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Steve R. Sun 2024-11-18 14:38:00 +08:00 committed by GitHub
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6 changed files with 319 additions and 43 deletions
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3
.github/workflows/ci.yml vendored
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@ -1019,7 +1019,6 @@ jobs:
git
mingw-w64-${{matrix.env}}-gcc
mingw-w64-${{matrix.env}}-python-pip
mingw-w64-${{matrix.env}}-python-numpy
mingw-w64-${{matrix.env}}-cmake
mingw-w64-${{matrix.env}}-make
mingw-w64-${{matrix.env}}-python-pytest
@ -1031,7 +1030,7 @@ jobs:
with:
msystem: ${{matrix.sys}}
install: >-
git
mingw-w64-${{matrix.env}}-python-numpy
mingw-w64-${{matrix.env}}-python-scipy
mingw-w64-${{matrix.env}}-eigen3

97
include/pybind11/numpy.h
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@ -215,6 +215,7 @@ constexpr int platform_lookup(int I, Ints... Is) {
}
struct npy_api {
// If you change this code, please review `normalized_dtype_num` below.
enum constants {
NPY_ARRAY_C_CONTIGUOUS_ = 0x0001,
NPY_ARRAY_F_CONTIGUOUS_ = 0x0002,
@ -486,6 +487,74 @@ DECL_NPY_SCALAR(std::complex<long double>, NPY_CLONGDOUBLE);
#undef DECL_NPY_SCALAR
// This table normalizes typenums by mapping NPY_INT_, NPY_LONG, ... to NPY_INT32_, NPY_INT64, ...
// This is needed to correctly handle situations where multiple typenums map to the same type,
// e.g. NPY_LONG_ may be equivalent to NPY_INT_ or NPY_LONGLONG_ despite having a different
// typenum. The normalized typenum should always match the values used in npy_format_descriptor.
// If you change this code, please review `enum constants` above.
static constexpr int normalized_dtype_num[npy_api::NPY_VOID_ + 1] = {
// NPY_BOOL_ =>
npy_api::NPY_BOOL_,
// NPY_BYTE_ =>
npy_api::NPY_BYTE_,
// NPY_UBYTE_ =>
npy_api::NPY_UBYTE_,
// NPY_SHORT_ =>
npy_api::NPY_INT16_,
// NPY_USHORT_ =>
npy_api::NPY_UINT16_,
// NPY_INT_ =>
sizeof(int) == sizeof(std::int16_t) ? npy_api::NPY_INT16_
: sizeof(int) == sizeof(std::int32_t) ? npy_api::NPY_INT32_
: sizeof(int) == sizeof(std::int64_t) ? npy_api::NPY_INT64_
: npy_api::NPY_INT_,
// NPY_UINT_ =>
sizeof(unsigned int) == sizeof(std::uint16_t) ? npy_api::NPY_UINT16_
: sizeof(unsigned int) == sizeof(std::uint32_t) ? npy_api::NPY_UINT32_
: sizeof(unsigned int) == sizeof(std::uint64_t) ? npy_api::NPY_UINT64_
: npy_api::NPY_UINT_,
// NPY_LONG_ =>
sizeof(long) == sizeof(std::int16_t) ? npy_api::NPY_INT16_
: sizeof(long) == sizeof(std::int32_t) ? npy_api::NPY_INT32_
: sizeof(long) == sizeof(std::int64_t) ? npy_api::NPY_INT64_
: npy_api::NPY_LONG_,
// NPY_ULONG_ =>
sizeof(unsigned long) == sizeof(std::uint16_t) ? npy_api::NPY_UINT16_
: sizeof(unsigned long) == sizeof(std::uint32_t) ? npy_api::NPY_UINT32_
: sizeof(unsigned long) == sizeof(std::uint64_t) ? npy_api::NPY_UINT64_
: npy_api::NPY_ULONG_,
// NPY_LONGLONG_ =>
sizeof(long long) == sizeof(std::int16_t) ? npy_api::NPY_INT16_
: sizeof(long long) == sizeof(std::int32_t) ? npy_api::NPY_INT32_
: sizeof(long long) == sizeof(std::int64_t) ? npy_api::NPY_INT64_
: npy_api::NPY_LONGLONG_,
// NPY_ULONGLONG_ =>
sizeof(unsigned long long) == sizeof(std::uint16_t) ? npy_api::NPY_UINT16_
: sizeof(unsigned long long) == sizeof(std::uint32_t) ? npy_api::NPY_UINT32_
: sizeof(unsigned long long) == sizeof(std::uint64_t) ? npy_api::NPY_UINT64_
: npy_api::NPY_ULONGLONG_,
// NPY_FLOAT_ =>
npy_api::NPY_FLOAT_,
// NPY_DOUBLE_ =>
npy_api::NPY_DOUBLE_,
// NPY_LONGDOUBLE_ =>
npy_api::NPY_LONGDOUBLE_,
// NPY_CFLOAT_ =>
npy_api::NPY_CFLOAT_,
// NPY_CDOUBLE_ =>
npy_api::NPY_CDOUBLE_,
// NPY_CLONGDOUBLE_ =>
npy_api::NPY_CLONGDOUBLE_,
// NPY_OBJECT_ =>
npy_api::NPY_OBJECT_,
// NPY_STRING_ =>
npy_api::NPY_STRING_,
// NPY_UNICODE_ =>
npy_api::NPY_UNICODE_,
// NPY_VOID_ =>
npy_api::NPY_VOID_,
};
inline PyArray_Proxy *array_proxy(void *ptr) { return reinterpret_cast<PyArray_Proxy *>(ptr); }
inline const PyArray_Proxy *array_proxy(const void *ptr) {
@ -833,6 +902,13 @@ public:
return detail::npy_format_descriptor<typename std::remove_cv<T>::type>::dtype();
}
/// Return the type number associated with a C++ type.
