`create_graph_component_from_pipeline_func` converts python pipeline function to a graph component object that can be saved, shared, composed or submitted for execution.

Example:

    producer_op = load_component(component_with_0_inputs_and_2_outputs)
    processor_op = load_component(component_with_2_inputs_and_2_outputs)

    def pipeline1(pipeline_param_1: int):
        producer_task = producer_op()
        processor_task = processor_op(pipeline_param_1, producer_task.outputs['Output 2'])

        return OrderedDict([
            ('Pipeline output 1', producer_task.outputs['Output 1']),
            ('Pipeline output 2', processor_task.outputs['Output 2']),
        ])

    graph_component = create_graph_component_from_pipeline_func(pipeline1)

Non-public create_graph_component_spec_from_pipeline_func creates ComponentSpec
Public create_graph_component_from_pipeline_func creates component and writes it to file.

…gnature

Stopped humanizing the input names for now. I think it's benefitial to extract interface from function signature the same way for both container and graph python components.

Remove the component spec from component reference unless it will make the reference empty or unless explicitly asked by the user