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[TRTLLM-17600][test] Run the per-ID B300 and DGX B300 MoE entries in one pytest process per function - #21797
Part of the MoE unit-test optimization (TRTLLM-17600): consolidate the B300 and DGX B300 MoE entries that are split by parameter ID.
l0_b300.yml and l0_dgx_b300.yml list a curated set of MoE module and Kimi K3 SiTu cases with one parameter ID per entry. Each entry is its own pytest process, so every case pays its own costs: the interpreter and tensorrt_llm import, collection of the whole parameter grid (1466 IDs for test_configurable_moe_single_gpu, 1926 for test_configurable_moe_multi_gpu), and on DGX B300 a new 4-rank MPI pool. Those costs are most of each entry's 20–50 s.
This PR lists the same node IDs, space-separated, on one entry per test function. test_unittests.pyshlex.splits an entry and passes every token to one pytest process. The cases therefore share one startup and one collection, and a node ID that no longer exists still fails the entry with ERROR: not found, just as the per-ID entries did.
List
Replaced
With
l0_b300
10 test_configurable_moe_single_gpu[...] entries
1 entry with those 10 node IDs
l0_b300
7 Kimi K3 SiTu cases that run MoE kernels
1 entry with those 7 node IDs
l0_dgx_b300
10 test_configurable_moe_multi_gpu[...] entries
1 entry with those 10 node IDs
l0_dgx_b300
3 test_configurable_moe_multi_gpu_eplb[...] entries + its -k "MEGAMOE_DEEPGEMM" and -k "MEGAMOE_CUTEDSL" entries
1 entry with those 5 node IDs
The cases that run are unchanged. The node IDs are copied verbatim from the replaced entries. The two MegaMoE EPLB -k entries each selected exactly one ID; they are now listed by that ID, so they too fail on a stale ID instead of silently selecting nothing.
Left for TRTLLM-17601:
The other 19 single-case entries in the Kimi K3 block. The B200 whole-file run already covers them.
The 3 DGX B300 e256 multi-GPU IDs. In CI mode, rule 1 in moe_test_utils.py runs e256 shapes only with DeepSeekV3 routing, bfloat16 and seq=1, so these always skip. A comment above them now says so.
.test_durations. The keys of the 32 replaced entries are swapped for the 4 merged entries. Each estimate is the sum of the replaced entries' recorded durations minus the per-entry startup measured on B200 (see below).
Expected effect per run (from the recorded durations):
Stage
Before
After (estimate)
Saved
B300-PyTorch (2 shards, sum)
335.1 s + 180.8 s
116.2 s + 53.8 s
about 5.8 min
DGX_B300-4_GPUs-PyTorch-1
541.1 s + 265.3 s
160.2 s + 158.3 s
about 8.1 min (about 0.54 GPU-h)
No production code changes.
Test Coverage
No new tests; the change only regroups existing entries. Run on main (345e0f1315) with the post-merge 3067 wheel (9a17f9b385, 16 commits behind; no change to the MoE tests or tensorrt_llm/_torch/moe in between) and pytest 9.0.3, the version pinned in requirements-dev.txt:
CI path.
trt-test-db 1.8.5 (pinned in jenkins/ci_versions.properties) renders the four entries intact.
pytest -p stubify_bindings --test-list=<those 4 lines> --co in tests/integration/defs collects them as 4 test_unittests_v2[...] items.
Built the inner command the way test_unittests.py does: shlex.split the entry, cwd=tests/, --ignore=tests/integration, and the GPU stages' -m "not cpu_only". --collect-only then returns exactly the listed IDs: 7/7, 10/10, 5/5 and 10/10.
Stale IDs fail. Appending a non-existent node ID to an entry makes it exit with code 4 and ERROR: not found.
