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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_square(node, **kwargs):
 """Map MXNet's square operator attributes to onnx's Pow operator and return the created node. """

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

    initializer = kwargs["initializer"]
    data_type = onnx.mapping.NP_TYPE_TO_TENSOR_TYPE[np.dtype('int64')]

    power2_name = "square_tensor" + str(kwargs["idx"])
    tensor_node = onnx.helper.make_tensor_value_info(power2_name, data_type, (1,))
    initializer.append(
        onnx.helper.make_tensor(
            name=power2_name,
            data_type=data_type,
            dims=(1,),
            vals=[2],
            raw=False,
        )
    )

    input_nodes.append(power2_name)

    node = onnx.helper.make_node(
        "Pow",
        input_nodes,
        [name],
        name=name
    )
    return [tensor_node, node]