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Motif-Technologies/
optimizer

Name: optimizer
Rating: 2.5 (141 reviews)

kernel

apache-2.0

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Optimizer

Optimizer is a python package that provides:

PyTorch implementation of recent optimizer algorithms
with support for parallelism techniques for efficient large-scale training.

Currently implemented

Parallel Muon with N-D sharding
- arxiv URL
- Supports general N-D sharding configurations
  - The implementation is not tied to any specific parallel strategy.
  - Verified from basic FSDP2 setups up to hybrid configurations such as (2 TP + 2 DP-Replicate + 2 DP-Shard).
  - Verified configurations can be found in test_muon.py

Usage

python

import torch
from torch.distributed.fsdp import FullyShardedDataParallel as FSDP
from kernels import get_kernel

optimizer = get_kernel("motif-technologies/optimizer")
get_default_muon_param_groups = optimizer.muon.get_default_muon_param_groups

model = None # your model here
fsdp_model = FSDP(model)

# muon, in nature, cannot use 1-d tensor
# we provide helper function to group such tensors
# you can use your own function, if necessary
params = get_default_muon_param_groups(model) # user can write own is_muon_func, if necessary

optim = optimizer.Muon(
    params,
    lr=0.01,
    momentum=0.9,
    weight_decay=1e-4,
)

Documentation

Implementation Guide — Detailed walkthrough of the internal architecture, parallel pipeline, distributed utilities, and QK clipping. Recommended for code reviewers and new contributors.
PyTorch 2.10 TP Fix — Root cause analysis and fixes for _StridedShard compatibility with PyTorch 2.10+.

Test

Check test/README.md for how to run the tests.

Pre-commit Hooks

This project uses pre-commit to automatically check and format code before commits.

Setup

Install pre-commit:

pip install pre-commit
Install the git hooks:

pre-commit install

Once installed, the configured hooks will run automatically on each commit.

Included Hooks

The following tools are run via pre-commit:

yapf – Python code formatter
typos – Spell checker for common typos
isort – Organizes and sorts Python imports
clang-format – Formats C++/CUDA code (--style=file)
pymarkdown – Lints and auto-fixes Markdown files
actionlint – Validates GitHub Actions workflows

Usage

Run all checks on the entire codebase:

pre-commit run --all-files
Run a specific hook (example: isort):

pre-commit run isort --all-files

Test

There is a simple unittest for Parallel Muon

Motif-Technologies/optimizer

Optimizer

Currently implemented

Usage

Documentation

Test

Pre-commit Hooks

Setup

Included Hooks

Usage

Test

Motif-Technologies/
optimizer