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Experiment with making float/int types inherit from np.floating/np.integer. #259

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Experiment with making float/int types inherit from np.floating/np.integer. #259

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3 changes: 2 additions & 1 deletion ml_dtypes/_src/custom_float.h
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Original file line number Diff line number Diff line change
Expand Up @@ -849,8 +849,9 @@ template <typename T>
bool RegisterFloatDtype(PyObject* numpy) {
// bases must be a tuple for Python 3.9 and earlier. Change to just pass
// the base type directly when dropping Python 3.9 support.
// Change to PyFloatingArrType_Type once we drop support for NumPy 1.X.
Safe_PyObjectPtr bases(
PyTuple_Pack(1, reinterpret_cast<PyObject*>(&PyGenericArrType_Type)));
PyTuple_Pack(1, reinterpret_cast<PyObject*>(&PyNumberArrType_Type)));
PyObject* type =
PyType_FromSpecWithBases(&CustomFloatType<T>::type_spec, bases.get());
if (!type) {
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4 changes: 3 additions & 1 deletion ml_dtypes/_src/intn_numpy.h
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Expand Up @@ -768,8 +768,10 @@ template <typename T>
bool RegisterIntNDtype(PyObject* numpy) {
// bases must be a tuple for Python 3.9 and earlier. Change to just pass
// the base type directly when dropping Python 3.9 support.
// Change to PySignedIntegerArrType_Type/PyUnsignedIntegerArrType_Type once
// we drop support for NumPy 1.X.
Safe_PyObjectPtr bases(
PyTuple_Pack(1, reinterpret_cast<PyObject*>(&PyGenericArrType_Type)));
PyTuple_Pack(1, reinterpret_cast<PyObject*>(&PyNumberArrType_Type)));
PyObject* type =
PyType_FromSpecWithBases(&IntNTypeDescriptor<T>::type_spec, bases.get());
if (!type) {
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5 changes: 5 additions & 0 deletions ml_dtypes/tests/custom_float_test.py
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Expand Up @@ -590,6 +590,11 @@ def testArgminOnPositiveInfinity(self, float_type):
def testDtypeFromString(self, float_type):
assert np.dtype(float_type.__name__) == np.dtype(float_type)

def testIssubdtype(self, float_type):
# We should switch to np.floating once we drop support for NumPy 1.X.
self.assertTrue(np.issubdtype(float_type, np.number))
self.assertTrue(np.issubdtype(np.dtype(float_type), np.number))


BinaryOp = collections.namedtuple("BinaryOp", ["op"])

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7 changes: 7 additions & 0 deletions ml_dtypes/tests/intn_test.py
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Expand Up @@ -245,6 +245,13 @@ def testCanCast(self, a, b):
((a, b) in allowed_casts), np.can_cast(a, b, casting="safe")
)

@parameterized.product(scalar_type=INTN_TYPES)
def testIssubdtype(self, scalar_type):
# We should switch to np.signedinteger/np.unsignedinteger once we drop
# support for NumPy 1.X.
self.assertTrue(np.issubdtype(scalar_type, np.number))
self.assertTrue(np.issubdtype(np.dtype(scalar_type), np.number))


# Tests for the Python scalar type
@multi_threaded(num_workers=3, skip_tests=["testBinaryUfuncs"])
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