CODEWITHSUNDEEP
tensorflow
Kasia
Kasia

Reputation: 1

Tensorflow subtract strange result

Can someone explain the weird results I get from this trivial code? Am I doing sth wrong? Why input params a_C and a_G change? What has the difference result to do with the passed values?

#-----------------------------

def dummy_function(a_C, a_G):

  diff = tf.subtract(a_C, a_G)    
  sqr = tf.square(diff)

  return a_C, a_G, diff, sqr

#-----------------------------

tf.reset_default_graph()

with tf.Session() as test:

  tf.set_random_seed(1)

  a_C = tf.random_normal([1], mean=1, stddev=4)    
  a_G = tf.random_normal([1], mean=1, stddev=4)    
  a_C_returned, a_G_returned, diff, sqr = dummy_function(a_C, a_G)

  print("a_C = " + str(a_C.eval()))    
  print("a_G = " + str(a_G.eval()))    
  print("a_C_returned = " + str(a_C_returned.eval()))    
  print("a_G_returned = " + str(a_G_returned.eval()))    
  print("diff = " + str(diff.eval()))    
  print("sqr = " + str(sqr.eval()))

#-----------------------------    
# results

a_C = [-1.68344498]    
a_G = [-0.39043474]    
a_C_returned = [ 4.70364952]
a_G_returned = [ 0.84769011]
diff = [-9.30598831]
sqr = [ 25.68828583]

Thank's in advance for any help, Best regards, Kasia

Upvotes: 0

Views: 103

Answers (1)

Patwie
Patwie

Reputation: 4450

Your a_C is not the resulting tensor of tf.random_normal!. It is the operation to get random numbers in each eval. That's the best demonstration for never using .eval().

Instead, you need to evaluate these tensors within one run like

import tensorflow as tf

def dummy_function(a_C, a_G):

  diff = tf.subtract(a_C, a_G)
  sqr = tf.square(diff)

  return a_C, a_G, diff, sqr

with tf.Session() as sess:

  tf.set_random_seed(1)

  a_C = tf.random_normal([1], mean=1, stddev=4)
  a_G = tf.random_normal([1], mean=1, stddev=4)
  a_C_returned, a_G_returned, diff, sqr = dummy_function(a_C, a_G)

  a_C_, a_G_, a_C_returned_, a_G_returned_, diff_, sqr_ = sess.run([a_C, a_G, a_C_returned, a_G_returned, diff, sqr])

  print("a_C = " + str(a_C_))
  print("a_G = " + str(a_G_))
  print("a_C_returned = " + str(a_C_returned_))
  print("a_G_returned = " + str(a_G_returned_))
  print("diff = " + str(diff_))
  print("sqr = " + str(sqr_))

This guarantees that all returned results are based on the same entry nodes (ie. a_C, a_g)

Upvotes: 2

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