When applying Transformer models to DNA sequences, what is the mathematical role of the 'attention mask' in managing variable-length genomic inputs?

In Transformer models, DNA sequences are processed in batches where all sequences must be padded with placeholder tokens, such as zeros, to reach a uniform length. The attention mask acts as a mathematical gate that tells the self-attention mechanism to ignore these padding tokens. Mathematically, the attention mechanism calculates scores by takin....