TensorFlow reuse variable with tf.layers.conv2d

Question

I am trying to make 2 conv layers share the same weights, however, it seems the API does not work.

import tensorflow as tf

x = tf.random_normal(shape=[10,          


        

Answer 1

In the code you wrote, variables do get reused between the two convolution layers. Try this :

import tensorflow as tf

x = tf.random_normal(shape=[10, 32, 32, 3])

conv1 = tf.layers.conv2d(x, 3, [2, 2], padding='SAME', reuse=None, name='conv')

conv2 = tf.layers.conv2d(x, 3, [2, 2], padding='SAME', reuse=True, name='conv')

print([x.name for x in tf.global_variables()])

# prints
# [u'conv/kernel:0', u'conv/bias:0']

Note that only one weight and one bias tensor has been created. Even though they share the weights, the layers do not share the actual computation. Hence you see the two different names for the operations.