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Bump nemo container requirement to 26.08 for MBridge examples - #2257
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In `@tests/gpu_megatron/torch/nas/plugins/test_megatron_model_stats.py`:
- Line 546: Correct the test description near the HybridModel setup to
acknowledge that the model includes MoE, matching the ME*- pattern and
num_moe_experts=4 configuration; do not change the model configuration or test
behavior.
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.github/workflows/example_tests.yml.github/workflows/gpu_tests.ymlCHANGELOG.rstdocs/source/guides/7_nas.rstexamples/megatron_bridge/README.mdexamples/megatron_bridge/_distillation_provider.pyexamples/megatron_bridge/distill.pyexamples/megatron_bridge/prune_minitron.pyexamples/megatron_bridge/tutorials/NVIDIA-Nemotron-3-Nano-30B-A3B-BF16/README.mdexamples/pruning/README.mdmodelopt/torch/export/plugins/megatron_importer.pymodelopt/torch/export/unified_export_megatron.pymodelopt/torch/nas/plugins/megatron.pymodelopt/torch/nas/plugins/megatron_model_stats.pymodelopt/torch/prune/plugins/mcore_minitron.pymodelopt/torch/quantization/plugins/megatron.pymodelopt/torch/utils/plugins/mbridge.pynoxfile.pytests/_test_utils/examples/megatron_bridge.pytests/_test_utils/torch/megatron/models.pytests/_test_utils/torch/megatron/utils.pytests/examples/megatron_bridge/test_distill.pytests/examples/megatron_bridge/test_export_distilled_megatron_to_hf.pytests/examples/megatron_bridge/test_prune_minitron.pytests/examples/megatron_bridge/test_qad.pytests/gpu_megatron/torch/export/test_megatron_importer.pytests/gpu_megatron/torch/nas/plugins/test_megatron_hybrid_dynamic_modules.pytests/gpu_megatron/torch/nas/plugins/test_megatron_model_stats.pytests/gpu_megatron/torch/prune/plugins/test_mcore_hybrid_minitron_pruning.pytests/gpu_megatron/torch/quantization/plugins/test_megatron.pytools/launcher/common/megatron_bridge/import/import.shtools/launcher/docs/configuration.mdtools/launcher/examples/nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-BF16/mbridge_prune.yamltools/launcher/examples/nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-BF16/mbridge_quantize.yamltools/launcher/examples/nvidia/NVIDIA-Nemotron-3-Super-120B-A12B-BF16/megatron_bridge_import.yamltools/launcher/examples/nvidia/NVIDIA-Nemotron-3.5-Lightning-30B-A3B-BF16/mbridge_qad.yaml
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Claude review — 2 IMPORTANT, 1 SUGGESTION
Scope: full review (the trigger comment carried no extra scoping). 36 files changed (+265/−575). Reviewed all modelopt/ files (export/plugins/megatron_importer.py, export/unified_export_megatron.py, nas/plugins/megatron.py, nas/plugins/megatron_model_stats.py, prune/plugins/mcore_minitron.py, quantization/plugins/megatron.py, utils/plugins/mbridge.py), all examples/megatron_bridge/ changes, the changed tests/ files, and tools/launcher/common/megatron_bridge/import/import.sh. I did not open the workflow yml / noxfile.py / launcher yaml / docs/ / README version bumps beyond reading their diffs — those are mechanical 26.06 → 26.08 string changes.
