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[https://nvbugs/6997728][fix] Fix DeepSeek-V4-Pro DEP4 MegaMoE CuTe DSL test: skip HF weight cache for oversized checkpoints, drop hard GSM8K floor, fix bootstrap hang - #21225
accuracy/test_llm_api_pytorch.py::TestDeepSeekV4ProDSpark::test_gsm8k_dep4_megamoe_cutedsl has not passed in post-merge CI since it was added. In the CI logs its 30-minute limit expires while the LLM is still waiting for its executor workers to initialize. This change removes one cause of that wait: the raw HF weight cache reading the checkpoint from storage during worker initialization.
Root cause of the part fixed here. The test session-reuse layer sets TRTLLM_HF_WEIGHT_CACHE=1 for the MPI worker pools it manages, which turns on HfWeightLoader's raw-weight cache. The cache fingerprints every tensor of a checkpoint when it stores it (_fingerprint) and recomputes every fingerprint when a later load hits it (_get_cached_weights). SafeTensors weights are read from the file pages when a tensor is first accessed, so these passes read the checkpoint itself. On a GB300 node, loading four shards (58.7 GB) took 4.3 s and grew the process RSS by 0.6 GB; fingerprinting them then took 8.4 s and grew the page cache by 57.9 GB.
The test loads the 878.7 GiB NVFP4 DeepSeek-V4-Pro checkpoint twice, for the target model and for the DSpark drafter embedded in the same directory, on 4x GB300 nodes with 770-829 GiB of available host memory. Measured on main without this change:
checkpoint preparation took 924.7 s for the store and 707.7 s for the hit, against 27.1 s and 29.7 s with the cache turned off;
worker initialization took 2537 s;
with the test's 30-minute limit the test timed out in worker initialization, alone and after another test on the same worker pool, as in CI.
Fix. Each rank checks the checkpoint against its own available host memory with the admission the rank-striped read-ahead uses (memory_admission over effective_available_host_memory()). A load that fails it skips the cache lookup and store, and evicts the old entry before it loads, as a miss does. It runs the same collectives as a miss, so ranks that decide differently stay in step. Checkpoints that pass the admission are cached as before, and nothing changes when the cache is off.
Test Coverage
New tests in tests/unittest/_torch/models/checkpoints/hf/test_weight_loader.py: test_weight_cache_skips_checkpoint_larger_than_host_memory and test_cache_skip_issues_the_miss_collectives. Both fail without the change and pass with it. With the change, tests/unittest/_torch/models/checkpoints, tests/unittest/llmapi/test_session_reuse.py and tests/unittest/llmapi/test_session_prefetcher.py pass (228 passed; without the change 226 passed and the two new tests failed).
TestDeepSeekV4ProDSpark::test_gsm8k_dep4_megamoe_cutedsl on 4x GB300 with the CI image and a CI build of main, run as the CI stage runs it with its TIMEOUT (30). Nine runs had this change, five alone and four after another test on the same worker pool:
In eight runs the cache was skipped for both loads. Checkpoint preparation took 25-32 s, and 21-49 s for the drafter. Worker initialization took 893-968 s and the test ended after 958-1113 s. Six of these runs passed and two failed the accuracy assertion described below. The four runs of the final version of this change all passed.
In one run the workers never reached checkpoint loading. They hung in the MegaMoE CuTe DSL bootstrap described below until the 30-minute limit expired.
TestDeepSeekV4ProDSpark::test_gsm8k_megamoe_deepgemm[dp4] (831.4 GiB FP8 export, loaded the same way) passed in 15.5 minutes.
