[v0.13.0][bugfix][accuracy] Fix ds indexer accuracy problem caused by k rope

[rjg-lyh]

What this PR does / why we need it?

The rotary algorithm in deepseek indexer should be neox-style instead of gptj style. PR #4641 fix this accuracy bug in original pytorch version. But PR #5701 accidentally removed the fixed code line and reverted the implementation back to the problematic version. This PR fixes it.

Does this PR introduce any user-facing change?

No.

How was this patch tested?

CI passed with new added/existing test.

[gemini-code-assist]

Summary of Changes

Hello, I'm Gemini Code Assist¹! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request addresses an accuracy regression in the DeepSeek indexer component. By correcting the rotary embedding application method to align with the expected NeoX-style implementation, the patch ensures consistent and accurate model behavior, resolving an issue introduced by a previous code reversion.

Highlights

• Rotary Embedding Correction: Updated the DeepSeek indexer to use the correct rotary embedding implementation by switching from npu_interleave_rope to npu_rotary_mul.
• Regression Fix: Restored the correct NeoX-style rotary algorithm that was inadvertently reverted in a previous pull request.

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[gemini-code-assist]

Code Review

Suggested PR Title:\n\nmarkdown\n[Attention][Misc] Update rotary embedding function in sfa_v1\n\n\nSuggested PR Summary:\n\nmarkdown\n### What this PR does / why we need it?\nThis PR updates the `indexer_select_pre_process` function in `vllm_ascend/attention/sfa_v1.py` by replacing the `torch_npu.npu_interleave_rope` call with `torch_npu.npu_rotary_mul`. This change ensures the attention mechanism uses the correct rotary multiplication operation for the key positional embeddings.\n\n### Does this PR introduce _any_ user-facing change?\nNo.\n\n### How was this patch tested?\nCI passed with existing tests.\n\n\nI have no feedback to provide.