remove some redundant tests for logic functions

Author: ndgrigorian

dpctl/tests/elementwise/test_logical_and.py

@@ -14,16 +14,13 @@
 #  See the License for the specific language governing permissions and
 #  limitations under the License.
 
-import ctypes
-
 import numpy as np
 import pytest
 
-import dpctl
 import dpctl.tensor as dpt
 from dpctl.tests.helper import get_queue_or_skip, skip_if_dtype_not_supported
 
-from .utils import _all_dtypes, _compare_dtypes, _usm_types
+from .utils import _all_dtypes, _compare_dtypes
 
 
 @pytest.mark.parametrize("op1_dtype", _all_dtypes)
@@ -157,148 +154,3 @@ def test_logical_and_complex_float():
             r3 = dpt.logical_and(ar3, ar1)
             expected3 = np.logical_and(ar3_np, ar1_np)
             assert (dpt.asnumpy(r3) == expected3).all()
-
-
-@pytest.mark.parametrize("op1_usm_type", _usm_types)
-@pytest.mark.parametrize("op2_usm_type", _usm_types)
-def test_logical_and_usm_type_matrix(op1_usm_type, op2_usm_type):
-    get_queue_or_skip()
-
-    sz = 128
-    ar1 = dpt.asarray(
-        np.random.randint(0, 2, sz), dtype="i4", usm_type=op1_usm_type
-    )
-    ar2 = dpt.asarray(
-        np.random.randint(0, 2, sz), dtype=ar1.dtype, usm_type=op2_usm_type
-    )
-
-    r = dpt.logical_and(ar1, ar2)
-    assert isinstance(r, dpt.usm_ndarray)
-    expected_usm_type = dpctl.utils.get_coerced_usm_type(
-        (op1_usm_type, op2_usm_type)
-    )
-    assert r.usm_type == expected_usm_type
-
-
-def test_logical_and_order():
-    get_queue_or_skip()
-
-    ar1 = dpt.ones((20, 20), dtype="i4", order="C")
-    ar2 = dpt.ones((20, 20), dtype="i4", order="C")
-    r1 = dpt.logical_and(ar1, ar2, order="C")
-    assert r1.flags.c_contiguous
-    r2 = dpt.logical_and(ar1, ar2, order="F")
-    assert r2.flags.f_contiguous
-    r3 = dpt.logical_and(ar1, ar2, order="A")
-    assert r3.flags.c_contiguous
-    r4 = dpt.logical_and(ar1, ar2, order="K")
-    assert r4.flags.c_contiguous
-
-    ar1 = dpt.ones((20, 20), dtype="i4", order="F")
-    ar2 = dpt.ones((20, 20), dtype="i4", order="F")
-    r1 = dpt.logical_and(ar1, ar2, order="C")
-    assert r1.flags.c_contiguous
-    r2 = dpt.logical_and(ar1, ar2, order="F")
-    assert r2.flags.f_contiguous
-    r3 = dpt.logical_and(ar1, ar2, order="A")
-    assert r3.flags.f_contiguous
-    r4 = dpt.logical_and(ar1, ar2, order="K")
-    assert r4.flags.f_contiguous
-
-    ar1 = dpt.ones((40, 40), dtype="i4", order="C")[:20, ::-2]
-    ar2 = dpt.ones((40, 40), dtype="i4", order="C")[:20, ::-2]
-    r4 = dpt.logical_and(ar1, ar2, order="K")
-    assert r4.strides == (20, -1)
