Thanks, it worked. I am observing a peculiar behavior, don’t know whether a gap in my knowledge or not.
data_transforms = transforms.Compose([transforms.RandomCrop(512,512),
                             transforms.ToTensor(),
                             transforms.Lambda(gaussian_blur),
                             transforms.Normalize(mean=train_mean, std=train_std),
                             transforms.RandomRotation([+90,+180]),
                             transforms.RandomRotation([+180,+270]),
                             transforms.RandomHorizontalFlip(),
                           ])

When I am showing the shape of the images, it is coming out to be not 512,512. Does Random Crop  doesn’t take the required size and then crop it or I am doing something wrong.
for images, labels in final_train_loader:  
    print('Image batch dimensions:', images.shape)

Image batch dimensions: torch.Size([3, 3, 584, 565])
Image label dimensions: torch.Size([3])