/// This is the constexpr equivalent of `dtype::of<T>().num()`.
template <typename T>
static constexpr int num_of() {
return detail::npy_format_descriptor<typename std::remove_cv<T>::type>::value;
}
/// Size of the data type in bytes.
#ifdef PYBIND11_NUMPY_1_ONLY
ssize_t itemsize() const { return detail::array_descriptor_proxy(m_ptr)->elsize; }
@ -874,7 +950,9 @@ public:
return detail::array_descriptor_proxy(m_ptr)->type;
}
/// type number of dtype.
/// Type number of dtype. Note that different values may be returned for equivalent types,
/// e.g. even though ``long`` may be equivalent to ``int`` or ``long long``, they still have
/// different type numbers. Consider using `normalized_num` to avoid this.
int num() const {
// Note: The signature, `dtype::num` follows the naming of NumPy's public
// Python API (i.e., ``dtype.num``), rather than its internal
@ -882,6 +960,17 @@ public:
return detail::array_descriptor_proxy(m_ptr)->type_num;
}
/// Type number of dtype, normalized to match the return value of `num_of` for equivalent
/// types. This function can be used to write switch statements that correctly handle
/// equivalent types with different type numbers.
int normalized_num() const {
int value = num();
if (value >= 0 && value <= detail::npy_api::NPY_VOID_) {
return detail::normalized_dtype_num[value];
}
return value;
}
/// Single character for byteorder
char byteorder() const { return detail::array_descriptor_proxy(m_ptr)->byteorder; }
@ -1545,7 +1634,11 @@ public:
};
template <typename T>
struct npy_format_descriptor<T, enable_if_t<is_same_ignoring_cvref<T, PyObject *>::value>> {
struct npy_format_descriptor<
T,
enable_if_t<is_same_ignoring_cvref<T, PyObject *>::value
|| ((std::is_same<T, handle>::value || std::is_same<T, object>::value)
&& sizeof(T) == sizeof(PyObject *))>> {
static constexpr auto name = const_name("object");
static constexpr int value = npy_api::NPY_OBJECT_;

84
tests/test_numpy_array.cpp
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@ -156,6 +156,55 @@ py::handle auxiliaries(T &&r, T2 &&r2) {
return l.release();
}
template <typename PyObjectType>
PyObjectType convert_to_pyobjecttype(py::object obj);
template <>
PyObject *convert_to_pyobjecttype<PyObject *>(py::object obj) {
return obj.release().ptr();
}
template <>
py::handle convert_to_pyobjecttype<py::handle>(py::object obj) {
return obj.release();
}
template <>
py::object convert_to_pyobjecttype<py::object>(py::object obj) {
return obj;
}
template <typename PyObjectType>
std::string pass_array_return_sum_str_values(const py::array_t<PyObjectType> &objs) {
std::string sum_str_values;
for (const auto &obj : objs) {
sum_str_values += py::str(obj.attr("value"));
}
return sum_str_values;
}
template <typename PyObjectType>
py::list pass_array_return_as_list(const py::array_t<PyObjectType> &objs) {
return objs;
}
template <typename PyObjectType>
py::array_t<PyObjectType> return_array_cpp_loop(const py::list &objs) {
py::size_t arr_size = py::len(objs);
py::array_t<PyObjectType> arr_from_list(static_cast<py::ssize_t>(arr_size));
PyObjectType *data = arr_from_list.mutable_data();
for (py::size_t i = 0; i < arr_size; i++) {
assert(!data[i]);
data[i] = convert_to_pyobjecttype<PyObjectType>(objs[i].attr("value"));
}
return arr_from_list;
}
template <typename PyObjectType>
py::array_t<PyObjectType> return_array_from_list(const py::list &objs) {
return objs;
}
// note: declaration at local scope would create a dangling reference!