-
-    ar1 = dpt.ones((40, 40), dtype="i4", order="C")[:20, ::-2].mT
-    ar2 = dpt.ones((40, 40), dtype="i4", order="C")[:20, ::-2].mT
-    r4 = dpt.logical_and(ar1, ar2, order="K")
-    assert r4.strides == (-1, 20)
-
-
-def test_logical_and_broadcasting():
-    get_queue_or_skip()
-
-    m = dpt.asarray(np.random.randint(0, 2, (100, 5)), dtype="i4")
-    v = dpt.arange(1, 6, dtype="i4")
-
-    r = dpt.logical_and(m, v)
-
-    expected = np.logical_and(dpt.asnumpy(m), dpt.asnumpy(v))
-    assert (dpt.asnumpy(r) == expected).all()
-
-    r2 = dpt.logical_and(v, m)
-    expected2 = np.logical_and(dpt.asnumpy(v), dpt.asnumpy(m))
-    assert (dpt.asnumpy(r2) == expected2).all()
-
-    r3 = dpt.empty_like(r)
-    dpt.logical_and(m, v, out=r3)
-    assert (dpt.asnumpy(r3) == expected).all()
-
-    r4 = dpt.empty_like(r)
-    dpt.logical_and(v, m, out=r4)
-    assert (dpt.asnumpy(r4) == expected).all()
-
-
-@pytest.mark.parametrize("arr_dt", _all_dtypes)
-@pytest.mark.parametrize("scalar_val", [0, 1])
-def test_logical_and_python_scalar(arr_dt, scalar_val):
-    q = get_queue_or_skip()
-    skip_if_dtype_not_supported(arr_dt, q)
-
-    X = dpt.asarray(
-        np.random.randint(0, 2, (10, 10)), dtype=arr_dt, sycl_queue=q
-    )
-    py_ones = (
-        bool(scalar_val),
-        int(scalar_val),
-        float(scalar_val),
-        complex(scalar_val),
-        np.float32(scalar_val),
-        ctypes.c_int(scalar_val),
-    )
-    for sc in py_ones:
-        R = dpt.logical_and(X, sc)
-        assert isinstance(R, dpt.usm_ndarray)
-        E = np.logical_and(dpt.asnumpy(X), sc)
-        assert (dpt.asnumpy(R) == E).all()
-
-        R = dpt.logical_and(sc, X)
-        assert isinstance(R, dpt.usm_ndarray)
-        E = np.logical_and(sc, dpt.asnumpy(X))
-        assert (dpt.asnumpy(R) == E).all()
-
-
-class MockArray:
-    def __init__(self, arr):
-        self.data_ = arr
-
-    @property
-    def __sycl_usm_array_interface__(self):
-        return self.data_.__sycl_usm_array_interface__
-
-
-def test_logical_and_mock_array():
-    get_queue_or_skip()
-    a = dpt.arange(10)
-    b = dpt.ones(10)
-    c = MockArray(b)
-    r = dpt.logical_and(a, c)
-    assert isinstance(r, dpt.usm_ndarray)
-
-
-def test_logical_and_canary_mock_array():
-    get_queue_or_skip()
-    a = dpt.arange(10)
-
-    class Canary:
-        def __init__(self):
-            pass
-
-        @property
-        def __sycl_usm_array_interface__(self):
-            return None
-
-    c = Canary()
-    with pytest.raises(ValueError):
-        dpt.logical_and(a, c)

