aiter-flash-attn: add AITER Flash Attention kernel for AMD ROCm

[danieldk]

This adds a Triton FlashAttention kernel for AMD ROCm, repackaged from the MHA implementation in AMD’s AITER project (https://github.com/ROCm/aiter).

The motivation is on the Transformers side: the ROCm FlashAttention fallback currently depends on installing the full aiter pip package, which reviewers (rightly) pushed back on. Having an equivalent kernel here means Transformers can route through get_kernel like every other FA backend instead of carrying a direct AITER dependency. Beyond just unblocking the dependency story, this is also an FA3-style kernel with native support for learnable attention sinks (sink=), which is required by models like gpt-oss on ROCm; something flash-attn2 does not provide.

It’s a slim copy; only the parts actually reachable from flash_attn_func and flash_attn_varlen_func, with the unused dao_ai implementation path removed and all absolute imports rewritten to be Hub-compliant. It has been tested locally on MI300X against an eager SDPA reference; numerics match within fp16 tolerance for dense, causal, and varlen cases.

Original PR: #890