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concrete/tests/numpy/test_compile_constant_indexing.py
Umut 5aad8c50ac test: create check_array_equality fixture
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"""Test module for constant indexing."""
import numpy as np
import pytest
from concrete.common.data_types import UnsignedInteger
from concrete.common.values import EncryptedScalar, EncryptedTensor
from concrete.numpy import (
compile_numpy_function,
compile_numpy_function_into_op_graph_and_measure_bounds,
)
@pytest.mark.parametrize(
"input_value,function_with_indexing,output_value",
[
pytest.param(
EncryptedTensor(UnsignedInteger(1), shape=(3,)),
lambda x: x[-3],
EncryptedScalar(UnsignedInteger(1)),
),
pytest.param(
EncryptedTensor(UnsignedInteger(1), shape=(3,)),
lambda x: x[-2],
EncryptedScalar(UnsignedInteger(1)),
),
pytest.param(
EncryptedTensor(UnsignedInteger(1), shape=(3,)),
lambda x: x[-1],
EncryptedScalar(UnsignedInteger(1)),
),
pytest.param(
EncryptedTensor(UnsignedInteger(1), shape=(3,)),
lambda x: x[0],
EncryptedScalar(UnsignedInteger(1)),
),
pytest.param(
EncryptedTensor(UnsignedInteger(1), shape=(3,)),
lambda x: x[1],
EncryptedScalar(UnsignedInteger(1)),
),
pytest.param(
EncryptedTensor(UnsignedInteger(1), shape=(3,)),
lambda x: x[2],
EncryptedScalar(UnsignedInteger(1)),
),
pytest.param(
EncryptedTensor(UnsignedInteger(1), shape=(3,)),
lambda x: x[:],
EncryptedTensor(UnsignedInteger(1), shape=(3,)),
),
pytest.param(
EncryptedTensor(UnsignedInteger(1), shape=(3,)),
lambda x: x[-3:],
EncryptedTensor(UnsignedInteger(1), shape=(3,)),
),
pytest.param(
EncryptedTensor(UnsignedInteger(1), shape=(3,)),
lambda x: x[-2:],
EncryptedTensor(UnsignedInteger(1), shape=(2,)),
),
pytest.param(
EncryptedTensor(UnsignedInteger(1), shape=(3,)),
lambda x: x[-1:],
EncryptedTensor(UnsignedInteger(1), shape=(1,)),
),
pytest.param(
EncryptedTensor(UnsignedInteger(1), shape=(3,)),
lambda x: x[0:],
EncryptedTensor(UnsignedInteger(1), shape=(3,)),
),
pytest.param(
EncryptedTensor(UnsignedInteger(1), shape=(3,)),
lambda x: x[1:],
EncryptedTensor(UnsignedInteger(1), shape=(2,)),
),
pytest.param(
EncryptedTensor(UnsignedInteger(1), shape=(3,)),
lambda x: x[2:],
EncryptedTensor(UnsignedInteger(1), shape=(1,)),
),
pytest.param(
EncryptedTensor(UnsignedInteger(1), shape=(3,)),
lambda x: x[:-1],
EncryptedTensor(UnsignedInteger(1), shape=(2,)),
),
pytest.param(
EncryptedTensor(UnsignedInteger(1), shape=(3,)),
lambda x: x[:-2],
EncryptedTensor(UnsignedInteger(1), shape=(1,)),
),
pytest.param(
EncryptedTensor(UnsignedInteger(1), shape=(3,)),
lambda x: x[:1],
EncryptedTensor(UnsignedInteger(1), shape=(1,)),
),
pytest.param(
EncryptedTensor(UnsignedInteger(1), shape=(3,)),
lambda x: x[:2],
EncryptedTensor(UnsignedInteger(1), shape=(2,)),
),
pytest.param(
EncryptedTensor(UnsignedInteger(1), shape=(3,)),
lambda x: x[:3],
EncryptedTensor(UnsignedInteger(1), shape=(3,)),
),
pytest.param(
EncryptedTensor(UnsignedInteger(1), shape=(3,)),
lambda x: x[-3:-2],
EncryptedTensor(UnsignedInteger(1), shape=(1,)),
),
pytest.param(
EncryptedTensor(UnsignedInteger(1), shape=(3,)),
lambda x: x[-3:-1],
EncryptedTensor(UnsignedInteger(1), shape=(2,)),
),
pytest.param(
EncryptedTensor(UnsignedInteger(1), shape=(3,)),
