Training broke with ResourceExausted error

Question

I am new to tensorflow and Machine Learning. Recently I am working on a model. My model is like below,

1. Character level Embedding Vector -> Embedding lookup

Answer 1

*Note *: The error occurred after 32 epoch. My question is why after 32 epoch there is an error. Why not at the initial epoch.

This is a major clue that the graph is not static during execution. By that I mean, you're likely doing sess.run(tf.something) instead of

my_something = tf.something
with tf.Session() as sess: 
    sess.run(my_something)

I ran into the same problem trying to implement a stateful RNN. I would occasionally reset the state, so I was doing sess.run([reset if some_condition else tf.no_op()]). Simply adding nothing = tf.no_op() to my graph and using sess.run([reset if some_condition else nothing]) solved my problem.

If you could post the training loop, it would be easier to tell if that is what's going wrong.