mirror of
https://github.com/zama-ai/concrete.git
synced 2026-02-09 03:55:04 -05:00
80 lines
2.4 KiB
Python
80 lines
2.4 KiB
Python
import pytest
|
|
import numpy as np
|
|
from concrete.compiler.utils import ACCEPTED_NUMPY_UINTS
|
|
from concrete.compiler import ClientSupport
|
|
|
|
|
|
@pytest.mark.parametrize(
|
|
"garbage",
|
|
[
|
|
pytest.param(None, id="None"),
|
|
pytest.param([0, 1, 2], id="list"),
|
|
pytest.param(0.5, id="float"),
|
|
pytest.param(2**70, id="large int"),
|
|
pytest.param(-8, id="negative int"),
|
|
pytest.param("aze", id="str"),
|
|
pytest.param(np.float64(0.8), id="np.float64"),
|
|
pytest.param(np.int8(9), id="np.int8"),
|
|
pytest.param(np.array([1, 2, 3], dtype=np.int64), id="np.array(np.int64)"),
|
|
],
|
|
)
|
|
def test_invalid_arg_type(garbage):
|
|
with pytest.raises(TypeError):
|
|
ClientSupport._create_lambda_argument(garbage)
|
|
|
|
|
|
@pytest.mark.parametrize(
|
|
"value",
|
|
[
|
|
pytest.param(5, id="int"),
|
|
pytest.param(np.uint8(5), id="uint8"),
|
|
pytest.param(np.uint16(7), id="uint16"),
|
|
pytest.param(np.uint32(9), id="uint32"),
|
|
pytest.param(np.uint64(1), id="uint64"),
|
|
],
|
|
)
|
|
def test_accepted_ints(value):
|
|
try:
|
|
arg = ClientSupport._create_lambda_argument(value)
|
|
except Exception:
|
|
pytest.fail(f"value of type {type(value)} should be supported")
|
|
assert arg.is_scalar(), "should have been a scalar"
|
|
assert arg.get_scalar() == value
|
|
|
|
|
|
# TODO: #495
|
|
@pytest.mark.parametrize(
|
|
"dtype, maxvalue",
|
|
[
|
|
pytest.param(np.uint8, 2**8 - 1, id="uint8"),
|
|
pytest.param(np.uint16, 2**16 - 1, id="uint16"),
|
|
pytest.param(np.uint32, 2**32 - 1, id="uint32"),
|
|
pytest.param(np.uint64, 2**64 - 1, id="uint64"),
|
|
],
|
|
)
|
|
def test_accepted_ndarray(dtype, maxvalue):
|
|
value = np.array([0, 1, 2, maxvalue], dtype=dtype)
|
|
try:
|
|
arg = ClientSupport._create_lambda_argument(value)
|
|
except Exception:
|
|
pytest.fail(f"value of type {type(value)} should be supported")
|
|
|
|
assert arg.is_tensor(), "should have been a tensor"
|
|
assert np.all(np.equal(arg.get_tensor_shape(), value.shape))
|
|
assert np.all(
|
|
np.equal(
|
|
value,
|
|
np.array(arg.get_tensor_data()).reshape(arg.get_tensor_shape()),
|
|
)
|
|
)
|
|
|
|
|
|
def test_accepted_array_as_scalar():
|
|
value = np.array(7, dtype=np.uint16)
|
|
try:
|
|
arg = ClientSupport._create_lambda_argument(value)
|
|
except Exception:
|
|
pytest.fail(f"value of type {type(value)} should be supported")
|
|
assert arg.is_scalar(), "should have been a scalar"
|
|
assert arg.get_scalar() == value
|