load_tf.py

import tensorflow as tf


### Save the graph g1
g1 = tf.Graph()
with g1.as_default():
    a = tf.placeholder(tf.float32, name='a')
    b = tf.Variable(initial_value=tf.truncated_normal((1,)), name='b')
    c = tf.multiply(a, b, name='c')

    s1 = tf.train.Saver()

with tf.compat.v1.Session(graph=g1) as sess:
    sess.run(tf.global_variables_initializer())
    s1.save(sess, 'g1')



### Load the graph g2 and manipulate it
g2 = tf.Graph()
with g2.as_default():
    tf.compat.v1.train.import_meta_graph("g1.meta")
    c = g2.get_tensor_by_name("c:0")
    d = tf.multiply(c, c, name='d')

with tf.compat.v1.Session(graph=g2) as sess:
    d = tf.get_default_graph().get_tensor_by_name("d:0")

    sess.run(tf.global_variables_initializer())
    d = sess.run(d, feed_dict={"a:0": 32})
    print(d)