code: def test_builder_to_backend_stress(
      self, use_cpu_only, backend, shape, upscale_factor
  ):
      val = np.random.rand(*shape)
      input_placeholders = {"x": mb.placeholder(shape=val.shape)}
      input_values = {"x": val}
  
      def build(x):
          return [mb.pixel_shuffle(x=x, upscale_factor=upscale_factor)]
  
      torch_pixel_shuffle = torch.nn.PixelShuffle(upscale_factor)
      expected_outputs = [
          torch_pixel_shuffle(torch.Tensor(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,
      )
  
imports: from coremltools.converters.mil import testing_reqs
  from coremltools.converters.mil.mil import get_new_symbol, get_new_variadic_symbol
  from coremltools.converters.mil.testing_reqs import *
  from .testing_utils import UNK_SYM, UNK_VARIADIC, run_compare_builder
label_desc: Use image node_id 2 for calling the TestPixelShuffle obj's underlying member method code with example usage: obj.test_builder_to_backend_stress(use_cpu_only, backend, shape, upscale_factor) and returns: list