During execution, we may need to maintain the state of the ops. We can do so by using tf.Variable(). Let's check out an example declaration of tf.Variable():

This line will create a variable called counter and initialize it to scalar value 0.

    state = tf.Variable(0, name="counter") 

Here are the ops to assign a value to the variable:

    one = tf.constant(1) 
    update = tf.assign(state, one) 

If you are working with variables, we have to initialize them all at once using the following function:

    init_op = tf.initialize_all_variables() 

After initialization, we have to run the graph for putting this into effect. We can run the previous ops using the following code:

    sess = tf.Session() 
    sess.run(init_op) 
    print(sess.run(state)) 
    sess.run(update)