code: def _get_max_steps(self):
      if self.max_steps == "auto":
          if self.loss == "log":
              max_steps = 0
          else:
              max_steps = 30
      else:
          max_steps = self.max_steps
      return max_steps
  
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 2 for calling the _BaseCD obj's underlying member method code with example usage: obj._get_max_steps() and returns: max_steps