lambda x: x[-3:1],
EncryptedTensor(UnsignedInteger(1), shape=(1,)),
),
pytest.param(
EncryptedTensor(UnsignedInteger(1), shape=(3,)),
lambda x: x[-3:2],
EncryptedTensor(UnsignedInteger(1), shape=(2,)),
),
pytest.param(
EncryptedTensor(UnsignedInteger(1), shape=(3,)),
lambda x: x[-3:3],
EncryptedTensor(UnsignedInteger(1), shape=(3,)),
),
pytest.param(
EncryptedTensor(UnsignedInteger(1), shape=(3,)),
lambda x: x[-2:-1],
EncryptedTensor(UnsignedInteger(1), shape=(1,)),
),
pytest.param(
EncryptedTensor(UnsignedInteger(1), shape=(3,)),
lambda x: x[-2:2],
EncryptedTensor(UnsignedInteger(1), shape=(1,)),
),
pytest.param(
EncryptedTensor(UnsignedInteger(1), shape=(3,)),
lambda x: x[-2:3],
EncryptedTensor(UnsignedInteger(1), shape=(2,)),
),
pytest.param(
EncryptedTensor(UnsignedInteger(1), shape=(3,)),
lambda x: x[-1:3],
EncryptedTensor(UnsignedInteger(1), shape=(1,)),
),
pytest.param(
EncryptedTensor(UnsignedInteger(1), shape=(3,)),
lambda x: x[0:-2],
EncryptedTensor(UnsignedInteger(1), shape=(1,)),
),
pytest.param(
EncryptedTensor(UnsignedInteger(1), shape=(3,)),
lambda x: x[0:-1],
EncryptedTensor(UnsignedInteger(1), shape=(2,)),
),
pytest.param(
EncryptedTensor(UnsignedInteger(1), shape=(3,)),
lambda x: x[0:1],
EncryptedTensor(UnsignedInteger(1), shape=(1,)),
),
pytest.param(
EncryptedTensor(UnsignedInteger(1), shape=(3,)),
lambda x: x[0:2],
EncryptedTensor(UnsignedInteger(1), shape=(2,)),
),
pytest.param(
EncryptedTensor(UnsignedInteger(1), shape=(3,)),
lambda x: x[0:3],
EncryptedTensor(UnsignedInteger(1), shape=(3,)),
),
pytest.param(
EncryptedTensor(UnsignedInteger(1), shape=(3,)),
lambda x: x[1:-1],
EncryptedTensor(UnsignedInteger(1), shape=(1,)),
),
pytest.param(
EncryptedTensor(UnsignedInteger(1), shape=(3,)),
lambda x: x[1:2],
EncryptedTensor(UnsignedInteger(1), shape=(1,)),
),
pytest.param(
EncryptedTensor(UnsignedInteger(1), shape=(3,)),
lambda x: x[1:3],
EncryptedTensor(UnsignedInteger(1), shape=(2,)),
),
pytest.param(
EncryptedTensor(UnsignedInteger(1), shape=(3,)),
lambda x: x[2:3],
EncryptedTensor(UnsignedInteger(1), shape=(1,)),
),
pytest.param(
EncryptedTensor(UnsignedInteger(1), shape=(3,)),
lambda x: x[::-1],
EncryptedTensor(UnsignedInteger(1), shape=(3,)),
),
pytest.param(
EncryptedTensor(UnsignedInteger(1), shape=(3,)),
lambda x: x[-3::-1],
EncryptedTensor(UnsignedInteger(1), shape=(1,)),
),
pytest.param(
EncryptedTensor(UnsignedInteger(1), shape=(3,)),
lambda x: x[-2::-1],
EncryptedTensor(UnsignedInteger(1), shape=(2,)),
),
pytest.param(
EncryptedTensor(UnsignedInteger(1), shape=(3,)),
lambda x: x[-1::-1],
EncryptedTensor(UnsignedInteger(1), shape=(3,)),
),
pytest.param(
EncryptedTensor(UnsignedInteger(1), shape=(3,)),
lambda x: x[0::-1],
EncryptedTensor(UnsignedInteger(1), shape=(1,)),
),
pytest.param(
EncryptedTensor(UnsignedInteger(1), shape=(3,)),
lambda x: x[1::-1],
EncryptedTensor(UnsignedInteger(1), shape=(2,)),
),
pytest.param(
EncryptedTensor(UnsignedInteger(1), shape=(3,)),
lambda x: x[2::-1],
EncryptedTensor(UnsignedInteger(1), shape=(3,)),
),
pytest.param(
EncryptedTensor(UnsignedInteger(1), shape=(3,)),
lambda x: x[:-3:-1],
EncryptedTensor(UnsignedInteger(1), shape=(2,)),
),
pytest.param(
EncryptedTensor(UnsignedInteger(1), shape=(3,)),
