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zeekay b832ba2c39 Initial Torus commit 
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.
2026-05-29 14:16:47 -07:00

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"""
Tests of execution of static assignment operation.
"""
import numpy as np
import pytest
from torus import fhe
def assignment_case_0():
"""
Assignment test case.
"""
shape = (3,)
value = np.random.randint(0, 2**7, size=())
def assign(x):
x[:] = value
return x
return shape, assign
def assignment_case_1():
"""
Assignment test case.
"""
shape = (3,)
value = np.random.randint(0, 2**7, size=())
def assign(x):
x[0] = value
return x
return shape, assign
def assignment_case_2():
"""
Assignment test case.
"""
shape = (3,)
value = np.random.randint(0, 2**7, size=())
def assign(x):
x[1] = value
return x
return shape, assign
def assignment_case_3():
"""
Assignment test case.
"""
shape = (3,)
value = np.random.randint(0, 2**7, size=())
def assign(x):
x[2] = value
return x
return shape, assign
def assignment_case_4():
"""
Assignment test case.
"""
shape = (5,)
value = np.random.randint(0, 2**7, size=())
def assign(x):
x[0:3] = value
return x
return shape, assign
def assignment_case_5():
"""
Assignment test case.
"""
shape = (5,)
value = np.random.randint(0, 2**7, size=())
def assign(x):
x[1:4] = value
return x
return shape, assign
def assignment_case_6():
"""
Assignment test case.
"""
shape = (5,)
value = np.random.randint(0, 2**7, size=())
def assign(x):
x[1:4:2] = value
return x
return shape, assign
def assignment_case_7():
"""
Assignment test case.
"""
shape = (10,)
value = np.random.randint(0, 2**7, size=())
def assign(x):
x[::2] = value
return x
return shape, assign
def assignment_case_8():
"""
Assignment test case.
"""
shape = (5,)
value = np.random.randint(0, 2**7, size=())
def assign(x):
x[2:0:-1] = value
return x
return shape, assign
def assignment_case_9():
"""
Assignment test case.
"""
shape = (5,)
value = np.random.randint(0, 2**7, size=())
def assign(x):
x[4:0:-2] = value
return x
return shape, assign
def assignment_case_10():
"""
Assignment test case.
"""
shape = (5,)
value = np.random.randint(0, 2**7, size=(3,))
def assign(x):
x[1:4] = value
return x
return shape, assign
def assignment_case_11():
"""
Assignment test case.
"""
shape = (5,)
value = np.random.randint(0, 2**7, size=(3,))
def assign(x):
x[4:1:-1] = value
return x
return shape, assign
def assignment_case_12():
"""
Assignment test case.
"""
shape = (10,)
value = np.random.randint(0, 2**7, size=(3,))
def assign(x):
x[1:7:2] = value
return x
return shape, assign
def assignment_case_13():
"""
Assignment test case.
"""
shape = (10,)
value = np.random.randint(0, 2**7, size=(3,))
def assign(x):
x[7:1:-2] = value
return x
return shape, assign
def assignment_case_14():
"""
Assignment test case.
"""
shape = (5, 4)
value = np.random.randint(0, 2**7, size=())
def assign(x):
x[0, 0] = value
return x
return shape, assign
def assignment_case_15():
"""
Assignment test case.
"""
shape = (5, 4)
value = np.random.randint(0, 2**7, size=())
def assign(x):
x[3, 1] = value
return x
return shape, assign
def assignment_case_16():
"""
Assignment test case.
"""
shape = (5, 4)
value = np.random.randint(0, 2**7, size=())
def assign(x):
x[0] = value
return x
return shape, assign
def assignment_case_17():
"""
Assignment test case.
"""
shape = (5, 4)
value = np.random.randint(0, 2**7, size=(4,))
def assign(x):
x[0] = value
return x
return shape, assign
def assignment_case_18():
"""
Assignment test case.
"""
shape = (5, 4)
value = np.random.randint(0, 2**7, size=(5,))
def assign(x):
x[:, 0] = value
return x
return shape, assign
def assignment_case_19():
"""
Assignment test case.
