The standard way of initializing variables in TensorFlow is
init = tf.initialize_all_variables()
sess = tf.Session()
There is no elegant* way to enumerate the uninitialized variables in a graph. However, if you have access to the new variable objects—let's call them
v_8—you can selectively initialize them using
init_new_vars_op = tf.initialize_variables([v_6, v_7, v_8]) sess.run(init_new_vars_op)
* A process of trial and error could be used to identify the uninitialized variables, as follows:
uninitialized_vars =  for var in tf.all_variables(): try: sess.run(var) except tf.errors.FailedPreconditionError: uninitialized_vars.append(var) init_new_vars_op = tf.initialize_variables(uninitialized_vars) # ...
...however, I would not condone such behavior :-).