The merged groups run like the per-ID entries. Each group's cases ran in one pytest process on B200 (SM100; no B300 was available), and so did each per-ID entry. Per-case results are identical in every group:
Group
One process, wall
Per-ID entries, total wall
Result (one process = per-ID)
B300 single-GPU module
82.0 s
300.9 s (10 runs)
10 passed
B300 Kimi K3 kernels
54.1 s
181.1 s (7 runs)
7 passed
DGX B300 multi-GPU module
108.8 s
489.7 s (10 runs)
7 passed, 3 failed
DGX B300 EPLB
27.3 s
134.3 s (5 runs)
5 skipped
The 3 multi-GPU failures are the NVLINK_ONE_SIDED cases. They fail the same way when run alone: pidfd_getfd ... Operation not permitted, because the container lacks --cap-add=SYS_PTRACE.
The EPLB cases skip because this host lacks host-accessible device memory.
So the DEEPEP → NVLINK_ONE_SIDED → MegaMoE sequence in one process has not yet run end to end; CI on the DGX B300 node is where it does.
python scripts/check_test_list.py --validate: OK.
python scripts/test_to_stage_mapping.py: the two l0_b300 entries map to B300-PyTorch-1/2, and the two l0_dgx_b300 entries map to DGX_B300-4_GPUs-PyTorch-1.
To confirm in CI: the inner pytest summaries should show 10 + 7 cases on B300-PyTorch-* and 10 + 5 on DGX_B300-4_GPUs-PyTorch-1, with the same results as the per-ID entries. l0_dgx_b300.yml is in the multi-GPU trigger list, so the DGX B300 stage runs on this PR. I will post those summaries after the run.
PR Checklist
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Dev Engineer Review
The change touches three files: tests/integration/test_lists/test-db/l0_b300.yml (+5/-21), tests/integration/test_lists/test-db/l0_dgx_b300.yml (+9/-21), and tests/integration/defs/.test_durations (+8/-64). No production code or public API changed.
The test-list edits mostly regroup existing node IDs. Each group is one YAML entry with space-separated node IDs, so each group runs in one pytest process. The l0_b300 diff shows the same Kimi K3 SiTU and single-GPU MoE IDs as before. The l0_dgx_b300 multi-GPU IDs also match the old list.
The EPLB change is not a pure regrouping. Two -k "MEGAMOE_..." selectors become four explicit IDs with slots=16-eplb=dynamic. This diff does not show that these IDs exist. Stale IDs fail with ERROR: not found instead of selecting no tests.
Shared-process execution reduces test isolation. A crash or hang in one case can affect the other cases in its group. Failure attribution also depends on the per-test output.
The three e256 multi-GPU entries remain. A new comment states that they always skip in CI mode and references TODO(TRTLLM-17601).
The .test_durations file replaces per-case timing records with grouped-command records. Durations for grouped commands reflect the shared process, not single cases.
QA Engineer Review
Modified test-list files: tests/integration/test_lists/test-db/l0_b300.yml and tests/integration/test_lists/test-db/l0_dgx_b300.yml. The duration file tests/integration/defs/.test_durations also changed.
No test functions were added or modified. No waivers were changed.
l0_b300: Kimi K3 SiTU kernel and reference tests, and the test_configurable_moe_single_gpu cases (CUTLASS, TRTLLM, CUTEDSL, DEEPGEMM), now run as grouped entries.
l0_dgx_b300: The test_configurable_moe_multi_gpu cases now run as grouped entries, including MEGAMOE_DEEPGEMM and MEGAMOE_CUTEDSL. The EPLB -k selectors for the MegaMoe backends are replaced by explicit dynamic-EPLB node IDs.
Reported validation: the author's CI run on an earlier commit with the same patch passed the two l0_b300 entries (7 and 10 items). The two l0_dgx_b300 entries did not run because the ci: full pre-merge approved label was missing. The author's earlier B200 runs covered the multi-GPU and EPLB cases, but not on DGX B300. Current CI completion for the DGX B300 entries is not available.
Coverage verdict: needs follow-up. Confirm that the new EPLB node IDs exist and that the DGX B300 grouped entries run to completion.
