import tensorflow as tf

my_local = tf.get_variable("my_local", shape=(), collections=[tf.GraphKeys.LOCAL_VARIABLES],
                           initializer=tf.constant_initializer(1.0))
my_global = tf.get_variable("my_global", shape=(),
                            initializer=tf.constant_initializer(2.0))

target_value = tf.constant(4.0)
loss = tf.abs(my_local + my_global - target_value)
optim = tf.train.AdamOptimizer(learning_rate=1.0).minimize(loss)

for v in tf.trainable_variables():
    print(v.name)

with tf.Session() as sess:
    sess.run(tf.global_variables_initializer())
    sess.run(tf.local_variables_initializer())
    print("local init: ", sess.run(my_local))
    print("global init: ", sess.run(my_global))
    for i in range(2):
        _, l = sess.run([optim, loss])
        print("loss {:.4f}".format(l))
        print("local: ", sess.run(my_local))
        print("global: ", sess.run(my_global))

my_local:0
my_global:0
local init:  1.0
global init:  2.0
loss 1.0000
local:  1.9999996
global:  2.9999995
loss 1.0000
local:  1.9473683
global:  2.9473681