Findings — CRITICAL: 0 · IMPORTANT: 2 · SUGGESTION: 1
-
[IMPORTANT Compatibility]
modelopt/torch/prune/plugins/mcore_minitron.py:818— removing themegatron.core.models.mamba.MambaModelrule key (and itsSUPPORTED_MODELS/DMRegistryregistration innas/plugins/megatron.py) makes existingmcore_minitroncheckpoints unrestorable. Configs are serialized withby_alias=True, so any state saved by a prior release carries that literal alias; on restore,ModeloptBaseRuleConfig._check_for_extra_fieldscallsDMRegistry.get_rule_class("megatron.core.models.mamba.MambaModel"), which now raisesKeyError: ... is not registered for a dynamic module!.load_state_dictonly warns on version drift — there is no key migration. The live-model path is fine (DMRegistry.get_keyresolvesMambaModelinstances to theHybridModelkey via forward-identity matching); it is purely the persisted alias that breaks. Keeping the deprecated alias registered under the existingHAS_MAMBAguard, with itsMCoreMinitronConfigrule entry, is the smallest fix — see the inline comment. This is exactly the case that the Preserve config and checkpoint backward compatibility rule in CONTRIBUTING.md calls out, and it is not mentioned in the CHANGELOG entry either. -
[IMPORTANT Compatibility]
tests/gpu_megatron/torch/quantization/plugins/test_megatron.py:1798—test_output_layer_extra_state_empty_when_nothing_quantizedpasses unchanged on pre-fix code, so the compress fix (the headline bug fix of this PR) still has no CI coverage. The subject is a plaintorch.nn.Linear, for which the oldnot isinstance(self, RealQuantLinear)guard and the newnot isinstance(self.weight, QTensorWrapper)guard both evaluate toTrue. The docstring claims it covers the post-mtq.compressRealQuantLinearcase, but nothing in the body is aRealQuantLinear— precisely the shape that killed every worker inGPTModel.sharded_state_dict. Since the e2e test isskip_flaky_on_blackwell, a re-regression of this guard would ship silently again. -
[SUGGESTION]
tools/launcher/common/megatron_bridge/import/import.sh:41—GPUS_PER_NODEdefaults vianvidia-smi -L | wc -l, which ignoresCUDA_VISIBLE_DEVICES(contradicting the "all visible GPUs" comment) and cannot fail underset -e(a pipeline reports the status ofwc), so a missingnvidia-smisilently yields--gpus-per-node 0.
Verified clean
- The compress fix itself is correct. Keying off
QTensorWrapperrather than theRealQuantLinearclass is the right root-cause fix: a compressed output_layer (whose weight is aQTensorWrapper) still emits itsq_tensor_state, while a disabled-but-converted one now contributes nothing, matching the mcore assertion that output layer extra state be empty. Theelif isinstance(self, RealQuantLinear)branch inreal_quant_module_get_extra_statewas exactly the source of the non-empty state. _DynamicMambaMixer/_MambaContextParallelProxy— dropping theconv1d-module branch and theconv1d_cp1proxy key is consistent: no remaining reference toconv1d_cp1anywhere inmodelopt/, and_slice_convoverconv1d_weight/conv1d_biasslices the sameconv_dimhparam the module branch used.megatron_importer._get_mamba_conv1dcorrectly retains the dual dispatch, so NemotronH import/export still works on 26.06 as the PR description claims — the one place the shim genuinely had to stay.prune_minitron.py— the hybrid-vs-dummy restructure preserves both original export paths;warn_rank_0is still used elsewhere in the file, and no dead references to_HYBRID_PROVIDER_TYPESorexported_config_onlyremain._inherit_base_model_rulesstill assigns correctly withMambaModelunregistered:isinstance(mod, HybridModel)holds for the subclass andDMRegistry.get_keyfolds it onto theHybridModelkey, so no module gets frozen.- Plugin laziness — the newly unconditional
megatron.core.models.hybridimports innas/plugins/megatron.py,nas/plugins/megatron_model_stats.pyandtests/_test_utils/torch/megatron/models.pydo not regress the optional-mamba_ssmstory: both of those modules already hard-importedmegatron.core.models.mambaat top level before this PR, so theimport_plugin("megatron")block already required mamba either way.
Risk: moderate. The container bump and shim removal are well scoped and the compress fix is the right one, but finding 1 is a silent checkpoint-restore break for Mamba/NemotronH Minitron users, and finding 2 means the fix that motivated the PR is still unguarded in CI.
