hey folks, I'm working on a PyTorch use case and figuring out how to convert the

images

column in my Daft df into proper pytorch tensors was pretty painful. I spent a few hours on this and had to get @jay to help me out in the end. Would be great to have some docs or a friendlier API for this :]

Any suggestions on good APIs here folks? I’m considering… 1. Syntactic sugar on top of pytorch transforms to work directly on our Image column types:

.image.torch_transform(my_transforms)

2. Baking in more of these transforms as Daft expressions:

.image.center_crop().<http://image.to|image.to>_tensor().image.normalize()

3. A

<http://Series.to|Series.to>_torch()

function that returns a correctly batched tensor a. We should probably also figure out our story around

def ___array___

for numpy array conversion?

Thanks @jay! I love (1), that's where my mind was going intuitively. It would be great to just run a

udf

directly on the

image

col instead of having to preprocess into separate

tensor

and

pytorch_tensor

cols