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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_random_uniform(node, **kwargs):
 """Map MXNet's random_uniform operator attributes to onnx's RandomUniform operator and return the created node. """

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

    # Converting to float32
    low = float(attrs.get("low", 0))
    high = float(attrs.get("high", 1.0))
    shape = convert_string_to_list(attrs.get('shape', '[]'))
    dtype = onnx.mapping.NP_TYPE_TO_TENSOR_TYPE[np.dtype(attrs.get('dtype', 'float32'))]

    node = onnx.helper.make_node(
        'RandomUniform',
        input_nodes,
        [name],
        low=low,
        high=high,
        dtype=dtype,
        shape=shape,
        name=name
    )
    return [node]