Codecov Report✅ All modified and coverable lines are covered by tests. Additional details and impacted files@@ Coverage Diff @@
## main #2257 +/- ##
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- Coverage 78.97% 78.51% -0.46%
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Files 523 523
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- Misses 12775 13042 +267
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Claude review (round 2) — 2 IMPORTANT, 0 CRITICAL
Scope: full review (the trigger comment carried no extra scoping). 36 files changed (+279/−578). This round re-verified the two open findings from the previous review and covered the files touched since it: tests/gpu_megatron/torch/quantization/plugins/test_megatron.py, tests/gpu_megatron/torch/nas/plugins/test_megatron_model_stats.py and tools/launcher/common/megatron_bridge/import/import.sh, plus a fresh pass over all modelopt/ files, examples/megatron_bridge/, the remaining changed tests/, and the launcher yamls. I did not open the workflow yml / noxfile.py / docs/ version bumps beyond their diffs — mechanical 26.0x string changes.
Findings — CRITICAL: 0 · IMPORTANT: 2 · SUGGESTION: 0
-
[IMPORTANT Compatibility]
modelopt/torch/prune/plugins/mcore_minitron.py:818— re-raised, unresolved. Removing themegatron.core.models.mamba.MambaModelrule key makes everymcore_minitroncheckpoint written by a prior release unrestorable, not only Mamba ones:ModeloptBaseConfig.model_dumpforcesby_alias=Trueand dumps all fields including defaults (opt/config.py:84), so a plainGPTModelrun persists that key too; on restoreextra="allow"(config.py:264) routes it intomodel_extra, and_check_for_extra_fields→get_rule_classraisesKeyError(opt/dynamic.py:1018-1023). No migration path, andload_state_dictonly warns on version drift. The live-model path is unaffected. Fix in the inline comment; also worth a CHANGELOG line either way. -
[IMPORTANT Compatibility]
tools/launcher/examples/nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-BF16/mbridge_prune.yaml:6— new this round. The config still pinsnemo:26.04whiletask_0runsmodules/Model-Optimizer/examples/megatron_bridge/prune_minitron.py, i.e. this PR's copy via the repo symlink.prune_minitron.py:49is now an unguardedfrom megatron.bridge.models.hybrid.hybrid_provider import HybridModelProvider, which the deleted shim itself labelled26.08+— so the job dies withModuleNotFoundErrorbefore parsing args.mbridge_quantize.yamlin the same directory was bumped to26.08, and thetransformers<5justification on line 42 is contradicted by the tutorial README edited in this PR. Either bump the container and dropreqs: "transformers<5", or remove the config and changelog the dropped model support — aNOTEpinning ModelOpt 0.46.0 cannot be honored by a symlink to HEAD.
Resolved since the previous review
- ✅ The compress regression test now discriminates.
test_output_layer_extra_state_empty_when_nothing_quantizedbuilds a realRealQuantLinearwith an uncompressed weight, so the oldnot isinstance(self, RealQuantLinear)guard fails the== {}assertion while the newQTensorWrapperguard passes, and theweight_quantizer.enable()half pins the positive direction. The fix that motivated the PR now has non-skipped coverage. - ✅
import.shGPU-count default now checksGPUS_PER_NODE -lt 1with an explicit error instead of silently passing--gpus-per-node 0, and the doc comment was corrected to "every GPU on the node".
