code: def test_norm_normalization_forward_backward(
      eps, axis, p, shape, seed, ctx, func_name
  ):
      from nbla_test_utils import cap_ignore_region, function_tester
      from sys import platform
  
      if platform == "darwin":
          pytest.skip("NormNormalization is not supported in macOS.")
  
      rng = np.random.RandomState(seed)
      inputs = [
          cap_ignore_region(
              rng.randn(*shape).astype(np.float32) * 2, (-1e-3, 1e-3)
          )
      ]
      func_args = [p, axis, eps]
      function_tester(
          rng,
          F.norm_normalization,
          ref_norm_normalization,
          inputs,
          ctx=ctx,
          func_name=func_name,
          func_args=func_args,
          backward=[True],
          disable_half_test=False,
          # The backward test on macOS doesn't pass with this tolerance.
          # Does Eigen library used in CPU computation backend produce
          # the different results on different platforms?
          # atol_b=3e-3,
          atol_b=1e-2,
          atol_accum=1e-2,
      )
  
imports: import pytest
  import numpy
  import nnabla.functions
  from nbla_test_utils import list_context
label_desc: Use image node_id 2 for calling a global function with example usage: test_norm_normalization_forward_backward(eps, axis, p, shape, seed, ctx, func_name) without return types