Update meta_trainer.py

trainer/meta_trainer.py

@@ -352,21 +352,20 @@ class MetaTrainer(object):
                 vl=0
                 va=0
             else:
-                with torch.no_grad():
-                    tqdm_gen = tqdm.tqdm(val_loader)
-                    for i, batch in enumerate(tqdm_gen, 1):
-                        if torch.cuda.is_available():
-                            data, _ = [_.cuda() for _ in batch]
-                        else:
-                            data = batch[0]
-                        p = args.shot * args.way
-                        data_shot, data_query = data[:p], data[p:]  
-                        data_shot = data_shot.unsqueeze(0).repeat(num_gpu, 1, 1, 1, 1)
-                        logits = model.meta_forward(data_shot, data_query)
-                        loss = F.cross_entropy(logits, label)
-                        acc = count_acc(logits, label)
-                        vl.add(loss.item())
-                        va.add(acc)
+                tqdm_gen = tqdm.tqdm(val_loader)
+                for i, batch in enumerate(tqdm_gen, 1):
+                    if torch.cuda.is_available():
+                        data, _ = [_.cuda() for _ in batch]
+                    else:
+                        data = batch[0]
+                    p = args.shot * args.way
+                    data_shot, data_query = data[:p], data[p:]  
+                    data_shot = data_shot.unsqueeze(0).repeat(num_gpu, 1, 1, 1, 1)
+                    logits = model.meta_forward(data_shot, data_query)
+                    loss = F.cross_entropy(logits, label)
+                    acc = count_acc(logits, label)
+                    vl.add(loss.item())
+                    va.add(acc)
 
                 vl = vl.item()
                 va = va.item()