Created
June 1, 2017 07:15
-
-
Save ageron/3fd3193cbd44b9874bcfcc45fc2d6b32 to your computer and use it in GitHub Desktop.
Batch norm variable names in TensorFlow
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
>>> import tensorflow as tf | |
>>> X = tf.placeholder(shape=[None, 5], dtype=tf.float32, name="X") | |
>>> with tf.variable_scope("layer1"): | |
... hidden1 = tf.layers.dense(X, 100, name="hidden1") | |
... bn1 = tf.layers.batch_normalization(hidden1) | |
... | |
>>> for v in tf.global_variables(): | |
... print(v.name) | |
... | |
layer1/hidden1/kernel:0 | |
layer1/hidden1/bias:0 | |
layer1/batch_normalization/beta:0 | |
layer1/batch_normalization/gamma:0 | |
layer1/batch_normalization/moving_mean:0 | |
layer1/batch_normalization/moving_variance:0 | |
>>> for v in tf.trainable_variables(): | |
... print(v.name) | |
... | |
layer1/hidden1/kernel:0 | |
layer1/hidden1/bias:0 | |
layer1/batch_normalization/beta:0 | |
layer1/batch_normalization/gamma:0 |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment