Update app.py

app.py

@@ -11,7 +11,7 @@ from datasets import load_dataset
 from datasets import Dataset,DatasetDict
 import librosa
 import torch
-
+from concurrent.futures import ThreadPoolExecutor
 model_enhance, df_state, _ = init_df()
 def Read_DataSet(link):
         dataset = load_dataset(link,token=os.environ.get("auth_acess_data"))
@@ -27,10 +27,10 @@ def remove_nn(wav, sample_rate=16000):
     
     audio=torch.tensor([audio])
   #  audio, _ = load_audio('full_generation.wav', sr=df_state.sr())
-    print(audio)
+  
     
     enhanced = enhance(model_enhance, df_state, audio)
-    print(enhanced)
+    
    # save_audio("enhanced.wav", enhanced, df_state.sr())
     audiodata=librosa.resample(enhanced[0].numpy(),orig_sr=df_state.sr(),target_sr=sample_rate)
    
@@ -228,7 +228,11 @@ class DataViewerApp:
         else :
             data=data[data['flag'] ==1]
             return self.set1(data),len(data)
-
+    def process_audio(index):
+        for i in range(len(df)):
+            x, y = remove_nn(df['audio'][i])
+            df['audio'][i] = y
+        return df
     def on_select(self,evt:gr.SelectData):
         index_now = evt.index[0]
         self.current_selected = (self.current_page * 10) + index_now
@@ -242,10 +246,10 @@ class DataViewerApp:
 
         return self.df
     def All_enhance(self):
-        for i in range(0,len(self.sdata)):
-              _,y=remove_nn(self.sdata[i])
-              self.sdata[i]=y
-        return self.data
+        with ThreadPoolExecutor() as executor:
+             future = executor.submit(process_audio, 0)
+             df_modified = future.result()
+             return df_modified
 
         return self.get_page_data(self.current_page)
     def get_output_audio(self):