ValueError: Expected tensor to be a tensor image of size (C, H, W). Got tensor.size() = torch.Size([8, 8])

vision
3

superb! should I have both norm_landmarks as well as torch.div by max value in the raw landmarks?


        norm_landmarks = transforms.Normalize(0.4949, 0.2165)
        landmarks = landmarks.unsqueeze_(0)
        landmarks = norm_landmarks(landmarks)
         
        #743 is max value in raw landmarks values
        landmarks = torch.div(landmarks, 743.)
        
        predictions = network(images)

with the above code, I still end up getting nans after first step.