Does the tide convolution being performed correctly?

[LDHo]

According to my understanding on the paper, in order for both images to be able to perform cross input neighborhood differences, the first two convolution layers must be tied in which their trained filters must be shared for two input images. Can I know whether the tide convolution is performed correctly as from my understanding, your codes are using totally different filters for both images.

[stickOverCarrot]

@LDHo
I think we can replace
[conv2_1 = tf.layers.conv2d(images2, 20, [5, 5], activation=tf.nn.relu,
kernel_regularizer=tf.contrib.layers.l2_regularizer(weight_decay), name='conv2_1')]
with
[ conv2_1 = tf.layers.conv2d(images2, 20, [5, 5], activation=tf.nn.relu, kernel_regularizer=tf.contrib.layers.l2_regularizer(weight_decay), name='conv1_1',reuse=True)].
Other conv layers can share weight and bias by this way.
In fact,we can try the both approaches and then compare the results to judge which is better!