code: def __init__(
      self, model_type="regressor", cpus_per_trial=1, **xgb_configs
  ):
      self.model_type = model_type
      self.model_config = xgb_configs.copy()
  
      if (
          "n_jobs" in xgb_configs
          and xgb_configs["n_jobs"] != cpus_per_trial
      ):
          logger.warning(
              f"Found n_jobs={xgb_configs['n_jobs']} in xgb_configs. It will not take "
              f"effect since we assign cpus_per_trials(={cpus_per_trial}) to xgboost "
              f"n_jobs. Please raise an issue if you do need different values for "
              f"xgboost n_jobs and cpus_per_trials."
          )
      self.model_config["n_jobs"] = cpus_per_trial
  
imports: import pickle
  import pandas
  from xgboost.sklearn import XGBRegressor
  from xgboost.sklearn import XGBClassifier
  from zoo.orca.automl.metrics import Evaluator
  from zoo.orca.automl.model.abstract import BaseModel, ModelBuilder
  import logging
label_desc: Use image node_id 1 to create a new XGBoostModelBuilder object from inherited base classes: ModelBuilder with example: obj = XGBoostModelBuilder(model_type, cpus_per_trial)