code: def forward_theta(fitted_model, y):
      m = fitted_model["m"]
      model = fitted_model["modeltype"]
      initial_smoothed = fitted_model["par"]["initial_smoothed"]
      alpha = fitted_model["par"]["alpha"]
      theta = fitted_model["par"]["theta"]
      return auto_theta(
          y=y,
          m=m,
          model=model,
          initial_smoothed=initial_smoothed,
          alpha=alpha,
          theta=theta,
      )
  
imports: import math
  from typing import Tuple
  import numpy
  from numba import njit
  from scipy.stats import norm
  from statsmodels.tsa.seasonal import seasonal_decompose
  from statsmodels.tsa.stattools import acf
  from .ets import restrict_to_bounds, results
  from .utils import _seasonal_naive, _repeat_val_seas, CACHE, NOGIL
label_desc: Use image node_id 17 for calling a global function with example usage: forward_theta(fitted_model, y) and returns: auto_theta