mirror of https://github.com/pybind/pybind11.git
feat: make `numpy.h` compatible with both NumPy 1.x and 2.x (#5050)
* API: Make `numpy.h` compatible with both NumPy 1.x and 2.x * TST: Update numpy dtype flags test to not covert flags to char * API: Add `numpy2.h` instead and make `numpy.h` safe This means that users of `numpy.h` cannot be broken, but need to update to `numpy2.h` if they want to compile for NumPy 2. Using Macros simply and didn't bother to try to remove unnecessary code paths. * API: Rather than `numpy2.h` use a define for the user. * Thread `PYBIND11_NUMPY2_SUPPORT` through things and try to adept test matrix * Small fixups (shouldn't matter)? * Fixup. Does upgrading scipy help? (it shouldn't?) (Some other small fixup) * Use NumPy 2 nightlies for ubuntu-latest job also * BUG: Fix numpy.bool check * TST: Fix complexwarning * BUG: Fix the fact that only the 50 slot is filled with the copy alias (There were 3 functions all doing the same, only this slot survived 2.x) * TST: One more test tweak * TST: Use "long" name for long, since it changed on windows * TST: Apparently we didn't always have ulong, so just use `L` * TST: Enforce dtype='l' for test as default isn't long anymore on windows * Rename macro and invert logic to PYBIND11_NUMPY_1_ONLY * PYBIND11_INTERNAL_NUMPY_1_ONLY_DETECTED * Test and code comment expansion * CI: Use pre-releases of numpy/scipy from pip via explicit version * CI: NumPy 2 only available on almalinux (as it is Python >=3.9) * MAINT: Match name more exactly and adopt error phrasing * MAINT: Pushed early, move helper to be private member * fix error message compilation when using NumPy 1.x-only backcompat * silence name shadowing warning * chore: minor optimization Signed-off-by: Henry Schreiner <henryschreineriii@gmail.com> --------- Signed-off-by: Henry Schreiner <henryschreineriii@gmail.com> Co-authored-by: Ralf W. Grosse-Kunstleve <rwgk@google.com> Co-authored-by: Henry Schreiner <henryschreineriii@gmail.com>
This commit is contained in:
Sebastian Berg
GitHub
parent
e0f2c71596
commit
705efccecd
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@ -108,12 +108,14 @@ jobs:
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run: python -m pip install pytest-github-actions-annotate-failures
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# First build - C++11 mode and inplace
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# More-or-less randomly adding -DPYBIND11_SIMPLE_GIL_MANAGEMENT=ON here.
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# More-or-less randomly adding -DPYBIND11_SIMPLE_GIL_MANAGEMENT=ON here
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# (same for PYBIND11_NUMPY_1_ONLY, but requires a NumPy 1.x at runtime).
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- name: Configure C++11 ${{ matrix.args }}
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run: >
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cmake -S . -B .
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-DPYBIND11_WERROR=ON
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-DPYBIND11_SIMPLE_GIL_MANAGEMENT=ON
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-DPYBIND11_NUMPY_1_ONLY=ON
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-DDOWNLOAD_CATCH=ON
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-DDOWNLOAD_EIGEN=ON
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-DCMAKE_CXX_STANDARD=11
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@ -138,11 +140,13 @@ jobs:
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# Second build - C++17 mode and in a build directory
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# More-or-less randomly adding -DPYBIND11_SIMPLE_GIL_MANAGEMENT=OFF here.
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# (same for PYBIND11_NUMPY_1_ONLY, but requires a NumPy 1.x at runtime).
