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Fed.py

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+import copy
+import torch
+
+
+def Aggregation(w, lens):
+    w_avg = None
+    if lens == None:
+        total_count = len(w)
+        lens = []
+        for i in range(len(w)):
+            lens.append(1.0)
+    else:
+        total_count = sum(lens)
+
+    for i in range(0, len(w)):
+        if i == 0:
+            w_avg = copy.deepcopy(w[0])
+            for k in w_avg.keys():
+                w_avg[k] = w[i][k] * lens[i]
+        else:
+            for k in w_avg.keys():
+                w_avg[k] += w[i][k] * lens[i]
+
+    for k in w_avg.keys():
+        w_avg[k] = torch.div(w_avg[k], total_count)
+
+    return w_avg