GSM8K accuracy assertion (second commit)
Besides the harness's hypothesis test (threshold 92.70), both TestDeepSeekV4ProDSpark tests asserted score >= ref_accuracy (95.9). That reference came from a single run, but greedy GSM8K on this path varies from run to run because the numerics depend on the batch (attention DP, DSpark acceptance and MegaMoE token counts change which requests share a batch). Eleven runs on 4x GB300, with and without the cache change, scored 95.72, 95.83, 95.87, 95.91, 95.94, 95.94, 96.10, 96.10, 96.17, 96.17 and 96.40 (mean 96.01, std 0.19). A 95.9 floor fails about 28% of such runs; 3 of 11 failed. The whole spread is about 9 of 1319 answers. All 11 runs pass the hypothesis test.
The second commit removes that assertion from test_gsm8k_dep4_megamoe_cutedsl and test_gsm8k_megamoe_deepgemm, so the score is gated by the hypothesis test as in the other accuracy tests. This matches #19554 (nvbugs/6737124), which removed the same assertion from TestDeepSeekV4Pro. The acceptance-length gates stay. The MIXED_PRECISION / DSpark comment in references/gsm8k.yaml now records the DEP4 distribution.
MegaMoE CuTe DSL bootstrap hang (third commit)
One of the 14 runs of this test hung before any checkpoint was loaded. Rank 0 logged MegaMoECuteDsl's "bootstrapping NCCL WORLD group" message twice, 4 s apart, and all four ranks then stayed in init_process_group -> _create_gloo_process_group until the 30-minute limit.
Root cause.MegaMoECuteDsl.__init__ ran the MPI bootstrap inside an except RuntimeError meant for the single-rank fallback. Every torch.distributed error (DistNetworkError, DistStoreError, DistBackendError) is a RuntimeError. So when init_process_group failed on rank 0, the error was swallowed and logged only at debug level, and the next MegaMoE layer bootstrapped again on rank 0 alone; that is the second log line. init_process_group names the default group from _world.group_count and increments it before the rendezvous, and each backend's store keys are prefixed with that name. Rank 0's retry therefore exchanged gloo addresses under 1/ keys while ranks 1-3 used 0/, and every rank waited until the gloo timeout (30 min by default). A two-process CPU reproduction in the PyTorch 26.05 container shows exactly this: rank 0 waits on /default_pg/1//cpu//0/1, rank 1 on /default_pg/0//cpu//0/0. Without the failed first attempt, both ranks initialize at once.
The first error itself was logged at debug level, so it is not in the run's log. Two likely causes, both removed here:
Port race. Rank 0 drew a free port, closed the socket, and let init_process_group bind it later. Something else can take the port in between.
Stale port. The bootstrap exported MASTER_ADDR/MASTER_PORT and honored them when present. Worker shutdown destroys the process group but not the environment, so the next LLM in a reused MPI worker pool reused the previous LLM's port.
Fix (mega_moe_cute_dsl.py):
Run the bootstrap before the single-rank except RuntimeError, so a failed bootstrap fails worker init with the real error instead of hanging for 30 minutes. The fallback still covers single-rank construction without a process group.
Rank 0 creates the rendezvous TCPStore on an OS-assigned port and broadcasts the address. All ranks then call init_process_group(store=...), which leaves no window between choosing the port and binding it.
MASTER_ADDR/MASTER_PORT are neither read nor written.
If rank 0 cannot create the store, the failure goes out in the same bcast and every rank raises together.
Verification.
Real torch.distributed run (4 processes, gloo, PyTorch 26.05 container) of _maybe_init_torch_dist_under_mpi, taken unchanged from this branch's source, with MPI faked over multiprocessing:
normal: all ranks connect to one store and a gloo all_reduce returns 10;
stale MASTER_PORT pointing at a port another socket holds: ignored, the env is left as it was, and the run succeeds;
rank 0's store creation failing: all four ranks raise the same RuntimeError within 0.1 s.
New unit tests in tests/unittest/_torch/moe/test_moe_backend.py:
The existing test_megamoe_cutedsl_mpi_bootstrap_keeps_executor_cuda_device is updated for the store argument. All four are now listed in l0_b200.yml; the existing test was not listed before. They have not been run locally yet, because that needs a current TensorRT-LLM build.
