integrated tensorboardx test-tube

pytorch_lightning/root_module/model_saving.py

@@ -107,6 +107,9 @@ class TrainerIO(object):
         # save exp to make sure we get all the metrics
         experiment.save()
 
+        # close experiment to avoid issues
+        experiment.close()
+
         ckpt_number = self.max_ckpt_in_folder(folderpath) + 1
 
         if not os.path.exists(folderpath):

pytorch_lightning/root_module/root_module.py

@@ -26,6 +26,7 @@ class LightningModule(GradInformation, ModelIO, OptimizerConfig, ModelHooks):
         self.gradient_clip = hparams.gradient_clip
         self.trainer = None
         self.from_lightning = True
+        self.experiment = None
 
         # track if gpu was requested for checkpointing
         self.on_gpu = False