code: def gaussian(self, window_size, sigma):
      gauss = paddle.to_tensor(
          [
              exp(
                  -((x - window_size // 2) ** 2) / float(2 * sigma**2)
              )
              for x in range(window_size)
          ]
      )
      return gauss / gauss.sum()
  
imports: from math import exp
  import paddle
  import paddle.nn.functional
  import paddle.nn
  import string
label_desc: Use image node_id 2 for calling the SSIM obj's underlying member method code with example usage: obj.gaussian(window_size, sigma) and returns: unknown