From a4b9b0a0e28f490a324aa93678ae2f7b10c5a4fc Mon Sep 17 00:00:00 2001 From: kpe Date: Fri, 24 May 2019 18:16:57 +0200 Subject: [PATCH] minor README update --- tests/ext/modeling.py | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) diff --git a/tests/ext/modeling.py b/tests/ext/modeling.py index f0d1efb..b4844cc 100644 --- a/tests/ext/modeling.py +++ b/tests/ext/modeling.py @@ -368,8 +368,9 @@ def layer_norm(input_tensor, name=None): epsilon = 1e-12 input_shape = input_tensor.shape - gamma = tf.compat.v1.get_variable(name="gamma", shape=input_shape[-1:], initializer=tf.compat.v1.initializers.ones(), trainable=True) - beta = tf.compat.v1.get_variable(name="beta", shape=input_shape[-1:], initializer=tf.compat.v1.initializers.zeros(), trainable=True) + with tf.compat.v1.variable_scope("LayerNorm"): + gamma = tf.compat.v1.get_variable(name="gamma", shape=input_shape[-1:], initializer=tf.compat.v1.initializers.ones(), trainable=True) + beta = tf.compat.v1.get_variable(name="beta", shape=input_shape[-1:], initializer=tf.compat.v1.initializers.zeros(), trainable=True) x = input_tensor if tf.__version__.startswith("2."):