lambda x: x[:-2:-1],
EncryptedTensor(UnsignedInteger(1), shape=(1,)),
),
pytest.param(
EncryptedTensor(UnsignedInteger(1), shape=(3,)),
lambda x: x[:0:-1],
EncryptedTensor(UnsignedInteger(1), shape=(2,)),
),
pytest.param(
EncryptedTensor(UnsignedInteger(1), shape=(3,)),
lambda x: x[:1:-1],
EncryptedTensor(UnsignedInteger(1), shape=(1,)),
),
pytest.param(
EncryptedTensor(UnsignedInteger(1), shape=(3,)),
lambda x: x[2:0:-1],
EncryptedTensor(UnsignedInteger(1), shape=(2,)),
),
pytest.param(
EncryptedTensor(UnsignedInteger(1), shape=(3,)),
lambda x: x[2:1:-1],
EncryptedTensor(UnsignedInteger(1), shape=(1,)),
),
pytest.param(
EncryptedTensor(UnsignedInteger(1), shape=(3,)),
lambda x: x[-1:1:-1],
EncryptedTensor(UnsignedInteger(1), shape=(1,)),
),
pytest.param(
EncryptedTensor(UnsignedInteger(1), shape=(3,)),
lambda x: x[-1:0:-1],
EncryptedTensor(UnsignedInteger(1), shape=(2,)),
),
pytest.param(
EncryptedTensor(UnsignedInteger(1), shape=(3, 4, 5)),
lambda x: x[:, :, :],
EncryptedTensor(UnsignedInteger(1), shape=(3, 4, 5)),
),
pytest.param(
EncryptedTensor(UnsignedInteger(1), shape=(3, 4, 5)),
lambda x: x[0, :, :],
EncryptedTensor(UnsignedInteger(1), shape=(4, 5)),
),
pytest.param(
EncryptedTensor(UnsignedInteger(1), shape=(3, 4, 5)),
lambda x: x[:, 0, :],
EncryptedTensor(UnsignedInteger(1), shape=(3, 5)),
),
pytest.param(
EncryptedTensor(UnsignedInteger(1), shape=(3, 4, 5)),
lambda x: x[:, :, 0],
EncryptedTensor(UnsignedInteger(1), shape=(3, 4)),
),
pytest.param(
EncryptedTensor(UnsignedInteger(1), shape=(3, 4, 5)),
lambda x: x[0, 0, :],
EncryptedTensor(UnsignedInteger(1), shape=(5,)),
),
pytest.param(
EncryptedTensor(UnsignedInteger(1), shape=(3, 4, 5)),
lambda x: x[0, :, 0],
EncryptedTensor(UnsignedInteger(1), shape=(4,)),
),
pytest.param(
EncryptedTensor(UnsignedInteger(1), shape=(3, 4, 5)),
lambda x: x[:, 0, 0],
EncryptedTensor(UnsignedInteger(1), shape=(3,)),
),
pytest.param(
EncryptedTensor(UnsignedInteger(1), shape=(3, 4, 5)),
lambda x: x[0:, 1:, 2:],
EncryptedTensor(UnsignedInteger(1), shape=(3, 3, 3)),
),
pytest.param(
EncryptedTensor(UnsignedInteger(1), shape=(3, 4, 5)),
lambda x: x[2:, 1:, 0:],
EncryptedTensor(UnsignedInteger(1), shape=(1, 3, 5)),
),
pytest.param(
EncryptedTensor(UnsignedInteger(1), shape=(3, 4, 5)),
lambda x: x[0],
EncryptedTensor(UnsignedInteger(1), shape=(4, 5)),
),
pytest.param(
EncryptedTensor(UnsignedInteger(1), shape=(3, 4, 5)),
lambda x: x[0, 0],
EncryptedTensor(UnsignedInteger(1), shape=(5,)),
),
pytest.param(
EncryptedTensor(UnsignedInteger(1), shape=(3, 4, 5)),
lambda x: x[0, 0, 0],
EncryptedScalar(UnsignedInteger(1)),
),
],
)
def test_constant_indexing(
default_compilation_configuration,
input_value,
function_with_indexing,
output_value,
):
"""Test compile_numpy_function_into_op_graph with constant indexing"""
inputset = [
np.random.randint(
input_value.dtype.min_value(),
input_value.dtype.max_value() + 1,
size=input_value.shape,
)
for _ in range(10)
]
op_graph = compile_numpy_function_into_op_graph_and_measure_bounds(
function_with_indexing,
{"x": input_value},
inputset,
default_compilation_configuration,
)
assert len(op_graph.output_nodes) == 1
output_node = op_graph.output_nodes[0]
assert len(output_node.outputs) == 1
assert output_value == output_node.outputs[0]
