              tensorboard[side] = tbs
          logger.info("Enabled TensorBoard Logging")
          return tensorboard
  
      def print_loss(self, loss):
          """ Override for specific model loss formatting """
          logger.trace(loss)
          output = list()
          for side in sorted(list(loss.keys())):
 
</s> remove             tbs = tf_keras.callbacks.TensorBoard(log_dir=log_dir,
                                                 histogram_freq=0,  # Must be 0 or hangs
                                                 batch_size=self.batch_size,
                                                 write_graph=True,
                                                 write_grads=True)
 </s> add             tbs = tf.keras.callbacks.TensorBoard(log_dir=log_dir, **self.tensorboard_kwargs) </s> remove                          "Specify a trainer with the '-t', '--trainer' option.")
 </s> add                          "Specify a trainer with the '-t', '--trainer' option.", len(statefile)) </s> remove             self.required_packages.append("tensorflow-gpu==1.12.0")
 </s> add             self.required_packages.append("tensorflow-gpu==1.13.1") </s> remove         self.conda_required_packages = [("ffmpeg", "conda-forge"), ("tk", )]
 </s> add         self.conda_required_packages = [("tk", )] </s> remove             self.required_packages.append("tensorflow==1.12.0")
 </s> add             self.required_packages.append("tensorflow==1.13.1")
    @property
    def tensorboard_kwargs(self):
        """ TF 1.13 + needs an additional kwarg which is not valid for earlier versions """
        kwargs = dict(histogram_freq=0,  # Must be 0 or hangs
                      batch_size=64,
                      write_graph=True,
                      write_grads=True)
        tf_version = [int(ver) for ver in tf.__version__.split(".")]
        logger.debug("Tensorflow version: %s", tf_version)
        if tf_version[0] > 1 or (tf_version[0] == 1 and tf_version[1] > 12):
            kwargs["update_freq"] = "batch"
        logger.debug(kwargs)
        return kwargs

              tensorboard[side] = tbs
          logger.info("Enabled TensorBoard Logging")
          return tensorboard
  
    @property
    def tensorboard_kwargs(self):
        """ TF 1.13 + needs an additional kwarg which is not valid for earlier versions """
        kwargs = dict(histogram_freq=0,  # Must be 0 or hangs
                      batch_size=64,
                      write_graph=True,
                      write_grads=True)
        tf_version = [int(ver) for ver in tf.__version__.split(".")]
        logger.debug("Tensorflow version: %s", tf_version)
        if tf_version[0] > 1 or (tf_version[0] == 1 and tf_version[1] > 12):
            kwargs["update_freq"] = "batch"
        logger.debug(kwargs)
        return kwargs

      def print_loss(self, loss):
          """ Override for specific model loss formatting """
          logger.trace(loss)
          output = list()
          for side in sorted(list(loss.keys())):
keep keep keep add keep keep keep keep keep
 Full RTX Support

Remove FFMPEG from Conda Requirements
Fix Tensorboard logging for Tensorflow 1.13.1
Bump default Conda Tensorflow to 1.13.1
Update max python version to 3.7 
plugins/train/trainer/_base.py