Simple run one operator and return the results.
        Args:
            outputs_info: a list of tuples, which contains the element type and
            shape of each output. First element of the tuple is the dtype, and
            the second element is the shape. More use case can be found in
            https://github.com/onnx/onnx/blob/master/onnx/backend/test/runner/__init__.py

def run_node(cls,
                 node,  # type: NodeProto
                 inputs,  # type: Any
                 device='CPU',  # type: Text
                 outputs_info=None,  # type: Optional[Sequence[Tuple[numpy.dtype, Tuple[int, ...]]]]
                 **kwargs  # type: Dict[Text, Any]
                 ):  # type: (...) -> Optional[Tuple[Any, ...]]
        '''Simple run one operator and return the results.
        Args:
            outputs_info: a list of tuples, which contains the element type and
            shape of each output. First element of the tuple is the dtype, and
            the second element is the shape. More use case can be found in
            https://github.com/onnx/onnx/blob/master/onnx/backend/test/runner/__init__.py
        '''
        # TODO Remove Optional from return type
        if 'opset_version' in kwargs:
            special_context = c_checker.CheckerContext()
            special_context.ir_version = IR_VERSION
            special_context.opset_imports = {'': kwargs['opset_version']}  # type: ignore
            onnx.checker.check_node(node, special_context)
        else:
            onnx.checker.check_node(node)
        return None