Sheaf is a functional language for differentiable computation. It is inspired by Clojure and is designed to operate within the Python/JAX machine learning ecosystem.
Sheaf has three main goals:
- Clojure Paradigm: Homoiconicity (code is data), immutability and minimalist syntax.
- Native XLA Performance: Sheaf code runs on GPUs/TPUs through JAX.
- Seamless Interop with Python: Compiled to pure JAX functions natively callable from Python.
Sample code:
(defn transformer-block [x layer-p config]
(as-> x h
(-> h ;; 1. Self-Attention
(layer-norm (get layer-p :ln1) 2)
(multi-head-attention layer-p config)
(first) ;; Attention output
(+ h)) ;; Residual 1
(-> h ;; 2. MLP
(layer-norm (get layer-p :ln2) 2)
(mlp (get layer-p :mlp))
(+ h)))) ;; Residual 2
Python interoperability
from sheaf import Sheaf
shf = Sheaf("mlp.shf")
for x, y in zip(X, shf.forward(X, params)):
print(f" {x} -> {y[0]:.3f}")
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Release files for sheaf-lang 1.2.0
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Source distribution (sdist)
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| sheaf_lang-1.2.0.tar.gz | 79.0 kB | Details |
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|---|---|---|---|---|
| sheaf_lang-1.2.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 161.3 kB
Release files / sheaf_lang-1.2.0.tar.gz
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