Per-File QA Perspective
tests/integration/defs/.test_durations: Replaces per-case duration records with grouped-command records. Verify that the recorded durations match the grouped runs.
tests/integration/test_lists/test-db/l0_b300.yml: Groups existing Kimi K3 SiTU and single-GPU MoE node IDs into shared-process entries. Verify that all listed cases still run.
tests/integration/test_lists/test-db/l0_dgx_b300.yml: Groups multi-GPU MoE node IDs. Replaces the MegaMoe EPLB -k selectors with explicit IDs. Verify that the new IDs exist and that the e256 skip entries remain documented.
No actionable comments were generated in the recent review.
Walkthrough
The B300 list groups Kimi K3 SiTU and single-GPU MoE tests into shared pytest commands. The DGX B300 list groups multi-GPU MoE and EPLB cases, updates the e256 note, and adds matching duration records.
Changes
Integration test selection
Layer / File(s)
Summary
B300 Kimi and single-GPU test commands tests/integration/test_lists/test-db/l0_b300.yml, tests/integration/defs/.test_durations
The B300 list adds Kimi K3 SiTU checks, groups Kimi kernel and reference tests, and consolidates single-GPU MoE cases. The duration file combines timings for selected Kimi and single-GPU tests.
DGX B300 multi-GPU and EPLB commands tests/integration/test_lists/test-db/l0_dgx_b300.yml, tests/integration/defs/.test_durations
The list groups multi-GPU MoE cases and EPLB cases, updates the e256 note, and replaces EPLB filters with explicit parameterized cases. The duration file adds records for selected multi-GPU and EPLB tests.
Possibly related PRs
NVIDIA/TensorRT-LLM#22111 — Changes the same B300 and DGX B300 test-list entries and duration records.
Suggested reviewers: xinhe-nv, juney-nvidia
Change: Other
Merge Risk: Minimal · up to bf52c
This PR regroups CI test selection and updates timing records. The earlier risk of silently selecting no tests has been addressed by using explicit node IDs for the multi-GPU MoE and EPLB cases. The DGX B300 stage still needs to run in CI to confirm the grouped commands.
Architecture risk: Low · up to bf52c
The change affects 1 system.
Changed systems:tests
Architecture concerns
No architecture-level concerns identified.
Review details
Systems and components
observed — tests (service) was modified; 3 changed files map to changed impact.
Before / after behavior
observed — Modified behavior in tests/integration/defs/.test_durations: The Kimi K3 SiTU duration entries combine several test cases into one shared timing record, replacing the separate timings for the BF16 reference and CUTEDSL cache-key tests.
observed — Modified behavior in tests/integration/defs/.test_durations: Separate duration records for the NVFP4 expert-reference, kernel SiTU, and streamed-expert tests were removed; their tests are included in the combined record at lines 2021–2022.
observed — Modified behavior in tests/integration/defs/.test_durations: Adds combined timing records for selected multi-GPU MoE cases and EPLB cases across backends, quantization modes, and communication configurations.
observed — Modified behavior in tests/integration/defs/.test_durations: Combines selected single-GPU MoE test cases across backends and quantization modes into one shared duration record, replacing their individual timings.
Pre-merge checks: 4
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The title names the change: the per-ID B300 and DGX B300 MoE entries are run in one pytest process per test function. It follows the [JIRA ticket][type] Summary pattern and matches the PR's main chang…
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The title names the change: the per-ID B300 and DGX B300 MoE entries are run in one pytest process per test function. It follows the [JIRA ticket][type] Summary pattern and matches the PR's main change, which the description and objectives confirm.
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The description follows the repository template. It has a clear Description section that explains the problem (per-ID pytest startup and collection costs) and the fix (grouping node IDs per test function). It gives a Test Coverage section with the validation steps and results, and it includes the PR checklist. The checklist is marked as reviewed. The description does not use the template's HTML comment prompts, but all required content is present. Test results on B200 are stated, and the DGX B300 end-to-end run is noted as pending CI.
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Check that the selector retains all ten intended cases.
