def _expand_dims(converter, node: Any, inputs: List[str]) -> Any:
    x_in = converter.outputs[inputs[0]]
    if isinstance(x_in, tf.NodeDef):
        input_out = _nodef_to_private_pond(converter, x_in)
    else:
        input_out = x_in
    input_axis = converter.outputs[inputs[1]]
    axis_attr = input_axis.attr['value'].tensor.int_val
    axis_val = array.array('i', axis_attr)[0]
    return converter.protocol.expand_dims(input_out, axis_val)
def _expand_dims(converter, node: Any, inputs: List[str]) -> Any:
    x_in = converter.outputs[inputs[0]]
    if isinstance(x_in, tf.NodeDef):
        input_out = _nodef_to_private_pond(converter, x_in)
    else:
        input_out = x_in
    input_axis = converter.outputs[inputs[1]]
    axis_attr = input_axis.attr['value'].tensor.int_val
    axis_val = array.array('i', axis_attr)[0]
    return converter.protocol.expand_dims(input_out, axis_val)