Tensorflow Fundamentals - Computation Graph Part 3

Next up, we want to now evaluate an expression from given input values. Let us construct a function (graph)

f(x,y) = x + y

where x,y are input values to fed into the graph f. To do this, we need to use tf.placeholder methods to define input nodes, and supply feed_dict parameter to run method as shown below:

	import tensorflow as tf
	import numpy as np
	# input nodes
	x = tf.placeholder(tf.int32)
	y = tf.placeholder(tf.int32)
	# operation
	f = tf.add(x, y)
	with tf.Session() as sess:
	inputs = np.random.randint(0, 10, size=(10,2))
	for _x, _y in inputs:
	print _x, '+', _y, '=', sess.run(f, feed_dict={x:_x, y:_y})

view raw tf_computation_graph_p3.py hosted with ❤ by GitHub

The code is easy enough to be self-explanatory. The output of the code shall look similar to

$ python tf_computation_graph_p3.py 2>/dev/null
8 + -6 = 2
-6 + 4 = -2
-10 + -1 = -11
-6 + 0 = -6
5 + 9 = 14
7 + 6 = 13
3 + 8 = 11
3 + 6 = 9
5 + -4 = 1
0 + -3 = -3