def METHOD_NAME(internal_ops: List[tf.Operation],
                                                  inner_op_types_to_quantize: List[str]) -> List[str]:
    """
    Get names of ops to insert activation quantizers for
    :param internal_ops: list of TensorFlow ops within a module
    :param inner_op_types_to_quantize: list of TensorFlow op types within recurrent module that are to be quantized
    This list is customizable per recurrent module type such as SimpleRNN, LSTM etc.
    :return: List of unique op names to insert activation quantize ops for within recurrent block
    """
    valid_tf_ops = [op for op in internal_ops if op.type in inner_op_types_to_quantize]
    # append only unique names
    op_names_to_quantize = set()
    for tf_op in valid_tf_ops:
        output_act_name = tf_op.outputs[0].op.name
        if is_op_quantizable(tf_op):
            op_names_to_quantize.add(output_act_name)
    # get inputs to recurrent MatMuls
    input_op_names = _get_input_ops_to_quantize(internal_ops)
    if input_op_names:
        op_names_to_quantize.update(input_op_names)
    return list(op_names_to_quantize)