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- name: Configure C++17
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run: >
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cmake -S . -B build2
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-DPYBIND11_WERROR=ON
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-DPYBIND11_SIMPLE_GIL_MANAGEMENT=OFF
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-DPYBIND11_NUMPY_1_ONLY=ON
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-DDOWNLOAD_CATCH=ON
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-DDOWNLOAD_EIGEN=ON
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-DCMAKE_CXX_STANDARD=17
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@ -660,6 +664,11 @@ jobs:
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run: |
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python3 -m pip install cmake -r tests/requirements.txt
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- name: Ensure NumPy 2 is used (required Python >= 3.9)
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if: matrix.container == 'almalinux:9'
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run: |
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python3 -m pip install 'numpy>=2.0.0b1' 'scipy>=1.13.0rc1'
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- name: Configure
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shell: bash
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run: >
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@ -895,8 +904,10 @@ jobs:
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python-version: ${{ matrix.python }}
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- name: Prepare env
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# Ensure use of NumPy 2 (via NumPy nightlies but can be changed soon)
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run: |
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python3 -m pip install -r tests/requirements.txt
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python3 -m pip install 'numpy>=2.0.0b1' 'scipy>=1.13.0rc1'
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- name: Update CMake
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uses: jwlawson/actions-setup-cmake@v2.0
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@ -109,6 +109,8 @@ option(PYBIND11_TEST "Build pybind11 test suite?" ${PYBIND11_MASTER_PROJECT})
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option(PYBIND11_NOPYTHON "Disable search for Python" OFF)
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option(PYBIND11_SIMPLE_GIL_MANAGEMENT
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"Use simpler GIL management logic that does not support disassociation" OFF)
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option(PYBIND11_NUMPY_1_ONLY
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"Disable NumPy 2 support to avoid changes to previous pybind11 versions." OFF)
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set(PYBIND11_INTERNALS_VERSION
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""
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CACHE STRING "Override the ABI version, may be used to enable the unstable ABI.")
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@ -116,6 +118,9 @@ set(PYBIND11_INTERNALS_VERSION
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if(PYBIND11_SIMPLE_GIL_MANAGEMENT)
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add_compile_definitions(PYBIND11_SIMPLE_GIL_MANAGEMENT)
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endif()
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if(PYBIND11_NUMPY_1_ONLY)
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add_compile_definitions(PYBIND11_NUMPY_1_ONLY)
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endif()
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cmake_dependent_option(
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USE_PYTHON_INCLUDE_DIR
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@ -327,8 +327,9 @@ public:
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value = false;
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return true;
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}
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if (convert || (std::strcmp("numpy.bool_", Py_TYPE(src.ptr())->tp_name) == 0)) {
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// (allow non-implicit conversion for numpy booleans)
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if (convert || is_numpy_bool(src)) {
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// (allow non-implicit conversion for numpy booleans), use strncmp
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// since NumPy 1.x had an additional trailing underscore.
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Py_ssize_t res = -1;
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if (src.is_none()) {
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@ -360,6 +361,15 @@ public:
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return handle(src ? Py_True : Py_False).inc_ref();
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}
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PYBIND11_TYPE_CASTER(bool, const_name("bool"));
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private:
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// Test if an object is a NumPy boolean (without fetching the type).
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static inline bool is_numpy_bool(handle object) {
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const char *type_name = Py_TYPE(object.ptr())->tp_name;
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// Name changed to `numpy.bool` in NumPy 2, `numpy.bool_` is needed for 1.x support
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return std::strcmp("numpy.bool", type_name) == 0
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|| std::strcmp("numpy.bool_", type_name) == 0;
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}
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};
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// Helper class for UTF-{8,16,32} C++ stl strings:
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@ -296,6 +296,10 @@ PYBIND11_WARNING_DISABLE_MSVC(4505)
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# undef copysign
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#endif
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#if defined(PYBIND11_NUMPY_1_ONLY)
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# define PYBIND11_INTERNAL_NUMPY_1_ONLY_DETECTED
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#endif
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#if defined(PYPY_VERSION) && !defined(PYBIND11_SIMPLE_GIL_MANAGEMENT)
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# define PYBIND11_SIMPLE_GIL_MANAGEMENT
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#endif
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@ -29,10 +29,15 @@
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#include <utility>
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#include <vector>
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#if defined(PYBIND11_NUMPY_1_ONLY) && !defined(PYBIND11_INTERNAL_NUMPY_1_ONLY_DETECTED)
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# error PYBIND11_NUMPY_1_ONLY must be defined before any pybind11 header is included.
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#endif
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/* This will be true on all flat address space platforms and allows us to reduce the
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whole npy_intp / ssize_t / Py_intptr_t business down to just ssize_t for all size
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and dimension types (e.g. shape, strides, indexing), instead of inflicting this
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upon the library user. */
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upon the library user.
