code: def test_builder_to_backend_stress(
      self,
      use_cpu_only,
      backend,
      input_shape,
      scale_factor,
      align_corners,
  ):
      def _get_torch_upsample_prediction(
          x, scale_factor=(2, 2), align_corners=False
      ):
          x = torch.from_numpy(x)
          m = torch.nn.Upsample(
              scale_factor=scale_factor,
              mode="bilinear",
              align_corners=align_corners,
          )
          out = m(x)
          return out.numpy()
  
      x = random_gen(input_shape, rand_min=-100, rand_max=100)
      torch_pred = _get_torch_upsample_prediction(
          x, scale_factor=scale_factor, align_corners=align_corners
      )
  
      input_placeholder_dict = {"x": mb.placeholder(shape=x.shape)}
      input_value_dict = {"x": x}
  
      def build_upsample(x):
          return mb.upsample_bilinear(
              x=x,
              scale_factor_height=scale_factor[0],
              scale_factor_width=scale_factor[1],
              align_corners=align_corners,
          )
  
      expected_output_type = torch_pred.shape + (types.fp32,)
      run_compare_builder(
          build_upsample,
          input_placeholder_dict,
          input_value_dict,
          expected_output_type,
          torch_pred,
          use_cpu_only=use_cpu_only,
          frontend_only=False,
          backend=backend,
      )
  
file_path: turicreate/src/external/coremltools_wrap/coremltools/coremltools/converters/mil/mil/ops/tests/test_image_resizing.py
imports: from coremltools.converters.mil import testing_reqs
  from coremltools.converters.mil.mil import get_new_symbol
  from coremltools.converters.mil.testing_reqs import *
  from .testing_utils import run_compare_builder
label_desc: Use image node_id 2 for calling the TestUpsampleBilinear obj's underlying member method code with example usage: obj.test_builder_to_backend_stress(use_cpu_only, backend, input_shape, scale_factor, align_corners) and returns: out, mb