tensorflow-getting-started.py

import tensorflow as tf

a = tf.constant(1)
b = tf.constant(2)
c = a + b
with tf.Session() as session:
    result = session.run(c)
    print("Tensorflow supports simple summation with op: 'a + b = {}'".format(result))
    # Tensorflow supports simple summation with op: a + b = 3

# Alternatively, since in practice we are just building a graph,
# we can explicitely declare to tensorflow how nodes are connected:

d = tf.add(a, b)
with tf.Session() as session:
    result = session.run(d)
    print("Tensorflow also supports simple summation via op: 'tf.add(a, b) = {}'".format(result))
    # Tensorflow also supports simple summation via op: tf.add(a, b) = 3

# If you are confused by the
#       with tf.Session() as session:
# statement, then do not worry, it is just a more concise manner to open and close automatically a session:
session = tf.Session()
result = session.run(d)
print("Run again the same computation graph: 'tf.add(a, b) = {}'".format(result))
# Run again the same computation graph: tf.add(a, b) = 3
session.close()