title: Tensorboard doesn't show scalars anymore
body: <p>I decided to update tensorboard because it wasn't showing the graph,
  on the graph panel all I could see was a blank page with no error message.
  Now that I have updated the graph, is the only thing my tensorboard shows. Now I cannot see scalars or histograms. I have the:</p>
  
  <pre><code>No scalar data was found.
  </code></pre>
  
  <p>message, and the same for histograms etc.</p>
  
  <p>This is the relevant parts of my code:</p>
  
  <pre><code>def train_model(self):
  
      with tf.Session(graph=self.graph) as session:
          session.run(tf.global_variables_initializer())#Now all variables should be initialized.
          print("Uninitialized variables: ", session.run(tf.report_uninitialized_variables())) #Just to check, should print nothing
  
          self.train_writer = tf.summary.FileWriter(self.default_folder+"/logs/train", graph=session.graph)
          self.test_writer = tf.summary.FileWriter(self.default_folder+"/logs/test", graph=session.graph)
  
          print("Training for ", self.n_steps)
          for step in range(self.n_steps):
  
              feed_train = self._create_feed_dict(self.X_train,step)
              feed_test = self._create_feed_dict(self.X_test,step)
  
              session.run(self.optimizer, feed_dict = {self.v_clamp: feed_train})
  
              #Get the loss in tensorborad
              loss_train = session.run(self.summary_loss, feed_dict = {self.v_clamp: feed_train})
              self.train_writer.add_summary(loss_train, step)
              self.train_writer.flush()
              loss_test = session.run(self.summary_loss, feed_dict = {self.v_clamp: feed_test})
              self.test_writer.add_summary(loss_test, step)
              self.test_writer.flush()
  
              if (step%1000)==0:
                  histograms = session.run(self.merged, feed_dict = {self.v_clamp: feed_train})
                  self.train_writer.add_summary(histograms, step)
                  self.train.flush()
                  self.saver.save(session, self.default_folder + self.model_name, global_step = step)
                  print(step)
  </code></pre>
  
  <p>I created these variables inside my build_model method.</p>
  
  <pre><code>def _build_model():
  ...
          with tf.variable_scope("hidden_layer_1"):
              self.W = tf.get_variable(name = "w", dtype = tf.float32, shape=[self.n_visibles, self.n_hidden], initializer=tf.random_uniform_initializer(maxval=0.01,minval=-0.01))
              hist1=tf.summary.histogram("hidden_layer_1" + '/weights', self.W)
  
              self.bh = tf.get_variable(name = "b_h", dtype = tf.float32, shape=[self.n_hidden], initializer=tf.random_uniform_initializer(maxval=0.01,minval=-0.01))
              hist2=tf.summary.histogram("hidden_layer_1" + '/biases', self.bh)
  
              if self.hidden_activation == 'sigma':
                  self.h_clamp = tf.nn.sigmoid(tf.matmul(self.v_clamp,self.W) + self.bh)
              elif self.hidden_activation == 'relu':
                  self.h_clamp = tf.nn.relu(tf.matmul(self.v_clamp,self.W) + self.bh)
              elif self.hidden_activation == 'tanh':
                  self.h_clamp = tf.nn.tanh(tf.matmul(self.v_clamp,self.W) + self.bh)  
              hist3=tf.summary.histogram("hidden_layer_1" + '/h', self.h_clamp)
  ...
         #Get loss in tensorboard       
          with tf.variable_scope("compute_loss"):
              self.loss_function = tf.sqrt(tf.reduce_mean(tf.square(self.v_clamp - v_free)))
              self.summary_loss = tf.summary.scalar("loss", self.loss_function) #this is what we need to run!
          self.merged = tf.summary.merge([hist1,hist2,hist3])
  
          #Object to save variable weights and more
          self.saver = tf.train.Saver()
  </code></pre>
  
  <p>My default_folder is "./models/GSSU-RBM/". and my model_name is "myRBM".</p>
  
  <p>I execute tensorboard like this:</p>
  
  <pre><code>tensorboard --logdir "C:\Users\isaac\Desktop\TFM\models\GSSU-RBM"
  </code></pre>
  
