Added update_parameters to EMA to fix calculation (#4406)

references/classification/utils.py

@@ -172,6 +172,17 @@ class ExponentialMovingAverage(torch.optim.swa_utils.AveragedModel):
                    decay * avg_model_param + (1 - decay) * model_param)
         super().__init__(model, device, ema_avg)
 
+    def update_parameters(self, model):
+        for p_swa, p_model in zip(self.module.state_dict().values(), model.state_dict().values()):
+            device = p_swa.device
+            p_model_ = p_model.detach().to(device)
+            if self.n_averaged == 0:
+                p_swa.detach().copy_(p_model_)
+            else:
+                p_swa.detach().copy_(self.avg_fn(p_swa.detach(), p_model_,
+                                     self.n_averaged.to(device)))
+            self.n_averaged += 1
+
 
 def accuracy(output, target, topk=(1,)):
     """Computes the accuracy over the k top predictions for the specified values of k"""