Update ser.py

optimize and update params

ser.py

@@ -62,6 +62,19 @@ class SearchMood:
 
 
         return(torch.tensor([samp_loss*-1]))
+
+
+
+    def search_compose(self):
+        for d in range(100):
+            optimizer = optim.Adagrad((self.prior_component[0], self.prior_component[1]))
+            optimizer.step(closure=self.loss_fn)
+            state_dict = optimizer.state_dict()        
+            params = state_dict['param_groups'][0]['params']
+
+            self.prior_component[0] = params[0]
+            self.prior_component[1] = params[1]
+