code: def predict(
      self,
      n_periods=10,
      X=None,
      return_conf_int=False,
      alpha=0.05,
  ):
      return self.model_.predict(
          n_periods=n_periods,
          X=X,
          return_conf_int=return_conf_int,
          alpha=alpha,
      )
  
imports: import numpy
  from sklearn.linear_model import LinearRegression
  import functools
  import time
  import warnings
  from ..base import BaseARIMA
  from .None import _doc
  from .None import _validation
  from .utils import ndiffs, is_constant, nsdiffs
  from ..utils import diff, is_iterable, check_endog
  from ..utils.metaestimators import if_has_delegate
  from ._context import AbstractContext, ContextType
  from .None import _auto_solvers
  from ..compat.numpy import DTYPE
  from ..compat import statsmodels
label_desc: Use image node_id 4 for calling the AutoARIMA obj's underlying member method code with example usage: obj.predict(n_periods, X, return_conf_int, alpha) and returns: self