Not changed.MegaMoEDeepGemm._maybe_init_dist_from_mpi retries init_process_group on RuntimeError. If only some ranks fail, it hits the same group-name mismatch. It is not on this test's path.
Fixes https://nvbugs/6997728 (removes the weight-cache reads of the checkpoint during worker initialization, the hard GSM8K floor, and the MegaMoE CuTe DSL bootstrap hang)
PR Checklist
PR description clearly explains what and why.
Test cases are provided for new code paths.
No unrelated changes.
Dev Engineer Review
The HF weight cache checks checkpoint size against each rank’s available host memory before fingerprinting. If admission fails, the loader evicts cached entries and loads without cache lookup or storage. Ranks can make different admission decisions near the limit, so verify that the skipped-cache path remains aligned with the miss path’s collectives.
MegaMoE CuTe DSL bootstraps MPI during construction. Rank 0 hosts a TCPStore on an OS-assigned port and broadcasts rendezvous details and startup errors. The bootstrap handles loopback resolution and no longer uses MASTER_ADDR or MASTER_PORT.
The two DeepSeek-V4-Pro GSM8K tests remove the reference-score floor and retain acceptance-length checks. The reference comments describe score variation and hypothesis-test gating.
Review findings and severity counts were not supplied. Reported validation is mixed and does not establish that all validation is complete.
QA Engineer Review
tests/unittest/_torch/models/checkpoints/hf/test_weight_loader.py adds tests for oversized-checkpoint cache bypass and collective ordering.
tests/unittest/_torch/moe/test_moe_backend.py adds bootstrap tests for CUDA-device preservation, TCPStore setup and failure, loopback cases, and constructor error propagation.
The B200 CI list contains six bootstrap test entries. Both relevant GSM8K DeepSeek-V4-Pro tests appear in the GB300 multi-GPU CI list and the manual-QA list. The DP8 DeepGEMM test also appears in the DGX B200 CI list.
Reported outcomes include passing unit suites and final target-test runs, but also an unstable CI pipeline and earlier failures. The new bootstrap tests were not run locally because they require a current TensorRT-LLM build.
Coverage verdict: needs follow-up. Tests cover major cache and bootstrap paths. Validation remains incomplete, and the implementation allows ranks to make different cache-admission decisions.
Per-File QA Perspective
tensorrt_llm/_torch/models/checkpoints/hf/weight_loader.py: Verify rank-local admission, cache eviction and bypass, and collective alignment when ranks make different admission decisions.
tests/unittest/_torch/models/checkpoints/hf/test_weight_loader.py: Tests cover oversized-checkpoint bypass and miss-equivalent collective ordering. These unit tests are not integration-list entries.
tests/integration/defs/accuracy/references/gsm8k.yaml: Updated reference comments describe DEP4 run variation and hypothesis-test gating. Verify that the documented gate matches the harness.
tests/integration/defs/accuracy/test_llm_api_pytorch.py: Both DeepSeek-V4-Pro DSpark GSM8K tests remove the reference-score assertion and retain acceptance-length checks. Both appear in the GB300 multi-GPU CI list and manual-QA list.
tensorrt_llm/_torch/moe/fused_moe/mega_moe/mega_moe_cute_dsl.py: MPI bootstrap creates and distributes a TCPStore rendezvous, propagates startup failures, and checks loopback addressing. Verify cross-rank initialization and single-host versus multi-host behavior.
tests/unittest/_torch/moe/test_moe_backend.py: Tests cover bootstrap setup, error propagation, loopback handling, and constructor failure. Six bootstrap tests appear in the B200 CI list; local execution was not reported.
tests/integration/test_lists/test-db/l0_b200.yml: Adds six MegaMoE CuTe DSL MPI-bootstrap test entries to the B100/B200 pre-merge list.
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The weight loader checks host-memory admission before using the weight cache. The MPI bootstrap creates and broadcasts a TCPStore endpoint before process-group initialization. Two GSM8K tests no longer compare scores with reference accuracy.
