diff --git a/re3_utils/tensorflow_util/tf_queue.py b/re3_utils/tensorflow_util/tf_queue.py
index d475e3dbb076699933a26187432c3f7ff293badf..327fc71f2f9754bad4abb5a8843dd7ac59f69552 100644
--- a/re3_utils/tensorflow_util/tf_queue.py
+++ b/re3_utils/tensorflow_util/tf_queue.py
@@ -83,7 +83,7 @@ class TFQueue(object):
                         len(self.data_buffer),
                         (len(self.data_buffer) - len(self.data_counts[self.data_counts > 0])),
                         np.max(self.data_counts),
-                        np.median(self.data_counts)))
+                        np.median(self.data_counts[:len(self.data_buffer)])))
             else:
                 print('Buffer Full. Num unused: %d  Max times used: %d  Median times used: %d\n' % (
                         (len(self.data_buffer) - len(self.data_counts[self.data_counts > 0])),
diff --git a/tracker/network.py b/tracker/network.py
index 1735e2bbdf6b3a23132a9176283a6413ff3db28c..b1c3d1803514ba9806025ea3c7de4c56dfb5a953 100644
--- a/tracker/network.py
+++ b/tracker/network.py
@@ -141,11 +141,8 @@ def inference(inputs, num_unrolls, train, batch_size=None, prevLstmState=None, r
                 lstmVars = [var for var in tf.trainable_variables() if 'lstm2' in var.name]
                 for var in lstmVars:
                     tf_util.variable_summaries(var, var.name[:-2])
-
-        with tf.variable_scope('lstm_output_concat'):
-            # BxTxC
-            outputs_concat = tf.concat(lstm2_outputs, 0)
-            outputs_reshape = tf_util.remove_axis(outputs_concat, 1)
+            # (BxT)xC
+            outputs_reshape = tf_util.remove_axis(lstm2_outputs, 1)
 
         # Final FC layer.
         with tf.variable_scope('fc_output'):