mirror of
https://github.com/luxfhe/torus.git
synced 2026-10-30 17:07:26 +00:00
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.
107 lines
2.6 KiB
Python
107 lines
2.6 KiB
Python
"""
|
|
Tests of execution of round bit pattern operation.
|
|
"""
|
|
|
|
import random
|
|
|
|
import numpy as np
|
|
import pytest
|
|
|
|
from torus import fhe
|
|
from torus.fhe.dtypes import Integer
|
|
|
|
# pylint: disable=redefined-outer-name
|
|
|
|
|
|
@pytest.mark.parametrize(
|
|
"sample,expected_output",
|
|
[
|
|
(0, 0),
|
|
(1, 1),
|
|
(-1, 0),
|
|
(10, 10),
|
|
(-10, 0),
|
|
],
|
|
)
|
|
def test_plain_relu(sample, expected_output):
|
|
"""
|
|
Test plain evaluation of relu.
|
|
"""
|
|
assert fhe.relu(sample) == expected_output
|
|
|
|
|
|
operations = [
|
|
lambda x: fhe.relu(x),
|
|
lambda x: fhe.relu(x) + 100,
|
|
]
|
|
cases = [
|
|
# fhe.relu(int1), should result in fhe.zero()
|
|
[
|
|
operation,
|
|
1,
|
|
True,
|
|
(),
|
|
0,
|
|
2,
|
|
]
|
|
for operation in operations
|
|
] + [
|
|
# fhe.relu should use an optimized TLU when it's assigned bit-width is bigger than the original
|
|
[
|
|
lambda x: fhe.relu(x) + (x + 10),
|
|
3,
|
|
True,
|
|
(),
|
|
10,
|
|
2,
|
|
]
|
|
]
|
|
|
|
with_tlu = set()
|
|
for function in operations:
|
|
for bit_width in [1, 2, 3, 4, 5, 8, 12, 16]:
|
|
for is_signed in [False, True]:
|
|
for shape in [(), (3,), (2, 3)]:
|
|
for threshold in [5, 7]:
|
|
for chunk_size in [2, 3]:
|
|
if bit_width < threshold:
|
|
key = (bit_width, is_signed)
|
|
if key in with_tlu:
|
|
continue
|
|
with_tlu.add(key)
|
|
|
|
cases += [
|
|
[
|
|
function,
|
|
bit_width,
|
|
is_signed,
|
|
shape,
|
|
threshold,
|
|
chunk_size,
|
|
]
|
|
]
|
|
|
|
|
|
@pytest.mark.parametrize(
|
|
"function,bit_width,is_signed,shape,threshold,chunk_size",
|
|
cases,
|
|
)
|
|
def test_relu(function, bit_width, is_signed, shape, threshold, chunk_size, helpers):
|
|
"""
|
|
Test encrypted evaluation of relu.
|
|
"""
|
|
|
|
dtype = Integer(is_signed, bit_width)
|
|
|
|
inputset = [np.random.randint(dtype.min(), dtype.max() + 1, size=shape) for _ in range(100)]
|
|
configuration = helpers.configuration().fork(
|
|
relu_on_bits_threshold=threshold,
|
|
relu_on_bits_chunk_size=chunk_size,
|
|
)
|
|
|
|
compiler = fhe.Compiler(function, {"x": "encrypted"})
|
|
circuit = compiler.compile(inputset, configuration)
|
|
|
|
for value in random.sample(inputset, 8):
|
|
helpers.check_execution(circuit, function, value, retries=3)
|