Fix KDA precision and MD checkpoint correctness - #64
Draft
andresnowak wants to merge 4 commits into
Draft
Conversation
Reject linear-attention controls that KDA does not implement, provide the KEEL post-layer norms in hybrid blocks, and keep KDA internal projections out of residual-output projection handling. Add focused regressions for each case.
Keep tagged KDA decay parameters in fp32 for FlashKDA and map native fp32 parameters alongside fp16/bf16 parameters in sharded optimizer state. Fall back to the loaded model values when an old checkpoint uses the former master parameter layout.
Store preserve-init update-normalization targets in optimizer state and project them through the existing flat-gain sharding path. Version the state with checkpoint content metadata so pre-fix torch_dist checkpoints still load and recompute their unavailable targets.
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
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Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be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.

Summary
A_loganddt_biasin FP32 through mixed-precision wrapping and support mixed-dtypetorch_distoptimizer stateout_projweightstorch_distcheckpoint resumesValidation
torch_distround trip passedtorch_distcheckpoint load passed0.0ruff checkandgit diff --checkpassed