val(n) for n in stat_names}
docs: Read the values inside the optimizer for the hyper-parameters.