src/similarity/siamese.py [183:198]:
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            logger.info('-' * 10)

            # Each epoch has a training and validation phase
            model.train()  # Set model to training mode

            running_loss = 0.0
            running_corrects = 0

            # Iterate over data.
            for data in train_dl:

                img1 = data['img1'].to(DEVICE)
                img1 = img1.view(-1,img1.shape[-3],img1.shape[-2],img1.shape[-1])
                
                img2 = data['img2'].to(DEVICE)
                img2 = img2.view(-1,img2.shape[-3],img2.shape[-2],img2.shape[-1])
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src/similarity/siamese2.py [138:153]:
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            logger.info('-' * 10)

            # Each epoch has a training and validation phase
            model.train()  # Set model to training mode

            running_loss = 0.0
            running_corrects = 0

            # Iterate over data.
            for data in train_dl:

                img1 = data['img1'].to(DEVICE)
                img1 = img1.view(-1,img1.shape[-3],img1.shape[-2],img1.shape[-1])
                
                img2 = data['img2'].to(DEVICE)
                img2 = img2.view(-1,img2.shape[-3],img2.shape[-2],img2.shape[-1])
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