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Note that NumPy 2 now uses ssize_t for `npy_intp` to simplify this. */
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static_assert(sizeof(::pybind11::ssize_t) == sizeof(Py_intptr_t), "ssize_t != Py_intptr_t");
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static_assert(std::is_signed<Py_intptr_t>::value, "Py_intptr_t must be signed");
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// We now can reinterpret_cast between py::ssize_t and Py_intptr_t (MSVC + PyPy cares)
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@ -53,7 +58,8 @@ struct handle_type_name<array> {
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template <typename type, typename SFINAE = void>
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struct npy_format_descriptor;
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struct PyArrayDescr_Proxy {
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/* NumPy 1 proxy (always includes legacy fields) */
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struct PyArrayDescr1_Proxy {
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PyObject_HEAD
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PyObject *typeobj;
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char kind;
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@ -68,6 +74,43 @@ struct PyArrayDescr_Proxy {
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PyObject *names;
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};
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#ifndef PYBIND11_NUMPY_1_ONLY
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struct PyArrayDescr_Proxy {
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PyObject_HEAD
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PyObject *typeobj;
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char kind;
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char type;
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char byteorder;
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char _former_flags;
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int type_num;
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/* Additional fields are NumPy version specific. */
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};
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#else
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/* NumPy 1.x only, we can expose all fields */
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using PyArrayDescr_Proxy = PyArrayDescr1_Proxy;
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#endif
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/* NumPy 2 proxy, including legacy fields */
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struct PyArrayDescr2_Proxy {
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PyObject_HEAD
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PyObject *typeobj;
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char kind;
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char type;
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char byteorder;
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char _former_flags;
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int type_num;
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std::uint64_t flags;
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ssize_t elsize;
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ssize_t alignment;
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PyObject *metadata;
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Py_hash_t hash;
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void *reserved_null[2];
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/* The following fields only exist if 0 <= type_num < 2056 */
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char *subarray;
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PyObject *fields;
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PyObject *names;
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};
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struct PyArray_Proxy {
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PyObject_HEAD
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char *data;
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@ -131,6 +174,14 @@ PYBIND11_NOINLINE module_ import_numpy_core_submodule(const char *submodule_name
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object numpy_version = numpy_lib.attr("NumpyVersion")(version_string);
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int major_version = numpy_version.attr("major").cast<int>();
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#ifdef PYBIND11_NUMPY_1_ONLY
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if (major_version >= 2) {
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throw std::runtime_error(
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"This extension was built with PYBIND11_NUMPY_1_ONLY defined, "
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"but NumPy 2 is used in this process. For NumPy2 compatibility, "
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"this extension needs to be rebuilt without the PYBIND11_NUMPY_1_ONLY define.");
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}
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#endif
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/* `numpy.core` was renamed to `numpy._core` in NumPy 2.0 as it officially
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became a private module. */
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std::string numpy_core_path = major_version >= 2 ? "numpy._core" : "numpy.core";
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@ -203,6 +254,8 @@ struct npy_api {
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NPY_ULONG_, NPY_ULONGLONG_, NPY_UINT_),
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};
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unsigned int PyArray_RUNTIME_VERSION_;
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struct PyArray_Dims {
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Py_intptr_t *ptr;
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int len;
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@ -241,6 +294,7 @@ struct npy_api {
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PyObject *(*PyArray_FromAny_)(PyObject *, PyObject *, int, int, int, PyObject *);
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int (*PyArray_DescrConverter_)(PyObject *, PyObject **);
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bool (*PyArray_EquivTypes_)(PyObject *, PyObject *);
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#ifdef PYBIND11_NUMPY_1_ONLY
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int (*PyArray_GetArrayParamsFromObject_)(PyObject *,
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PyObject *,
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unsigned char,
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@ -249,6 +303,7 @@ struct npy_api {
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Py_intptr_t *,
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PyObject **,
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PyObject *);
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#endif
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PyObject *(*PyArray_Squeeze_)(PyObject *);
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// Unused. Not removed because that affects ABI of the class.
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int (*PyArray_SetBaseObject_)(PyObject *, PyObject *);
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@ -266,7 +321,8 @@ private:
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API_PyArray_DescrFromScalar = 57,
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API_PyArray_FromAny = 69,
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API_PyArray_Resize = 80,
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API_PyArray_CopyInto = 82,
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// CopyInto was slot 82 and 50 was effectively an alias. NumPy 2 removed 82.