Verified clean this round
- The compress fix itself — keying off
QTensorWrapperrather than theRealQuantLinearclass is the right root-cause fix. The only newly-dropped case is aRealQuantLinearwith an uncompressed weight and all quantizers disabled; restore re-derives the disabled state from the quantize config, and a compressed output_layer (weight is aQTensorWrapper) still emits itsq_tensor_stateviareal_quant_module_get_extra_state. - No dangling references to any removed symbol:
get_te_mamba_stack_spec,HAS_HYBRID,_HYBRID_PROVIDER_TYPES,MambaModelProvider,get_mcore_mamba_hybrid_model,qwen35_moe_bridge_supportedandmegatron.core.models.mambaare all gone repo-wide (the sole remainingMambaModelmention is a comment). megatron_importer._get_mamba_conv1dkeeps the dualconv1d/conv1d_weightdispatch — the one shim that genuinely had to stay for NemotronH on 26.06._DynamicMambaMixer/_MambaContextParallelProxy— the_slice_convpath slices the sameconv_dimhparam the deleted module branch did, and the renamed hybrid test asserts it via_dm_attribute_manager.da_keys().test_distill.pymerge —eval_interval=1pluscheckpoint_keep_last=-1does checkpoint every iteration (distill.py:541defaultssave_intervaltoeval_interval),_get_checkpoint_export_pathsand--export_iterationsexist as the new unit tests assume, and thesys.path.insert(...parents[3]/"examples"/...)idiom matches the established convention intests/examples/llm_qatandtests/examples/alpamayo.- Plugin import structure —
nas/plugins/__init__.pyalready importedmegatron_model_stats, which hard-requiredmegatron.core.models.mambabefore this PR, inside the sameimport_plugin("megatron")block; making the hybrid imports unconditional innas/plugins/megatron.pytherefore does not change the mamba-less story.
Risk: moderate. The container bump, shim removal and the compress fix are all well scoped and correct, and the test gap from last round is properly closed. Both remaining findings are backward-compatibility issues rather than algorithmic ones: finding 1 is a silent KeyError on restore for every existing Minitron checkpoint, and finding 2 is a shipped launcher config that cannot run against the code in this same commit.
Bump the Megatron-Bridge examples, tests and launcher configs to nemo:26.08 and remove the version-gated fallbacks they carried. Megatron-Core's HybridModel is available since 26.06, so MambaModel / MambaModelProvider (deprecated aliases of HybridModel / HybridModelProvider) are no longer referenced anywhere. Fixes a crash in every compressed sharded-state-dict test: mtq.compress converts even a disabled output_layer to RealQuantLinear, which the #2112 guard excluded, so the layer emitted extra state and tripped mcore's "output layer extra state to be empty" assert. Replaces the megatron-bridge checkpoint import entry point, which 26.08 moved from examples/conversion/convert_checkpoints.py to scripts/conversion/convert.sh. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Signed-off-by: Keval Morabia <28916987+kevalmorabia97@users.noreply.github.com>
The output_layer extra-state test used a plain nn.Linear, which satisfies both the old and the new guard, so it passed on pre-fix code. Build a RealQuantLinear with an uncompressed weight instead -- what mtq.compress leaves behind for a disabled output_layer -- which fails against the old guard. Also error out when import.sh cannot detect a GPU (a failing nvidia-smi through `wc -l` silently yielded 0), and describe the hybrid model-stats test as the Mamba/MoE/attention/MLP model it actually builds. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Signed-off-by: Keval Morabia <28916987+kevalmorabia97@users.noreply.github.com>
The launcher mounts modules/Model-Optimizer as this repo, so the "needs 0.46.0" pin cannot be honored by anyone running the yaml from main -- say so, and name the Nemotron-3.5-Lightning prune config that works on current versions. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Signed-off-by: Keval Morabia <28916987+kevalmorabia97@users.noreply.github.com>
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On sm_120 with the nemo:26.08 TE/CUDA stack this test's partially-frozen LoRA backward raises a CUDA illegal memory access, which poisons the process CUDA context and cascades into the rest of the file. Deterministic across CI runs, and passes on sm_89 with the same container as well as on nemo:26.06. Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com> Signed-off-by: Keval Morabia <28916987+kevalmorabia97@users.noreply.github.com>
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Claude review — 26.08 bump / MambaModel removal
Scope: trigger comment was a bare /claude review, so this is a full pass. All 37 changed files were considered; source review focused on modelopt/ (7 files) and examples/ + tools/ (7 files), then tests/ (10 files). Docs/CI/CHANGELOG/launcher YAMLs were skimmed.