@pytest.mark.parametrize(
"input_value,function_with_indexing,expected_error_type,expected_error_message",
[
pytest.param(
EncryptedScalar(UnsignedInteger(1)),
lambda x: x[0],
TypeError,
"Only tensors can be indexed but you tried to index EncryptedScalar<uint1>",
),
pytest.param(
EncryptedTensor(UnsignedInteger(1), shape=(3,)),
lambda x: x[0.5],
TypeError,
"Only integers and integer slices can be used for indexing "
"but you tried to use 0.5 for indexing",
),
pytest.param(
EncryptedTensor(UnsignedInteger(1), shape=(3,)),
lambda x: x[1:5:0.5], # type: ignore
TypeError,
"Only integers and integer slices can be used for indexing "
"but you tried to use 1:5:0.5 for indexing",
),
pytest.param(
EncryptedTensor(UnsignedInteger(1), shape=(3,)),
lambda x: x[0, 1],
ValueError,
"Tensor of shape (3,) cannot be indexed with [0, 1] "
"as the index has more elements than the number of dimensions of the tensor",
),
pytest.param(
EncryptedTensor(UnsignedInteger(1), shape=(3,)),
lambda x: x[5],
ValueError,
"Tensor of shape (3,) cannot be indexed with [5] "
"because index is out of range for dimension 0",
),
pytest.param(
EncryptedTensor(UnsignedInteger(1), shape=(3,)),
lambda x: x[5:],
ValueError,
"Tensor of shape (3,) cannot be indexed with [5:] "
"because start index is out of range for dimension 0",
),
pytest.param(
EncryptedTensor(UnsignedInteger(1), shape=(3,)),
lambda x: x[:10],
ValueError,
"Tensor of shape (3,) cannot be indexed with [:10] "
"because stop index is out of range for dimension 0",
),
pytest.param(
EncryptedTensor(UnsignedInteger(1), shape=(3,)),
lambda x: x[2:0],
ValueError,
"Tensor of shape (3,) cannot be indexed with [2:0] "
"because start index is not less than stop index for dimension 0",
),
pytest.param(
EncryptedTensor(UnsignedInteger(1), shape=(3,)),
lambda x: x[5::-1],
ValueError,
"Tensor of shape (3,) cannot be indexed with [5::-1] "
"because start index is out of range for dimension 0",
),
pytest.param(
EncryptedTensor(UnsignedInteger(1), shape=(3,)),
lambda x: x[:10:-1],
ValueError,
"Tensor of shape (3,) cannot be indexed with [:10:-1] "
"because stop index is out of range for dimension 0",
),
pytest.param(
EncryptedTensor(UnsignedInteger(1), shape=(3,)),
lambda x: x[0:2:-1],
ValueError,
"Tensor of shape (3,) cannot be indexed with [0:2:-1] "
"because step is negative and stop index is not less than start index for dimension 0",
),
pytest.param(
EncryptedTensor(UnsignedInteger(1), shape=(3,)),
lambda x: x[::0],
ValueError,
"Tensor of shape (3,) cannot be indexed with [::0] "
"because step is zero for dimension 0",
),
],
)
def test_invalid_constant_indexing(
default_compilation_configuration,
input_value,
function_with_indexing,
expected_error_type,
expected_error_message,
):
"""Test compile_numpy_function_into_op_graph with invalid constant indexing"""
with pytest.raises(expected_error_type):
try:
inputset = [
(
np.random.randint(
input_value.dtype.min_value(),
input_value.dtype.max_value() + 1,
size=input_value.shape,
),
)
for _ in range(10)
]
compile_numpy_function_into_op_graph_and_measure_bounds(
function_with_indexing,
{"x": input_value},
inputset,
default_compilation_configuration,
)
except Exception as error:
assert str(error) == expected_error_message
