code: def test_builder_to_backend_stress(
      self, use_cpu_only, backend, rank, size, alpha, beta, k
  ):
      shape = np.random.randint(low=2, high=5, size=rank)
      x_val = random_gen(shape=shape)
      input_placeholders = {"x": mb.placeholder(shape=x_val.shape)}
      input_values = {"x": x_val}
  
      def build(x):
          return mb.local_response_norm(
              x=x, size=size, alpha=alpha, beta=beta, k=k
          )
  
      torch_lrn = torch.nn.LocalResponseNorm(
          size=size, alpha=alpha, beta=beta, k=k
      )
      expected_outputs = [torch_lrn(torch.as_tensor(x_val)).numpy()]
      expected_output_types = [
          o.shape[:] + (types.fp32,) for o in expected_outputs
      ]
  
      run_compare_builder(
          build,
          input_placeholders,
          input_values,
          expected_output_types,
          expected_outputs,
          use_cpu_only=use_cpu_only,
          backend=backend,
          atol=1e-2,
          rtol=1e-3,
      )
  
file_path: turicreate/src/external/coremltools_wrap/coremltools/coremltools/converters/mil/mil/ops/tests/test_normalization.py
imports: from coremltools.converters.mil import testing_reqs
  from coremltools.converters.mil.testing_reqs import *
  from .testing_utils import run_compare_builder
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(use_cpu_only, backend, rank, size, alpha, beta, k) and returns: mb