Findings — CRITICAL: 1, IMPORTANT: 1, SUGGESTION: 2
CRITICAL (ModeState / plugin laziness) — nas/plugins/megatron.py:39-42: the hybrid spec / HybridModel imports moved to unconditional module top, but the module still keeps HAS_MAMBA and a if HAS_MAMBA: registration block. Megatron-Core's hybrid stack spec and HybridModel both pull in MambaMixer, which raises at import time without mamba_ssm — which is precisely why the pre-PR code guarded them. Because nas/plugins/__init__.py wraps this in import_plugin(\"megatron\") with no msg_if_missing, the failure is completely silent, and it takes out GPTModel pruning too: the module never executes, so @DMRegistry.register(SUPPORTED_MODELS) never runs and import_plugin(\"mcore_minitron\") fails as a knock-on. Pre-PR this path worked. Same pattern in tests/_test_utils/torch/megatron/models.py, where get_hybrid_stack_modelopt_spec moved out of the import mamba_ssm block.
IMPORTANT (Compatibility) — prune/plugins/mcore_minitron.py:818-824: dropping the megatron.core.models.mamba.MambaModel rule field makes previously-saved mcore_minitron ModelOpt states unrestorable, including states for plain GPTModel. model_dump(by_alias=True) writes every rule field into the serialized config, and on restore ModeloptBaseRuleConfig._check_for_extra_fields resolves each unknown alias through DMRegistry.get_rule_class, which raises KeyError. MambaModel still exists on 26.08, so keeping the alias resolvable is cheap.
SUGGESTIONs (non-blocking): the deleted test_get_mamba_conv1d_returns_legacy_module removes the only coverage of the 26.06 conv1d-module branch the PR explicitly retains; and the pinned mbridge_prune.yaml documents a recipe that cannot run from this checkout (container still nemo:26.04, script now needs 26.08).
What checked out
- The compress fix is right. Keying the
output_layerextra-state guard offisinstance(self.weight, QTensorWrapper)rather than theRealQuantLinearclass matchespack_real_quantize_weight's skip-disabled-quantizers behavior, and it can't mask the compressed-and-enabled case (theis_enabledclause already short-circuits there).test_output_layer_extra_state_empty_when_nothing_quantizedasserts both directions and isn't Blackwell-skipped. Root cause, not side effect. _DynamicMambaMixer/_MambaContextParallelProxy/_get_mamba_conv1d: the raw-parameter slicing and the retained 26.06 dispatch in the importer are consistent with the stated compatibility split.SUPPORTED_MODELSordering:GPTModelfirst,HybridModelsecond is fine —MambaModelsharesHybridModel.forward, so_get_registered_nn_classresolves those instances to the hybrid registration.prune_minitron.pyrestructure preserves the original branch semantics (config-only bridge for hybrid non-VLM, dummy-model export otherwise).import.sh: theGPUS_PER_NODEdefault is safe (set -ewithoutset -u, so the unset expansion is fine) and the explicit-lt 1check does handle thewc -lswallow it calls out.- Test consolidation, the
manualmarker on the gemma3vl QAD param (registered inpyproject.toml), andda_keys()in the renamed hybrid NAS test are all valid.
Risk
Medium. The Megatron-Bridge/26.08 bump itself is well-tested per the Testing section, and the compress fix is a real bug fix with direct coverage. The risk is concentrated in the two findings above, both of which affect environments CI does not exercise: a Megatron-Core install without mamba_ssm (silently loses all mcore_minitron pruning), and restore of mcore_minitron states written by prior releases.
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Replied to all four findings above — the [CRITICAL] one does not reproduce (Megatron-Core guards its own /claude review |
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Claude review (round 4) — 26.08 bump / MambaModel removal
Scope: trigger was a bare /claude review with a status note, so this is a full pass. 37 files changed (+291/−578), HEAD = e8421a44af, unchanged since round 3. Re-verified the four round-3 findings against the current tree and did a fresh pass over modelopt/ (7 files), examples/megatron_bridge/ + tools/launcher/, and the 10 changed tests/ files. Workflow YAMLs, noxfile.py, docs/, and the README version bumps were read as diffs only — mechanical 26.0x string changes.