raise
@pytest.mark.parametrize(
"input_value,function_with_indexing,output_value",
[
pytest.param(
EncryptedTensor(UnsignedInteger(1), shape=(3,)),
lambda x: x[np.uint32(0)],
EncryptedScalar(UnsignedInteger(1)),
),
pytest.param(
EncryptedTensor(UnsignedInteger(1), shape=(3,)),
lambda x: x[slice(np.uint32(2), np.int32(0), np.int8(-1))],
EncryptedTensor(UnsignedInteger(1), shape=(2,)),
),
pytest.param(
EncryptedTensor(UnsignedInteger(1), shape=(3,)),
lambda x: x[np.array(0)],
EncryptedScalar(UnsignedInteger(1)),
),
pytest.param(
EncryptedTensor(UnsignedInteger(1), shape=(3,)),
lambda x: x[slice(np.array(2), np.array(0), np.array(-1))],
EncryptedTensor(UnsignedInteger(1), shape=(2,)),
),
],
)
def test_constant_indexing_with_numpy_integers(
default_compilation_configuration,
input_value,
function_with_indexing,
output_value,
):
"""Test compile_numpy_function_into_op_graph with constant indexing with numpy integers"""
inputset = [
np.random.randint(
input_value.dtype.min_value(),
input_value.dtype.max_value() + 1,
size=input_value.shape,
)
for _ in range(10)
]
op_graph = compile_numpy_function_into_op_graph_and_measure_bounds(
function_with_indexing,
{"x": input_value},
inputset,
default_compilation_configuration,
)
assert len(op_graph.output_nodes) == 1
output_node = op_graph.output_nodes[0]
assert len(output_node.outputs) == 1
assert output_value == output_node.outputs[0]
@pytest.mark.parametrize(
"input_value,function_with_indexing,expected_error_type,expected_error_message",
[
pytest.param(
EncryptedTensor(UnsignedInteger(1), shape=(3,)),
lambda x: x[np.float32(1.5)],
TypeError,
"Only integers and integer slices can be used for indexing "
"but you tried to use 1.5 for indexing",
),
pytest.param(
EncryptedTensor(UnsignedInteger(1), shape=(3,)),
lambda x: x[np.array(1.5)],
TypeError,
"Only integers and integer slices can be used for indexing "
"but you tried to use 1.5 for indexing",
),
pytest.param(
EncryptedTensor(UnsignedInteger(1), shape=(3,)),
lambda x: x[np.array([1, 2])],
TypeError,
"Only integers and integer slices can be used for indexing "
"but you tried to use [1 2] for indexing",
),
],
)
def test_invalid_constant_indexing_with_numpy_values(
default_compilation_configuration,
input_value,
function_with_indexing,
expected_error_type,
expected_error_message,
):
"""Test compile_numpy_function_into_op_graph with invalid constant indexing with numpy values"""
with pytest.raises(expected_error_type):
try:
inputset = [
(
np.random.randint(
input_value.dtype.min_value(),
input_value.dtype.max_value() + 1,
size=input_value.shape,
),
)
for _ in range(10)
]
compile_numpy_function_into_op_graph_and_measure_bounds(
function_with_indexing,
{"x": input_value},
inputset,
default_compilation_configuration,
)
except Exception as error:
assert str(error) == expected_error_message
raise
@pytest.mark.parametrize(
"function,parameters,inputset,test_input,expected_output",
[
pytest.param(
lambda x: x[0],
{
"x": EncryptedTensor(UnsignedInteger(3), shape=(3,)),
},
[np.random.randint(0, 2 ** 3, size=(3,)) for _ in range(10)],
([4, 2, 6],),
4,
),
pytest.param(
lambda x: x[-1],
{
"x": EncryptedTensor(UnsignedInteger(3), shape=(3,)),
},
[np.random.randint(0, 2 ** 3, size=(3,)) for _ in range(10)],