static int data_i = 42;
@ -520,28 +569,21 @@ TEST_SUBMODULE(numpy_array, sm) {
sm.def("round_trip_float", [](double d) { return d; });
sm.def("pass_array_pyobject_ptr_return_sum_str_values",
[](const py::array_t<PyObject *> &objs) {
std::string sum_str_values;
for (const auto &obj : objs) {
sum_str_values += py::str(obj.attr("value"));
}
return sum_str_values;
});
pass_array_return_sum_str_values<PyObject *>);
sm.def("pass_array_handle_return_sum_str_values",
pass_array_return_sum_str_values<py::handle>);
sm.def("pass_array_object_return_sum_str_values",
pass_array_return_sum_str_values<py::object>);
sm.def("pass_array_pyobject_ptr_return_as_list",
[](const py::array_t<PyObject *> &objs) -> py::list { return objs; });
sm.def("pass_array_pyobject_ptr_return_as_list", pass_array_return_as_list<PyObject *>);
sm.def("pass_array_handle_return_as_list", pass_array_return_as_list<py::handle>);
sm.def("pass_array_object_return_as_list", pass_array_return_as_list<py::object>);
sm.def("return_array_pyobject_ptr_cpp_loop", [](const py::list &objs) {
py::size_t arr_size = py::len(objs);
py::array_t<PyObject *> arr_from_list(static_cast<py::ssize_t>(arr_size));
PyObject **data = arr_from_list.mutable_data();
for (py::size_t i = 0; i < arr_size; i++) {
assert(data[i] == nullptr);
data[i] = py::cast<PyObject *>(objs[i].attr("value"));
}
return arr_from_list;
});
sm.def("return_array_pyobject_ptr_cpp_loop", return_array_cpp_loop<PyObject *>);
sm.def("return_array_handle_cpp_loop", return_array_cpp_loop<py::handle>);
sm.def("return_array_object_cpp_loop", return_array_cpp_loop<py::object>);
sm.def("return_array_pyobject_ptr_from_list",
[](const py::list &objs) -> py::array_t<PyObject *> { return objs; });
sm.def("return_array_pyobject_ptr_from_list", return_array_from_list<PyObject *>);
sm.def("return_array_handle_from_list", return_array_from_list<py::handle>);
sm.def("return_array_object_from_list", return_array_from_list<py::object>);
}

52
tests/test_numpy_array.py
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@ -629,45 +629,61 @@ def UnwrapPyValueHolder(vhs):
return [vh.value for vh in vhs]
def test_pass_array_pyobject_ptr_return_sum_str_values_ndarray():
PASS_ARRAY_PYOBJECT_RETURN_SUM_STR_VALUES_FUNCTIONS = [
m.pass_array_pyobject_ptr_return_sum_str_values,
m.pass_array_handle_return_sum_str_values,
m.pass_array_object_return_sum_str_values,
]
@pytest.mark.parametrize(
"pass_array", PASS_ARRAY_PYOBJECT_RETURN_SUM_STR_VALUES_FUNCTIONS
)
def test_pass_array_object_return_sum_str_values_ndarray(pass_array):
# Intentionally all temporaries, do not change.
assert (
m.pass_array_pyobject_ptr_return_sum_str_values(
np.array(WrapWithPyValueHolder(-3, "four", 5.0), dtype=object)
)
pass_array(np.array(WrapWithPyValueHolder(-3, "four", 5.0), dtype=object))
== "-3four5.0"
)
def test_pass_array_pyobject_ptr_return_sum_str_values_list():
@pytest.mark.parametrize(
"pass_array", PASS_ARRAY_PYOBJECT_RETURN_SUM_STR_VALUES_FUNCTIONS
)
def test_pass_array_object_return_sum_str_values_list(pass_array):
