Update app.py

app.py

@@ -42,16 +42,14 @@ import librosa
 
 
 
-# def set_seed(seed):
-#     torch.manual_seed(seed)
-#     if torch.cuda.is_available():
-#         torch.cuda.manual_seed_all(seed)
-#     np.random.seed(seed)
-#     random.seed(seed)
-#     torch.backends.cudnn.deterministic = True
-#     torch.backends.cudnn.benchmark = False
-
-# set_seed(42)
+def set_seed(seed):
+    torch.manual_seed(seed)
+    if torch.cuda.is_available():
+        torch.cuda.manual_seed_all(seed)
+    np.random.seed(seed)
+    torch.backends.cudnn.benchmark = False
+
+set_seed(997)
 # Load model directly
 from transformers import AutoProcessor, AutoModelForTextToSpectrogram
 
@@ -128,7 +126,7 @@ def tts_fn(slider_value, input_text):
         inputs = processor(text = text, return_tensors="pt")
 
     with torch.no_grad():
-        spectrogram = model.generate_speech(inputs["input_ids"], speaker_embedding, minlenratio = 2, maxlenratio = 4, threshold = 0.3)
+        spectrogram = model.generate_speech(inputs["input_ids"], speaker_embedding, minlenratio = 2, maxlenratio = 4, threshold = 0.4)
 
     with torch.no_grad():
         speech = vocoder(spectrogram)