How to do Xavier initialization on TensorFlow
I'm porting my Caffe network over to TensorFlow but it doesn't seem to have xavier initialization. I'm using
truncated_normal but this seems to be making it a lot harder to train.
Since version 0.8 there is a Xavier initializer, see here for the docs.
You can use something like this:
W = tf.get_variable("W", shape=[784, 256], initializer=tf.contrib.layers.xavier_initializer())