code: def test_pass_unsupported_option(self):
      model = self._get_test_model()
      example_input = torch.rand(1, 1, 28, 28)
      traced_model = torch.jit.trace(model, example_input)
  
      pipeline = ct.PassPipeline()
      pipeline.set_options(
          "common::fuse_conv_batchnorm",
          {"skip_ops_by_type": "conv,linear"},
      )
      with pytest.raises(
          NotImplementedError,
          match="The graph pass `fuse_conv_batchnorm` doesn't support option `skip_ops_by_type`.",
      ):
          ct.convert(
              traced_model,
              inputs=[ct.TensorType(shape=example_input.shape)],
              convert_to="mlprogram",
              pass_pipeline=pipeline,
          )
  
imports: import copy
  import os
  import tempfile
  import numpy
  import pytest
  import coremltools
  from coremltools._deps import _HAS_TORCH
  from coremltools.converters.mil import Builder
  from coremltools.converters.mil.mil import Function, Program, get_new_symbol
  from coremltools.converters.mil.testing_utils import get_op_types_in_program
label_desc: Use image node_id 9 for calling the TestGraphPassManagement obj's underlying member method code with example usage: obj.test_pass_unsupported_option() without return types