title: Tensor Flow all predictions are 0
body: <p>I'm running the following code for TensorFlow and all the probabilities are <code>NaN</code> and all the predictions are <code>0</code>. The accuracy works, however. I have no idea how to debug this. Any and all help is appreciated.</p>
  
  <pre><code>x = tf.placeholder("float", shape=[None, 22])
  W = tf.Variable(tf.zeros([22, 5]))
  
  y = tf.nn.softmax(tf.matmul(x, W))
  y_ = tf.placeholder(tf.float32, [None, 5])
  
  cross_entropy = tf.reduce_mean(-tf.reduce_sum(y_ * tf.log(y), reduction_indices=[1]))
  #cross_entropy = -tf.reduce_sum(tf_softmax_correct*tf.log(tf_softmax  + 1e-50))
  train_step = tf.train.GradientDescentOptimizer(0.5).minimize(cross_entropy)
  init = tf.initialize_all_variables()
  
  sess = tf.Session()
  sess.run(init)
  
  for i in range(100):
      batch_xs, batch_ys = random.sample(allTrainingArray,100), random.sample(allTrainingSkillsArray,100)
      sess.run(train_step, feed_dict={x: batch_xs, y_: batch_ys})
  
  #test on itself
  correct_prediction = tf.equal(tf.argmax(y,1), tf.argmax(y_,1))
  accuracy = tf.reduce_mean(tf.cast(correct_prediction, "float"))
  print "accuracy", sess.run(accuracy, feed_dict={x: batch_xs, y_: batch_ys})
  
  probabilities = y
  print "probabilities", probabilities.eval(feed_dict={x: allTrainingArray}, session=sess)
  
  prediction=tf.argmax(y,1)
  print "predictions", prediction.eval(feed_dict={x: allTrainingArray}, session = sess)
  </code></pre>