Open source TPU-friendly ragged paged attention kernel.

Key features:
* ***Support mixed prefill and decode*** to increase throughput for inference. (eg., ***5x*** speedup compared to padded Muti-Queries Paged Attention implementation for llama-3-8b.)
* ***No explicit `swapaxes`*** for `seq_len` and `num_head` in pre/post kernel. The kernel takes `num_head` in 2nd minor as it naturally was. We fold swapaxes to strided load/store in the kernel and apply transpose on the fly.
* ***No GMM (Grouped Matmul) Metadata required!*** We calculate the metadata on the fly in the kernel. This can speed up ***10%***!
* ***Increase MXU utilization 8x in GQA*** by grouping shared q heads for MXU in decode.
* ***Minimize recompilation:*** The only factors can cause recompilation are model specs, `max_num_batched_tokens` and `max_num_seqs` in the setting of mixed engine.

PiperOrigin-RevId: 734269519

Author: bythew3i