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Merged
merged 5 commits into from
Apr 15, 2025
Merged

update test_ndarray.py #2419

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9534ccc
update test_ndarray.py
vtavana Apr 12, 2025
3aae5e9
Merge branch 'master' into update-ndarray
vtavana Apr 14, 2025
5962785
Apply suggestions from code review
vtavana Apr 14, 2025
18e048d
use assert_allclose instead of assert
vtavana Apr 14, 2025
8d32f3d
Merge branch 'master' into update-ndarray
vtavana Apr 14, 2025
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69 changes: 33 additions & 36 deletions dpnp/tests/test_ndarray.py
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Original file line number Diff line number Diff line change
Expand Up @@ -23,7 +23,7 @@
class TestAsType:
@pytest.mark.usefixtures("suppress_complex_warning")
@pytest.mark.parametrize("res_dtype", get_all_dtypes())
@pytest.mark.parametrize("arr_dtype", get_all_dtypes())
@pytest.mark.parametrize("arr_dtype", get_all_dtypes(no_none=True))
@pytest.mark.parametrize(
"arr",
[[-2, -1, 0, 1, 2], [[-2, -1], [1, 2]], []],
Expand All @@ -35,7 +35,7 @@ def test_basic(self, arr, arr_dtype, res_dtype):

expected = a.astype(res_dtype)
result = ia.astype(res_dtype)
assert_allclose(expected, result)
assert_allclose(result, expected)

def test_subok_error(self):
x = dpnp.ones(4)
Expand Down Expand Up @@ -88,18 +88,18 @@ def test_create_from_usm_ndarray_error(arr):
dpnp.ndarray._create_from_usm_ndarray(arr)


@pytest.mark.parametrize("arr_dtype", get_all_dtypes())
@pytest.mark.parametrize("arr_dtype", get_all_dtypes(no_none=True))
@pytest.mark.parametrize(
"arr",
[[-2, -1, 0, 1, 2], [[-2, -1], [1, 2]], []],
ids=["[-2, -1, 0, 1, 2]", "[[-2, -1], [1, 2]]", "[]"],
)
def test_flatten(arr, arr_dtype):
numpy_array = get_abs_array(arr, arr_dtype)
dpnp_array = dpnp.array(numpy_array)
expected = numpy_array.flatten()
result = dpnp_array.flatten()
assert_array_equal(expected, result)
a = get_abs_array(arr, arr_dtype)
ia = dpnp.array(a)
expected = a.flatten()
result = ia.flatten()
assert_array_equal(result, expected)


@pytest.mark.parametrize(
Expand All @@ -110,17 +110,16 @@ def test_flatten(arr, arr_dtype):
@pytest.mark.parametrize("order", ["C", "F"])
def test_flags(shape, order):
usm_array = dpt.usm_ndarray(shape, order=order)
numpy_array = numpy.ndarray(shape, order=order)
dpnp_array = dpnp.ndarray(shape, order=order)
assert usm_array.flags == dpnp_array.flags
assert numpy_array.flags.c_contiguous == dpnp_array.flags.c_contiguous
assert numpy_array.flags.f_contiguous == dpnp_array.flags.f_contiguous
a = numpy.ndarray(shape, order=order)
ia = dpnp.ndarray(shape, order=order)
assert usm_array.flags == ia.flags
assert a.flags.c_contiguous == ia.flags.c_contiguous
assert a.flags.f_contiguous == ia.flags.f_contiguous


@pytest.mark.parametrize(
"dtype",
[numpy.complex64, numpy.float32, numpy.int64, numpy.int32, numpy.bool_],
ids=["complex64", "float32", "int64", "int32", "bool"],
)
@pytest.mark.parametrize("strides", [(1, 4), (4, 1)], ids=["(1, 4)", "(4, 1)"])
@pytest.mark.parametrize("order", ["C", "F"])
Expand All @@ -130,13 +129,11 @@ def test_flags_strides(dtype, order, strides):
usm_array = dpt.usm_ndarray(
(4, 4), dtype=dtype, order=order, strides=strides
)
numpy_array = numpy.ndarray(
(4, 4), dtype=dtype, order=order, strides=numpy_strides
)
dpnp_array = dpnp.ndarray((4, 4), dtype=dtype, order=order, strides=strides)
assert usm_array.flags == dpnp_array.flags
assert numpy_array.flags.c_contiguous == dpnp_array.flags.c_contiguous
assert numpy_array.flags.f_contiguous == dpnp_array.flags.f_contiguous
a = numpy.ndarray((4, 4), dtype=dtype, order=order, strides=numpy_strides)
ia = dpnp.ndarray((4, 4), dtype=dtype, order=order, strides=strides)
assert usm_array.flags == ia.flags
assert a.flags.c_contiguous == ia.flags.c_contiguous
assert a.flags.f_contiguous == ia.flags.f_contiguous


def test_flags_writable():
Expand Down Expand Up @@ -383,9 +380,9 @@ def test_print_dpnp_zero_shape():
"dtype", get_all_dtypes(no_float16=False, no_complex=True)
)
def test_scalar_type_casting(func, shape, dtype):
numpy_array = numpy.full(shape, 5, dtype=dtype)
dpnp_array = dpnp.full(shape, 5, dtype=dtype)
assert func(numpy_array) == func(dpnp_array)
a = numpy.full(shape, 5, dtype=dtype)
ia = dpnp.full(shape, 5, dtype=dtype)
assert func(a) == func(ia)


# Numpy will raise an error when converting a.ndim > 0 to a scalar
Expand All @@ -396,12 +393,12 @@ def test_scalar_type_casting(func, shape, dtype):
)
@pytest.mark.parametrize("shape", [tuple(), (1,), (1, 1), (1, 1, 1)])
@pytest.mark.parametrize(
"dtype", get_all_dtypes(no_float16=False, no_complex=True, no_none=True)
"dtype", get_all_dtypes(no_float16=False, no_complex=True)
)
def test_scalar_type_casting_by_method(method, shape, dtype):
numpy_array = numpy.full(shape, 4.7, dtype=dtype)
dpnp_array = dpnp.full(shape, 4.7, dtype=dtype)
assert getattr(numpy_array, method)() == getattr(dpnp_array, method)()
a = numpy.full(shape, 4.7, dtype=dtype)
ia = dpnp.full(shape, 4.7, dtype=dtype)
assert_allclose(getattr(a, method)(), getattr(ia, method)(), rtol=1e-06)


@pytest.mark.parametrize("shape", [(1,), (1, 1), (1, 1, 1)])
Expand Down Expand Up @@ -452,18 +449,18 @@ def test_ravel():


def test_repeat():
numpy_array = numpy.arange(4).repeat(3)
dpnp_array = dpnp.arange(4).repeat(3)
assert_array_equal(numpy_array, dpnp_array)
a = numpy.arange(4).repeat(3)
ia = dpnp.arange(4).repeat(3)
assert_array_equal(a, ia)


def test_clip():
numpy_array = numpy.arange(10)
dpnp_array = dpnp.arange(10)
result = dpnp.clip(dpnp_array, 3, 7)
expected = numpy.clip(numpy_array, 3, 7)
a = numpy.arange(10)
ia = dpnp.arange(10)
result = dpnp.clip(ia, 3, 7)
expected = numpy.clip(a, 3, 7)

assert_array_equal(expected, result)
assert_array_equal(result, expected)


def test_rmatmul_dpnp_array():
Expand Down
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