github/concrete
1
1
Fork 0
mirror of https://github.com/zama-ai/concrete.git synced 2026-02-09 03:55:04 -05:00
Code Issues Packages Projects Releases Wiki Activity
Files
511b6bd6c0c537a1159acb8636775bddd2ce1c19
concrete/tests/common/representation/test_intermediate.py
Umut 5aad8c50ac test: create check_array_equality fixture
2021-12-06 16:44:32 +03:00

433 lines
15 KiB
Python
Raw Blame History

"""Test file for intermediate representation"""
from copy import deepcopy
import numpy
import pytest
from concrete.common.data_types.floats import Float
from concrete.common.data_types.integers import Integer
from concrete.common.representation import intermediate as ir
from concrete.common.values import ClearScalar, ClearTensor, EncryptedScalar, EncryptedTensor
@pytest.mark.parametrize(
"node,input_data,expected_result",
[
pytest.param(
ir.Add([EncryptedScalar(Integer(64, False)), EncryptedScalar(Integer(64, False))]),
[10, 4589],
4599,
id="Add",
),
pytest.param(
ir.Sub([EncryptedScalar(Integer(64, False)), EncryptedScalar(Integer(64, False))]),
[10, 4589],
-4579,
id="Sub",
),
pytest.param(
ir.Mul([EncryptedScalar(Integer(64, False)), EncryptedScalar(Integer(64, False))]),
[10, 4589],
45890,
id="Mul",
),
pytest.param(ir.Input(ClearScalar(Integer(32, True)), "in", 0), [42], 42, id="Input"),
pytest.param(ir.Constant(42), None, 42, id="Constant"),
pytest.param(ir.Constant(-42), None, -42, id="Constant"),
pytest.param(
ir.GenericFunction(
[EncryptedScalar(Integer(7, False))],
lambda x: x + 3,
EncryptedScalar(Integer(7, False)),
op_kind="TLU",
),
[10],
13,
id="GenericFunction, x + 3",
),
pytest.param(
ir.GenericFunction(
[EncryptedScalar(Integer(7, False))],
lambda x, y: x + y,
EncryptedScalar(Integer(7, False)),
op_kind="TLU",
op_kwargs={"y": 3},
),
[10],
13,
id="GenericFunction, (x, y) -> x + y, where y is constant == 3",
),
pytest.param(
ir.GenericFunction(
[EncryptedScalar(Integer(7, False))],
lambda x, y: y[x],
EncryptedScalar(Integer(7, False)),
op_kind="TLU",
op_kwargs={"y": (1, 2, 3, 4)},
),
[2],
3,
id="GenericFunction, (x, y) -> y[x], where y is constant == (1, 2, 3, 4)",
),
pytest.param(
ir.GenericFunction(
[EncryptedScalar(Integer(7, False))],
lambda x, y: y[3],
EncryptedScalar(Integer(7, False)),
op_kind="TLU",
op_kwargs={"y": (1, 2, 3, 4)},
),
[2],
4,
id="GenericFunction, x, y -> y[3], where y is constant == (1, 2, 3, 4)",
),
pytest.param(
ir.Dot(
[
EncryptedTensor(Integer(32, True), shape=(4,)),
ClearTensor(Integer(32, True), shape=(4,)),
],
Integer(32, True),
),
[[1, 2, 3, 4], [4, 3, 2, 1]],
20,
id="Dot, [1, 2, 3, 4], [4, 3, 2, 1]",
),
pytest.param(
ir.Dot(
[
EncryptedTensor(Float(32), shape=(4,)),
ClearTensor(Float(32), shape=(4,)),
],
Float(32),
),
[[1.0, 2.0, 3.0, 4.0], [4.0, 3.0, 2.0, 1.0]],
20,
id="Dot, [1.0, 2.0, 3.0, 4.0], [4.0, 3.0, 2.0, 1.0]",
),
pytest.param(
ir.Dot(
[
EncryptedTensor(Integer(32, True), shape=(4,)),
ClearTensor(Integer(32, True), shape=(4,)),
],
Integer(32, True),
delegate_evaluation_function=numpy.dot,
),
[
numpy.array([1, 2, 3, 4], dtype=numpy.int32),
numpy.array([4, 3, 2, 1], dtype=numpy.int32),
],
20,
id="Dot, np.array([1, 2, 3, 4]), np.array([4, 3, 2, 1])",
),
pytest.param(
ir.IndexConstant(EncryptedTensor(Integer(4, True), shape=(4,)), (0,)),
[
numpy.array([1, 2, 3, 4], dtype=numpy.int32),
],
1,
id="IndexConstant, np.array([1, 2, 3, 4])[0]",
),
pytest.param(
ir.IndexConstant(EncryptedTensor(Integer(4, True), shape=(4,)), (slice(1, 3, None),)),
[
numpy.array([1, 2, 3, 4], dtype=numpy.int32),
],
numpy.array([2, 3]),
id="IndexConstant, np.array([1, 2, 3, 4])[1:3]",
