MaskRCNN Training on Images with no Annotations

Hi all,
I am working on a little MaskRCNN training program and ran into an issue. I know it is common practice to remove any images from the dataset that lack annotations upon initializing the dataset which I am doing. However, I am running a series of transforms using albumentations on my image and my mask. One of these transforms is a random crop and sometimes the resulting mask image no longer contains any instances. I was trying to find a way to pass in an empty tensor of some kind without much success. Would it be common practice just to remove it from the batch, and if so what happens if you had a batch size of 1 or an image that only had one annotation and the chances the random crop came across it are really low. I was able to create an empty tensor and pass it in but then received this error.

RuntimeError: cannot reshape tensor of 0 elements into shape [0, -1] because the unspecified dimension size -1 can be any value and is ambiguous

This is because my box tensor had a shape of 0, 4 which is what I want since there are no instances. I read some of the other issue reports and they talked about creating a background class and just making a small bounding box and having an empty segmentation mask but this seems a little hacky and I was wondering if there would be a better solution for my specific use case.

The issue names no repository files or tests. Start by reproducing the reported reshape error with an empty 0×4 box tensor and the described random-crop pipeline, then inspect the relevant dataset and Mask R-CNN target-handling entry points. Done requires an agreed behavior for crops with no remaining instances and a regression test, but the issue does not specify either.