restore Tensorflow model without extracting from directory

I'm currently saving and restoring neural network models using Tensorflow's Saver class, as shown below:

saver.save(sess, checkpoint_prefix, global_step=step)

saver.restore(sess, checkpoint_file)

This saves .ckpt files of the model to a specified path. Because I am running multiple experiments, I have limited space to save these models.

I would like to know if there is a way to save these models without saving content in specified directories.

Ex. can I just pass some object at the last checkpoint to some evaluate() function and restore the model from that object?

So far as I see, the save_path parameter in tf.train.Saver.restore() is not optional.

Any insight would be much appreciated.

Thanks

from restore Tensorflow model without extracting from directory