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Added optional KV cache to speed up inference.
Cache only added for main transformer layers, not s2 inference (DependencyAwareLayer). Not sure if adding it make sense as there is only one attention block.
Cache resets every step after (context len + num generated tokens ) exceeds max_context. This does not affect outputs, but performance will degrade to non-cached version. To avoid cache reset, keep (context + pred_len) under max_context (e.g. 480 + 32).
Cache rolling resulted in regression in one test so I just kept things safe. It's possible that this is a flaky test, but I was not able to debug it.
Results
On A100 with 400 context throughput improved 5.17 -> 44.3 batch/sec (165 -> 1418 token/sec). Saturates with ~256 batch size at 6.8 batch/sec (1740 token/sec).