Tensorflow session and graph context

Question

My question is about context and the TensorFlow default sessions and graph.

The problem: Tensorflow is unable to feed a placeholder in the following scenario: Function Test defines a graph. Function Test_Once defines a session. When Function Test calls Test_Once -> Feeding fails. When I change the code so function Test declares the graph + the session -> all is working.

Here is the code:

def test_once(g, saver, summary_writer, logits, images, summary_op):
  """Run a session once for a givven test image.

  Args:
    saver: Saver.
    summary_writer: Summary writer.
    logits: 
    summary_op: Summary op.
  """
  with tf.Session(graph=g) as sess:
    ckpt = tf.train.get_checkpoint_state(FLAGS.checkpoint_dir)
    if ckpt and ckpt.model_checkpoint_path:
      # Restores from checkpoint
      saver.restore(sess, ckpt.model_checkpoint_path)

      # extract global_step from it.
      global_step = ckpt.model_checkpoint_path.split('/')[-1].split('-')[-1]
    else:
      print('No checkpoint file found')
      return

    images.astype(np.float32)

    predictions = sess.run(logits, feed_dict={'InputPlaceHolder/TestInput:0':images})

    summary = tf.Summary()
    summary.ParseFromString(sess.run(summary_op))
    summary_writer.add_summary(summary, global_step)

    return (predictions)


def test():
  """Test LCPR with a test image"""
  with tf.Graph().as_default() as g:

    # Get image for testing
    images, labels = lcpr.test_input()

    # Build a Graph that computes the logits predictions from the
    # inference model.
    with tf.name_scope('InputPlaceHolder'):

        test_image_placeholder = tf.placeholder(tf.float32, (None,None,None,3), 'TestInput')
        # Display the training images in the visualizer.
        # The 'max_outputs' default is 3. Not stated. (Max number of batch elements to generate images for.)
        #tf.summary.image('input_images', test_image_placeholder)


    with tf.name_scope('Inference'):
        logits = lcpr.inference(test_image_placeholder)


    # Restore the moving average version of the learned variables for eval.
    variable_averages = tf.train.ExponentialMovingAverage(
        lcpr.MOVING_AVERAGE_DECAY)
    variables_to_restore = variable_averages.variables_to_restore()
    saver = tf.train.Saver(variables_to_restore)

    # Build the summary operation based on the TF collection of Summaries.
    writer = tf.summary.FileWriter("/tmp/lcpr/test")
    writer.add_graph(g) 

    summary_op = tf.summary.merge_all()
    summary_writer = tf.summary.FileWriter(FLAGS.test_dir, g)

    #Sadly, this will not work:     
    predictions = test_once(g, saver, summary_writer, logits, images, summary_op)

    '''Alternative working option :  
    with tf.Session() as sess:
        ckpt = tf.train.get_checkpoint_state(FLAGS.checkpoint_dir)
        if ckpt and ckpt.model_checkpoint_path:
          # Restores from checkpoint
          saver.restore(sess, ckpt.model_checkpoint_path)
          # Assuming model_checkpoint_path looks something like:
          #   /my-favorite-path/cifar10_train/model.ckpt-0,
          # extract global_step from it.
          global_step = ckpt.model_checkpoint_path.split('/')[-1].split('-')[-1]
        else:
          print('No checkpoint file found')
          return

        x = sess.run(logits, feed_dict={'InputPlaceHolder/TestInput:0':images})
        print(x)
    '''

The above code yeilds an error that the placeholder is not fed:

InvalidArgumentError (see above for traceback): You must feed a value for placeholder tensor 'InputPlaceHolder/TestInput' with dtype float

And it's not that TensorFlow does not recognize the placeholder. If I change the name from 'InputPlaceHolder/TestInput:0' to 'InputPlaceHolder/TestInput:1' I receive a message calming that 'InputPlaceHolder/TestInput' exists but has only 1 output. This makes sense, and I guess the session runs on my default graph.

Things only work for me if I stay within the same def: If I change the code by running the commented part (starting ' with tf.Session() as sess:) directly from within the first function all works.

I wonder what am I missing? My guess that is context related, maybe not assigning the session to the graph?

Answer 1

Solved. Stupid mistake test_once calls sess.run twice. On the second time, indeed no placeholder is fed.... : summary.ParseFromString(sess.run(summary_op))