How to do it...

We proceed with the recipe as follows:

1. We consider a simple example of adding two vectors, we have two inputs vectors v_1 and v_2 they are to be fed as input to the Add operation. The graph we want to build is as follows:

1. The corresponding code to define the computation graph is as follows:

v_1 = tf.constant([1,2,3,4]) 
v_2 = tf.constant([2,1,5,3]) 
v_add = tf.add(v_1,v_2)  # You can also write v_1 + v_2 instead 

1. Next, we execute the graph in the session:

with tf.Session() as sess: 
    prin(sess.run(v_add)) 

The above two commands are equivalent to the following code. The advantage of using with block is that one need not close the session explicitly.

sess = tf.Session() 
print(ses.run(tv_add)) 
sess.close() 

1. This results in printing the sum of two vectors:

[3 3 8 7] 

Remember that each Session needs to be explicitly closed using the close() method, with block implicitly closes the session when it ends.