code: def test_ellipsis_ops_numpy():
      x = numpy.arange(2 * 3 * 4 * 5 * 6).reshape([2, 3, 4, 5, 6])
      for pattern in identity_patterns:
          assert numpy.array_equal(x, rearrange(x, pattern)), pattern
  
      for pattern1, pattern2 in equivalent_rearrange_patterns:
          assert numpy.array_equal(
              rearrange(x, pattern1), rearrange(x, pattern2)
          )
  
      for reduction in ["min", "max", "sum"]:
          for pattern1, pattern2 in equivalent_reduction_patterns:
              assert numpy.array_equal(
                  reduce(x, pattern1, reduction=reduction),
                  reduce(x, pattern2, reduction=reduction),
              )
  
      # now just check coincidence with numpy
      all_rearrange_patterns = [*identity_patterns]
      for pattern_pairs in equivalent_rearrange_patterns:
          all_rearrange_patterns.extend(pattern_pairs)
  
imports: import itertools
  import numpy
  import pytest
  from einops import EinopsError
  from einops.einops import rearrange, reduce, repeat, _enumerate_directions
  from .None import collect_test_backends, is_backend_tested, FLOAT_REDUCTIONS
label_desc: Use image node_id 2 for calling a global function with example usage: test_ellipsis_ops_numpy() without return types