Transparency on one limitation: in this environment gh api .../pulls/2257/comments is not permitted, so I could read your summary comment but not the full text of the four in-thread replies. I judged each finding against the code directly rather than against the reply wording; where your stated position is that a break is deliberate, I checked whether the code supports that being a defensible call, not whether I'd have made the same one.
Findings — CRITICAL: 0 · IMPORTANT: 0 · SUGGESTION: 2
- [SUGGESTION]
CHANGELOG.rst:40— the entry covers the container bump but not the removal of the exportedget_te_mamba_stack_spechelper or themegatron.core.models.mamba.MambaModelsearch-space key. The ask is discoverability of theKeyError: megatron.core.models.mamba.MambaModel is not registered for a dynamic module!string, not reversing the decision. Suggested wording inline. - [SUGGESTION]
tests/gpu_megatron/torch/peft/plugins/test_megatron_peft.py:42— second module-local copy of the sm-12 skip predicate;tests/_test_utils/torch/misc.pyalready hostsminimum_sm/minimum_gpu.
On the round-3 findings
- [CRITICAL] plugin laziness /
mamba_ssm— withdrawn. I cannot reproduce it either way here (nomegatron.corein this runner), and my round-3 claim was static inference from the fact that the pre-PR code guarded those imports. You probed the actual container and reportGPTModelregistration intact withoutmamba_ssm; empirical evidence from the real stack beats my inference, so I'm not carrying this forward. Worth noting the PR makes the config schema less environment-dependent in passing:megatron.core.models.hybrid.HybridModelis now an unconditionalSUPPORTED_MODELS/MCoreMinitronConfigkey rather than one gated on whethermamba_ssmandmegatron.core.models.hybridhappened to import, so the serialized rule set no longer varies with the install. - [IMPORTANT]
MambaModelrule-key removal — not re-raised as blocking. The mechanism is real and I re-confirmed it (add_modepersistsconfig.model_dump(by_alias=True)atopt/conversion.py:294; on restoreextra="allow"routes the stale alias intomodel_extraand_check_for_extra_fields→get_rule_classraises atopt/dynamic.py:1022). ButCONTRIBUTING.md's compatibility rule is "make breaking changes explicit and intentional," not "never break," and you've now declared this one intentional as CODEOWNER. The blast radius is also narrower than I implied in round 2: no in-tree flow restores a persistedmcore_minitronstate —prune_minitron.py:612callsModeloptStateManager.remove_statebefore export, andtest_mcore_hybrid_pruning's{"checkpoint": ckpt_dir}is the importance-scores cache, not amodelopt_state. Three rounds is enough; the only residual is the changelog line above. - The two remaining SUGGESTIONs (deleted
test_get_mamba_conv1d_returns_legacy_module, pinnedmbridge_prune.yaml) — accepted as-is. TheNOTEyou added tombridge_prune.yamldocumenting the 0.46.0 pin and pointing at the Nemotron-3.5 config is a reasonable resolution for a config that a symlinked checkout cannot version-pin.
What checked out this round
- The compress fix is the right root-cause fix.
quant_module_get_extra_statekeying offisinstance(getattr(self, "weight", None), QTensorWrapper)rather than theRealQuantLinearclass matchespack_real_quantize_weight's skip-disabled behavior. Traced the drop for safety: the only newly-suppressed case is aRealQuantLinearwith an uncompressed weight and every quantizer disabled, andreal_quant_module_set_extra_stateconsumes onlymodelopt_q_tensor_state(empty there) while deliberately skippingmodelopt_real_quantizer_stateas redundant with the fake-quantizer state — so nothing restorable is lost. The compressed-and-enabled path still emitsq_tensor_statevia theelifatplugins/megatron.py:117-122. - The regression test discriminates and runs.
