      def get_timestamps(self, session_id=None, is_training=False):
          """ Read the timestamps from the TensorBoard logs.
  
          As loss timestamps are slightly different for each loss, we collect the timestamp from the
          `batch_total` key.
  
          Parameters
          ----------
          session_id: int, optional
              The Session ID to return the timestamps for. Set to ``None`` to return all session
 
</s> remove         loss = np.array(loss, dtype="float32")
        timestamps = np.array(timestamps, dtype="float64")
 </s> add         try:
            loss = np.array(loss, dtype="float32")
        except ValueError as err:
            # When collecting live loss, the current batch may not be completely populated
            # Carry over the last loss to the next collection
            if "setting an array element with a sequence" in str(err):
                carry_over = loss[-1]
                logger.debug("Carrying over data: (carry_over: %s, new loss: %s)",
                             carry_over, loss[:-1])
                loss = np.array(loss[:-1], dtype="float32")
            else:
                raise </s> remove     """ Add a handler that stores the last 100 debug lines to :attr:'_debug_buffer' for use in
 </s> add     """ Add a handler that stores the last 100 debug lines to :attr:'_DEBUG_BUFFER' for use in </s> remove     """ On a crash, write out the contents of :func:`_debug_buffer` containing the last 100 lines
 </s> add     """ On a crash, write out the contents of :func:`_DEBUG_BUFFER` containing the last 100 lines
        `batch_loss` key.
      def get_timestamps(self, session_id=None, is_training=False):
          """ Read the timestamps from the TensorBoard logs.
  
          As loss timestamps are slightly different for each loss, we collect the timestamp from the
        `batch_loss` key.
  
          Parameters
          ----------
          session_id: int, optional
              The Session ID to return the timestamps for. Set to ``None`` to return all session
keep keep keep keep replace keep keep keep keep keep
 Update to TF2.3 (#1100)

* Minimum requirements to tf2.3.
  - Handle upgrades for Windows users with tf2.2 installed by Pip
  - Handle windows upgrade from pip tf2.2
  - Explicitly install Cuda for Conda installs

* Update tensorflow errors api reference
* Suppress AutoGraph warning messages
* Update GUI Stats to work with tf2.3
* Fix live graph for tf2.3
* DSSIMObjective - autoGraph bugfix
* Update Travis test 
lib/gui/stats.py