code: def test_ssim(
      available_device,
      shape,
      kernel_size,
      gaussian,
      use_sample_covariance,
  ):
      y_pred = torch.rand(shape, device=available_device)
      y = y_pred * 0.8
  
      compare_ssim_ignite_skiimg(
          y_pred,
          y,
          available_device,
          kernel_size=kernel_size,
          gaussian=gaussian,
          use_sample_covariance=use_sample_covariance,
      )
  
file_path: ignite/tests/ignite/metrics/test_ssim.py
imports: from typing import Sequence, Union
  import numpy
  import pytest
  import torch
  from skimage.metrics import structural_similarity
  import ignite.distributed
  from ignite.exceptions import NotComputableError
  from ignite.metrics import SSIM
label_desc: Use image node_id 3 for calling a global function with example usage: test_ssim(available_device, shape, kernel_size, gaussian, use_sample_covariance) without return types