seed=1, TensorFlor- Xavier_initializer
It's to define the random seed. By this means, the weight values are always initialized by the same values.
From Wiki: A random seed is a number (or vector) used to initialize a pseudo-random number generator.
What does seed=1 is doing in the following code:
W3 = tf.get_variable("W3", [L3, L2], initializer = tf.contrib.layers.xavier_initializer(seed=1))