RealQuantLinear.convert(QuantModuleRegistry.convert(nn.Linear(4, 4)))resolves throughQuantModule.convert,quant_module_get_extra_stateis the exact function_register_extra_state_callbacksinstalls (plugins/megatron.py:372), and theweight_quantizer.enable()half pins the positive direction. Not Blackwell-skipped. - No dangling references to any removed symbol:
HAS_MAMBA/HAS_HYBRIDare gone frommcore_minitron.py's imports and unreferenced there;_DynamicMambaMixer(nas/plugins/megatron.py:1210) and_DynamicMambaLayer(:1280) are module-level definitions, somcore_minitron's unconditional import of them is as safe as it was pre-PR (only theDMRegistryregistration at:1309isHAS_MAMBA-gated). import.sh—set -ewithoutset -u, so the bare${GPUS_PER_NODE}expansion at line 41 is fine, and the explicit-lt 1check handles thewc -lexit-status swallow its own comment calls out.prune_minitron.py— theif/elserestructure preserves both original destinations (config-only bridge for hybrid non-VLM, dummy-model export otherwise); the behavior change is that asave_hf_pretrainedfailure now propagates instead of silently falling back, which is what dropping 26.06 support means.- Test consolidation —
test_distill_llm_hf_exportreaches both saved iterations (eval_interval=1drivessave_interval,checkpoint_keep_last=-1retains them), the two path-selection unit tests moved over intact, andpytest.mark.manualon thegemma3vlQAD param is a registered marker. - Renames —
get_mcore_mamba_hybrid_model→get_mcore_hybrid_modeland the twomamba→hybridtest-file renames are applied consistently across all call sites; the hybrid NAS test'sda_keys()assertion is the right replacement for the deleted_DynamicConvNdcheck.
Risk
Low-to-moderate, and lower than round 3. The compress fix is a real bug fix with non-skipped, discriminating coverage; the shim removal is mechanical and consistently applied; the retained _get_mamba_conv1d dual dispatch is the one place 26.06 support genuinely had to stay. The residual risk is the declared-intentional restore break for pre-existing mcore_minitron states, which no in-tree flow exercises. Approving — nothing blocking remains, and the changelog line is a nice-to-have.
| "pipeline_dtype": torch.bfloat16, | ||
| "seq_length": 4096, | ||
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| moe_grouped_gemm=False, |
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does removing this now use TEGroupedLinear?
| from export_distilled_megatron_to_hf import _get_checkpoint_export_paths | ||
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| @pytest.mark.timeout(360) # distill + inline HF export + export of every iteration |
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why does this test need 360 seconds?
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Merged 2 mostly similar tests into 1 so slightly increased timeout
| args = argparse.Namespace( | ||
| megatron_path=str(checkpoint_root), | ||
| hf_export_path=str(hf_export_root), | ||
| export_iterations=["2", "1", "2"], |
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why is it "2 1 2" but only returns checkpoints 1 and 2 ?
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I just refactored existing test. I guess it remvoes duplicates if present in the list
4 participants
What does this PR do?
Type of change: Bug fix
Bumps the Megatron-Bridge examples, tests and launcher configs to
nemo:26.08and removes the version-gated fallbacks they carried, plus the fixes needed to make the suites green on that container.26.08 bump and shim removal
noxfile.pyand thembridge_*launcher configs move tonemo:26.08.examples/megatron_bridge/_distillation_provider.pyis deleted — 26.08's Megatron-Bridge shipsconvert_to_distillation_provider(..., distill_submodule=...)natively, sodistill.pyimports it directly.prune_minitron.pydrops theAutoBridge.from_hf_config/ config-only-export probing;--no_moe_grouped_gemmis no longer needed in the MoE pruning tests, and the Qwen3.5-MoEskipifis gone (native MoE expert mappings are in 26.08)._DynamicMambaMixertargets only the rawconv1d_weight/conv1d_biasparameters that replaced theconv1dmodule in Megatron-Core.MambaModel / MambaModelProvider removal