Changes
Weight cache admission
Layer / File(s)
Summary
Admission and cache-skip behavior tensorrt_llm/_torch/models/checkpoints/hf/weight_loader.py, tests/unittest/_torch/models/checkpoints/hf/test_weight_loader.py
The loader checks checkpoint size against effective available host memory before creating a cache key. When admission fails, it evicts to make room and loads without cache lookup or storage. Tests verify repeated uncached loads and confirm that a cache skip preserves the Allreduce-then-Barrier sequence.
MegaMoE CuTeDSL MPI bootstrap
Layer / File(s)
Summary
TCPStore bootstrap and initialization tensorrt_llm/_torch/moe/fused_moe/mega_moe/mega_moe_cute_dsl.py, tests/unittest/_torch/moe/test_moe_backend.py, tests/integration/test_lists/test-db/l0_b200.yml
The constructor runs MPI bootstrap before resolving the EP process group. Rank 0 creates a TCPStore on an assigned port and broadcasts its endpoint or creation error. Process-group initialization uses the store. Tests cover endpoint broadcast, failure propagation, hostname fallback, constructor error propagation, and CUDA-device retention. The pre-merge test list includes seven bootstrap tests.
GSM8K accuracy checks
Layer / File(s)
Summary
Reference and test updates tests/integration/defs/accuracy/references/gsm8k.yaml, tests/integration/defs/accuracy/test_llm_api_pytorch.py
The reference comments report DEP4 results across 11 runs on 4x GB300 and clarify that 95.9 is not a per-run floor. Two MegaMoE tests still evaluate GSM8K and check acceptance length, but no longer assert that scores meet reference accuracy.
sequenceDiagram
participant MPIRanks
participant Rank0
participant TCPStore
participant ProcessGroup
MPIRanks->>Rank0: Request store endpoint
Rank0->>TCPStore: Create store on assigned port
TCPStore-->>Rank0: Endpoint or creation error
Rank0-->>MPIRanks: Broadcast endpoint or error
MPIRanks->>ProcessGroup: Initialize with TCPStore
Insufficient-memory loads can still retain cached weights and increase memory pressure. Clear cached weights on this path before merging; the resolved-loopback bootstrap concern has been addressed.
Pre-merge checks: 5
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The title clearly identifies the bug fix and its three main changes: oversized-checkpoint cache handling, GSM8K floor removal, and MegaMoE bootstrap hang prevention. It is longer than ideal but remain…
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The title clearly identifies the bug fix and its three main changes: oversized-checkpoint cache handling, GSM8K floor removal, and MegaMoE bootstrap hang prevention. It is longer than ideal but remains specific and relevant.
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The existing tests cover nonempty admission and rejection, but no test loads an admitted nonempty checkpoint twice while retaining the cache entry. Add a test with ample reported memory and assert one loader call and one cache hit.
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Review comment at @tensorrt_llm/_torch/models/checkpoints/hf/weight_loader.py
around lines 366 - 368:
Add a regression test for the admitted nonempty cache path around
_weight_cache_admits and _weight_files_cache_key: load the same nonempty
checkpoint twice with ample reported memory while retaining the cache entry, and
assert the loader is called once and the second load registers one cache hit.
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Review comments at @tensorrt_llm/_torch/models/checkpoints/hf/weight_loader.py:
- Line 370: Update the memory-admission-failure branch around
_evict_to_make_room() to clear all cached weights when admission fails, rather
than evicting only one entry; use the existing cache-clearing mechanism.
