[Refactor][WIP] Refactor mla_v1 by moving all MLA preprocessing ops into mla_v1 attention impl.

[whx-sjtu]

In order to support fused kernels, multi-stream, communication optimization etc, it's better to aggregate all opreations in Attention layer togather. This PR tries to refactor mla_v1 by moving all MLA preprocessing ops into mla_v1 attention impl.
Later I will provide a diagram showing the structure of refactored mla_v1.
Note that new mla_v1 doesn't take torchair into consideration. So this PR can only be merged after torchair related mla_v1 is isolated into a new file.

• vLLM version: v0.10.0
• vLLM main: vllm-project/vllm@d983769

[gemini-code-assist]

Code Review

This pull request refactors the MLA v1 attention implementation by moving all preprocessing operations into the AscendMLAImpl class. This is a good architectural improvement that centralizes the attention logic and simplifies the model code. However, I've found two critical bugs in the new implementation in vllm_ascend/attention/mla_v1.py that will cause runtime errors due to incorrect function calls. Please see the detailed comments for fixes.

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