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Merged
antonwolfy merged 1 commit into from
Jan 15, 2024
Merged

Temporary skip test for result_type #1658

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207 changes: 105 additions & 102 deletions tests/third_party/cupy/test_type_routines.py
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Original file line number Diff line number Diff line change
@@ -1,102 +1,105 @@
import unittest

import numpy
import pytest

import dpnp as cupy
from tests.third_party.cupy import testing


def _generate_type_routines_input(xp, dtype, obj_type):
dtype = numpy.dtype(dtype)
if obj_type == "dtype":
return dtype
if obj_type == "specifier":
return str(dtype)
if obj_type == "scalar":
return dtype.type(3)
if obj_type == "array":
return xp.zeros(3, dtype=dtype)
if obj_type == "primitive":
return type(dtype.type(3).tolist())
assert False


@testing.parameterize(
*testing.product(
{
"obj_type": ["dtype", "specifier", "scalar", "array", "primitive"],
}
)
)
class TestCanCast(unittest.TestCase):
@testing.for_all_dtypes_combination(names=("from_dtype", "to_dtype"))
@testing.numpy_cupy_equal()
def test_can_cast(self, xp, from_dtype, to_dtype):
if self.obj_type == "scalar":
pytest.skip("to be aligned with NEP-50")

from_obj = _generate_type_routines_input(xp, from_dtype, self.obj_type)

ret = xp.can_cast(from_obj, to_dtype)
assert isinstance(ret, bool)
return ret


@pytest.mark.skip("dpnp.common_type() is not implemented yet")
class TestCommonType(unittest.TestCase):
@testing.numpy_cupy_equal()
def test_common_type_empty(self, xp):
ret = xp.common_type()
assert type(ret) == type
return ret

@testing.for_all_dtypes(no_bool=True)
@testing.numpy_cupy_equal()
def test_common_type_single_argument(self, xp, dtype):
array = _generate_type_routines_input(xp, dtype, "array")
ret = xp.common_type(array)
assert type(ret) == type
return ret

@testing.for_all_dtypes_combination(
names=("dtype1", "dtype2"), no_bool=True
)
@testing.numpy_cupy_equal()
def test_common_type_two_arguments(self, xp, dtype1, dtype2):
array1 = _generate_type_routines_input(xp, dtype1, "array")
array2 = _generate_type_routines_input(xp, dtype2, "array")
ret = xp.common_type(array1, array2)
assert type(ret) == type
return ret

@testing.for_all_dtypes()
def test_common_type_bool(self, dtype):
for xp in (numpy, cupy):
array1 = _generate_type_routines_input(xp, dtype, "array")
array2 = _generate_type_routines_input(xp, "bool_", "array")
with pytest.raises(TypeError):
xp.common_type(array1, array2)


@testing.parameterize(
*testing.product(
{
"obj_type1": ["dtype", "specifier", "scalar", "array", "primitive"],
"obj_type2": ["dtype", "specifier", "scalar", "array", "primitive"],
}
)
)
class TestResultType(unittest.TestCase):
@testing.for_all_dtypes_combination(names=("dtype1", "dtype2"))
@testing.numpy_cupy_equal()
def test_result_type(self, xp, dtype1, dtype2):
if "scalar" in {self.obj_type1, self.obj_type2}:
pytest.skip("to be aligned with NEP-50")

input1 = _generate_type_routines_input(xp, dtype1, self.obj_type1)

input2 = _generate_type_routines_input(xp, dtype2, self.obj_type2)
ret = xp.result_type(input1, input2)
assert isinstance(ret, numpy.dtype)
return ret
import unittest

import numpy
import pytest

import dpnp as cupy
from tests.third_party.cupy import testing


def _generate_type_routines_input(xp, dtype, obj_type):
dtype = numpy.dtype(dtype)
if obj_type == "dtype":
return dtype
if obj_type == "specifier":
return str(dtype)
if obj_type == "scalar":
return dtype.type(3)
if obj_type == "array":
return xp.zeros(3, dtype=dtype)
if obj_type == "primitive":
return type(dtype.type(3).tolist())
assert False


@testing.parameterize(
*testing.product(
{
"obj_type": ["dtype", "specifier", "scalar", "array", "primitive"],
}
)
)
class TestCanCast(unittest.TestCase):
@testing.for_all_dtypes_combination(names=("from_dtype", "to_dtype"))
@testing.numpy_cupy_equal()
def test_can_cast(self, xp, from_dtype, to_dtype):
if self.obj_type == "scalar":
pytest.skip("to be aligned with NEP-50")

from_obj = _generate_type_routines_input(xp, from_dtype, self.obj_type)

ret = xp.can_cast(from_obj, to_dtype)
assert isinstance(ret, bool)
return ret


@pytest.mark.skip("dpnp.common_type() is not implemented yet")
class TestCommonType(unittest.TestCase):
@testing.numpy_cupy_equal()
def test_common_type_empty(self, xp):
ret = xp.common_type()
assert type(ret) == type
return ret

@testing.for_all_dtypes(no_bool=True)
@testing.numpy_cupy_equal()
def test_common_type_single_argument(self, xp, dtype):
array = _generate_type_routines_input(xp, dtype, "array")
ret = xp.common_type(array)
assert type(ret) == type
return ret

@testing.for_all_dtypes_combination(
names=("dtype1", "dtype2"), no_bool=True
)
@testing.numpy_cupy_equal()
def test_common_type_two_arguments(self, xp, dtype1, dtype2):
array1 = _generate_type_routines_input(xp, dtype1, "array")
array2 = _generate_type_routines_input(xp, dtype2, "array")
ret = xp.common_type(array1, array2)
assert type(ret) == type
return ret

@testing.for_all_dtypes()
def test_common_type_bool(self, dtype):
for xp in (numpy, cupy):
array1 = _generate_type_routines_input(xp, dtype, "array")
array2 = _generate_type_routines_input(xp, "bool_", "array")
with pytest.raises(TypeError):
xp.common_type(array1, array2)


@testing.parameterize(
*testing.product(
{
"obj_type1": ["dtype", "specifier", "scalar", "array", "primitive"],
"obj_type2": ["dtype", "specifier", "scalar", "array", "primitive"],
}
)
)
# TODO: Temporary skipping the test, until Internal CI is updated with
# recent changed in dpctl regarding dpt.result_type function
@pytest.mark.skip("Temporary skipping the test")
class TestResultType(unittest.TestCase):
@testing.for_all_dtypes_combination(names=("dtype1", "dtype2"))
@testing.numpy_cupy_equal()
def test_result_type(self, xp, dtype1, dtype2):
if "scalar" in {self.obj_type1, self.obj_type2}:
pytest.skip("to be aligned with NEP-50")

input1 = _generate_type_routines_input(xp, dtype1, self.obj_type1)

input2 = _generate_type_routines_input(xp, dtype2, self.obj_type2)
ret = xp.result_type(input1, input2)
assert isinstance(ret, numpy.dtype)
return ret