mHC optimization for expansion rate 4 (flag controlled)#3890
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shuningjin
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May 21, 2026
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Thanks for implementing mHC-lite! The core logic looks solid.
- Your implementation aligns with Eqs (2) and (3), and the parameter shapes are correct.
- Generalize k: The shortcut is currently hardcoded for k=4. While the
$k!$ permutation scaling limits large$k$ in practice, the underlying math applies to any$k$ . Let's parameterize it for flexibility. - Cleanup: I left a few minor inline comments. Please also revert unrelated formatting changes.
Also thanks for adding the unit tests! As a follow-up, you can run an end-to-end test to verify training stability and performance.
| [None, get_test_config_path()], | ||
| **extra_args, | ||
| run_name="test_mhc", | ||
| skip_jax_distributed_system=True, |
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do not skip, instead mark @pytest.mark.tpu_only for relavent tests
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remove skip_jax_distributed_system=True?
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shuningjin
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May 22, 2026
| [None, get_test_config_path()], | ||
| **extra_args, | ||
| run_name="test_mhc", | ||
| skip_jax_distributed_system=True, |
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remove skip_jax_distributed_system=True?
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parambole
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…tions and add enable_mhc_k4_shortcut feature gate
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Description
When expansion rate is equal to four we don't need to do sinkhorn as we can generate the doubly-stochastic matrix by taking a random convex combination of the permutation matrices (there are 4! = 24 of them when using expansion rate 4).
Based on https://arxiv.org/pdf/2601.05732.
Tests
Just tested with unit tests, adding the gemini-review now.
Waiting to performance test it once we get baseline DeepSeek v4 numbers.
Checklist
Before submitting this PR, please make sure (put X in square brackets):
gemini-reviewlabel.