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Prior to performing attention, we need to permute query, key and value. Currently we call Contiguous after each of these permutations, which is correct but expensive. Avoiding the 3 calls to Contiguous increases performance by over 20%. The permutations of query and key do not violate the continuity rules for mulmat and the Contiguous call can be simply removed. Value requires a different permutation and does require Contiguous. However, we can use the copy into the cache as a way to perform this without further overhead. To support this and avoid unexpected tensor shapes that are seen by models, we need tighter integration between attention, cache and backend. Future optimization will also likely need this structure - for example, flash attention has special padding requirements in the cache and other backends may have their own needs. This further contains the operations that go into attention so that these and other optimizations can be handled transparently. Models that have special requirements for attention can still implement their own version of it.