Hi ptrblck,
I really appreciate that you have been helping me with this.  I have been trying to confirm as much as I can, although the holiday has been eating my time thankfully. 
I used the following code to try and prove that the weights are being reloaded on a restart.
        f = open('./data/weights.txt', 'w')
        for x in model.parameters():
            f.write(str(x.data))
        f.close()

I run this code at the end of each epoch and after loading the model.
I have managed to confirm that the model is setting the weights on load.  That said, the loss still goes back to basically the starting values.  I am struggling to interpret this behavior. I am left with the following questions:

Is there a reasonable explanation for this behavior?
Is this a function of the loss measure?

Given that this is an unsupervised process, I cannot tell if the model is trained enough.  I would assume that I would run it until the loss flatlines, but I cannot run this on my laptop that long, which is why I am focus on the restart function.
Any advice would be appreciated.