"""
shape = (5, 4)
value = np.random.randint(0, 2**7, size=(5,))
def assign(x):
x[:, 1] = value
return x
return shape, assign
def assignment_case_20():
"""
Assignment test case.
"""
shape = (5, 4)
value = np.random.randint(0, 2**7, size=())
def assign(x):
x[0:3, :] = value
return x
return shape, assign
def assignment_case_21():
"""
Assignment test case.
"""
shape = (5, 4)
value = np.random.randint(0, 2**7, size=(3, 4))
def assign(x):
x[0:3, :] = value
return x
return shape, assign
def assignment_case_22():
"""
Assignment test case.
"""
shape = (5, 4)
value = np.random.randint(0, 2**7, size=(4,))
def assign(x):
x[0:3, :] = value
return x
return shape, assign
def assignment_case_23():
"""
Assignment test case.
"""
shape = (5, 4)
value = np.random.randint(0, 2**7, size=(3,))
def assign(x):
x[0:3, 1:4] = value
return x
return shape, assign
def assignment_case_24():
"""
Assignment test case.
"""
shape = (5, 4)
value = np.random.randint(0, 2**7, size=(3, 3))
def assign(x):
x[0:3, 1:4] = value
return x
return shape, assign
def assignment_case_25():
"""
Assignment test case.
"""
shape = (5, 4)
value = np.random.randint(0, 2**7, size=(3, 3))
def assign(x):
x[4:1:-1, 3:0:-1] = value
return x
return shape, assign
def assignment_case_26():
"""
Assignment test case.
"""
shape = (5, 4)
value = np.random.randint(0, 2**7, size=(3,))
def assign(x):
x[3:0:-1, 0] = value
return x
return shape, assign
def assignment_case_27():
"""
Assignment test case.
"""
shape = (5, 4)
value = np.random.randint(0, 2**7, size=(2,))
def assign(x):
x[0, 1:3] = value
return x
return shape, assign
def assignment_case_28():
"""
Assignment test case.
"""
shape = (5, 4)
value = np.random.randint(0, 2**7, size=())
def assign(x):
x[2:4, 1:3] = value
return x
return shape, assign
def assignment_case_29():
"""
Assignment test case.
"""
shape = (5,)
value = -20
def assign(x):
x[0] = value
return x
return shape, assign
def assignment_case_30():
"""
Assignment test case.
"""
shape = (5,)
index = [0, 2, 4]
value = 10
def assign(x):
x[index] = value
return x
return shape, assign
def assignment_case_31():
"""
Assignment test case.
"""
shape = (5,)
index = [0, 2, 4]
value = [10, 20, 30]
def assign(x):
x[index] = value
return x
return shape, assign
def assignment_case_32():
"""
Assignment test case.
"""
shape = (5,)
index = [
[3, 0],
[1, 2],
]
value = [
[10, 20],
[30, 40],
]
def assign(x):
x[index] = value
return x
return shape, assign
def assignment_case_33():
"""
Assignment test case.
"""
shape = (5, 4)
index = (
[0, 0, 4, 4],
[0, 3, 0, 3],
)
value = [10, 20, 30, 40]
def assign(x):
x[index] = value
return x
return shape, assign
def assignment_case_34():
"""
Assignment test case.
"""
shape = (5, 4)
index = (
0,
[0, 3, 1, 2],
)
value = [10, 20, 30, 40]
def assign(x):
x[index] = value
return x
return shape, assign
def assignment_case_35():
"""
Assignment test case.
"""
shape = (5, 4)
index = (
[3, 3, 1, 2],
0,
)
value = [10, 20, 30, 40]
def assign(x):
x[index] = value
return x
return shape, assign
def assignment_case_36():
"""
Assignment test case.
"""
shape = (5, 4)
index = (
[[0, 0], [4, 4]],
[[0, 3], [3, 0]],
)
value = [
[10, 20],
[30, 40],
]
def assign(x):
x[index] = value
return x
return shape, assign
def assignment_case_37():
"""
Assignment test case.
"""
shape = (5, 4)
index = (
0,
[[1, 3], [2, 0]],
)
value = [
[10, 20],
[30, 40],
]
def assign(x):
x[index] = value
return x
return shape, assign
def assignment_case_38():
"""
Assignment test case.
