code: def test_builder_to_backend_stress(
      self,
      compute_unit,
      backend,
      rank,
      size,
      alpha,
      beta,
      k,
      x_param_dtype,
  ):
      x_dtype, param_dtype = x_param_dtype
      x_builtin_dtype = types.numpy_type_to_builtin_type(x_dtype)
  
      if x_dtype == np.float16 and backend.backend == "neuralnetwork":
          pytest.skip("No need to test fp16 for neuralnetwork backend.")
  
      shape = np.random.randint(low=2, high=5, size=rank)
      x_val = random_gen(shape=shape).astype(x_dtype)
      input_placeholders = {
          "x": mb.placeholder(shape=x_val.shape, dtype=x_builtin_dtype)
      }
      input_values = {"x": x_val}
  
      def build(x):
          return mb.local_response_norm(
              x=x,
              size=size,
              alpha=param_dtype(alpha),
              beta=param_dtype(beta),
              k=param_dtype(k),
          )
  
      torch_lrn = torch.nn.LocalResponseNorm(
          size=size, alpha=alpha, beta=beta, k=k
      )
      # PyTorch doesn't support LocalResponseNorm with fp16, so need to cast to float32 first.
      expected_outputs = [
          torch_lrn(torch.as_tensor(x_val.astype(np.float32))).numpy()
      ]
      expected_output_types = [
          o.shape[:] + (x_builtin_dtype,) for o in expected_outputs
      ]
  
      run_compare_builder(
          build,
          input_placeholders,
          input_values,
          expected_output_types,
          expected_outputs,
          compute_unit=compute_unit,
          backend=backend,
          atol=1e-2,
          rtol=1e-3,
      )
  
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 2 for calling the TestNormalizationLocalResponseNorm obj's underlying member method code with example usage: obj.test_builder_to_backend_stress(compute_unit, backend, rank, size, alpha, beta, k, x_param_dtype) and returns: mb