Working with multiple graphs in TensorFlow

Question

Can someone explain to me how name_scope works in TensorFlow?

Suppose I have the following code:

Answer 1

Your problem is that you are calling the latest variable product which points to a tensor created on g2 - you overwrote it in your second scope. Just relabel all your variables and you should be good to go. The working code is below.

import tensorflow as tf

g1 = tf.Graph() with g1.as_default() as g:
    with g.name_scope( "g1" ) as scope:
        matrix11 = tf.constant([[3., 3.]])
        matrix21 = tf.constant([[2.],[2.]])
        product1 = tf.matmul(matrix11, matrix21)

tf.reset_default_graph()

g2 = tf.Graph() with g2.as_default() as g:
    with g.name_scope( "g2" ) as scope:
        matrix12 = tf.constant([[4., 4.]])
        matrix22 = tf.constant([[5.],[5.]])
        product2 = tf.matmul(matrix12, matrix22)

tf.reset_default_graph()

with tf.Session( graph = g1 ) as sess:
    result = sess.run( product1 )
    print( result )