---
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Review comments at @tensorrt_llm/_torch/models/checkpoints/hf/weight_loader.py:
- Around line 366-368: Add a regression test for the admitted nonempty cache
path around _weight_cache_admits and _weight_files_cache_key: load the same
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reasonsolo
changed the title
[https://nvbugs/6997728][fix] Skip the raw HF weight cache for checkpoints larger than host memory
[https://nvbugs/6997728][fix] Skip the raw HF weight cache for checkpoints larger than host memory; drop the hard GSM8K floor in DSpark tests
Oct 29, 2026
reasonsolo
changed the title
[https://nvbugs/6997728][fix] Skip the raw HF weight cache for checkpoints larger than host memory; drop the hard GSM8K floor in DSpark tests
[https://nvbugs/6997728][fix] Fix DeepSeek-V4-Pro DEP4 MegaMoE CuTe DSL test: skip HF weight cache for oversized checkpoints, drop hard GSM8K floor, fix bootstrap hang
Oct 29, 2026
The rank-0 test covers only successful hostname resolution. Add a case where socket.gethostbyname raises socket.gaierror, then assert that TCPStore receives "127.0.0.1", 0, ... and that mpi_comm.bcast carries "127.0.0.1". Without this regression test, a change to the loopback fallback can go undetected.
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Review comment at @tests/unittest/_torch/moe/test_moe_backend.py around lines
2124 - 2153:
Add a rank-0 regression case alongside
test_megamoe_cutedsl_mpi_bootstrap_rank0_hosts_store_on_bound_port that makes
socket.gethostbyname raise socket.gaierror. Assert TCPStore receives the
loopback address with port 0 and mpi_comm.bcast carries the loopback address,
preserving the existing test’s other relevant bootstrap checks.
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@tensorrt_llm/_torch/moe/fused_moe/mega_moe/mega_moe_cute_dsl.py:
- Around line 878-882: Update the rendezvous bootstrap around dist.TCPStore and
mpi_comm().bcast() to check whether all MPI ranks are on the same host using the
node-local MPI communicator. On hostname-resolution failure, use loopback only
for single-host ranks; otherwise place the DNS error in the broadcast payload
and still call bcast() so peers do not wait indefinitely.
---
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Review comments at @tests/unittest/_torch/moe/test_moe_backend.py:
- Around line 2124-2153: Add a rank-0 regression case alongside
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socket.gethostbyname raise socket.gaierror. Assert TCPStore receives the
loopback address with port 0 and mpi_comm.bcast carries the loopback address,
preserving the existing test’s other relevant bootstrap checks.
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@tensorrt_llm/_torch/moe/fused_moe/mega_moe/mega_moe_cute_dsl.py:
- Line 875: Update `_maybe_init_torch_dist_under_mpi` to set `loopback` based on
whether the resolved `addr` starts with `127.`, covering both successful
hostname resolution and the existing `127.0.0.1` fallback. Add a unit test
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and verify rank 0 raises the cross-host `RuntimeError` on every rank.
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…oints larger than host memory
The raw HF weight cache (TRTLLM_HF_WEIGHT_CACHE=1, which the test
session-reuse layer sets for the MPI pools it manages) samples every
tensor when it stores a checkpoint and again when a later load hits it.
SafeTensors weights are read from the file pages on first access, so for
a checkpoint that does not fit in host memory each of these passes reads
most of the checkpoint from storage.
TestDeepSeekV4ProDSpark::test_gsm8k_dep4_megamoe_cutedsl loads the
878.7 GiB NVFP4 DeepSeek-V4-Pro checkpoint twice on a 4x GB300 node with
770-829 GiB of available host memory: once for the target model and once
for the DSpark drafter embedded in the same directory. Checkpoint
preparation took 924.7 s for the store and 707.7 s for the hit, and
worker initialization 2537 s, so with the test's 30-minute limit the
workers were still initializing when it expired.
Each rank now checks the checkpoint against its own available host
memory with the admission the rank-striped read-ahead uses
(memory_admission). A load that fails it skips the cache lookup and
store, and evicts the old entry first as a miss does. It runs the same
collectives as a miss, so ranks that decide differently stay in step.