),
pytest.param(
ir.IndexConstant(EncryptedTensor(Integer(4, True), shape=(4,)), (slice(3, 1, -1),)),
[
numpy.array([1, 2, 3, 4], dtype=numpy.int32),
],
numpy.array([4, 3], dtype=numpy.int32),
id="IndexConstant, np.array([1, 2, 3, 4])[3:1:-1]",
),
pytest.param(
ir.IndexConstant(
EncryptedTensor(Integer(5, True), shape=(4, 4)), (slice(1, 3, 1), slice(2, 0, -1))
),
[
numpy.array(
[
[1, 2, 3, 4],
[5, 6, 7, 8],
[9, 10, 11, 12],
[13, 14, 15, 16],
],
dtype=numpy.int32,
),
],
numpy.array(
[
[7, 6],
[11, 10],
],
dtype=numpy.int32,
),
id="IndexConstant, np.array([[1, 2, 3, 4]...[13, 14, 15, 16]])[1:3, 2:0:-1]",
),
pytest.param(
ir.MatMul(
[
EncryptedTensor(Integer(32, True), shape=(3, 2)),
ClearTensor(Integer(32, True), shape=(2, 3)),
],
Integer(32, True),
),
[numpy.arange(1, 7).reshape(3, 2), numpy.arange(1, 7).reshape(2, 3)],
numpy.array([[9, 12, 15], [19, 26, 33], [29, 40, 51]]),
id="MatMul, numpy.arange(1, 7).reshape(3, 2), numpy.arange(1, 7).reshape(2, 3)",
),
pytest.param(
ir.GenericFunction(
[EncryptedTensor(Integer(32, False), shape=(3, 5))],
lambda x: numpy.transpose(x),
EncryptedTensor(Integer(32, False), shape=(5, 3)),
op_kind="Memory",
),
[numpy.arange(15).reshape(3, 5)],
numpy.array([[0, 5, 10], [1, 6, 11], [2, 7, 12], [3, 8, 13], [4, 9, 14]]),
id="GenericFunction, x transpose",
),
pytest.param(
ir.GenericFunction(
[EncryptedTensor(Integer(32, False), shape=(3, 5))],
lambda x: numpy.ravel(x),
EncryptedTensor(Integer(32, False), shape=(5, 3)),
op_kind="Memory",
),
[numpy.arange(15).reshape(3, 5)],
numpy.arange(15),
id="GenericFunction, x ravel",
),
pytest.param(
ir.GenericFunction(
[EncryptedTensor(Integer(32, False), shape=(3, 5))],
lambda x: numpy.reshape(x, (5, 3)),
output_value=EncryptedTensor(Integer(32, False), shape=(5, 3)),
op_kind="Memory",
),
[numpy.arange(15).reshape(3, 5)],
numpy.arange(15).reshape(5, 3),
id="GenericFunction, x reshape",
),
],
)
def test_evaluate(
node: ir.IntermediateNode,
input_data,
expected_result: int,
check_array_equality,
):
"""Test evaluate methods on IntermediateNodes"""
if isinstance(expected_result, numpy.ndarray):
check_array_equality(node.evaluate(input_data), expected_result)
else:
assert node.evaluate(input_data) == expected_result
@pytest.mark.parametrize(
"node1,node2,expected_result",
[
(
ir.Add([EncryptedScalar(Integer(32, False)), EncryptedScalar(Integer(32, False))]),
ir.Add([EncryptedScalar(Integer(32, False)), EncryptedScalar(Integer(32, False))]),
True,
),
(
ir.Add([EncryptedScalar(Integer(16, False)), EncryptedScalar(Integer(32, False))]),
ir.Add([EncryptedScalar(Integer(32, False)), EncryptedScalar(Integer(16, False))]),
True,
),
(
ir.Add([EncryptedScalar(Integer(32, False)), EncryptedScalar(Integer(32, False))]),
ir.Sub([EncryptedScalar(Integer(32, False)), EncryptedScalar(Integer(32, False))]),
False,
),
(
ir.Sub([EncryptedScalar(Integer(32, False)), EncryptedScalar(Integer(32, False))]),
ir.Sub([EncryptedScalar(Integer(32, False)), EncryptedScalar(Integer(32, False))]),
True,
),
(
ir.Sub([EncryptedScalar(Integer(32, False)), EncryptedScalar(Integer(16, False))]),
ir.Sub([EncryptedScalar(Integer(32, False)), EncryptedScalar(Integer(16, False))]),
True,
),
(
ir.Sub([EncryptedScalar(Integer(32, False)), EncryptedScalar(Integer(16, False))]),
ir.Sub([EncryptedScalar(Integer(16, False)), EncryptedScalar(Integer(32, False))]),
False,
),
(
ir.Mul([EncryptedScalar(Integer(32, False)), EncryptedScalar(Integer(32, False))]),
ir.Mul([EncryptedScalar(Integer(32, False)), EncryptedScalar(Integer(32, False))]),
True,
),
(
