code: def test_cond(self):
      model = TestScriptedModels.get_cond_model()
      model_spec = torch.jit.script(model)
      mlmodel = ct.convert(
          model_spec,
          inputs=[
              ct.TensorType(name="data", shape=(1,), dtype=np.float32)
          ],
          convert_to="mlprogram",
          compute_units=ComputeUnit.CPU_ONLY,
      )
      roundtrip_and_compare_mlmodel(mlmodel, {"data": np.array([1.0])})
      roundtrip_and_compare_mlmodel(mlmodel, {"data": np.array([11.0])})
  
imports: import numpy
  import pytest
  import coremltools
  from coremltools import ComputeUnit
  from coremltools._deps import _HAS_TF_2, _HAS_TORCH
  from coremltools.converters._converters_entry import _get_metadata_from_mlmodel
  from coremltools.converters.mil import Builder
  from coremltools.converters.mil.converter import mil_convert
  from coremltools.converters.mil.frontend.milproto.load import load
  from coremltools.converters.mil.frontend.tensorflow.test.test_ops import TestTensorArray
  from coremltools.converters.mil.frontend.tensorflow.test.testing_utils import run_compare_tf
  from coremltools.converters.mil.mil.ops.tests.testing_utils import compare_backend
  from coremltools.converters.mil.testing_utils import get_op_names_in_program, get_op_types_in_program
label_desc: Use image node_id 5 for calling the TestE2ENumericalCorrectness obj's underlying member method code with example usage: obj.test_cond() without return types