code: def test_builder_eval_stress(self, rank_and_axes, epsilon):
      rank, axes = rank_and_axes
      shape = np.random.randint(low=2, high=6, size=rank)
      x_val = random_gen(shape=shape, rand_min=-100.0, rand_max=100.0)
      positive_axes = [
          axis + rank if axis < 0 else axis for axis in axes
      ]
      normalized_shape = [
          shape[i] for i in range(rank) if i in positive_axes
      ]
      gamma_val = random_gen(
          shape=normalized_shape, rand_min=-100, rand_max=100
      )
      beta_val = random_gen(
          shape=normalized_shape, rand_min=-100, rand_max=100
      )
      with Function({}):
          res = mb.layer_norm(
              x=x_val,
              axes=axes,
              epsilon=epsilon,
              gamma=gamma_val,
              beta=beta_val,
          )
          ref = TestNormalizationLayerNorm._np_layer_norm(
              x=x_val,
              axes=axes,
              epsilon=epsilon,
              gamma=gamma_val,
              beta=beta_val,
          )
          np.testing.assert_allclose(
              ref, res.val, atol=1e-04, rtol=1e-05
          )
  
imports: import itertools
  import platform
  import numpy
  import pytest
  import coremltools
  from coremltools._deps import _HAS_TF_2, _HAS_TORCH, MSG_TF2_NOT_FOUND, MSG_TORCH_NOT_FOUND
  from coremltools.converters.mil.mil import Builder
  from coremltools.converters.mil.mil import Function, get_new_symbol, types
  from coremltools.converters.mil.mil.ops.tests.iOS14 import backends
  from coremltools.converters.mil.mil.ops.tests.testing_utils import UNK_SYM, construct_inputs_from_placeholders, run_compare_builder
  from coremltools.converters.mil.testing_reqs import compute_units
  from coremltools.converters.mil.testing_utils import random_gen
label_desc: Use image node_id 8 for calling the TestNormalizationLayerNorm obj's underlying member method code with example usage: obj.test_builder_eval_stress(rank_and_axes, epsilon) without return types