TF1_1/tf_2_manual.py

import tensorflow as tf

node1 = tf.constant(3.0, tf.float32)
node2 = tf.constant(4.0)  # also tf.float32 implicitly
node3 = tf.add(node1, node2)

sess = tf.Session()
print("node3: ", node3)
print("sess.run(node3): ", sess.run(node3))

a = tf.placeholder(tf.float32)
b = tf.placeholder(tf.float32)
adder_node = a + b  # + provides a shortcut for tf.add(a, b)

print(sess.run(adder_node, {a: 3, b: 4.5}))
print(sess.run(adder_node, {a: [1, 3], b: [2, 4]}))

W = tf.Variable([.3], tf.float32)
b = tf.Variable([-.3], tf.float32)
x = tf.placeholder(tf.float32)
linear_model = W * x + b

init = tf.global_variables_initializer()
sess.run(init)

print(sess.run(linear_model, {x: [1, 2, 3, 4]}))

fixW = tf.assign(W, [-1.])
fixb = tf.assign(b, [1.])
sess.run([fixW, fixb])
print(sess.run(linear_model, {x: [1, 2, 3, 4]}))