code: def test_builder_to_backend_stress(
      self,
      compute_unit,
      backend,
      shape,
      downscale_factor,
  ):
      val = np.random.rand(*shape)
      input_placeholders = {"x": mb.placeholder(shape=val.shape)}
      input_values = {"x": val}
  
      def build(x):
          return [
              mb.pixel_unshuffle(
                  x=x, downscale_factor=np.uint32(downscale_factor)
              )
          ]
  
      torch_pixel_unshuffle = torch.nn.PixelUnshuffle(downscale_factor)
      expected_outputs = [
          torch_pixel_unshuffle(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,
          compute_unit=compute_unit,
          backend=backend,
      )
  
file_path: coremltools/coremltools/converters/mil/mil/ops/tests/iOS16/test_tensor_transformation.py
imports: import itertools
  import numpy
  import pytest
  from coremltools._deps import _HAS_TORCH, MSG_TORCH_NOT_FOUND
  from coremltools.converters.mil import testing_reqs
  from coremltools.converters.mil.mil import Builder
  from coremltools.converters.mil.mil import types
  from coremltools.converters.mil.mil.ops.tests.iOS16 import backends
  from coremltools.converters.mil.mil.ops.tests.testing_utils import run_compare_builder
  from coremltools.converters.mil.mil.types.type_mapping import numpy_type_to_builtin_type
label_desc: Use image node_id 2 for calling the TestPixelUnshuffle obj's underlying member method code with example usage: obj.test_builder_to_backend_stress(compute_unit, backend, shape, downscale_factor) and returns: list