src/similarity/siamese.py [201:217]:
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                labels = labels.view(-1)

                # zero the parameter gradients
                optimizer.zero_grad()

                distance = model.forward(img1,img2)

                loss = contrastive_loss(distance, labels)
                loss.backward()
                optimizer.step()

                # statistics
                predictions = (torch.abs(distance - labels) < args.similarity_margin).int()
                running_loss += loss.item()
                running_corrects += torch.sum(predictions)

            print()
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src/similarity/siamese2.py [156:172]:
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                labels = labels.view(-1)

                # zero the parameter gradients
                optimizer.zero_grad()

                distance = model.forward(img1,img2)

                loss = contrastive_loss(distance, labels)
                loss.backward()
                optimizer.step()

                # statistics
                predictions = (torch.abs(distance - labels) < args.similarity_margin).int()
                running_loss += loss.item()
                running_corrects += torch.sum(predictions)

            print()
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