gsbDBI / torch-choice

Choice modeling with PyTorch: logit model and nested logit model
MIT License
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Handling of sparse matrix #40

Open giheungkim opened 1 year ago

giheungkim commented 1 year ago

Hi,

Thank you so much for the useful package.

I am am dealing with quite a few items (+10,000) across sessions (+6,000) and sessions are more or less block diagonal in availability of items. In fact the sparsity of availability and session-item matrices are around 5%, meaning 5% of SxI matrix elements are non-zeros.

My understanding is that current version of torch-choice does not support sparse tensors. Is there any way I could get around this issue?

Thank you!