code: def _get_loss(self):
      params = {
          "max_steps": self._get_max_steps(),
          "sigma": self.sigma,
          "beta": self.beta,
          "verbose": self.verbose,
      }
  
      losses = {
          "squared": Squared(verbose=self.verbose),
          "smooth_hinge": SmoothHinge(**params),
          "squared_hinge": SquaredHinge(**params),
          "modified_huber": ModifiedHuber(**params),
          "log": Log(**params),
      }
  
      return losses[self.loss]
  
imports: import numpy
  from joblib import Parallel, delayed
  from .base import BaseClassifier
  from .base import BaseRegressor
  from .dataset_fast import get_dataset
  from .primal_cd_fast import _primal_cd
  from .primal_cd_fast import Squared
  from .primal_cd_fast import SmoothHinge
  from .primal_cd_fast import SquaredHinge
  from .primal_cd_fast import ModifiedHuber
  from .primal_cd_fast import Log
label_desc: Use image node_id 1 for calling the _BaseCD obj's underlying member method code with example usage: obj._get_loss() and returns: losses