TensorFlow Machine Learning Cookbook - Second Edition

How to do it...

It is also important to note how the data will change shape as it passes through. We will feed in two NumPy arrays of size 3 x 5. We will multiply each matrix by a constant of size 5 x 1, which will result in a matrix of size 3 x 1. We will then multiply this by a 1 x 1 matrix resulting in a 3 x 1 matrix again. Finally, we add a 3 x 1 matrix at the end, as follows:

1. First, we create the data to feed in and the corresponding placeholder:

my_array = np.array([[1., 3., 5., 7., 9.], 
                   [-2., 0., 2., 4., 6.], 
                   [-6., -3., 0., 3., 6.]]) 
x_vals = np.array([my_array, my_array + 1]) 
x_data = tf.placeholder(tf.float32, shape=(3, 5)) 

2. Next, we create the constants that we will use for matrix multiplication and addition:

m1 = tf.constant([[1.], ...