Megatron-Core has shipped
HybridModelsince 26.06 andMambaModelis a deprecated subclass that shares itsforward, soDMRegistryresolves those instances to theHybridModelregistration and the separate entry is redundant. Same forMambaModelProvidervsHybridModelProvideron the bridge side.MambaMixer/MambaLayer/ExtendedRMSNormare untouched — the layers still exist. The deprecatedget_te_mamba_stack_specis removed; useget_te_hybrid_stack_spec.Bug fix: compressed output_layer extra state
mtq.compressconverts even a disabledoutput_layerinto aRealQuantLinear(its weight is left uncompressed, sincepack_real_quantize_weightskips disabled quantizers). The guard added in #2112 excludedRealQuantLinearby class, so the layer emitted extra state and every worker died inGPTModel.sharded_state_dict:The guard now keys off whether the weight was actually compressed (
QTensorWrapper) instead of the class. This took out all 12test_homogeneous_compressed_sharded_state_dictparams, and the crashed workers poisoned the pool, which surfaced as unrelated timeouts and NCCL errors intest_layer_sync_moe_local_experts_amax,test_kv_cache_quant,test_kv_cache_amax_sync,test_convert_mcore_te_gpt_modelandtest_homogeneous_sharded_state_dict_te_spec— 21 tests in total. The e2e coverage isskip_flaky_on_blackwell, so CI never ran it;test_output_layer_extra_state_empty_when_nothing_quantizednow asserts the contract directly and is not skipped.Checkpoint import entry point
26.08 replaced
examples/conversion/convert_checkpoints.pywithscripts/conversion/convert.sh, sotools/launcher/common/megatron_bridge/import/import.shand the three README snippets are retargeted.import.shuses the distributed GPU backend withGPUS_PER_NODE/TP/PP/EPknobs.Megatron-LM on nemo:26.06 keeps working:
_get_mamba_conv1dstill dispatches between theconv1dmodule (26.06 and earlier) and the raw parameters (26.08+), soimport_mcore_gpt_from_hf/export_mcore_gpt_to_hfhandle NemotronH on both. Only the Megatron-Bridge examples and Minitron pruning of Mamba/hybrid models require 26.08.Test consolidation
test_export_distilled_megatron_to_hf.pyis merged intotest_distill.py:test_distill_llmbecomestest_distill_llm_hf_exportand covers the standalone--export_iterations allrun on the checkpoints it already produces, saving one full distillation (~185 s of CI time). The two mamba-named gpu test files are renamed tohybrid.Usage
Testing
All on
nvcr.io/nvidia/nemo:26.08, 2x RTX 6000 Ada, no timeout overrides:tests/examples/megatron_bridge: 16 passed, 1 skipped (28m14s). The skip is thegemma3vlQAD param, now@pytest.mark.manualsinceqwen3_5_moe_vlcovers the VLM QAD path.tests/gpu_megatron(_extensions,distill,export,opt,peft,sparsity,speculative,utils): 61 passed, 5 xpassed.tests/gpu_megatron/torch/exportre-run after the conv1d dispatch change: 27 passed.tests/gpu_megatron/torch/{nas,prune}: verified separately.import.shequivalence on a toyqwen3_moe, comparing all 12 weight tensors after flattening each dist checkpoint withdcp_to_torch_save— the GPU backend at 1 GPU,--tp 2,--pp 2,--ep 2, andimport.shend-to-end (GPUS_PER_NODE=2 EP=2) are all byte-identical to--device cpu.nemo:26.06compatibility was checked directly in that image:megatron.core.models.hybrid.HybridModel, the modelopt hybrid spec andhybrid_layer_patternare all present, whilemegatron.bridge.models.hybridand the bridge'sdistill_submoduleare not. The NemotronH round-trip test failed there before the conv1d dispatch was restored and the dispatch is back in place; per project convention the suites themselves only run on 26.08.Before your PR is "Ready for review"
nemo:26.08. Megatron-LM quantization and checkpoint export still run onnemo:26.06.CONTRIBUTING.md: N/Atest_output_layer_extra_state_empty_when_nothing_quantizedfor the compress fix; existing tests extended for the merged export coverage.🤖 Generated with Claude Code
Summary by CodeRabbit
New Features
Improvements
Bug Fixes
Documentation