A parameter-ID change can remove one case from this -k selection while the remaining cases pass. The previous individual node IDs would fail when an ID became stale. Check the selected IDs against the intended cases; a zero-match check alone is not enough.
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Review comment at @tests/integration/test_lists/test-db/l0_dgx_b300.yml at line
108:
Update the test_configurable_moe_multi_gpu selector validation to verify that
all ten intended cases are selected, not merely that the -k expression matches
at least one case; fail when any intended case is omitted, including after a
parameter ID changes.
With 188 multiprocessors, 4096 slots require 22 warp groups. The current cases would still pass if the check incorrectly rejected exactly 14 warp groups. Add a fitting case with 2632 slots and a rejected case with 2633 slots. These cases exercise the stated 14-group limit directly. (raw.githubusercontent.com)
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Review comment at @tests/unittest/_torch/moe/test_communication_factory.py at
line 296:
Update the communication-factory test cases around the 4096-slot entry to cover
the 14-warp-group boundary directly: add a fitting case with 2632 slots and a
rejected case with 2633 slots, preserving the existing expected-result format.
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Review comments at @tests/integration/test_lists/test-db/l0_dgx_b300.yml:
- Line 108: Update the test_configurable_moe_multi_gpu selector validation to
verify that all ten intended cases are selected, not merely that the -k
expression matches at least one case; fail when any intended case is omitted,
including after a parameter ID changes.
Review comments at @tests/unittest/_torch/moe/test_communication_factory.py:
- Line 296: Update the communication-factory test cases around the 4096-slot
entry to cover the 14-warp-group boundary directly: add a fitting case with 2632
slots and a rejected case with 2633 slots, preserving the existing
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This review covers only the one commit this PR adds on top of #21703 (015b201, "Merge the per-ID B300 and DGX B300 MoE entries into -k entries"); #21703's changes are reviewed in that PR. I evaluated the four new expressions with pytest's own -k parser against the CI-mode parameter grid, and they select exactly the replaced 10/7/10/5 cases. The test-list parser, test_unittests.py, the new .test_durations keys, CBTS and waives all handle the new lines. Counts: 0 blockers, 0 possibly blocking, 1 required, 4 nice to have (3 inline, 1 below).
[Required] Please delete the auto-generated CodeRabbit block at the top of the description, or regenerate it after rebasing onto main once #21703 merges. It summarizes #21703's A10/B200/RTX PRO 6000 list edits and six test files. It also says it could not verify anything ("Test execution and current-head validation results are not available", "Coverage verdict: needs follow-up"). After the rebase it will describe changes this PR does not make. The PR template asks: "If using CodeRabbit's summary, please make sure it makes sense." Your hand-written Description section already covers everything.
[Nice to have] CI has not run on this head yet. In the B200 runs cited in the description, all 5 EPLB cases skipped and the 3 NVLINK_ONE_SIDED cases failed on container permissions. So the DEEPEP → NVLINK_ONE_SIDED → MegaMoE sequence in one shared MPI pool has not run anywhere yet. MoE entries write their inner results to moe-results-sub-unittests-*.xml, which the stage does not collect (test_unittests.py:260-275), so the stage JUnit only shows the outer test_unittests_v2 result. After /bot run, please post the inner pytest summaries: 10 + 7 cases on B300-PyTorch and 10 + 5 on DGX_B300-4_GPUs-PyTorch-1 (or their -cbts variants), with the same pass/skip results as the per-ID entries.
