# Understand TensorFLow Global Variables and Local Variables – TensorFlow Tutorial

By | August 26, 2021

In this tutorial, we will introduce the difference between global variables and local variables in tensorflow. You can learn how to use them correctly.

## TensorFlow Global Variables

TensorFlow global variables are shared across machines in a distributed environment. We can use tf.Variable() and tf.get_variable() to create a global variable.

In order to list all global variables, we can do as follows:

print([x for x in tf.global_variables()])

In order to initialize global variables, we can use sess.run(tf.global_variables_initializer()). Here is the tutorial:

An Explain to sess.run(tf.global_variables_initializer()) for Beginners – TensorFlow Tutorial

## TensorFlow Local Variables

TensorFlow local variables only can be used in local environment, they are not shared in a distributed environment. We can use tf.local_variable() to create a local variable.

In order to list all local variables, we can do as follows:

print([x for x in tf.local_variables()])

To initialize local varaibles, we can do:

with tf.Session() as sess:
sess.run(tf.local_variables_initializer())