# Intentionally all temporaries, do not change.
assert (
m.pass_array_pyobject_ptr_return_sum_str_values(
WrapWithPyValueHolder(2, "three", -4.0)
)
== "2three-4.0"
)
assert pass_array(WrapWithPyValueHolder(2, "three", -4.0)) == "2three-4.0"
def test_pass_array_pyobject_ptr_return_as_list():
@pytest.mark.parametrize(
"pass_array",
[
m.pass_array_pyobject_ptr_return_as_list,
m.pass_array_handle_return_as_list,
m.pass_array_object_return_as_list,
],
)
def test_pass_array_object_return_as_list(pass_array):
# Intentionally all temporaries, do not change.
assert UnwrapPyValueHolder(
m.pass_array_pyobject_ptr_return_as_list(
np.array(WrapWithPyValueHolder(-1, "two", 3.0), dtype=object)
)
pass_array(np.array(WrapWithPyValueHolder(-1, "two", 3.0), dtype=object))
) == [-1, "two", 3.0]
@pytest.mark.parametrize(
("return_array_pyobject_ptr", "unwrap"),
("return_array", "unwrap"),
[
(m.return_array_pyobject_ptr_cpp_loop, list),
(m.return_array_handle_cpp_loop, list),
(m.return_array_object_cpp_loop, list),
(m.return_array_pyobject_ptr_from_list, UnwrapPyValueHolder),
(m.return_array_handle_from_list, UnwrapPyValueHolder),
(m.return_array_object_from_list, UnwrapPyValueHolder),
],
)
def test_return_array_pyobject_ptr_cpp_loop(return_array_pyobject_ptr, unwrap):
def test_return_array_object_cpp_loop(return_array, unwrap):
# Intentionally all temporaries, do not change.
arr_from_list = return_array_pyobject_ptr(WrapWithPyValueHolder(6, "seven", -8.0))
arr_from_list = return_array(WrapWithPyValueHolder(6, "seven", -8.0))
assert isinstance(arr_from_list, np.ndarray)
assert arr_from_list.dtype == np.dtype("O")
assert unwrap(arr_from_list) == [6, "seven", -8.0]

104
tests/test_numpy_dtypes.cpp
View File

@ -11,6 +11,9 @@
#include "pybind11_tests.h"
#include <cstdint>
#include <stdexcept>
#ifdef __GNUC__
# define PYBIND11_PACKED(cls) cls __attribute__((__packed__))
#else
@ -297,6 +300,15 @@ py::list test_dtype_ctors() {
return list;
}
template <typename T>
py::array_t<T> dispatch_array_increment(py::array_t<T> arr) {
py::array_t<T> res(arr.shape(0));
for (py::ssize_t i = 0; i < arr.shape(0); ++i) {
res.mutable_at(i) = T(arr.at(i) + 1);
}
return res;
}
struct A {};
struct B {};
@ -496,6 +508,98 @@ TEST_SUBMODULE(numpy_dtypes, m) {
}
return list;
});
m.def("test_dtype_num_of", []() -> py::list {
py::list res;
#define TEST_DTYPE(T) res.append(py::make_tuple(py::dtype::of<T>().num(), py::dtype::num_of<T>()));
TEST_DTYPE(bool)
TEST_DTYPE(char)
TEST_DTYPE(unsigned char)
TEST_DTYPE(short)
TEST_DTYPE(unsigned short)
TEST_DTYPE(int)
TEST_DTYPE(unsigned int)
TEST_DTYPE(long)
TEST_DTYPE(unsigned long)
TEST_DTYPE(long long)
TEST_DTYPE(unsigned long long)
TEST_DTYPE(float)
TEST_DTYPE(double)
TEST_DTYPE(long double)
TEST_DTYPE(std::complex<float>)
TEST_DTYPE(std::complex<double>)
TEST_DTYPE(std::complex<long double>)
TEST_DTYPE(int8_t)
TEST_DTYPE(uint8_t)
TEST_DTYPE(int16_t)
TEST_DTYPE(uint16_t)
TEST_DTYPE(int32_t)
TEST_DTYPE(uint32_t)
TEST_DTYPE(int64_t)
TEST_DTYPE(uint64_t)
#undef TEST_DTYPE
return res;
});
m.def("test_dtype_normalized_num", []() -> py::list {
py::list res;
#define TEST_DTYPE(NT, T) \
res.append(py::make_tuple(py::dtype(py::detail::npy_api::NT).normalized_num(), \
py::dtype::num_of<T>()));
TEST_DTYPE(NPY_BOOL_, bool)
TEST_DTYPE(NPY_BYTE_, char);
TEST_DTYPE(NPY_UBYTE_, unsigned char);
