code: def test_fusion_rotate_360_flip_rotate_360(img_5x5):
      img = img_5x5
      dc = slc.DataContainer((img,), "I")
  
      ppl = slc.Stream(
          [
              slc.Stream(
                  [
                      slt.Rotate((45, 45), padding="z", p=1),
                      slt.Rotate((45, 45), padding="z", p=1),
                      slt.Rotate((45, 45), padding="z", p=1),
                      slt.Rotate((45, 45), padding="z", p=1),
                      slt.Rotate((45, 45), padding="z", p=1),
                      slt.Rotate((45, 45), padding="z", p=1),
                      slt.Rotate((45, 45), padding="z", p=1),
                      slt.Rotate((45, 45), padding="z", p=1),
                  ],
                  optimize_stack=True,
              ),
              slt.Flip(p=1, axis=1),
              slc.Stream(
                  [
                      slt.Rotate((45, 45), padding="z", p=1),
                      slt.Rotate((45, 45), padding="z", p=1),
                      slt.Rotate((45, 45), padding="z", p=1),
                      slt.Rotate((45, 45), padding="z", p=1),
                      slt.Rotate((45, 45), padding="z", p=1),
                      slt.Rotate((45, 45), padding="z", p=1),
                      slt.Rotate((45, 45), padding="z", p=1),
                      slt.Rotate((45, 45), padding="z", p=1),
                  ],
                  optimize_stack=True,
              ),
          ]
      )
  
      img_res = ppl(dc, return_torch=False)[0][0]
  
      np.testing.assert_array_almost_equal(
          cv2.flip(img, 1).reshape(5, 5, 1), img_res
      )
  
imports: import itertools
  import random
  import cv2
  import numpy
  import pytest
  import torch
  import solt.core
  import solt.transforms
  import solt.utils
  from .fixtures import *
label_desc: Use image node_id 20 for calling a global function with example usage: test_fusion_rotate_360_flip_rotate_360(img_5x5) without return types