Mooncake
Implementation of language-level autograd compiler for Julia
Science Score: 52.0%
This score indicates how likely this project is to be science-related based on various indicators:
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✓CITATION.cff file
Found CITATION.cff file -
✓codemeta.json file
Found codemeta.json file -
✓.zenodo.json file
Found .zenodo.json file -
○DOI references
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○Academic publication links
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○Academic email domains
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✓Institutional organization owner
Organization chalk-lab has institutional domain (mlg.eng.cam.ac.uk) -
○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (14.2%) to scientific vocabulary
Repository
Implementation of language-level autograd compiler for Julia
Basic Info
- Host: GitHub
- Owner: chalk-lab
- License: mit
- Language: Julia
- Default Branch: main
- Homepage: https://chalk-lab.github.io/Mooncake.jl/
- Size: 22.9 MB
Statistics
- Stars: 301
- Watchers: 7
- Forks: 19
- Open Issues: 84
- Releases: 214
Metadata Files
README.md
The goal of the Mooncake.jl project is to produce an AD package which is written entirely in Julia, which improves over ForwardDiff.jl, ReverseDiff.jl and Zygote.jl in several ways, and is competitive with Enzyme.jl.
Please refer to the docs for more info.
Getting Started
Check that you're running a version of Julia that Mooncake.jl supports.
See the SUPPORT_POLICY.md file for more info.
There are several ways to interact with Mooncake.jl.
We recommend that people interact with Mooncake.jl via DifferentiationInterface.jl.
For example, use it as follows to compute the gradient of a function mapping a Vector{Float64} to Float64.
```julia
using DifferentiationInterface
import Mooncake
f(x) = sum(cos, x)
backend = AutoMooncake() # Reverse-mode AD. For forward-mode AD, use AutoMooncakeForward().
x = ones(1000)
prep = preparegradient(f, backend, x)
gradient(f, prep, backend, x)
``
You should expect thatprepare_gradienttakes a little bit of time to run, but thatgradient` is fast.
We are committed to ensuring support for DifferentiationInterface, which is why we recommend using that.
If you are interested in interacting more directly with Mooncake.jl, you should consider Mooncake.value_and_gradient!!.
See its docstring for more info.
Owner
- Name: Learning and Inference Group
- Login: chalk-lab
- Kind: organization
- Location: United Kingdom
- Website: https://mlg.eng.cam.ac.uk/hong/
- Repositories: 1
- Profile: https://github.com/chalk-lab
Hong Ge's Research Group at Cambridge University
Citation (CITATION.cff)
cff-version: 1.2.0 message: "If you use this software, please cite it as below." authors: - family-names: "Tebbutt" given-names: "Will" - family-names: "Ge" given-names: "Hong" title: "Differentiable learning and simulation with Mooncake" date-released: 2024 url: "https://github.com/chalk-lab/Mooncake.jl"
Issues and Pull Requests
Last synced: 6 months ago
All Time
- Total issues: 72
- Total pull requests: 170
- Average time to close issues: about 1 month
- Average time to close pull requests: 3 days
- Total issue authors: 28
- Total pull request authors: 16
- Average comments per issue: 2.39
- Average comments per pull request: 3.86
- Merged pull requests: 106
- Bot issues: 0
- Bot pull requests: 6
Past Year
- Issues: 70
- Pull requests: 170
- Average time to close issues: about 1 month
- Average time to close pull requests: 3 days
- Issue authors: 28
- Pull request authors: 16
- Average comments per issue: 2.39
- Average comments per pull request: 3.86
- Merged pull requests: 106
- Bot issues: 0
- Bot pull requests: 6
Top Authors
Issue Authors
- yebai (16)
- MilesCranmer (10)
- willtebbutt (10)
- gdalle (4)
- penelopeysm (3)
- PTWaade (3)
- tpapp (2)
- Red-Portal (2)
- mhauru (2)
- ChrisRackauckas (2)
- timholy (1)
- yolhan83 (1)
- araujoms (1)
- deveshjawla (1)
- KookiesNKareem (1)
Pull Request Authors
- yebai (44)
- willtebbutt (37)
- AstitvaAggarwal (21)
- MilesCranmer (20)
- Copilot (18)
- sunxd3 (8)
- github-actions[bot] (5)
- shravanngoswamii (5)
- gdalle (3)
- kshyatt (2)
- lukas-weber (2)
- cncastillo (1)
- dependabot[bot] (1)
- ErikQQY (1)
- MasonProtter (1)
Top Labels
Issue Labels
Pull Request Labels
Packages
- Total packages: 1
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Total downloads:
- julia 247 total
- Total dependent packages: 0
- Total dependent repositories: 0
- Total versions: 156
juliahub.com: Mooncake
Implementation of language-level autograd compiler for Julia
- Homepage: https://chalk-lab.github.io/Mooncake.jl/
- Documentation: https://docs.juliahub.com/General/Mooncake/stable/
- License: MIT
-
Latest release: 0.4.154
published 7 months ago
Rankings
Dependencies
- actions/checkout v4 composite
- julia-actions/cache v1 composite
- julia-actions/julia-buildpkg v1 composite
- julia-actions/julia-runtest v1 composite
- julia-actions/setup-julia v1 composite
- JuliaRegistries/TagBot v1 composite