code: def _test_single_node(
      op_type,  # type: Text
      input_shapes,  # type: Sequence[Tuple[int, ...]]
      output_shapes,  # type: Sequence[Tuple[int, ...]]
      initializer=[],  # type: Sequence[TensorProto]
      decimal=5,  # type: int
      test_name="",  # type: Text
      onnx_coreml_input_shape_map={},  # type: Dict[Text, List[int,...]]
      coreml_input_shape={},  # type: Dict[Text, List[int,...]]
      minimum_ios_deployment_target="12",
      **kwargs,  # type: Any
  ):
      # type: (...) -> None
      model = _onnx_create_single_node_model(
          op_type, input_shapes, output_shapes, initializer, **kwargs
      )
      if not test_name:
          test_name = sys._getframe(1).f_code.co_name
      _test_onnx_model(
          model,
          test_name=test_name,
          decimal=decimal,
          onnx_coreml_input_shape_map=onnx_coreml_input_shape_map,
          coreml_input_shape=coreml_input_shape,
          minimum_ios_deployment_target=minimum_ios_deployment_target,
      )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from __future__ import unicode_literals
  import numpy
  import numpy.testing
  import numpy.random
  from onnx import helper, ModelProto, ValueInfoProto, TensorProto, NodeProto
  from typing import Any, Sequence, Text, Tuple, Optional, Dict, List, TypeVar
  from coremltools.converters.onnx import convert
  from coremltools.converters.onnx._converter import SupportedVersion
  from coremltools._deps import _IS_MACOS
  import sys
label_desc: Use image node_id 12 for calling a global function with example usage: _test_single_node(op_type, input_shapes, output_shapes, initializer, decimal, test_name, onnx_coreml_input_shape_map, coreml_input_shape, minimum_ios_deployment_target) without return types