- unittest/_torch/moe/test_kimi_k3_situ_moe.py -k "test_nvfp4_streamed_experts_forward_runs or test_cutlass_situ_bf16_matches_reference or test_nvfp4_kernel_actually_applies_situ[CUTEDSL] or test_nvfp4_kernel_actually_applies_situ[TRTLLM] or test_cutedsl_situ_betas_reach_the_kernel_cache_key or test_nvfp4_experts_match_situ_reference[CUTLASS-static_1.0] or test_nvfp4_experts_match_situ_reference[TRTLLM-static_1.0]"
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[Nice to have] Selecting by substring -k loses the failure the explicit IDs gave when a listed case no longer exists. pytest fails a missing node ID with "not found" (exit 4), but a -k clause that matches nothing is just false; only an empty selection fails. scripts/check_test_list.py --validate reads only the first token (if "::" not in token: return None, L84-86), so it now skips this entry entirely; it used to check these 7 test names and 4 parameter IDs. A later rename of one of these tests, or of a quant/backend value or ID field in test_moe_module.py, would then silently drop that case on B300/DGX B300 while the stage stays green. The same applies to l0_b300.yml:120 and l0_dgx_b300.yml:108/:115. Likewise, on a DGX B300 node whose NVLink probe fails (test_moe_module.py:1110-1115 drops DEEPEP/NVLINK_ONE_SIDED from the grid), the merged entries run only their 2 + 2 MegaMoE cases. Today only the three e256 per-ID entries left at l0_dgx_b300.yml:109-111 would still fail on such a node. Suggestion: test_unittests.py shlex-splits the case into one pytest process, so you can list the exact node IDs space-separated on one line. That keeps the single startup and the "not found" failure. Alternatively, commit the equivalence script you ran as a test that pins the 10/7/10/5 selections.
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Agreed, and thanks for the pointer to the shlex split. Each merged entry now lists the exact node IDs space-separated, so test_unittests.py runs them in one pytest process and a stale ID still fails the entry: appending a non-existent ID returns exit code 4 with ERROR: not found. This also covers the NVLink-probe case. If DEEPEP / NVLINK_ONE_SIDED drop out of the grid on a node, those IDs are not found and the entry fails, as the per-ID entries did. The two MegaMoE EPLB -k entries are now listed by their one ID each, too. check_test_list.py --validate still reads only the first token, but the runtime not found now catches the rest.
# DeepSeekV3 routing: IGNORE e8 MEGAMOE_DEEPGEMM W4A8_MXFP4_MXFP8 and MEGAMOE_CUTEDSL NVFP4.
- unittest/_torch/moe/test_moe_module.py::test_configurable_moe_multi_gpu -k "DEP-comm and bfloat16 and ((Renormalize] and ((DEEPEP-e60_k4_h2048_i1408 and ((CUTLASS-quant and FP8-routing and not MXFP8-routing and not W4A8) or (TRTLLM-quant and W4A8_NVFP4_FP8) or (CUTEDSL-quant and NVFP4-routing) or (DEEPGEMM-quant and FP8_BLOCK_SCALES))) or (NVLINK_ONE_SIDED-e60_k4_h2048_i1408 and CUTLASS-quant and (NVFP4-routing or W4A8_MXFP4_MXFP8)) or (DEEPEP-e8_k1_h512_i512 and TRTLLM-quant and NVFP4-routing) or (NVLINK_ONE_SIDED-e8_k1_h512_i512 and TRTLLM-quant and W4A8_MXFP4_MXFP8))) or (DeepSeekV3 and IGNORE-e8_k1_h512_i512 and ((MEGAMOE_DEEPGEMM-quant and W4A8_MXFP4_MXFP8) or (MEGAMOE_CUTEDSL-quant and NVFP4-routing))))"
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[Nice to have] Unlike the single-GPU entry, this expression has no not MEGAMOE. CUTEDSL-quant and DEEPGEMM-quant also match MEGAMOE_CUTEDSL-quant and MEGAMOE_DEEPGEMM-quant, and the main generator keeps the MegaMoE backends in its list (test_moe_module.py:1749-1756). The selection is exactly 10 today only because the MegaMoE skip rejects DEEPEP comm. The expression also has no seq pin, so with TRTLLM_TEST_MOE_CI=0 it adds the 10 seq=1 twins. Suggest DEP-comm and 8-dtype and bfloat16 and ((Renormalize] and not MEGAMOE and (...)) or (DeepSeekV3 and ...)), which selects the same 10 IDs in both CI and local mode.
