code: def test_builder_to_backend_smoke(self, compute_unit, backend):
      if backend.backend == "mlprogram":
          pytest.xfail(
              "Seg fault: rdar://78343191 ((MIL GPU) Core ML Tools Unit Test failures [failure to load or Seg fault])"
          )
  
      if (
          backend.backend == "neuralnetwork"
          and compute_unit == ct.ComputeUnit.CPU_ONLY
      ):
          pytest.xfail(
              "rdar://85318710 (Coremltools Smoke test on ResizeBilinear failing on NNv1 backend.)"
          )
  
      x = np.array([0, 1], dtype=np.float32).reshape(1, 1, 2)
      input_placeholder_dict = {"x": mb.placeholder(shape=x.shape)}
      input_value_dict = {"x": x}
  
      def build_mode_0(x):
          return mb.resize_bilinear(
              x=x,
              target_size_height=1,
              target_size_width=5,
              sampling_mode="STRICT_ALIGN_CORNERS",
          )
  
      expected_output_type = (1, 1, 5, types.fp32)
      expected_output = np.array(
          [0, 0.25, 0.5, 0.75, 1], dtype=np.float32
      ).reshape(1, 1, 5)
  
      run_compare_builder(
          build_mode_0,
          input_placeholder_dict,
          input_value_dict,
          expected_output_type,
          expected_output,
          compute_unit=compute_unit,
          backend=backend,
      )
  
      def build_mode_2(x):
          return mb.resize_bilinear(
              x=x,
              target_size_height=1,
              target_size_width=5,
              sampling_mode="DEFAULT",
          )
  
      expected_output = np.array(
          [0, 0.4, 0.8, 1, 1], dtype=np.float32
      ).reshape(1, 1, 5)
  
      run_compare_builder(
          build_mode_2,
          input_placeholder_dict,
          input_value_dict,
          expected_output_type,
          expected_output,
          compute_unit=compute_unit,
          backend=backend,
      )
  
      def build_mode_3(x):
          return mb.resize_bilinear(
              x=x,
              target_size_height=1,
              target_size_width=5,
              sampling_mode="OFFSET_CORNERS",
          )
  
      expected_output = np.array(
          [0.1, 0.3, 0.5, 0.7, 0.9], dtype=np.float32
      ).reshape(1, 1, 5)
  
      run_compare_builder(
          build_mode_3,
          input_placeholder_dict,
          input_value_dict,
          expected_output_type,
          expected_output,
          compute_unit=compute_unit,
          backend=backend,
      )
  
imports: import functools
  import itertools
  import numpy
  import pytest
  import coremltools
  from coremltools._deps import _HAS_TORCH, MSG_TORCH_NOT_FOUND
  from coremltools.converters.mil.mil import Builder
  from coremltools.converters.mil.mil import get_new_symbol, types
  from coremltools.converters.mil.mil.ops.tests.iOS14 import backends
  from coremltools.converters.mil.mil.ops.tests.testing_utils import mark_api_breaking, 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 1 for calling the TestResizeBilinear obj's underlying member method code with example usage: obj.test_builder_to_backend_smoke(compute_unit, backend) and returns: mb, mb, mb