add torchscan for summary and receptive field (wip)

Deep-SAD-PyTorch/src/optim/DeepSAD_trainer.py

@@ -212,6 +212,7 @@ class DeepSADTrainer(BaseTrainer):
         start_time = time.time()
         idx_label_score = []
         net.eval()
+        net.summary(receptive_field=True)
         with torch.no_grad():
             for data in test_loader:
                 inputs, labels, semi_targets, idx, _ = data
@@ -267,6 +268,7 @@ class DeepSADTrainer(BaseTrainer):
         c = torch.zeros(net.rep_dim, device=self.device)
 
         net.eval()
+        net.summary(receptive_field=True)
         with torch.no_grad():
             for data in train_loader:
                 # get the inputs of the batch