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No longer applies: this entry now lists the 10 node IDs instead of a -k expression, so it selects the same 10 cases in CI and local mode, with or without the MegaMoE skip.
# DeepSeekV3 routing: IGNORE e8 MEGAMOE_DEEPGEMM W4A8_MXFP4_MXFP8 and MEGAMOE_CUTEDSL NVFP4.
- unittest/_torch/moe/test_moe_module.py::test_configurable_moe_multi_gpu -k "DEP-comm and bfloat16 and ((Renormalize] and ((DEEPEP-e60_k4_h2048_i1408 and ((CUTLASS-quant and FP8-routing and not MXFP8-routing and not W4A8) or (TRTLLM-quant and W4A8_NVFP4_FP8) or (CUTEDSL-quant and NVFP4-routing) or (DEEPGEMM-quant and FP8_BLOCK_SCALES))) or (NVLINK_ONE_SIDED-e60_k4_h2048_i1408 and CUTLASS-quant and (NVFP4-routing or W4A8_MXFP4_MXFP8)) or (DEEPEP-e8_k1_h512_i512 and TRTLLM-quant and NVFP4-routing) or (NVLINK_ONE_SIDED-e8_k1_h512_i512 and TRTLLM-quant and W4A8_MXFP4_MXFP8))) or (DeepSeekV3 and IGNORE-e8_k1_h512_i512 and ((MEGAMOE_DEEPGEMM-quant and W4A8_MXFP4_MXFP8) or (MEGAMOE_CUTEDSL-quant and NVFP4-routing))))"
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[Nice to have] These three e256 IDs lost their backend comments, and the comment above now describes only the merged entry. A one-line note would keep the reason in the file, e.g. # e256 IDs: skipped in CI mode by should_skip_to_accelerate_ci (rule 1: DeepSeekV3, bfloat16, seq=1 only). TODO(TRTLLM-17601): remove.
rosong11
changed the title
[TRTLLM-17600][test] Merge the per-ID B300 and DGX B300 MoE entries into -k entries
[TRTLLM-17600][test] Run the per-ID B300 and DGX B300 MoE entries in one pytest process per function
Nov 11, 2026
Silent drop with -k: taken your suggestion. Each merged entry now lists the exact node IDs, space-separated. A stale ID fails the entry with ERROR: not found (rc 4), and the entries no longer need the substring expressions. Details are in the inline replies and the updated Test Coverage section.
CI evidence: triggering /bot run now. After it finishes I will post the inner pytest summaries for the 10 + 7 cases on B300-PyTorch-* and the 10 + 5 on DGX_B300-4_GPUs-PyTorch-1.
Could you please rebase this branch onto the latest upstream main to include the CI hang fix in #22101 (6edbe383497a)? The current branch still contains the regression that can cause pipelines to hang for an extended period and worsen CI queueing
…one pytest process per function
B300 and DGX B300 listed MoE module and Kimi K3 SiTu cases one parameter
ID per entry, so each case paid its own pytest startup and collection of
the whole parameter grid, and on DGX B300 its own MPI pool. List the same
node IDs space-separated on one entry per test function instead;
test_unittests.py passes them to a single pytest process, and a node ID
that no longer exists still fails the entry with "not found":
- l0_b300: the 10 test_configurable_moe_single_gpu IDs, and the 7 Kimi K3
SiTu cases that run MoE kernels.
- l0_dgx_b300: the 10 test_configurable_moe_multi_gpu IDs other than the
three e256 ones, and the 5 test_configurable_moe_multi_gpu_eplb cases
(the two MEGAMOE -k entries each selected one ID; they are now listed
by ID).
Note why the three e256 IDs always skip in CI mode. Swap the
.test_durations keys of the replaced entries for the merged ones.
Signed-off-by: rosong11 <rosong@nvidia.com>
@hanjingtian Rebased onto main at 737bf56, which includes #22101 (6edbe383497a). The PR is now the single commit bf52cbb; the patch is unchanged.
