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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 _add_sync_queues_and_barrier(self, name, dependencies):
 """Adds ops to enqueue on all worker queues. Args: name: prefixed for the shared_name of ops. dependencies: control dependency from ops. Returns: an op that should be used as control dependency before starting next step. """

        self._sync_queue_counter += 1
        with tf.device(self.sync_queue_devices[self._sync_queue_counter % len(self.sync_queue_devices)]):
            sync_queues = [
                tf.FIFOQueue(self.num_worker, [tf.bool], shapes=[[]],
                             shared_name='%s%s' % (name, i))
                for i in range(self.num_worker)]
            queue_ops = []
            # For each other worker, add an entry in a queue, signaling that it can finish this step.
            token = tf.constant(False)
            with tf.control_dependencies(dependencies):
                for i, q in enumerate(sync_queues):
                    if i != self.task_index:
                        queue_ops.append(q.enqueue(token))

            # Drain tokens off queue for this worker, one for each other worker.
            queue_ops.append(
                sync_queues[self.task_index].dequeue_many(len(sync_queues) - 1))

            return tf.group(*queue_ops, name=name)