How to do it...

1. Import tensorflow  this imports the TensorFlow library and allows you to use its wonderful features.

 import tensorflow as tf 

1. Since the message we want to print is a constant string, we use tf.constant:

message = tf.constant('Welcome to the exciting world of Deep Neural Networks!')

1. To execute the graph element, we need to define the Session using with and run the session using run:

with tf.Session() as sess:
     print(sess.run(message).decode()) 

1. The output contains a series of warning messages (W), depending on your computer system and OS, claiming that code could run faster if compiled for your specific machine:

The TensorFlow library wasn't compiled to use SSE instructions, but these are available on your machine and could speed up CPU computations. 
The TensorFlow library wasn't compiled to use SSE2 instructions, but these are available on your machine and could speed up CPU computations. 
The TensorFlow library wasn't compiled to use SSE3 instructions, but these are available on your machine and could speed up CPU computations. 
The TensorFlow library wasn't compiled to use SSE4.1 instructions, but these are available on your machine and could speed up CPU computations. 
The TensorFlow library wasn't compiled to use SSE4.2 instructions, but these are available on your machine and could speed up CPU computations. 
The TensorFlow library wasn't compiled to use AVX instructions, but these are available on your machine and could speed up CPU computations. 
The TensorFlow library wasn't compiled to use AVX2 instructions, but these are available on your machine and could speed up CPU computations. 
The TensorFlow library wasn't compiled to use FMA instructions, but these are available on your machine and could speed up CPU computations. 

1. If you are working with TensorFlow GPU, you also get a list of informative messages (I) giving details of the devices used:

Found device 0 with properties:  
name: GeForce GTX 1070 
major: 6 minor: 1 memoryClockRate (GHz) 1.683 
pciBusID 0000:01:00.0 
Total memory: 8.00GiB 
Free memory: 6.66GiB 
DMA: 0  
0:   Y  
Creating TensorFlow device (/gpu:0) -> (device: 0, name: GeForce GTX 1070, pci bus id: 0000:01:00.0) 

1. At the end is the message we asked to print in the session:

Welcome to the exciting world of Deep Neural Networks