Something wrong with my dataloader (apparently)

Hi friends !

I’m trying my hand on the new FastAI version and I’m completely stuck in front of a message saying:
Could not do one pass in your dataloader, there is something wrong in it

Specifically, I’m tackling the Facial Keypoint Detection on Kaggle. The training data is in a csv, where the first 30 columns are the x and y key point location and the last column is a string with the image pixel values. (

I wrote a function to get_x

def get_image(x): 
    im= np.array(x['Image'].split(' '), dtype = float).reshape(96,96)
    return p_image.fromarray(np.zeros((96,96))) # I know I'm not returning the loaded image, but I was trying to figure out the shape and if it was supposed to be a PIL image instead of a np.array 

And to get y:

def get_labels(x): 
    points = x.drop('Image')
    #px = points.drop([idx for idx in points.index if idx.endswith('_y')])
    #py = points.drop([idx for idx in points.index if idx.endswith('_x')])
    #kps = np.concatenate([px.values.astype(float).reshape(-1,1), py.values.astype(float).reshape(-1,1)], axis = 1)

   # I'm only taking a single point as a debug process. However, I do not now if TensorPoint is necessary ? 
    debug_x = x['nose_tip_x']
    debug_y = x['nose_tip_y']
    kps = np.array([debug_x, debug_y], dtype = np.float32).reshape(-1)
    return TensorPoint.create(kps)

And finally constructing the dataloader:

dblock = DataBlock(blocks = (ImageBlock, PointBlock),
                   get_x= get_image, get_y = get_labels, 
                   item_tfms = RandomResizedCrop(128, min_scale=0.35))
dls = dblock.dataloaders(train_data)

When calling show batch, I get the following error:

AttributeError: 'PointScaler' object has no attribute 'sz'

Could someone please explain to me (or point me in the direction of) the reason why it does that ?

Thanks a lot !