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So far, subsampling is only properly implemented for dense, square tensors and arrays. Other RelationData subclasses internally are converted to dense representations for subsampling. This is memory-inefficient. For the triangular representations, the index lists must be converted accordingly to enable a direct indexing without having to call to_square...(). For the sparse matrix representation it should be enough to check that subsampling works properly with a similar implementation as for the dense case.
The text was updated successfully, but these errors were encountered:
So far, subsampling is only properly implemented for dense, square tensors and arrays. Other
RelationData
subclasses internally are converted to dense representations for subsampling. This is memory-inefficient. For the triangular representations, the index lists must be converted accordingly to enable a direct indexing without having to callto_square...()
. For the sparse matrix representation it should be enough to check that subsampling works properly with a similar implementation as for the dense case.The text was updated successfully, but these errors were encountered: