BSND to TND and FA_UPDATE replacement

[pichangping]

What this PR does / why we need it?

Does this PR introduce any user-facing change?

How was this patch tested?

• vLLM version: v0.11.0rc3
• vLLM main: vllm-project/vllm@c9461e0

[github-actions]

This pull request has conflicts, please resolve those before we can evaluate the pull request.

[gemini-code-assist]

Code Review

This pull request refactors the attention mechanism to use the TND tensor format directly, removing the need for packing and unpacking between TND and BSND formats. It also replaces a manual attention update implementation with a more optimized npu_attention_update kernel.

I've found a critical bug in the graph capture path for decoding, where several typos would lead to an AttributeError. Additionally, I've identified a potential issue with a hardcoded attention mask size that could cause problems for models with long context lengths.

[gemini-code-assist]

There are several typos on these lines within the graph capture logic that will cause an AttributeError at runtime:

1. attn_metadata.decode should be attn_metadata.decode_meta.
2. num_computed_tokens_of_cp_dcp should be num_computed_tokens_of_pcp_dcp.
3. self.cp_rank should be self.pcp_rank.

These seem to be typos introduced during refactoring, as the previous version of the code used the correct names.

Suggested change

	self.key_cache.shape[1], attn_metadata.decode.
	num_computed_tokens_of_cp_dcp[:, self.cp_rank, self.dcp_rank],
	self.key_cache.shape[1], attn_metadata.decode_meta.
	num_computed_tokens_of_pcp_dcp[:, self.pcp_rank, self.dcp_rank],

[github-actions]

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