code: def test_builder_to_backend_smoke(self, compute_unit, backend):
      x_val = np.array([0.0], dtype=np.float32)
      input_placeholders = {"x": mb.placeholder(shape=x_val.shape)}
      input_values = {"x": x_val}
  
      def build(x):
          return [
              mb.add(x=x, y=x),
              mb.random_bernoulli(
                  shape=np.array([2, 1, 3], np.int32), prob=1.0
              ),
              mb.random_bernoulli(
                  shape=np.array([3, 1, 2], np.int32), prob=0.0
              ),
          ]
  
      expected_outputs = [
          np.array(np.zeros(shape=(1,)), np.float32),
          np.array(np.ones(shape=(2, 1, 3)), np.float32),
          np.array(np.zeros(shape=(3, 1, 2)), np.float32),
      ]
  
      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=expected_outputs,
          compute_unit=compute_unit,
          backend=backend,
      )
  
imports: import itertools
  import numpy
  import pytest
  from coremltools.converters.mil.mil import Builder
  from coremltools.converters.mil.mil import types
  from coremltools.converters.mil.mil.ops.tests.iOS14 import backends
  from coremltools.converters.mil.mil.ops.tests.testing_utils import UNK_SYM, run_compare_builder
  from coremltools.converters.mil.testing_reqs import compute_units
  from coremltools.converters.mil.testing_utils import get_core_ml_prediction
  from coremltools.models.utils import _macos_version
label_desc: Use image node_id 1 for calling the TestRandomBernoulli obj's underlying member method code with example usage: obj.test_builder_to_backend_smoke(compute_unit, backend) and returns: list