code: def test_builder_to_backend_smoke(
      self,
      compute_unit,
      backend,
      InputShape_RefShapes_Begins_Ends_EndMasks,
      x_dtype,
      ref_dtype,
  ):
      (
          input_shape,
          ref_shapes,
          begins,
          ends,
          end_masks,
      ) = InputShape_RefShapes_Begins_Ends_EndMasks
      ref_shape_1, ref_shape_2 = ref_shapes
      x_builtin_dtype = numpy_type_to_builtin_type(x_dtype)
      ref_builtin_dtype = numpy_type_to_builtin_type(ref_dtype)
  
      x_val = np.random.randint(low=0, high=6, size=input_shape).astype(
          x_dtype
      )
      ref_tensor_1 = np.random.randint(
          low=0, high=6, size=ref_shape_1
      ).astype(ref_dtype)
      ref_tensor_2 = np.random.randint(
          low=0, high=6, size=ref_shape_2
      ).astype(ref_dtype)
  
      input_placeholders = {
          "x": mb.placeholder(shape=x_val.shape, dtype=x_builtin_dtype),
          "ref_tensor_1": mb.placeholder(
              shape=ref_shape_1, dtype=ref_builtin_dtype
          ),
          "ref_tensor_2": mb.placeholder(
              shape=ref_shape_2, dtype=ref_builtin_dtype
          ),
      }
      input_values = {
          "x": x_val,
          "ref_tensor_1": ref_tensor_1,
          "ref_tensor_2": ref_tensor_2,
      }
  
      def build(x, ref_tensor_1, ref_tensor_2):
          return mb.reshape_like(
              x=x,
              ref_tensors=(ref_tensor_1, ref_tensor_2),
              begins=begins,
              ends=ends,
              end_masks=end_masks,
          )
  
      output_shape = ()
      for ref_shape, begin, end, end_mask in zip(
          (ref_shape_1, ref_shape_2), begins, ends, end_masks
      ):
          if end_mask:
              output_shape += tuple(ref_shape[begin:])
          else:
              output_shape += tuple(ref_shape[begin:end])
  
      expected_output_types = [output_shape + (x_builtin_dtype,)]
      expected_outputs = [
          np.reshape(x_val, output_shape).astype(x_dtype)
      ]
  
      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 1 for calling the TestReshapeLike obj's underlying member method code with example usage: obj.test_builder_to_backend_smoke(compute_unit, backend, InputShape_RefShapes_Begins_Ends_EndMasks, x_dtype, ref_dtype) and returns: mb