class_docstr: Ideas comes from AutoFormer
  Decompose a time series into trends and seasonal
  
  Refs:  https://arxiv.org/abs/2106.13008
code: def __init__(self, kernel_size):
      super().__init__()
      self.kernel_size = kernel_size
  
imports: import pgl
  import paddle
  import paddle.nn
  import paddle.nn.functional
  import numpy
  from pgl.utils.logger import log
  import pgl.nn
  import math
label_desc: Use image node_id 1 to create a new SeriesDecomp object from inherited base classes: nn with example: obj = SeriesDecomp(kernel_size)