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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def convert_multinomial(node, **kwargs):
 """Map MXNet's multinomial operator attributes to onnx's Multinomial operator and return the created node. """

    name, input_nodes, attrs = get_inputs(node, kwargs)
    dtype = onnx.mapping.NP_TYPE_TO_TENSOR_TYPE[np.dtype(attrs.get("dtype", 'int32'))]
    sample_size = convert_string_to_list(attrs.get("shape", '1'))
    if len(sample_size) < 2:
        sample_size = sample_size[-1]
    else:
        raise AttributeError("ONNX currently supports integer sample_size only")
    node = onnx.helper.make_node(
        "Multinomial",
        input_nodes,
        [name],
        dtype=dtype,
        sample_size=sample_size,
        name=name,
    )
    return [node]