TEST_DTYPE(NPY_SHORT_, short);
TEST_DTYPE(NPY_USHORT_, unsigned short);
TEST_DTYPE(NPY_INT_, int);
TEST_DTYPE(NPY_UINT_, unsigned int);
TEST_DTYPE(NPY_LONG_, long);
TEST_DTYPE(NPY_ULONG_, unsigned long);
TEST_DTYPE(NPY_LONGLONG_, long long);
TEST_DTYPE(NPY_ULONGLONG_, unsigned long long);
TEST_DTYPE(NPY_FLOAT_, float);
TEST_DTYPE(NPY_DOUBLE_, double);
TEST_DTYPE(NPY_LONGDOUBLE_, long double);
TEST_DTYPE(NPY_CFLOAT_, std::complex<float>);
TEST_DTYPE(NPY_CDOUBLE_, std::complex<double>);
TEST_DTYPE(NPY_CLONGDOUBLE_, std::complex<long double>);
TEST_DTYPE(NPY_INT8_, int8_t);
TEST_DTYPE(NPY_UINT8_, uint8_t);
TEST_DTYPE(NPY_INT16_, int16_t);
TEST_DTYPE(NPY_UINT16_, uint16_t);
TEST_DTYPE(NPY_INT32_, int32_t);
TEST_DTYPE(NPY_UINT32_, uint32_t);
TEST_DTYPE(NPY_INT64_, int64_t);
TEST_DTYPE(NPY_UINT64_, uint64_t);
#undef TEST_DTYPE
return res;
});
m.def("test_dtype_switch", [](const py::array &arr) -> py::array {
switch (arr.dtype().normalized_num()) {
case py::dtype::num_of<int8_t>():
return dispatch_array_increment<int8_t>(arr);
case py::dtype::num_of<uint8_t>():
return dispatch_array_increment<uint8_t>(arr);
case py::dtype::num_of<int16_t>():
return dispatch_array_increment<int16_t>(arr);
case py::dtype::num_of<uint16_t>():
return dispatch_array_increment<uint16_t>(arr);
case py::dtype::num_of<int32_t>():
return dispatch_array_increment<int32_t>(arr);
case py::dtype::num_of<uint32_t>():
return dispatch_array_increment<uint32_t>(arr);
case py::dtype::num_of<int64_t>():
return dispatch_array_increment<int64_t>(arr);
case py::dtype::num_of<uint64_t>():
return dispatch_array_increment<uint64_t>(arr);
case py::dtype::num_of<float>():
return dispatch_array_increment<float>(arr);
case py::dtype::num_of<double>():
return dispatch_array_increment<double>(arr);
case py::dtype::num_of<long double>():
return dispatch_array_increment<long double>(arr);
default:
throw std::runtime_error("Unsupported dtype");
}
});
m.def("test_dtype_methods", []() {
py::list list;
auto dt1 = py::dtype::of<int32_t>();

22
tests/test_numpy_dtypes.py
View File

@ -188,6 +188,28 @@ def test_dtype(simple_dtype):
chr(np.dtype(ch).flags) for ch in expected_chars
]
for a, b in m.test_dtype_num_of():
assert a == b
for a, b in m.test_dtype_normalized_num():
assert a == b
arr = np.array([4, 84, 21, 36])
# Note: "ulong" does not work in NumPy 1.x, so we use "L"
assert (m.test_dtype_switch(arr.astype("byte")) == arr + 1).all()
assert (m.test_dtype_switch(arr.astype("ubyte")) == arr + 1).all()
assert (m.test_dtype_switch(arr.astype("short")) == arr + 1).all()
assert (m.test_dtype_switch(arr.astype("ushort")) == arr + 1).all()
assert (m.test_dtype_switch(arr.astype("intc")) == arr + 1).all()
assert (m.test_dtype_switch(arr.astype("uintc")) == arr + 1).all()
assert (m.test_dtype_switch(arr.astype("long")) == arr + 1).all()
assert (m.test_dtype_switch(arr.astype("L")) == arr + 1).all()
assert (m.test_dtype_switch(arr.astype("longlong")) == arr + 1).all()
assert (m.test_dtype_switch(arr.astype("ulonglong")) == arr + 1).all()
assert (m.test_dtype_switch(arr.astype("single")) == arr + 1).all()
assert (m.test_dtype_switch(arr.astype("double")) == arr + 1).all()
assert (m.test_dtype_switch(arr.astype("longdouble")) == arr + 1).all()
def test_recarray(simple_dtype, packed_dtype):
elements = [(False, 0, 0.0, -0.0), (True, 1, 1.5, -2.5), (False, 2, 3.0, -5.0)]