Signed-off-by: trtllm-agent <296075020+trtllm-agent@users.noreply.github.com>
…m the DeepSeek-V4-Pro DSpark tests
Both TestDeepSeekV4ProDSpark tests asserted score >= ref_accuracy (95.9)
on top of the harness's hypothesis test (threshold 92.70). The reference
was set from a single run, but greedy GSM8K at DEP4 varies run to run
through batch-dependent numerics: eleven runs on 4x GB300 scored
95.72-96.40 (mean 96.01, std 0.19), so the floor failed about one run
in four with no regression. Rely on the hypothesis test as the other
accuracy tests do, matching NVIDIA#19554 for TestDeepSeekV4Pro. The
acceptance-length gates are kept.
Signed-off-by: Lizhi Zhou <1432185+reasonsolo@users.noreply.github.com>
…uted bootstrap fail together instead of hanging
MegaMoECuteDsl.__init__ ran the MPI bootstrap inside an except RuntimeError
meant for the single-rank fallback. Every torch.distributed error is a
RuntimeError, so a failed init_process_group on one rank was swallowed
(logged at debug) and the next MegaMoE layer bootstrapped again on that
rank alone. init_process_group names the default group from a counter it
increments before the rendezvous, so the retrying rank exchanged gloo
addresses under "1/" store keys while its peers used "0/", and every rank
waited in _create_gloo_process_group until the 30-minute timeout. This
matches the hang seen with test_gsm8k_dep4_megamoe_cutedsl, where rank 0
logged the bootstrap twice.
- Run the bootstrap before the single-rank fallback so its errors
propagate.
- Rank 0 binds the rendezvous TCPStore on an OS-assigned port and
broadcasts it, with init_process_group(store=...). This removes the
window between drawing a free port and binding it.
- Neither read nor write MASTER_ADDR / MASTER_PORT. An MPI worker
outlives the LLM that set them, so a reused pool would get the previous
LLM's port.
- Broadcast rank 0's store failure so every rank raises together.
Add unit tests for the store ownership, the shared failure and the
constructor not swallowing a bootstrap error, and list them with the
existing bootstrap test in l0_b200.yml.
Signed-off-by: Lizhi Zhou <1432185+reasonsolo@users.noreply.github.com>
Automatically added "ci: full pre-merge approved" because this PR has satisfied the required GitHub review approvals. Unresolved review conversations and other required checks remain independent merge requirements.
…che admission
- Rename _weight_cache_admits to _can_cache_weights.
- Log a skipped cache at warning level.
- Import weight_loader once at module level in test_weight_loader.py
instead of in each test.
Signed-off-by: Lizhi Zhou <1432185+reasonsolo@users.noreply.github.com>
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Description
accuracy/test_llm_api_pytorch.py::TestDeepSeekV4ProDSpark::test_gsm8k_dep4_megamoe_cutedslhas not passed in post-merge CI since it was added. In the CI logs its 30-minute limit expires while the LLM is still waiting for its executor workers to initialize. This change removes one cause of that wait: the raw HF weight cache reading the checkpoint from storage during worker initialization.Root cause of the part fixed here. The test session-reuse layer sets
TRTLLM_HF_WEIGHT_CACHE=1for the MPI worker pools it manages, which turns onHfWeightLoader's raw-weight cache. The cache fingerprints every tensor of a checkpoint when it stores it (_fingerprint) and recomputes every fingerprint when a later load hits it (_get_cached_weights). SafeTensors weights are read from the file pages when a tensor is first accessed, so these passes read the checkpoint itself. On a GB300 node, loading four shards (58.7 GB) took 4.3 s and grew the process RSS by 0.6 GB; fingerprinting them then took 8.4 s and grew the page cache by 57.9 GB.The test loads the 878.7 GiB NVFP4 DeepSeek-V4-Pro checkpoint twice, for the target model and for the DSpark drafter embedded in the same directory, on 4x GB300 nodes with 770-829 GiB of available host memory. Measured on main without this change:
Fix. Each rank checks the checkpoint against its own available host memory with the admission the rank-striped read-ahead uses (
