import tensorflow as tf

matrix1 = tf.constant([[3, 3]])
matrix2 = tf.constant([[2],[2]])
product = tf.matmul(matrix1, matrix2)  # matrix multiply np.dot(m1, m2)

# method 1
sess = tf.Session()
result = sess.run(product)
print(result)
sess.close()

# method 2
with tf.Session() as sess:
  result2 = sess.run(product)
  print(result2)

import tensorflow as tf

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

one = tf.constant(1)

new_value = tf.add(state, one)
update = tf.assign(state, new_value)

# tf.initialize_all_variables() no long valid from
# 2017-03-02 if using tensorflow >= 0.12
if int((tf.__version__).split('.')[1]) < 12 and int((tf.__version__).split('.')[0]) < 1:
  init = tf.initialize_all_variables()
else:
  init = tf.global_variables_initializer()

with tf.Session() as sess:
  sess.run(init)
  for _ in range(3):
    sess.run(update)
    print(sess.run(state))

import tensorflow as tf

input1 = tf.placeholder(tf.float32)
input2 = tf.placeholder(tf.float32)
output = tf.multiply(input1, input2)

with tf.Session() as sess:
  print(sess.run(output, feed_dict={input1: [7.], input2: [2.]}))