mirror of
https://github.com/zama-ai/concrete.git
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7e535f33db
- We tests few things that aren't costly to tests like wrappers - we reduce encrypted computation tests, as it's already done in cpp tests, while we add tests to cover supported types
80 lines
2.4 KiB
Python
80 lines
2.4 KiB
Python
import pytest
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import numpy as np
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from concrete.compiler.utils import ACCEPTED_NUMPY_UINTS
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from concrete.compiler import ClientSupport
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@pytest.mark.parametrize(
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"garbage",
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[
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pytest.param(None, id="None"),
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pytest.param([0, 1, 2], id="list"),
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pytest.param(0.5, id="float"),
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pytest.param(2**70, id="large int"),
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pytest.param(-8, id="negative int"),
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pytest.param("aze", id="str"),
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pytest.param(np.float64(0.8), id="np.float64"),
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pytest.param(np.int8(9), id="np.int8"),
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pytest.param(np.array([1, 2, 3], dtype=np.int64), id="np.array(np.int64)"),
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],
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)
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def test_invalid_arg_type(garbage):
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with pytest.raises(TypeError):
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ClientSupport._create_lambda_argument(garbage)
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@pytest.mark.parametrize(
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"value",
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[
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pytest.param(5, id="int"),
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pytest.param(np.uint8(5), id="uint8"),
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pytest.param(np.uint16(7), id="uint16"),
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pytest.param(np.uint32(9), id="uint32"),
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pytest.param(np.uint64(1), id="uint64"),
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],
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)
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def test_accepted_ints(value):
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try:
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arg = ClientSupport._create_lambda_argument(value)
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except Exception:
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pytest.fail(f"value of type {type(value)} should be supported")
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assert arg.is_scalar(), "should have been a scalar"
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assert arg.get_scalar() == value
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# TODO: #495
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# @pytest.mark.parametrize(
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# "dtype",
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# [
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# pytest.param(np.uint8, id="uint8"),
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# pytest.param(np.uint16, id="uint16"),
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# pytest.param(np.uint32, id="uint32"),
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# pytest.param(np.uint64, id="uint64"),
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# ],
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# )
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# def test_accepted_ndarray(dtype):
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# value = np.array([0, 1, 2], dtype=dtype)
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# try:
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# arg = ClientSupport._create_lambda_argument(value)
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# except Exception:
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# pytest.fail(f"value of type {type(value)} should be supported")
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# assert arg.is_tensor(), "should have been a tensor"
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# assert np.all(np.equal(arg.get_tensor_shape(), value.shape))
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# assert np.all(
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# np.equal(
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# value,
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# np.array(arg.get_tensor_data()).reshape(arg.get_tensor_shape()),
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# )
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# )
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def test_accepted_array_as_scalar():
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value = np.array(7, dtype=np.uint16)
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try:
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arg = ClientSupport._create_lambda_argument(value)
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except Exception:
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pytest.fail(f"value of type {type(value)} should be supported")
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assert arg.is_scalar(), "should have been a scalar"
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assert arg.get_scalar() == value
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