CI results. L0_MergeRequest_PR #69491 ran on the previous head 04238d1, which has the same patch. CBTS selected only B300-PyTorch-1-cbts, and that stage ran both l0_b300 entries this PR changes. The inner pytest summaries below come from the uploaded stdout of each test_unittests_v2 item; the stage does not collect the moe-results-sub-unittests-*.xml files.
Entry
Inner pytest
Entry wall
Replaced per-ID entries (recorded)
Kimi K3 SiTu kernel cases
collected 7 items, 7 passed in 34.75s
54.6 s
7 entries, 180.8 s
test_configurable_moe_single_gpu
collected 10 items, 10 passed in 63.44s
80.0 s
10 entries, 335.1 s
All 17 cases are exactly the listed node IDs, and all pass.
The two l0_dgx_b300 entries (10 + 5 cases) did not run, because multi-GPU stages need the ci: full pre-merge approved label. I will post their summaries once the label is in place and CI is re-run on the new head.
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sunnyqgg
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LarryXFly
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Description
Part of the MoE unit-test optimization (TRTLLM-17600): consolidate the B300 and DGX B300 MoE entries that are split by parameter ID.
l0_b300.ymlandl0_dgx_b300.ymllist a curated set of MoE module and Kimi K3 SiTu cases with one parameter ID per entry. Each entry is its own pytest process, so every case pays its own costs: the interpreter andtensorrt_llmimport, collection of the whole parameter grid (1466 IDs fortest_configurable_moe_single_gpu, 1926 fortest_configurable_moe_multi_gpu), and on DGX B300 a new 4-rank MPI pool. Those costs are most of each entry's 20–50 s.This PR lists the same node IDs, space-separated, on one entry per test function.
test_unittests.pyshlex.splits an entry and passes every token to one pytest process. The cases therefore share one startup and one collection, and a node ID that no longer exists still fails the entry withERROR: not found, just as the per-ID entries did.l0_b300test_configurable_moe_single_gpu[...]entriesl0_b300l0_dgx_b300test_configurable_moe_multi_gpu[...]entriesl0_dgx_b300test_configurable_moe_multi_gpu_eplb[...]entries + its-k "MEGAMOE_DEEPGEMM"and-k "MEGAMOE_CUTEDSL"entriesThe cases that run are unchanged. The node IDs are copied verbatim from the replaced entries. The two MegaMoE EPLB
-kentries each selected exactly one ID; they are now listed by that ID, so they too fail on a stale ID instead of silently selecting nothing.moe_test_utils.pyruns e256 shapes only with DeepSeekV3 routing, bfloat16 and seq=1, so these always skip. A comment above them now says so..test_durations. The keys of the 32 replaced entries are swapped for the 4 merged entries. Each estimate is the sum of the replaced entries' recorded durations minus the per-entry startup measured on B200 (see below).Expected effect per run (from the recorded durations):
B300-PyTorch(2 shards, sum)DGX_B300-4_GPUs-PyTorch-1No production code changes.
Test Coverage
No new tests; the change only regroups existing entries. Run on
main(345e0f1315) with the post-merge 3067 wheel (9a17f9b385, 16 commits behind; no change to the MoE tests ortensorrt_llm/_torch/moein between) and pytest 9.0.3, the version pinned inrequirements-dev.txt:CI path.
