title: Failed to get the value of tensor
body: <p>When running the MNIST data set, I want to know what actually my model outputs during training the batch.Here is my code:(I haven't added the optimizer and the loss function):</p>
  
  <pre><code>import tensorflow as tf 
  from tensorflow.examples.tutorials.mnist import input_data
  
  INPUT_NODE  = 784 # the total pixels of the input images
  OUTPUT_NODE = 10  # the output varies from 0 to 9
  LAYER_NODE = 500
  BATCH_SIZE = 100
  TRAINING_STEPS = 10
  
  def inference(input_tensor, avg_class, weight1, biase1, weight2, biase2):
      if avg_class == None:
          layer = tf.nn.relu(tf.matmul(input_tensor, weight1) + biase1)
          return tf.matmul(layer, weight2)+biase2
      else:
          layer = tf.nn.relu(tf.matmul(input_tensor, avg_class.average(weight1)) + 
                  avg_class.average(biase1))
          return tf.matmul(layer, avg_class.average(weight2)) + avg_class.average(biase2)
  
  
  def train(mnist):
      x = tf.placeholder(tf.float32, [None, INPUT_NODE], name = 'x-input')
      y = tf.placeholder(tf.float32, [None, OUTPUT_NODE],name = 'y-input')
  
      weight1 = tf.Variable(tf.truncated_normal([INPUT_NODE, LAYER_NODE], stddev = 0.1))
      biase1  = tf.Variable(tf.constant(0.1, shape = [LAYER_NODE]))
      weight2 = tf.Variable(tf.truncated_normal([LAYER_NODE, OUTPUT_NODE], stddev = 0.1))
      biase2  = tf.Variable(tf.constant(0.1, shape = [OUTPUT_NODE]))
  
      out = inference(x, None, weight1, biase1, weight2, biase2)
  
      with tf.Session() as sess:
          tf.global_variables_initializer().run()
          validate_feed = {x:mnist.validation.images, y:mnist.validation.labels}
          test_feed = {x:mnist.test.images, y:mnist.test.labels}
  
          for i in range(TRAINING_STEPS):
  
              xs, ys = mnist.train.next_batch(BATCH_SIZE)
              sess.run(out, feed_dict= {x:xs, y:ys})
              print(out)
  
  def main(arg = None):
      mnist = input_data.read_data_sets("/home/vincent/Tensorflow/MNIST/data/", one_hot = True)
      train(mnist)
  
  if __name__ == '__main__':
      tf.app.run()
  </code></pre>
  
  <p>I try to print out:</p>
  
  <blockquote>
    <p>Tensor("add_1:0", shape=(?, 10), dtype=float32)</p>
  </blockquote>
  
  <p>If I want to know the value of out, what should I do?
  I tried to <code>print(out.eval())</code>, and it raised error</p>