ir.Mul([EncryptedScalar(Integer(32, False)), EncryptedScalar(Integer(32, False))]),
ir.Sub([EncryptedScalar(Integer(32, False)), EncryptedScalar(Integer(32, False))]),
False,
),
(
ir.Input(EncryptedScalar(Integer(32, False)), "x", 0),
ir.Sub([EncryptedScalar(Integer(32, False)), EncryptedScalar(Integer(32, False))]),
False,
),
(
ir.Input(EncryptedScalar(Integer(32, False)), "x", 0),
ir.Input(EncryptedScalar(Integer(32, False)), "x", 0),
True,
),
(
ir.Input(EncryptedScalar(Integer(32, False)), "x", 0),
ir.Input(EncryptedScalar(Integer(32, False)), "y", 0),
False,
),
(
ir.Input(EncryptedScalar(Integer(32, False)), "x", 0),
ir.Input(EncryptedScalar(Integer(32, False)), "x", 1),
False,
),
(
ir.Input(EncryptedScalar(Integer(32, False)), "x", 0),
ir.Input(EncryptedScalar(Integer(8, False)), "x", 0),
False,
),
(
ir.Constant(10),
ir.Constant(10),
True,
),
(
ir.Constant(10),
ir.Input(EncryptedScalar(Integer(8, False)), "x", 0),
False,
),
(
ir.Constant(10),
ir.Constant(10.0),
False,
),
(
ir.GenericFunction(
[EncryptedScalar(Integer(8, False))],
lambda x: x,
EncryptedScalar(Integer(8, False)),
op_kind="TLU",
),
ir.GenericFunction(
[EncryptedScalar(Integer(8, False))],
lambda x: x,
EncryptedScalar(Integer(8, False)),
op_kind="TLU",
),
True,
),
(
ir.GenericFunction(
[EncryptedScalar(Integer(8, False))],
lambda x: x,
EncryptedScalar(Integer(8, False)),
op_kind="TLU",
op_args=(1, 2, 3),
),
ir.GenericFunction(
[EncryptedScalar(Integer(8, False))],
lambda x: x,
EncryptedScalar(Integer(8, False)),
op_kind="TLU",
),
False,
),
(
ir.GenericFunction(
[EncryptedScalar(Integer(8, False))],
lambda x: x,
EncryptedScalar(Integer(8, False)),
op_kind="TLU",
op_kwargs={"tuple": (1, 2, 3)},
),
ir.GenericFunction(
[EncryptedScalar(Integer(8, False))],
lambda x: x,
EncryptedScalar(Integer(8, False)),
op_kind="TLU",
),
False,
),
(
ir.Dot(
[
EncryptedTensor(Integer(32, True), shape=(4,)),
ClearTensor(Integer(32, True), shape=(4,)),
],
Integer(32, True),
delegate_evaluation_function=numpy.dot,
),
ir.Dot(
[
EncryptedTensor(Integer(32, True), shape=(4,)),
ClearTensor(Integer(32, True), shape=(4,)),
],
Integer(32, True),
delegate_evaluation_function=numpy.dot,
),
True,
),
(
ir.Dot(
[
EncryptedTensor(Integer(32, True), shape=(4,)),
ClearTensor(Integer(32, True), shape=(4,)),
],
Integer(32, True),
delegate_evaluation_function=numpy.dot,
),
ir.Dot(
[
EncryptedTensor(Integer(32, True), shape=(4,)),
ClearTensor(Integer(32, True), shape=(4,)),
],
Integer(32, True),
),
False,
),
],
)
def test_is_equivalent_to(
node1: ir.IntermediateNode,
node2: ir.IntermediateNode,
expected_result: bool,
test_helpers,
):
"""Test is_equivalent_to methods on IntermediateNodes"""
assert (
test_helpers.nodes_are_equivalent(node1, node2)
== test_helpers.nodes_are_equivalent(node2, node1)
== expected_result
)
@pytest.mark.parametrize(
"list_to_fill,expected_list",
[
pytest.param([None, 1, 2, 3, None, None], [1, 1, 2, 3, 3, 3]),
pytest.param([None], None, marks=pytest.mark.xfail(strict=True)),
pytest.param([None, None, None, None, 7, None, None, None], [7, 7, 7, 7, 7, 7, 7, 7]),
pytest.param([None, None, 3, None, None, None, 2, None], [3, 3, 3, 3, 3, 2, 2, 2]),
],
)
def test_flood_replace_none_values(list_to_fill: list, expected_list: list):
"""Unit test for flood_replace_none_values"""
# avoid modifying the test input
list_to_fill_copy = deepcopy(list_to_fill)
ir.flood_replace_none_values(list_to_fill_copy)
assert all(value is not None for value in list_to_fill_copy)
assert list_to_fill_copy == expected_list
Reference in New Issue View Git Blame Copy Permalink