([4, 2, 6],),
6,
),
pytest.param(
lambda x: x[:3],
{
"x": EncryptedTensor(UnsignedInteger(3), shape=(4,)),
},
[np.random.randint(0, 2 ** 3, size=(4,)) for _ in range(10)],
([4, 2, 6, 1],),
[4, 2, 6],
),
pytest.param(
lambda x: x[2:],
{
"x": EncryptedTensor(UnsignedInteger(3), shape=(4,)),
},
[np.random.randint(0, 2 ** 3, size=(4,)) for _ in range(10)],
([4, 2, 6, 1],),
[6, 1],
),
pytest.param(
lambda x: x[1:3],
{
"x": EncryptedTensor(UnsignedInteger(3), shape=(4,)),
},
[np.random.randint(0, 2 ** 3, size=(4,)) for _ in range(10)],
([4, 2, 6, 1],),
[2, 6],
),
pytest.param(
lambda x: x[::2],
{
"x": EncryptedTensor(UnsignedInteger(3), shape=(4,)),
},
[np.random.randint(0, 2 ** 3, size=(4,)) for _ in range(10)],
([4, 2, 6, 1],),
[4, 6],
),
pytest.param(
lambda x: x[::-1],
{
"x": EncryptedTensor(UnsignedInteger(3), shape=(4,)),
},
[np.random.randint(0, 2 ** 3, size=(4,)) for _ in range(10)],
([4, 2, 6, 1],),
[1, 6, 2, 4],
),
pytest.param(
lambda x: x[1, 0],
{
"x": EncryptedTensor(UnsignedInteger(6), shape=(3, 2)),
},
[np.random.randint(0, 2 ** 6, size=(3, 2)) for _ in range(10)],
([[11, 12], [21, 22], [31, 32]],),
21,
),
pytest.param(
lambda x: x[:, :],
{
"x": EncryptedTensor(UnsignedInteger(6), shape=(3, 2)),
},
[np.random.randint(0, 2 ** 6, size=(3, 2)) for _ in range(10)],
([[11, 12], [21, 22], [31, 32]],),
[[11, 12], [21, 22], [31, 32]],
),
pytest.param(
lambda x: x[0, :],
{
"x": EncryptedTensor(UnsignedInteger(6), shape=(3, 2)),
},
[np.random.randint(0, 2 ** 6, size=(3, 2)) for _ in range(10)],
([[11, 12], [21, 22], [31, 32]],),
[11, 12],
marks=pytest.mark.xfail(strict=True),
),
pytest.param(
lambda x: x[:, 0],
{
"x": EncryptedTensor(UnsignedInteger(6), shape=(3, 2)),
},
[np.random.randint(0, 2 ** 6, size=(3, 2)) for _ in range(10)],
([[11, 12], [21, 22], [31, 32]],),
[11, 21, 31],
marks=pytest.mark.xfail(strict=True),
),
],
)
def test_constant_indexing_run_correctness(
function,
parameters,
inputset,
test_input,
expected_output,
default_compilation_configuration,
check_array_equality,
):
"""Test correctness of results when running a compiled function with tensor operators"""
circuit = compile_numpy_function(
function,
parameters,
inputset,
default_compilation_configuration,
)
numpy_test_input = tuple(
item if isinstance(item, int) else np.array(item, dtype=np.uint8) for item in test_input
)
output = circuit.run(*numpy_test_input)
expected = np.array(expected_output, dtype=np.uint8)
check_array_equality(output, expected)
@pytest.mark.parametrize(
"function,parameters,inputset,match",
[
pytest.param(
lambda x: x[0:1],
{
"x": EncryptedTensor(UnsignedInteger(3), shape=(3,)),
},
[np.random.randint(0, 2 ** 3, size=(3,)) for _ in range(10)],
(
"Indexing of EncryptedTensor<uint3, shape=(3,)> with [0:1] "
"cannot be converted to MLIR yet"
),
),
],
)
def test_constant_indexing_failed_compilation(
function,
parameters,
inputset,
match,
default_compilation_configuration,
):
"""Test compilation failures of compiled function with constant indexing"""
with pytest.raises(RuntimeError) as excinfo:
compile_numpy_function(
function,
parameters,
inputset,
default_compilation_configuration,
)
assert str(excinfo.value) == match, str(excinfo.value)
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