Reduce data waste with "resmixid"

DatasetLoader.py

@@ -229,16 +229,33 @@ def __iter__(self):
                 flattened_list.append([data[i] for i in indices])
 
         ## Mix data in random order
-        mixid           = torch.randperm(len(flattened_label), generator=g).tolist()
+        mixid           = torch.randperm(len(flattened_label), generator=g).tolist()  # numpy.arange(len(flattened_label)).tolist()
         mixlabel        = []
         mixmap          = []
-
-        ## Prevent two pairs of the same speaker in the same batch
-        for ii in mixid:
-            startbatch = round_down(len(mixlabel), self.batch_size)
-            if flattened_label[ii] not in mixlabel[startbatch:]:
-                mixlabel.append(flattened_label[ii])
-                mixmap.append(ii)
+        resmixid = []
+        mixlabel_ins = 1 # for start while
+
+        # ## Prevent two pairs of the same speaker in the same batch
+        # for ii in mixid:
+        #     startbatch = round_down(len(mixlabel), self.batch_size)
+        #     if flattened_label[ii] not in mixlabel[startbatch:]:
+        #         mixlabel.append(flattened_label[ii])
+        #         mixmap.append(ii)
+        #         mixlabel_ins += 1
+
+        ## Prevent two pairs of the same speaker in the same batch (Reduce data waste with "resmixid")
+        while len(mixid)>0 and mixlabel_ins>0:
+            mixlabel_ins = 0
+            for ii in mixid:
+                startbatch = round_down(len(mixlabel), self.batch_size)
+                if flattened_label[ii] not in mixlabel[startbatch:]:
+                    mixlabel.append(flattened_label[ii])
+                    mixmap.append(ii)
+                    mixlabel_ins += 1
+                else:
+                    resmixid.append(ii)
+            mixid = resmixid
+            resmixid = []
 
         mixed_list = [flattened_list[i] for i in mixmap]