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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_norm(node, **kwargs):
 """Map MXNet's norm operator attributes to onnx's ReduceL1 and ReduceL2 operators and return the created node. """

    name, input_nodes, attrs = get_inputs(node, kwargs)

    mx_axis = attrs.get("axis", None)
    axes = convert_string_to_list(str(mx_axis)) if mx_axis else None

    keepdims = get_boolean_attribute_value(attrs, "keepdims")
    ord = int(attrs.get("ord", 2))

    onnx_op_name = "ReduceL1" if ord == 1 else "ReduceL2"

    if axes:
        reduce_node = onnx.helper.make_node(
            onnx_op_name,
            input_nodes,
            [name],
            axes=axes,
            keepdims=keepdims,
            name=name
        )
        return [reduce_node]
    else:
        reduce_node = onnx.helper.make_node(
            onnx_op_name,
            input_nodes,
            [name],
            keepdims=keepdims,
            name=name
        )
        return [reduce_node]