dpctl/tests/elementwise/test_logical_not.py

@@ -20,7 +20,7 @@
 import dpctl.tensor as dpt
 from dpctl.tests.helper import get_queue_or_skip, skip_if_dtype_not_supported
 
-from .utils import _all_dtypes, _compare_dtypes, _usm_types
+from .utils import _all_dtypes, _compare_dtypes
 
 
 @pytest.mark.parametrize("op_dtype", _all_dtypes)
@@ -131,49 +131,3 @@ def test_logical_not_complex_float():
             r2 = dpt.logical_not(ar2)
             expected2 = np.logical_not(dpt.asnumpy(ar2))
             assert (dpt.asnumpy(r2) == expected2).all()
-
-
-@pytest.mark.parametrize("op_usm_type", _usm_types)
-def test_logical_not_usm_type_matrix(op_usm_type):
-    get_queue_or_skip()
-
-    sz = 128
-    ar1 = dpt.asarray(
-        np.random.randint(0, 2, sz), dtype="i4", usm_type=op_usm_type
-    )
-
-    r = dpt.logical_not(ar1)
-    assert isinstance(r, dpt.usm_ndarray)
-    assert r.usm_type == op_usm_type
-
-
-def test_logical_not_order():
-    get_queue_or_skip()
-
-    ar1 = dpt.ones((20, 20), dtype="i4", order="C")
-    r1 = dpt.logical_not(ar1, order="C")
-    assert r1.flags.c_contiguous
-    r2 = dpt.logical_not(ar1, order="F")
-    assert r2.flags.f_contiguous
-    r3 = dpt.logical_not(ar1, order="A")
-    assert r3.flags.c_contiguous
-    r4 = dpt.logical_not(ar1, order="K")
-    assert r4.flags.c_contiguous
-
-    ar1 = dpt.zeros((20, 20), dtype="i4", order="F")
-    r1 = dpt.logical_not(ar1, order="C")
-    assert r1.flags.c_contiguous
-    r2 = dpt.logical_not(ar1, order="F")
-    assert r2.flags.f_contiguous
-    r3 = dpt.logical_not(ar1, order="A")
-    assert r3.flags.f_contiguous
-    r4 = dpt.logical_not(ar1, order="K")
-    assert r4.flags.f_contiguous
-
-    ar1 = dpt.ones((40, 40), dtype="i4", order="C")[:20, ::-2]
-    r4 = dpt.logical_not(ar1, order="K")
-    assert r4.strides == (20, -1)
-
-    ar1 = dpt.zeros((40, 40), dtype="i4", order="C")[:20, ::-2].mT
-    r4 = dpt.logical_not(ar1, order="K")
-    assert r4.strides == (-1, 20)

dpctl/tests/elementwise/test_logical_or.py

@@ -14,16 +14,13 @@
 #  See the License for the specific language governing permissions and
 #  limitations under the License.
 
-import ctypes
-
 import numpy as np
 import pytest
 
-import dpctl
 import dpctl.tensor as dpt
 from dpctl.tests.helper import get_queue_or_skip, skip_if_dtype_not_supported
 
-from .utils import _all_dtypes, _compare_dtypes, _usm_types
+from .utils import _all_dtypes, _compare_dtypes
 
