Update app.py

app.py

@@ -36,6 +36,7 @@ minimumGain = -45
 maximumGain = -5
 attenLimDB = 3
 
+'''
 try:
     raise(RuntimeError("Not an error"))
     #device = xm.xla_device()
@@ -46,6 +47,7 @@ except RuntimeError as e:
     device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
     print(f"Using {device} instead.")
 #device = xm.xla_device()
+'''
 
 # Instantiate and prepare model for training.
 dfModel, dfState, _ = init_df(model_base_dir="DeepFilterNet3")
@@ -111,6 +113,9 @@ audio_tabs = []
 temp_dir = tempfile.mkdtemp()
 
 if uploaded_file_paths is not None:
+    valid_files = []
+    file_paths = []
+    audio_tabs = []
     # Reset valid_files?
     for uploaded_file in uploaded_file_paths:
         if not uploaded_file.name.endswith(supported_file_types):