code: def test_poincare_normalize_dim_array():
      x_shape = [20, 7, 3]
      epsilon = 1e-5
      tol = 1e-6
      np.random.seed(1)
      inputs = np.random.random_sample(x_shape).astype(np.float32)
      dim = [1, 2]
  
      outputs_expected = _poincare_normalize(inputs, dim, epsilon)
  
      outputs = test_utils.layer_test(
          PoincareNormalize,
          kwargs={"axis": dim, "epsilon": epsilon},
          input_data=inputs,
          expected_output=outputs_expected,
      )
      for y in outputs_expected, outputs:
          norm = np.linalg.norm(y, axis=tuple(dim))
          assert norm.max() <= 1.0 - epsilon + tol
  
imports: import pytest
  import numpy
  from tensorflow_addons.layers.poincare import PoincareNormalize
  from tensorflow_addons.utils import test_utils
label_desc: Use image node_id 3 for calling a global function with example usage: test_poincare_normalize_dim_array() without return types