In this recipe, we will learn how to put multiple operations on the same computational graph.
It's important to know how to chain operations together. This will set up layered operations in the computational graph. For a demonstration we will multiply a placeholder by two matrices and then perform addition. We will feed in two matrices in the form of a three-dimensional
import tensorflow as tf sess = tf.Session()
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 3x5. We will multiply each matrix by a constant of size 5x1, which will result in a matrix of size 3x1. We will then multiply this by 1x1 matrix resulting ...