code: def test_builder_to_backend_smoke(self, use_cpu_only, backend):
      t = np.array([[1, 2, 3], [4, 5, 6]], dtype=np.float32)
      input_placeholders = {"x": mb.placeholder(shape=t.shape)}
      input_values = {"x": t}
  
      def build(x):
          return [
              mb.expand_dims(x=x, axes=[0]),
              mb.expand_dims(x=x, axes=[1]),
              mb.expand_dims(x=x, axes=[2]),
              mb.expand_dims(x=x, axes=[-1]),
              mb.expand_dims(x=x, axes=[0, 1]),
              mb.expand_dims(x=x, axes=[-2, -1]),
          ]
  
      expected_output_types = [
          (1, 2, 3, types.fp32),
          (2, 1, 3, types.fp32),
          (2, 3, 1, types.fp32),
          (2, 3, 1, types.fp32),
          (1, 1, 2, 3, types.fp32),
          (2, 3, 1, 1, types.fp32),
      ]
      expected_outputs = [
          np.array([[[1, 2, 3], [4, 5, 6]]], dtype=np.float32),
          np.array([[[1, 2, 3]], [[4, 5, 6]]], dtype=np.float32),
          np.array(
              [[[1], [2], [3]], [[4], [5], [6]]], dtype=np.float32
          ),
          np.array(
              [[[1], [2], [3]], [[4], [5], [6]]], dtype=np.float32
          ),
          np.array([[[[1, 2, 3], [4, 5, 6]]]], dtype=np.float32),
          np.array(
              [[[[1]], [[2]], [[3]]], [[[4]], [[5]], [[6]]]],
              dtype=np.float32,
          ),
      ]
  
      run_compare_builder(
          build,
          input_placeholders,
          input_values,
          expected_output_types,
          expected_outputs,
          use_cpu_only=use_cpu_only,
          frontend_only=False,
          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 1 for calling the TestExpandDims obj's underlying member method code with example usage: obj.test_builder_to_backend_smoke(use_cpu_only, backend) and returns: list