I have been using the introductory example of matrix multiplication in TensorFlow.
matrix1 = tf.constant([[3., 3.]])
matrix2 = tf.constant([[2.],[2.]])
produ
Reiterating what others said, its not possible to check the values without running the graph.
A simple snippet for anyone looking for an easy example to print values is as below. The code can be executed without any modification in ipython notebook
import tensorflow as tf
#define a variable to hold normal random values
normal_rv = tf.Variable( tf.truncated_normal([2,3],stddev = 0.1))
#initialize the variable
init_op = tf.initialize_all_variables()
#run the graph
with tf.Session() as sess:
sess.run(init_op) #execute init_op
#print the random values that we sample
print (sess.run(normal_rv))
Output:
[[-0.16702934 0.07173464 -0.04512421]
[-0.02265321 0.06509651 -0.01419079]]