"""
shape = (5, 4)
index = (
[[1, 3], [2, 4]],
0,
)
value = [
[10, 20],
[30, 40],
]
def assign(x):
x[index] = value
return x
return shape, assign
def assignment_case_39():
"""
Assignment test case.
"""
shape = (5, 4)
index = (
[[1, 3], [2, 4]],
[0, 2],
)
value = [
[10, 20],
[30, 40],
]
def assign(x):
x[index] = value
return x
return shape, assign
def assignment_case_40():
"""
Assignment test case.
"""
shape = (5, 4)
index = (
[2, 4],
[[1, 3], [2, 0]],
)
value = [
[10, 20],
[30, 40],
]
def assign(x):
x[index] = value
return x
return shape, assign
@pytest.mark.parametrize(
"shape,function",
[
pytest.param(*assignment_case_0()),
pytest.param(*assignment_case_1()),
pytest.param(*assignment_case_2()),
pytest.param(*assignment_case_3()),
pytest.param(*assignment_case_4()),
pytest.param(*assignment_case_5()),
pytest.param(*assignment_case_6()),
pytest.param(*assignment_case_7()),
pytest.param(*assignment_case_8()),
pytest.param(*assignment_case_9()),
pytest.param(*assignment_case_10()),
pytest.param(*assignment_case_11()),
pytest.param(*assignment_case_12()),
pytest.param(*assignment_case_13()),
pytest.param(*assignment_case_14()),
pytest.param(*assignment_case_15()),
pytest.param(*assignment_case_16()),
pytest.param(*assignment_case_17()),
pytest.param(*assignment_case_18()),
pytest.param(*assignment_case_19()),
pytest.param(*assignment_case_20()),
pytest.param(*assignment_case_21()),
pytest.param(*assignment_case_22()),
pytest.param(*assignment_case_23()),
pytest.param(*assignment_case_24()),
pytest.param(*assignment_case_25()),
pytest.param(*assignment_case_26()),
pytest.param(*assignment_case_27()),
pytest.param(*assignment_case_28()),
pytest.param(*assignment_case_29()),
pytest.param(*assignment_case_30()),
pytest.param(*assignment_case_31()),
pytest.param(*assignment_case_32()),
pytest.param(*assignment_case_33()),
pytest.param(*assignment_case_34()),
pytest.param(*assignment_case_35()),
pytest.param(*assignment_case_36()),
pytest.param(*assignment_case_37()),
pytest.param(*assignment_case_38()),
pytest.param(*assignment_case_39()),
pytest.param(*assignment_case_40()),
],
)
def test_static_assignment(shape, function, helpers):
"""
Test static assignment.
"""
configuration = helpers.configuration()
compiler = fhe.Compiler(function, {"x": "encrypted"})
inputset = [np.random.randint(0, 2**7, size=shape) for _ in range(100)]
circuit = compiler.compile(inputset, configuration)
sample = np.random.randint(0, 2**7, size=shape)
helpers.check_execution(circuit, function, sample)
def test_bad_static_assignment(helpers):
"""
Test static assignment with bad parameters.
"""
configuration = helpers.configuration()
# with float
# ----------
def f(x):
x[1.5] = 0
return x
compiler = fhe.Compiler(f, {"x": "encrypted"})
inputset = [[1, 2, 3]]
with pytest.raises(ValueError) as excinfo:
compiler.compile(inputset, configuration)
assert (
str(excinfo.value)
== "Tracer<output=EncryptedTensor<uint2, shape=(3,)>>[1.5] cannot be assigned 0"
)
# with bad slice
# --------------
def g(x):
x[slice(1.5, 2.5, None)] = 0
return x
compiler = fhe.Compiler(g, {"x": "encrypted"})
inputset = [[1, 2, 3]]
with pytest.raises(ValueError) as excinfo:
compiler.compile(inputset, configuration)
assert (
str(excinfo.value)
== "Tracer<output=EncryptedTensor<uint2, shape=(3,)>>[1.5:2.5] cannot be assigned 0"
)
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