  <p>And I get the following message: </p>
  
  <pre><code>Exception in thread Reloader:
  Traceback (most recent call last):
    File "c:\users\isaac\anaconda3\envs\tensorflow-gpu\lib\threading.py", line 914, in _bootstrap_inner
      self.run()
    File "c:\users\isaac\anaconda3\envs\tensorflow-gpu\lib\threading.py", line 862, in run
      self._target(*self._args, **self._kwargs)
    File "c:\users\isaac\anaconda3\envs\tensorflow-gpu\lib\site-packages\tensorboard\backend\application.py", line 361, in _reload_forever
      reload_multiplexer(multiplexer, path_to_run)
    File "c:\users\isaac\anaconda3\envs\tensorflow-gpu\lib\site-packages\tensorboard\backend\application.py", line 335, in reload_multiplexer
      multiplexer.Reload()
    File "c:\users\isaac\anaconda3\envs\tensorflow-gpu\lib\site-packages\tensorboard\backend\event_processing\plugin_event_multiplexer.py", line 195, in Reload
      accumulator.Reload()
    File "c:\users\isaac\anaconda3\envs\tensorflow-gpu\lib\site-packages\tensorboard\backend\event_processing\plugin_event_accumulator.py", line 186, in Reload
      self._ProcessEvent(event)
    File "c:\users\isaac\anaconda3\envs\tensorflow-gpu\lib\site-packages\tensorboard\backend\event_processing\plugin_event_accumulator.py", line 332, in _ProcessEvent
      value = data_compat.migrate_value(value)
    File "c:\users\isaac\anaconda3\envs\tensorflow-gpu\lib\site-packages\tensorboard\data_compat.py", line 57, in migrate_value
      return handler(value) if handler else value
    File "c:\users\isaac\anaconda3\envs\tensorflow-gpu\lib\site-packages\tensorboard\data_compat.py", line 106, in _migrate_scalar_value
      tensor_proto = tf.make_tensor_proto(scalar_value)
  AttributeError: module 'tensorflow' has no attribute 'make_tensor_proto'
  </code></pre>
  
  <p>BTW I'm running this with tensorflow-gpu on Windows 10, on a jupyter notebook on anaconda. I installed tensorboard like <code>pip install tensorboard</code> and tensorflow-gpu through conda.</p>
  
  <p>EDIT: Also, the edit from my --inspect
  Doing: <code>tensorboard --inspect --logdir "C:\Users\isaac\Desktop\TFM\models\GSSU-RBM"</code>
  I get:</p>
  
  <pre><code>These tags are in C:\Users\isaac\Desktop\TFM\models\GSSU-RBM\logs\test:
  audio -
  histograms -
  images -
  scalars
     compute_loss/loss
  tensor -
  ======================================================================
  
  Event statistics for C:\Users\isaac\Desktop\TFM\models\GSSU-RBM\logs\test:
  audio -
  graph
     first_step           0
     last_step            0
     max_step             0
     min_step             0
     num_steps            1
     outoforder_steps     []
  histograms -
  images -
  scalars
     first_step           0
     last_step            84487
     max_step             84487
     min_step             0
     num_steps            84488
     outoforder_steps     []
  sessionlog:checkpoint -
  sessionlog:start -
  sessionlog:stop -
  tensor -
  ======================================================================
  
  These tags are in C:\Users\isaac\Desktop\TFM\models\GSSU-RBM\logs\train:
  audio -
  histograms
     hidden_layer_1/hidden_layer_1/biases
     hidden_layer_1/hidden_layer_1/h
     hidden_layer_1/hidden_layer_1/weights
  images -
  scalars
     compute_loss/loss
  tensor -
  ======================================================================
  
  Event statistics for C:\Users\isaac\Desktop\TFM\models\GSSU-RBM\logs\train:
  audio -
  graph
     first_step           0
     last_step            0
     max_step             0
     min_step             0
     num_steps            1
     outoforder_steps     []
  histograms
     first_step           0
     last_step            84000
     max_step             84000
     min_step             0
     num_steps            85
     outoforder_steps     []
  images -
  scalars
     first_step           0
     last_step            84599
     max_step             84599
     min_step             0
     num_steps            84600
     outoforder_steps     []
  sessionlog:checkpoint -
  sessionlog:start -
  sessionlog:stop -
  tensor -
  ======================================================================
  </code></pre>