Is class numbering with gaps supported for training on custom datasets?

[MJ0t]

Checklist

• I have searched for similar issues.
• I have tested with the latest development wheel.
• I have checked the release documentation and the latest documentation (for main branch).

My Question

Hi,

I have data following the standard Las classification, meaning that some indices are unused or reserved. If possible I would like to use this data directly and only configure dataset and pipeline to handle the class to index mapping.
I am fine-tuning a KP-Conv model with the output layer modified to fit our number of classes.

From the CustomDataset3D label_to_index - template I assume that a mapping from a arbitrary class number to the consecutive output-channel index is somehow supported.

When running the training pipeline, I get an index out of bounds error here, since the 'label' == 65 is greater than my number of classes.

It is not a big deal to write the processing to re-index the class numbers. I am just wondering: is this functionality is actually supported? And, I am missing something completely?

Thanks in advance for any support

[Inshu0302]

Hi, facing similar issue, did you find any solution to this. I have 17 classes but I want to ignore some during training but getting the same number of classes in accuracy and val.