trt-test-db1.8.5 (pinned injenkins/ci_versions.properties) renders the four entries intact.pytest -p stubify_bindings --test-list=<those 4 lines> --cointests/integration/defscollects them as 4test_unittests_v2[...]items.test_unittests.pydoes:shlex.splitthe entry,cwd=tests/,--ignore=tests/integration, and the GPU stages'-m "not cpu_only".--collect-onlythen returns exactly the listed IDs: 7/7, 10/10, 5/5 and 10/10.Stale IDs fail. Appending a non-existent node ID to an entry makes it exit with code 4 and
ERROR: not found.The merged groups run like the per-ID entries. Each group's cases ran in one pytest process on B200 (SM100; no B300 was available), and so did each per-ID entry. Per-case results are identical in every group:
NVLINK_ONE_SIDEDcases. They fail the same way when run alone:pidfd_getfd ... Operation not permitted, because the container lacks--cap-add=SYS_PTRACE.python scripts/check_test_list.py --validate: OK.python scripts/test_to_stage_mapping.py: the twol0_b300entries map toB300-PyTorch-1/2, and the twol0_dgx_b300entries map toDGX_B300-4_GPUs-PyTorch-1.To confirm in CI: the inner pytest summaries should show 10 + 7 cases on
B300-PyTorch-*and 10 + 5 onDGX_B300-4_GPUs-PyTorch-1, with the same results as the per-ID entries.l0_dgx_b300.ymlis in the multi-GPU trigger list, so the DGX B300 stage runs on this PR. I will post those summaries after the run.PR Checklist
Please review the following before submitting your PR:
PR description clearly explains what and why. If using CodeRabbit's summary, please make sure it makes sense.
PR Follows TRT-LLM CODING GUIDELINES to the best of your knowledge.
Test cases are provided for new code paths (see test instructions)
If PR introduces API changes, an appropriate PR label is added - either
api-compatibleorapi-breaking. Forapi-breaking, includeBREAKINGin the PR title.Any new dependencies have been scanned for license and vulnerabilities
CODEOWNERS updated if ownership changes
Documentation updated as needed
Update tava architecture diagram if there is a significant design change in PR.
The reviewers assigned automatically/manually are appropriate for the PR.
Please check this after reviewing the above items as appropriate for this PR.
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/bot help.Dev Engineer Review
tests/integration/test_lists/test-db/l0_b300.yml(+5/-21),tests/integration/test_lists/test-db/l0_dgx_b300.yml(+9/-21), andtests/integration/defs/.test_durations(+8/-64). No production code or public API changed.l0_b300diff shows the same Kimi K3 SiTU and single-GPU MoE IDs as before. Thel0_dgx_b300multi-GPU IDs also match the old list.-k "MEGAMOE_..."selectors become four explicit IDs withslots=16-eplb=dynamic. This diff does not show that these IDs exist. Stale IDs fail withERROR: not foundinstead of selecting no tests.TODO(TRTLLM-17601)..test_durationsfile replaces per-case timing records with grouped-command records. Durations for grouped commands reflect the shared process, not single cases.QA Engineer Review
tests/integration/test_lists/test-db/l0_b300.ymlandtests/integration/test_lists/test-db/l0_dgx_b300.yml. The duration filetests/integration/defs/.test_durationsalso changed.l0_b300: Kimi K3 SiTU kernel and reference tests, and thetest_configurable_moe_single_gpucases (CUTLASS, TRTLLM, CUTEDSL, DEEPGEMM), now run as grouped entries.l0_dgx_b300: Thetest_configurable_moe_multi_gpucases now run as grouped entries, including MEGAMOE_DEEPGEMM and MEGAMOE_CUTEDSL. The EPLB-kselectors for the MegaMoe backends are replaced by explicit dynamic-EPLB node IDs.l0_b300entries (7 and 10 items). The twol0_dgx_b300entries did not run because theci: full pre-merge approvedlabel was missing. The author's earlier B200 runs covered the multi-GPU and EPLB cases, but not on DGX B300. Current CI completion for the DGX B300 entries is not available.Per-File QA Perspective
tests/integration/defs/.test_durations: Replaces per-case duration records with grouped-command records. Verify that the recorded durations match the grouped runs.tests/integration/test_lists/test-db/l0_b300.yml: Groups existing Kimi K3 SiTU and single-GPU MoE node IDs into shared-process entries. Verify that all listed cases still run.tests/integration/test_lists/test-db/l0_dgx_b300.yml: Groups multi-GPU MoE node IDs. Replaces the MegaMoe EPLB-kselectors with explicit IDs. Verify that the new IDs exist and that the e256 skip entries remain documented.