Tensorflow Copy Weights Issue

Question

I am using Tensorflow 0.8 to train the Deep Neural Networks. Currently, I encounter an issue that I want to define two exact same Neural Networks N1 and N2, and I train N1, during the training loop, I copy updated weights from N1 to N2 every 4 iterations. In fact, I know there is way using tf.train.saver.save() to save all N1 weights into a .ckpt file on Disk, and using tf.train.saver.restore() to load those weights from .ckpt file, which is equivalent to the copy functionality. However, this load/reload will impact the training speed, and I wonder if there are other more efficient ways to do the copy (For example, do in-memory copy, etc.). Thanks!

Answer 1

If you could have your code/ more detail here that would be beneficial. However, you can return the session you're using to train N1 and access it while you want to train N2.