zeekay
b832ba2c39
Forked from upstream concrete (BSD-3-Clause-Clear, © 2024 ZAMA) at HEAD
ecb729bb. Modifications copyright © 2026 Lux Industries Inc.
Rebranding scope:
- Python module concrete → torus (across frontends/torus-python)
- Rust module concrete-* → torus-* (across frontends/torus-rust)
- MLIR dialect concretelang → toruslang (across compilers/torus-compiler)
- Compiler optimizer concrete-optimizer → torus-optimizer
- Backend concrete-cpu / concrete-cuda → torus-cpu / torus-cuda
- Wire protocol concrete-protocol → torus-protocol
- Parameter-curves concrete-security-curves-* → torus-security-curves-*
- Public symbols concretelib → toruslib, ConcreteLang → TorusLang
- URLs github.com/zama-ai/concrete → github.com/luxfhe/torus
- URLs docs.zama.ai/concrete → docs.luxfhe.com/torus
Legal compliance:
- LICENSE.txt retains original Copyright © 2024 ZAMA verbatim (§1-§2)
- LICENSE.txt adds modifications copyright © 2026 Lux Industries Inc.
- §3 endorsement clause: Torus is marketed exclusively as a Lux product;
no Zama name used in README, docs, or marketing
- NOTICE file provides factual attribution per legal best practice
(not endorsement; required by upstream BSD-3-Clause-Clear)
README + NOTICE rewritten from scratch with Lux brand:
- Quick-start in Python (torus.fhe)
- Architecture diagram showing the gen-1 vtbl integration path
(luxcpp/gpu → lux-private/gpu-kernels for CUDA/Metal/WebGPU)
- Scheme coverage table: TFHE (luxfi/fhe), CKKS/BGV/BFV (luxfi/lattice)
- Lux FHE family table: Torus / TorusVM / TorusEVM / TorusML / TorusNet
Known limitations (phase-2A scope):
- PyPI package torus-fhe not yet published; the torus Python module
is renamed structurally but pip-installable distribution is a
follow-up (Phase 2A.1)
- MLIR dialect rename is text-level; the compiler-internal LLVM
rebuild (concrete-compiler-internal-llvm-project submodule) is
structural and works; tablegen files renamed concrete→torus but the
generated .inc files in the source tree will regenerate at build
time
- backends/torus-cuda/implementation/ is an upstream submodule
pointer to the tfhe-rs source (not fetched in the staging clone);
the CUDA backend body is delivered out-of-tree
- ~100 test-fixture variable names like concrete_encoded_sample
retain "concrete" as a math term (vs symbolic); these are inside
tests/, not the public API; cleanup is a follow-up commit
- 295 Python `from concrete import ...` residuals in luxfhe/ml-sdk
consumer remain; that repo's import update is Phase 2B
This commit is the seed for the luxfhe/torus repo. Push as the first
commit to a fresh GitHub repo; do not re-import upstream Zama git
history.
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Formatting and drawing
This document explains how to format and draw a compiled circuit in Python.
Formatting
To convert your compiled circuit into its textual representation, use the str function:
str(circuit)
If you just want to see the output on your terminal, you can directly print it as well:
print(circuit)
{% hint style="warning" %} Formatting is designed for debugging purpose only. It's not possible to create the circuit back from its textual representation. See How to Deploy if that's your goal. {% endhint %}
Drawing
{% hint style="danger" %} Drawing functionality requires the installation of the package with the full feature set. See the Installation section for instructions. {% endhint %}
To draw your compiled circuit, use the draw method:
drawing = circuit.draw()
This method draws the circuit, saves it as a temporary PNG file and returns the file path.
You can display the drawing in a Jupyter notebook:
from PIL import Image
drawing = Image.open(circuit.draw())
drawing.show()
drawing.close()
Alternatively, you can use the show option of the draw method to display the drawing with matplotlib:
circuit.draw(show=True)
{% hint style="danger" %} Using this option will clear any existing matplotlib plots. {% endhint %}
Lastly, to save the drawing to a specific path, use the save_to option:
destination = "/tmp/path/of/your/choice.png"
drawing = circuit.draw(save_to=destination)
assert drawing == destination