  
                  if self._args["flatten_outliers"]:
                      loss = self._flatten_outliers(loss)
  
                  self.stats["raw_{}".format(loss_name)] = loss
  
              self._iterations = 0 if not iterations else min(iterations)
              if self._limit > 1:
                  self._start_iteration = max(0, self._iterations - self._limit)
                  self._iterations = min(self._iterations, self._limit)
 
</s> remove         self._stats = dict()
 </s> add         self._stats = {} </s> remove                     self.stats = {lossname: np.array(list(), dtype=loss.dtype)
 </s> add                     self.stats = {lossname: np.array([], dtype=loss.dtype) </s> remove         self._sessions = dict()
        self._lowest_avg_loss = dict()
        self._config = dict()
 </s> add         self._sessions = {}
        self._lowest_avg_loss = {}
        self._config = {} </s> remove         filename = "{}_state.{}".format(model_name, self._serializer.file_extension)
 </s> add         filename = f"{model_name}_state.{self._serializer.file_extension}" </s> remove         self._sessions = state.get("sessions", dict())
        self._lowest_avg_loss = state.get("lowest_avg_loss", dict())
 </s> add         self._sessions = state.get("sessions", {})
        self._lowest_avg_loss = state.get("lowest_avg_loss", {})
                self.stats[f"raw_{loss_name}"] = loss
  
                  if self._args["flatten_outliers"]:
                      loss = self._flatten_outliers(loss)
  
                self.stats[f"raw_{loss_name}"] = loss
  
              self._iterations = 0 if not iterations else min(iterations)
              if self._limit > 1:
                  self._start_iteration = max(0, self._iterations - self._limit)
                  self._iterations = min(self._iterations, self._limit)
keep keep keep keep replace keep keep keep keep keep
 Update code to support Tensorflow versions up to 2.8 (#1213)

* Update maximum tf version in setup + requirements

* - bump max version of tf version in launcher
- standardise tf version check

* update keras get_custom_objects  for tf>2.6

* bugfix: force black text in GUI file dialogs (linux)

* dssim loss - Move to stock tf.ssim function

* Update optimizer imports for compatibility

* fix logging for tf2.8

* Fix GUI graphing for TF2.8

* update tests

* bump requirements.txt versions

* Remove limit on nvidia-ml-py

* Graphing bugfixes
  - Prevent live graph from displaying if data not yet available

* bugfix: Live graph. Collect loss labels correctly

* fix: live graph - swallow inconsistent loss errors

* Bugfix: Prevent live graph from clearing during training

* Fix graphing for AMD 
lib/gui/analysis/stats.py