TensorFlow 1.x Deep Learning Cookbook

How to do it...

We proceed with the recipe as follows:

1. We start an interactive session so that the results can be evaluated easily:

import tensorflow as tf#Start an Interactive Sessionsess = tf.InteractiveSession()#Define a 5x5 Identity matrixI_matrix = tf.eye(5)print(I_matrix.eval()) # This will print a 5x5 Identity matrix#Define a Variable initialized to a 10x10 identity matrixX = tf.Variable(tf.eye(10))X.initializer.run()  # Initialize the Variableprint(X.eval()) # Evaluate the Variable and print the result#Create a random 5x10 matrixA = tf.Variable(tf.random_normal([5,10]))A.initializer.run()#Multiply two matricesproduct = tf.matmul(A, X)print(product.eval())#create a random matrix of 1s and 0s, size 5x10b = tf.Variable(tf.random_uniform([5,10], ...