I am working on an experimental approach to text classification for which I need to use pure Tensorflow (no Keras). As I am implementing Leave-One-Out CV, I need to reset (or reinitialize, call it as you wish) all of my trainable variables in one session - after model learns for several epochs and predicts my test observation it goes to another test observation, however, it should train completely from scratch (without the knowledge received from current test observation which previously used also in learning).
I have done some comprehensive online research, but I did not find anything helpful. Is there any method for that or do you have any suggestions how to modify my algorithm?
Thanks in advance.