docstr: Build a Decomposition model wrapper.
  
  :param models: tuple, (model, model_copy) two basic forecaster models.
  :param kernel_size: int, Specify the kernel size in moving average.
docstr_tok: ["Build","a","Decomposition","model","wrapper",".",":","param","models",":","tuple",",","(","model",",","model_copy",")","two","basic","forecaster","models",".",":","param","kernel_size",":","int",",","Specify","the","kernel","size","in","moving","average","."]
code: def __init__(self, models, kernel_size=25):
      """
      Build a Decomposition model wrapper.
  
      :param models: tuple, (model, model_copy) two basic forecaster models.
      :param kernel_size: int, Specify the kernel size in moving average.
      """
      super(DecompositionTSModel, self).__init__()
      self.decompsition = series_decomp(kernel_size)
      self.linear_seasonal = models[0]
      self.linear_trend = models[1]
  
file_path: BigDL/python/chronos/src/bigdl/chronos/pytorch/model_wrapper/decomposition.py
imports: import torch.nn
  import torch
label_desc: Use image node_id 1 to create a new DecompositionTSModel object from inherited base classes: nn with example: obj = DecompositionTSModel(models, kernel_size)