code: def prepare_model(
      self, n_estimators: int
  ) -> CausalRandomForestRegressor:
      crforest = CausalRandomForestRegressor(
          criterion="causal_mse",
          control_name=self.control_name,
          n_estimators=n_estimators,
          n_jobs=mp.cpu_count() - 1,
      )
      return crforest
  
imports: import multiprocessing
  from abc import abstractmethod
  import pandas
  import pytest
  from sklearn.model_selection import train_test_split
  from causalml.inference.tree import CausalTreeRegressor, CausalRandomForestRegressor
  from causalml.metrics import ape
  from causalml.metrics import qini_score
  from .const import RANDOM_SEED, ERROR_THRESHOLD
label_desc: Use image node_id 1 for calling the TestCausalRandomForestRegressor obj's underlying member method code with example usage: obj.prepare_model(n_estimators) and returns: crforest