WARNING: Do not confuse this article with "Mastering TensorFlow Tensors in 5 Easy Steps"! If you are reading this article, I am sure that we share similar interests and are/will be in similar industries. So let's connect via Linkedin! Please do not hesitate to send a contact request! In this tutorial, we will focus on TensorFlow Variables.

Then we print out the version of TensorFlow we are using. We are using TensorFlow 1.0.1. We import NumPy as np. Then we print out the version of NumPy we are using. We are using NumPy 1.13.3.

And then we print the TensorFlow version. We are using TensorFlow 1.0.1. Now, we're going to create two TensorFlow variables that will hold random numbers. We use TensorFlow Variable so that they maintain the same state across multiple calls of the session run. We're creating this TensorFlow Variable using the tf.random_uniform functionality and we're going to generate a tensor that is 2x3x4, has a minimum value of 0, a max value of 10, and the data type is tf.int32.

Lots of methods in TensorFlow create ops in the computation graph, but do not execute them. You may want to execute multiple times, but that doesn't mean you should create lots of copies of the same ops. A new initializer op is created every time the argument to session.run() This creates multiple initializer ops in the graph. Having multiple copies isn't a big deal for small ops in an interactive session, and you might even want to do it in the case of the initializer if you've created more variables that need to be included in initialization.

Lots of methods in TensorFlow create ops in the computation graph, but do not execute them. You may want to execute multiple times, but that doesn't mean you should create lots of copies of the same ops. A new initializer op is created every time the argument to session.run() This creates multiple initializer ops in the graph. Having multiple copies isn't a big deal for small ops in an interactive session, and you might even want to do it in the case of the initializer if you've created more variables that need to be included in initialization.