memory_admissionovereffective_available_host_memory()). A load that fails it skips the cache lookup and store, and evicts the old entry before it loads, as a miss does. It runs the same collectives as a miss, so ranks that decide differently stay in step. Checkpoints that pass the admission are cached as before, and nothing changes when the cache is off.Test Coverage
tests/unittest/_torch/models/checkpoints/hf/test_weight_loader.py:test_weight_cache_skips_checkpoint_larger_than_host_memoryandtest_cache_skip_issues_the_miss_collectives. Both fail without the change and pass with it. With the change,tests/unittest/_torch/models/checkpoints,tests/unittest/llmapi/test_session_reuse.pyandtests/unittest/llmapi/test_session_prefetcher.pypass (228 passed; without the change 226 passed and the two new tests failed).TestDeepSeekV4ProDSpark::test_gsm8k_dep4_megamoe_cutedslon 4x GB300 with the CI image and a CI build of main, run as the CI stage runs it with itsTIMEOUT (30). Nine runs had this change, five alone and four after another test on the same worker pool:TestDeepSeekV4ProDSpark::test_gsm8k_megamoe_deepgemm[dp4](831.4 GiB FP8 export, loaded the same way) passed in 15.5 minutes.GSM8K accuracy assertion (second commit)
Besides the harness's hypothesis test (threshold 92.70), both
TestDeepSeekV4ProDSparktests assertedscore >= ref_accuracy(95.9). That reference came from a single run, but greedy GSM8K on this path varies from run to run because the numerics depend on the batch (attention DP, DSpark acceptance and MegaMoE token counts change which requests share a batch). Eleven runs on 4x GB300, with and without the cache change, scored 95.72, 95.83, 95.87, 95.91, 95.94, 95.94, 96.10, 96.10, 96.17, 96.17 and 96.40 (mean 96.01, std 0.19). A 95.9 floor fails about 28% of such runs; 3 of 11 failed. The whole spread is about 9 of 1319 answers. All 11 runs pass the hypothesis test.The second commit removes that assertion from
test_gsm8k_dep4_megamoe_cutedslandtest_gsm8k_megamoe_deepgemm, so the score is gated by the hypothesis test as in the other accuracy tests. This matches #19554 (nvbugs/6737124), which removed the same assertion fromTestDeepSeekV4Pro. The acceptance-length gates stay. TheMIXED_PRECISION/ DSpark comment inreferences/gsm8k.yamlnow records the DEP4 distribution.MegaMoE CuTe DSL bootstrap hang (third commit)
One of the 14 runs of this test hung before any checkpoint was loaded. Rank 0 logged
MegaMoECuteDsl's "bootstrapping NCCL WORLD group" message twice, 4 s apart, and all four ranks then stayed ininit_process_group->_create_gloo_process_groupuntil the 30-minute limit.Root cause.
MegaMoECuteDsl.__init__ran the MPI bootstrap inside anexcept RuntimeErrormeant for the single-rank fallback. Every torch.distributed error (DistNetworkError,DistStoreError,DistBackendError) is aRuntimeError. So wheninit_process_groupfailed on rank 0, the error was swallowed and logged only at debug level, and the next MegaMoE layer bootstrapped again on rank 0 alone; that is the second log line.init_process_groupnames the default group from_world.group_countand increments it before the rendezvous, and each backend's store keys are prefixed with that name. Rank 0's retry therefore exchanged gloo addresses under1/keys while ranks 1-3 used0/, and every rank waited until the gloo timeout (30 min by default). A two-process CPU reproduction in the PyTorch 26.05 container shows exactly this: rank 0 waits on/default_pg/1//cpu//0/1, rank 1 on/default_pg/0//cpu//0/0. Without the failed first attempt, both ranks initialize at once.The first error itself was logged at debug level, so it is not in the run's log. Two likely causes, both removed here:
init_process_groupbind it later. Something else can take the port in between.MASTER_ADDR/MASTER_PORTand honored them when present. Worker shutdown destroys the process group but not the environment, so the next LLM in a reused MPI worker pool reused the previous LLM's port.Fix (
mega_moe_cute_dsl.py):except RuntimeError, so a failed bootstrap fails worker init with the real error instead of hanging for 30 minutes. The fallback still covers single-rank construction without a process group.TCPStoreon an OS-assigned port and broadcasts the address. All ranks then callinit_process_group(store=...), which leaves no window between choosing the port and binding it.MASTER_ADDR/MASTER_PORTare neither read nor written.Verification.
