code: def __init__(
      self, model: object, fit_params: Dict[str, object] = None
  ) -> None:
      super(BaseModelAdapter, self).__init__()
  
      self.model = model
      self.last_x, self.last_y = None, None
      self.clean = False
      self.fit_params = {} if fit_params is None else fit_params
  
imports: import abc
  from typing import Dict
  import numpy
  from sklearn.base import BaseEstimator
  from lightwood.analysis.nc.util import t_softmax
label_desc: Use image node_id 1 to create a new BaseModelAdapter object from inherited base classes: BaseEstimator with example: obj = BaseModelAdapter(model, fit_params)