Conversation
Signed-off-by: Kai Xu <kaix@nvidia.com>
## Summary Consolidates the complete reviewed fix stack for #2375 into one DCO-safe commit: - harden package exports, measurement semantics, wrapper handling, and actionable calibration errors - validate exact installed GDN identities plus ModelOpt dynamic subclasses; reject lookalikes, ordinary subclasses, incomplete layers, and partial layer sets - make stale checkpoints saveable and restorable while keeping deployment export strict - make DASC recalibration replace and deduplicate existing mode state without stale-metadata refresh - record the declared decay-parameter checkpoint storage dtype and use derived FP16/BF16/FP32 rounding bounds - preserve BF16/FP16 storage and wider/cross-dtype reload compatibility without globally widening FP32 tolerance - add installed Transformers path coverage, optional Megatron gating, lifecycle, tamper, lossy-cast, and mixed-layer regressions - document the explicit storage-dtype contract This consolidated PR supersedes the mechanically stacked review-fix PRs #2377, #2378, #2379, #2380, #2382, #2383, #2384, and #2385. Its tree is byte-identical to the independently reviewed leaf commit from #2386. ## Validation - focused DASC suite: 23 passed, 1 absent optional Megatron skip - DASC plus weight sparsity plus attention sparsity compatibility suite: 134 passed, 1 optional skip - DASC package coverage: 408/408 statements, 100% - full pre-commit on all touched files: passed - real Transformers Qwen3NextGatedDeltaNet BF16 storage to FP32 reload smoke: passed - commit author and Signed-off-by identity both use kaix-nv <kaix@nvidia.com> <!-- This is an auto-generated comment: release notes by coderabbit.ai --> ## Summary by CodeRabbit * **New Features** * Added support for configuring decay-parameter storage precision with FP16, BF16, or FP32. * Added safer recalibration that replaces existing DASC state. * Expanded compatibility with supported GDN adapter classes and model wrappers. * Added improved validation for sparsity policies, measurements, model structure, and decay parameters. * Added support for perplexity-retention values above 1. * **Documentation** * Clarified evaluation responsibilities, recalibration behavior, stale-policy handling, supported adapters, and dtype requirements. <!-- end of auto-generated comment: release notes by coderabbit.ai --> --------- Signed-off-by: kaix-nv <kaix@nvidia.com>
Signed-off-by: Kai Xu <kaix@nvidia.com>
|
Auto-sync is disabled for draft pull requests in this repository. Workflows must be run manually. Contributors can view more details about this message here. |
Contributor
|
Important Draft PR not reviewedDraft PRs are not automatically reviewed by default.
To automatically review draft PRs, update your CodeRabbit configuration: reviews:
auto_review:
drafts: trueComment |
Contributor
|
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
1 participant
Add this suggestion to a batch that can be applied as a single commit.This suggestion is invalid because no changes were made to the code.Suggestions cannot be applied while the pull request is closed.Suggestions cannot be applied while viewing a subset of changes.Only one suggestion per line can be applied in a batch.Add this suggestion to a batch that can be applied as a single commit.Applying suggestions on deleted lines is not supported.You must change the existing code in this line in order to create a valid suggestion.Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be applied on multi-line comments.Suggestions cannot be applied while the pull request is queued to merge.Suggestion cannot be applied right now. Please check back later.
What does this PR do?
Type of change: new feature
Adds an experimental modelopt.torch.sparsity.state_sparsity API for the first ModelOpt DASC milestone:
This change is policy-only and does not alter model execution. Runtime ragged checkpoint packing, suffix replay, KDA support, quantization, and GDN or KDA kernels are intentionally out of scope. A serving implementation must preserve convolution state and materialize ordinary dense recurrent state before continuation.
This draft supersedes #2375 and includes all review fixes accumulated there.
Usage
Import modelopt.torch.sparsity.state_sparsity, call calibrate with the model, configuration, and paired measurements, then call export_policy to obtain the deployment policy. The complete executable example and schema are in the sparsity guide.
Measurements contain paired dense-versus-DASC quality and physical checkpoint-storage results for every configured candidate.
Testing
Before your PR is Ready for review
Additional Information
Algorithm reference: https://arxiv.org/abs/2608.30386
The mode stores calibration evidence rather than treating weight-derived horizons as sufficient proof. A future runtime milestone should consume this policy in the serving prefix-cache serializer and loader and qualify matched-HBM capacity plus prefix-hit latency.