[Bugfix][ROCm][Attention] Add missing record_logical_topk_ready to sparse MLA impls

[HzTTT]

Purpose

MultiHeadLatentAttentionWrapper.forward_native calls self.mla_attn.impl.record_logical_topk_ready() on every sparse MLA layer (vllm/model_executor/layers/mla.py:235). The hook only exists on SparseMLACommonImpl; ROCMAiterMLASparseImpl and XPUMLASparseImpl inherit MLAAttentionImpl + SharedTopkIndicesBuffer directly, so serving GLM-5.3-Flash (Glm5NextForConditionalGeneration) on ROCm crashes at model load:

RuntimeError: Worker failed with error ''ROCMAiterMLASparseImpl' object
has no attribute 'record_logical_topk_ready''

The hook records an event for HiSparse host-resident top-k prefetching via the optional SparseMLAIndexGroup. Neither affected backend ever receives an index group (GLM-5.3-Flash allocates only the shared topk_indices_buffer; no builder is passed to ROCm/XPU impls), so the correct semantics for them is a no-op — the same default SparseMLACommonImpl already provides when self.index_group is None.

Changes

• Add a no-op record_logical_topk_ready default to the MLAAttentionImpl base class (next to the existing prepare_for_batch no-op), so every current and future sparse MLA implementation satisfies the interface.
• Drop the now-redundant # type: ignore[attr-defined] at both call sites (mla.py, deepseek_v32/attention.py).
• SparseMLACommonImpl keeps its index-group-aware override (asserted by a test).

Duplicate-work check: no open PR addresses this (gh pr list --search "record_logical_topk_ready" is empty; fwht/glm5next searches return unrelated refactor #55358, which moves files but does not touch the hook or fp8 dtype).

Test Plan

pytest tests/v1/attention/test_sparse_mla_topk_ready_hook.py -v

CPU-only; no accelerator required (skip_global_cleanup avoids the conftest teardown).

Test Result

Unit tests: 5 passed on the fix; 4 failed / 1 passed with the fix stashed (negative control — the direct-impl tests fail pre-fix exactly on the missing attribute):

tests/v1/attention/test_sparse_mla_topk_ready_hook.py::test_mla_attention_impl_base_provides_default_hook PASSED
tests/v1/attention/test_sparse_mla_topk_ready_hook.py::test_sparse_common_impl_still_overrides_hook PASSED
tests/v1/attention/test_sparse_mla_topk_ready_hook.py::test_direct_sparse_impls_satisfy_hook[rocm_aiter_mla_sparse-ROCMAiterMLASparseImpl] PASSED
tests/v1/attention/test_sparse_mla_topk_ready_hook.py::test_direct_sparse_impls_satisfy_hook[xpu_mla_sparse-XPUMLASparseImpl] PASSED
tests/v1/attention/test_sparse_mla_topk_ready_hook.py::test_stub_impls_flow_through_wrapper_hook PASSED
======================== 5 passed, 15 warnings in 0.05s ========================

End-to-end on 8× MI308X (gfx942), GLM-5.3-Flash TP8 + MTP-3, vllm/vllm-openai-rocm:nightly:

• Before: engine fails to initialize (AttributeError above); the server never becomes healthy.
• After: healthy serving — GSM8K spot checks 4/4, long-context probes 40K/65K/128K complete cleanly, MTP-3 decode ~140 tok/s single-stream.

Related issues

• The hook was introduced with HiSparse host-resident prefetching ([3/N] HiSparse: host-resident sparse-MLA decode hot-buffering #53781, NVIDIA-only). The ROCm sparse backend predates it and was never updated for the new call-site contract.

AI assistance was used for investigation, implementation, and this description.

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[HzTTT]

Hi @tjtanaa @dllehr-amd — ROCm sparse-MLA fix in your area. MultiHeadLatentAttentionWrapper calls impl.record_logical_topk_ready() on every sparse layer, but ROCMAiterMLASparseImpl (and XPUMLASparseImpl) don't inherit SparseMLACommonImpl, so GLM-5.3-Flash on ROCm fails at model load with AttributeError. Fix adds the no-op default to the MLAAttentionImpl base next to the existing prepare_for_batch no-op. Unit tests are CPU-only. Could you take a look when you have a moment?