Real torch.distributed run (4 processes, gloo, PyTorch 26.05 container) of
_maybe_init_torch_dist_under_mpi, taken unchanged from this branch's source, with MPI faked over multiprocessing:all_reducereturns 10;MASTER_PORTpointing at a port another socket holds: ignored, the env is left as it was, and the run succeeds;RuntimeErrorwithin 0.1 s.New unit tests in
tests/unittest/_torch/moe/test_moe_backend.py:test_megamoe_cutedsl_mpi_bootstrap_rank0_hosts_store_on_bound_porttest_megamoe_cutedsl_mpi_bootstrap_store_failure_raises_on_every_ranktest_megamoe_cutedsl_init_raises_bootstrap_failureThe existing
test_megamoe_cutedsl_mpi_bootstrap_keeps_executor_cuda_deviceis updated for the store argument. All four are now listed inl0_b200.yml; the existing test was not listed before. They have not been run locally yet, because that needs a current TensorRT-LLM build.Not changed.
MegaMoEDeepGemm._maybe_init_dist_from_mpiretriesinit_process_grouponRuntimeError. If only some ranks fail, it hits the same group-name mismatch. It is not on this test's path.Fixes https://nvbugs/6997728 (removes the weight-cache reads of the checkpoint during worker initialization, the hard GSM8K floor, and the MegaMoE CuTe DSL bootstrap hang)
PR Checklist
Dev Engineer Review
TCPStoreon an OS-assigned port and broadcasts rendezvous details and startup errors. The bootstrap handles loopback resolution and no longer usesMASTER_ADDRorMASTER_PORT.QA Engineer Review
tests/unittest/_torch/models/checkpoints/hf/test_weight_loader.pyadds tests for oversized-checkpoint cache bypass and collective ordering.tests/unittest/_torch/moe/test_moe_backend.pyadds bootstrap tests for CUDA-device preservation, TCPStore setup and failure, loopback cases, and constructor error propagation.Per-File QA Perspective
tensorrt_llm/_torch/models/checkpoints/hf/weight_loader.py: Verify rank-local admission, cache eviction and bypass, and collective alignment when ranks make different admission decisions.tests/unittest/_torch/models/checkpoints/hf/test_weight_loader.py: Tests cover oversized-checkpoint bypass and miss-equivalent collective ordering. These unit tests are not integration-list entries.tests/integration/defs/accuracy/references/gsm8k.yaml: Updated reference comments describe DEP4 run variation and hypothesis-test gating. Verify that the documented gate matches the harness.tests/integration/defs/accuracy/test_llm_api_pytorch.py: Both DeepSeek-V4-Pro DSpark GSM8K tests remove the reference-score assertion and retain acceptance-length checks. Both appear in the GB300 multi-GPU CI list and manual-QA list.tensorrt_llm/_torch/moe/fused_moe/mega_moe/mega_moe_cute_dsl.py: MPI bootstrap creates and distributes a TCPStore rendezvous, propagates startup failures, and checks loopback addressing. Verify cross-rank initialization and single-host versus multi-host behavior.tests/unittest/_torch/moe/test_moe_backend.py: Tests cover bootstrap setup, error propagation, loopback handling, and constructor failure. Six bootstrap tests appear in the B200 CI list; local execution was not reported.tests/integration/test_lists/test-db/l0_b200.yml: Adds six MegaMoE CuTe DSL MPI-bootstrap test entries to the B100/B200 pre-merge list.