Update model.py

model.py

@@ -585,9 +585,10 @@ def update_lr(lr):
   opt_disc.learning_rate = lr
 
 #Build models and initialize optimizers
+load_model_path='MELGANVC-0.4886211-0.5750153-0-20230612T163214Z-001\MELGANVC-0.4886211-0.5750153-0' #@param {type:"string"}
 #If load_model=True, specify the path where the models are saved
 
-gen,critic,siam, [opt_gen,opt_disc] = get_networks(shape, load_model=True,path="MELGANVC-0.4886211-0.5750153-0")
+gen,critic,siam, [opt_gen,opt_disc] = get_networks(shape, load_model=True,path=load_model_path)
 
 #After Training, use these functions to convert data with the generator and save the results
 
@@ -635,7 +636,10 @@ def towave(spec, name, path='../content/', show=False):
   abwv = deprep(ab)
   print('Saving...')
   pathfin = f'{path}/{name}'
-  os.mkdir(pathfin)
+  try:
+    os.mkdir(pathfin)
+  except:
+    pass
   sf.write(pathfin+'/AB.wav', abwv, sr)
   sf.write(pathfin+'/A.wav', awv, sr)
   print('Saved WAV!')
@@ -650,4 +654,4 @@ def towave(spec, name, path='../content/', show=False):
     axs[1].axis('off')
     axs[1].set_title('Generated')
     plt.show()
-  return abwv
+  return abwv