          if iterations == 0:
              # Initialize session stats and set initial timestamp
              self.train_stats["timestamp"] = time()
  
          if not get_config().session.initialized and iterations > 0:
              # Don't initialize session until after the first iteration as state
              # file must exist first
              get_config().session.initialize_session(is_training=True)
  
          iterations += 1
          self.train_stats["iterations"] = iterations
  
          elapsed = self.calc_elapsed()
          message = "Elapsed: {} | Session Iterations: {}  {}".format(
 
</s> remove             # Initialize session stats and set initial timestamp
 </s> add             # Set initial timestamp </s> remove             timeout = get_config().tk_vars["traintimeout"].get()
 </s> add             timeout = self.config.tk_vars["traintimeout"].get() </s> remove         dst = str(get_folder("{}_snapshot_{}_iters".format(self.model_dir, iterations)))
 </s> add         snapshot_dir = "{}_snapshot_{}_iters".format(self.model_dir, iterations)

        if os.path.isdir(snapshot_dir):
            logger.debug("Removing previously existing snapshot folder: '%s'", snapshot_dir)
            rmtree(snapshot_dir)

        dst = str(get_folder(snapshot_dir))
          if iterations == 0:
              # Initialize session stats and set initial timestamp
              self.train_stats["timestamp"] = time()
  





          iterations += 1
          self.train_stats["iterations"] = iterations
  
          elapsed = self.calc_elapsed()
          message = "Elapsed: {} | Session Iterations: {}  {}".format(
keep keep keep keep replace replace replace replace replace keep keep keep keep keep
 Bugfixes

- Fix filter/nfilter for convert
- Remove existing snapshot folder before creating if it pre-exists
- Don't initialize training session until after first save. "Nonetype" session fix 
lib/gui/wrapper.py