 
 @pytest.mark.parametrize("op1_dtype", _all_dtypes)
@@ -158,148 +155,3 @@ def test_logical_or_complex_float():
             r3 = dpt.logical_or(ar3, ar1)
             expected3 = np.logical_or(ar3_np, ar1_np)
             assert (dpt.asnumpy(r3) == expected3).all()
-
-
-@pytest.mark.parametrize("op1_usm_type", _usm_types)
-@pytest.mark.parametrize("op2_usm_type", _usm_types)
-def test_logical_or_usm_type_matrix(op1_usm_type, op2_usm_type):
-    get_queue_or_skip()
-
-    sz = 128
-    ar1 = dpt.asarray(
-        np.random.randint(0, 2, sz), dtype="i4", usm_type=op1_usm_type
-    )
-    ar2 = dpt.asarray(
-        np.random.randint(0, 2, sz), dtype=ar1.dtype, usm_type=op2_usm_type
-    )
-
-    r = dpt.logical_or(ar1, ar2)
-    assert isinstance(r, dpt.usm_ndarray)
-    expected_usm_type = dpctl.utils.get_coerced_usm_type(
-        (op1_usm_type, op2_usm_type)
-    )
-    assert r.usm_type == expected_usm_type
-
-
-def test_logical_or_order():
-    get_queue_or_skip()
-
-    ar1 = dpt.ones((20, 20), dtype="i4", order="C")
-    ar2 = dpt.ones((20, 20), dtype="i4", order="C")
-    r1 = dpt.logical_or(ar1, ar2, order="C")
-    assert r1.flags.c_contiguous
-    r2 = dpt.logical_or(ar1, ar2, order="F")
-    assert r2.flags.f_contiguous
-    r3 = dpt.logical_or(ar1, ar2, order="A")
-    assert r3.flags.c_contiguous
-    r4 = dpt.logical_or(ar1, ar2, order="K")
-    assert r4.flags.c_contiguous
-
-    ar1 = dpt.ones((20, 20), dtype="i4", order="F")
-    ar2 = dpt.ones((20, 20), dtype="i4", order="F")
-    r1 = dpt.logical_or(ar1, ar2, order="C")
-    assert r1.flags.c_contiguous
-    r2 = dpt.logical_or(ar1, ar2, order="F")
-    assert r2.flags.f_contiguous
-    r3 = dpt.logical_or(ar1, ar2, order="A")
-    assert r3.flags.f_contiguous
-    r4 = dpt.logical_or(ar1, ar2, order="K")
-    assert r4.flags.f_contiguous
-
-    ar1 = dpt.ones((40, 40), dtype="i4", order="C")[:20, ::-2]
-    ar2 = dpt.ones((40, 40), dtype="i4", order="C")[:20, ::-2]
-    r4 = dpt.logical_or(ar1, ar2, order="K")
-    assert r4.strides == (20, -1)
-
-    ar1 = dpt.ones((40, 40), dtype="i4", order="C")[:20, ::-2].mT
-    ar2 = dpt.ones((40, 40), dtype="i4", order="C")[:20, ::-2].mT
-    r4 = dpt.logical_or(ar1, ar2, order="K")
-    assert r4.strides == (-1, 20)
-
-
-def test_logical_or_broadcasting():
-    get_queue_or_skip()
-
-    m = dpt.asarray(np.random.randint(0, 2, (100, 5)), dtype="i4")
-    v = dpt.arange(1, 6, dtype="i4")
-
-    r = dpt.logical_or(m, v)
-
-    expected = np.logical_or(dpt.asnumpy(m), dpt.asnumpy(v))
-    assert (dpt.asnumpy(r) == expected).all()
-
-    r2 = dpt.logical_or(v, m)
-    expected2 = np.logical_or(dpt.asnumpy(v), dpt.asnumpy(m))
-    assert (dpt.asnumpy(r2) == expected2).all()
-
-    r3 = dpt.empty_like(r)
-    dpt.logical_or(m, v, out=r3)
-    assert (dpt.asnumpy(r3) == expected).all()
-
-    r4 = dpt.empty_like(r)
-    dpt.logical_or(v, m, out=r4)
-    assert (dpt.asnumpy(r4) == expected).all()
-
-
-@pytest.mark.parametrize("arr_dt", _all_dtypes)
-@pytest.mark.parametrize("scalar_val", [0, 1])
-def test_logical_or_python_scalar(arr_dt, scalar_val):
-    q = get_queue_or_skip()
-    skip_if_dtype_not_supported(arr_dt, q)
-
-    X = dpt.asarray(
-        np.random.randint(0, 2, (10, 10)), dtype=arr_dt, sycl_queue=q
-    )
-    py_ones = (
-        bool(scalar_val),
-        int(scalar_val),
-        float(scalar_val),
-        complex(scalar_val),
-        np.float32(scalar_val),
-        ctypes.c_int(scalar_val),
-    )
-    for sc in py_ones:
-        R = dpt.logical_or(X, sc)
-        assert isinstance(R, dpt.usm_ndarray)
-        E = np.logical_or(dpt.asnumpy(X), sc)
-        assert (dpt.asnumpy(R) == E).all()
-
-        R = dpt.logical_or(sc, X)
-        assert isinstance(R, dpt.usm_ndarray)
-        E = np.logical_or(sc, dpt.asnumpy(X))
-        assert (dpt.asnumpy(R) == E).all()
-
-
-class MockArray:
-    def __init__(self, arr):
-        self.data_ = arr
-
-    @property
-    def __sycl_usm_array_interface__(self):
-        return self.data_.__sycl_usm_array_interface__
-
-
-def test_logical_or_mock_array():
-    get_queue_or_skip()
-    a = dpt.arange(10)
-    b = dpt.ones(10)
-    c = MockArray(b)
-    r = dpt.logical_or(a, c)
-    assert isinstance(r, dpt.usm_ndarray)
-
-
-def test_logical_or_canary_mock_array():
-    get_queue_or_skip()
-    a = dpt.arange(10)
-
-    class Canary:
-        def __init__(self):
-            pass
-
-        @property
-        def __sycl_usm_array_interface__(self):
-            return None
-
-    c = Canary()
-    with pytest.raises(ValueError):
-        dpt.logical_or(a, c)