Hi, I’m trying to implement the model in this paper: https://arxiv.org/pdf/1912.08967.pdf 78
My inputs to the model are a triplet of outfit images (3 images), positive image (1 image), negative images (3 images).
Let’s ignore the labels of the images because they’re not important
I created a custom dataset that can return that triplet like this:
return (outfit_imgs, positive_img, negative_imgs)

The shape of a single training example is: ((3, 3, 244, 224), (1, 3, 224, 224), (3, 3, 224, 224))
Everything went fine with a single training example but when I try to use the dataloader and set batchsize=4 the training example’s shape becomes ((4, 3, 3, 224, 224), (4, 1, 3, 224, 224), (4, 3, 3, 224, 224)) that my model can’t understand.
Have anyone countered this situation before?
Do I need to reshape the training example or are there any other ways to work around?
Thank you very much.