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[None][test] Validate Kimi default KVCM V2 accuracy and disaggregated transfer - #19387
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WalkthroughTests cover Kimi’s default KV cache manager selection and KDA transfers with both V1 and V2 Mamba cache managers. The Python/NIXL routing test and waiver identify the explicit V1 configuration. Model documentation describes the manager selection and related caching settings. ChangesKimi Cache Manager Test Coverage
Priority: ⬇️ Low Estimated code review effort: 3 (Moderate) | ~20 minutes Change: Other Suggested reviewers: Merge Risk: 🔵 Low · up to
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Check name Status Explanation Linked Issues check Check skipped because no linked issues were found for this pull request. Out of Scope Changes check Check skipped because no linked issues were found for this pull request. Description Check Check skipped - CodeRabbit’s high-level summary is enabled. Title check The title clearly summarizes the main changes: validating Kimi default KVCM V2 accuracy and disaggregated transfer. The "[None]" prefix is unnecessary noise but does not make the title misleading.
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In `@tensorrt_llm/_torch/models/modeling_kimi_linear.py`:
- Line 2123: Add a Kimi-specific NIXL test in the existing cache-manager test
suite that resolves the automatic KV-cache-manager and Python transceiver
settings, then calls get_kv_cache_manager_cls with is_disagg=True and asserts
the result is MambaHybridCacheManagerV2.
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docs/source/features/kvcache.mdtensorrt_llm/_torch/models/modeling_kimi_linear.pytests/unittest/_torch/executor/kv_cache/test_mamba_cache_manager.pytests/unittest/llmapi/test_llm_args.py
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This test still enforces v1 KVCM.
We should check on the "V2 x KDA-hybrid long-generation path" mentioned.
@eopXD I have several fix for the scheduler deadlock issue, will test it to see whether I've fixed the issue or not |
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Sounds good! Thank you. |
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Description
Remove the explicit
use_kv_cache_manager_v2=Falseoverride fromTestKimiK3::test_gpqa_diamond_w4a16_mxfp4so the existing GPQA Diamond case exercises the current default V2 manager. The global default is alreadyTrueon main through #17495; this PR does not add a Kimi model preference or change aggregated/disaggregated serving defaults.Add a regression checking that Kimi's default cache configuration resolves to
MambaHybridCacheManagerV2with the Python NIXL transceiver in disaggregated serving. Extend the existing real NIXL KDA loopback test to cover both V1 and V2 managers across six matched/heterogeneous TP and attention-DP configurations, checking BF16 convolution and FP32 recurrent state bitwise on the generation side. The V2 fixture allocates context and generation caches through the scheduler-facing APIs before preparing the batch; the Kimi model mock supplies the currentmappingandspec_configdefaults. Rename the explicit V1 routing regression and its existing NVBug 6818710 waiver to make that configuration clear.Correct the Kimi cache overview, block-reuse rationale, and manager-routing comments to distinguish the configured
use_kv_cache_manager_v2=Truedefault from model-preference-based"auto"resolution.KimiLinearForCausalLMdeclares no V2 preference, so"auto"falls back to V1; V1 compatibility routes therefore cover both explicitFalseand resolved"auto". Block reuse remains opt-in because its combination with SA speculative decoding is not validated. These are documentation-only changes.The GPQA workload, 198-sample dataset, accuracy threshold, and GB300 16-GPU CI stage remain unchanged. The KDA transfer module is already selected by B200 CI, and the new default-V2 routing regression is not waived.
For the historical long-generation concern, #19202 fixes retained KV claims after failed first-context admission, and #19235 adds scheduler preemption and improves no-progress detection. Both are present in the rebased head and the earlier GPQA-tested head. They address related failure modes; the original Kimi hang has not been attributed to either fix. The full-workload evidence and its limitations are recorded below.
Test Coverage
Rebased onto main at
a8d7911bed9bcfa75bc01bd6413411bd702f528c. Local regression results cover the test changes in1a6a6c3de59934ffcc683667fdfea61808002835. The subsequent documentation commits change only comments/docstrings; comparison of both modified modules confirms their executable ASTs are unchanged from the tested version.cpp/buildtree withscripts/build_wheel.py --clean, regenerate FMHA sources, and fetch dependencies again. All native targets and stub generation completed with exit 0. Runtime: Python 3.12, NVIDIA PyTorch 2.14.0a0 nv26.09, CUDA 13.4, NIXL 1.4.0. Native sources are unchanged between the build commit0cc4d14and the final test-only commit.umbriel-b200-034,tests/unittest/disaggregated/test_kda_mamba_transfer.py: 24 passed, no failures/errors/skips, exit 0. This includes all 12 real NIXL transfer cases (V1/V2 across six TP/attention-DP configurations), bitwise BF16/FP32 state checks, transfer-byte accounting, and descriptor/peer validation.tests/unittest/_torch/executor/kv_cache/test_mamba_cache_manager.py -k kimi: 16 passed, 170 deselected, no failures/errors/skips, exit 0. Includes default V2 selection withis_disagg=True, explicit V1 compatibility, rejected unsupported transceiver routes, and KDA state geometry/replay configuration./tmpas the external launch CWD and absolute test paths, with the project's sys.path guard enabled. Full stdout/stderr and JUnit artifacts are retained under/home/scratch.yizhan_sw_1/logs/2026-10-13/umbriel-b200-034/.674b75bbcdf61c5c310f32012d61c04bdfb9a062: 198 samples, TP16/EP16, MXFP4, and the original 32K output limit. All 16 ranks selectedMambaHybridCacheManagerV2. Accuracy was 88.8889% (176/198), above the unchanged 85.234% threshold. JUnit recorded 1 passed, 0 failures, 0 errors, 0 skips.git diff --checkpassed for the final diff.The disaggregated test is a single-node NIXL loopback with real GPU state tensors and mocked rank collectives. It does not cover full-model context/generation inference, cross-node transport, or SA with block reuse. UCX reported no accelerated IB support on this node; these tests validate loopback correctness, not network performance.
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MambaHybridCacheManagerV2and the Python transceiver runtime. The explicit V1 routing test and its NVBug waiver selector now identify that scope.QA Engineer Review
Four test-related files changed: three test-code files and
tests/integration/test_lists/waives.txt. The changes cover Kimi cache-manager routing and KDA state transfer. The KDA test is in the B200 CI list; the GPQA test is in the GB300 4-node CI list. The affected unit tests have waiver entries, but no CI or manual-QA list entry for that unit-test file was found. Coverage verdict: needs follow-up.Per-File QA Perspective
tests/unittest/_torch/executor/kv_cache/test_mamba_cache_manager.py— Adds a regression for Kimi’s default V2 route with Python NIXL and renames the explicit V1 routing test. The affected tests have entries inwaives.txt; notest-db/orqa/entry for this file was found.tests/integration/defs/accuracy/test_kimi3.py— Removes the explicit V1 override so the GPQA test uses the default manager selection. The test is listed in the GB300 4-node CI list.tests/integration/test_lists/waives.txt— Renames the explicit V1 Kimi routing waiver selector; the NVBug reference remains unchanged. This changes test waiver matching.tests/unittest/disaggregated/test_kda_mamba_transfer.py— Adds V1/V2 loopback transfer coverage across six TP and attention-DP configurations, including bitwise state checks. The test is listed intests/integration/test_lists/test-db/l0_b200.yml.