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API_PyArray_CopyInto = 50,
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API_PyArray_NewCopy = 85,
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API_PyArray_NewFromDescr = 94,
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API_PyArray_DescrNewFromType = 96,
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@ -275,7 +331,9 @@ private:
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API_PyArray_View = 137,
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API_PyArray_DescrConverter = 174,
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API_PyArray_EquivTypes = 182,
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#ifdef PYBIND11_NUMPY_1_ONLY
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API_PyArray_GetArrayParamsFromObject = 278,
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#endif
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API_PyArray_SetBaseObject = 282
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};
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@ -290,7 +348,8 @@ private:
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npy_api api;
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#define DECL_NPY_API(Func) api.Func##_ = (decltype(api.Func##_)) api_ptr[API_##Func];
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DECL_NPY_API(PyArray_GetNDArrayCFeatureVersion);
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if (api.PyArray_GetNDArrayCFeatureVersion_() < 0x7) {
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api.PyArray_RUNTIME_VERSION_ = api.PyArray_GetNDArrayCFeatureVersion_();
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if (api.PyArray_RUNTIME_VERSION_ < 0x7) {
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pybind11_fail("pybind11 numpy support requires numpy >= 1.7.0");
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}
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DECL_NPY_API(PyArray_Type);
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@ -309,7 +368,9 @@ private:
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DECL_NPY_API(PyArray_View);
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DECL_NPY_API(PyArray_DescrConverter);
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DECL_NPY_API(PyArray_EquivTypes);
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#ifdef PYBIND11_NUMPY_1_ONLY
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DECL_NPY_API(PyArray_GetArrayParamsFromObject);
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#endif
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DECL_NPY_API(PyArray_SetBaseObject);
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#undef DECL_NPY_API
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@ -331,6 +392,14 @@ inline const PyArrayDescr_Proxy *array_descriptor_proxy(const PyObject *ptr) {
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return reinterpret_cast<const PyArrayDescr_Proxy *>(ptr);
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}
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inline const PyArrayDescr1_Proxy *array_descriptor1_proxy(const PyObject *ptr) {
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return reinterpret_cast<const PyArrayDescr1_Proxy *>(ptr);
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}
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inline const PyArrayDescr2_Proxy *array_descriptor2_proxy(const PyObject *ptr) {
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return reinterpret_cast<const PyArrayDescr2_Proxy *>(ptr);
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}
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inline bool check_flags(const void *ptr, int flag) {
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return (flag == (array_proxy(ptr)->flags & flag));
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}
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@ -610,10 +679,32 @@ public:
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}
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/// Size of the data type in bytes.
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#ifdef PYBIND11_NUMPY_1_ONLY
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ssize_t itemsize() const { return detail::array_descriptor_proxy(m_ptr)->elsize; }
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#else
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ssize_t itemsize() const {
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if (detail::npy_api::get().PyArray_RUNTIME_VERSION_ < 0x12) {
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return detail::array_descriptor1_proxy(m_ptr)->elsize;
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}
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return detail::array_descriptor2_proxy(m_ptr)->elsize;
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}
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#endif
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/// Returns true for structured data types.
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#ifdef PYBIND11_NUMPY_1_ONLY
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bool has_fields() const { return detail::array_descriptor_proxy(m_ptr)->names != nullptr; }
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#else
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bool has_fields() const {
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if (detail::npy_api::get().PyArray_RUNTIME_VERSION_ < 0x12) {
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return detail::array_descriptor1_proxy(m_ptr)->names != nullptr;
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}
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const auto *proxy = detail::array_descriptor2_proxy(m_ptr);
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if (proxy->type_num < 0 || proxy->type_num >= 2056) {
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return false;
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}
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return proxy->names != nullptr;
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}
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#endif
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/// Single-character code for dtype's kind.
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/// For example, floating point types are 'f' and integral types are 'i'.
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@ -639,11 +730,29 @@ public:
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/// Single character for byteorder
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char byteorder() const { return detail::array_descriptor_proxy(m_ptr)->byteorder; }
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/// Alignment of the data type
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/// Alignment of the data type
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#ifdef PYBIND11_NUMPY_1_ONLY
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int alignment() const { return detail::array_descriptor_proxy(m_ptr)->alignment; }
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#else
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ssize_t alignment() const {
|
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if (detail::npy_api::get().PyArray_RUNTIME_VERSION_ < 0x12) {
|
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return detail::array_descriptor1_proxy(m_ptr)->alignment;
|
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}
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return detail::array_descriptor2_proxy(m_ptr)->alignment;
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}
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#endif
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|
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/// Flags for the array descriptor
|
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/// Flags for the array descriptor
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#ifdef PYBIND11_NUMPY_1_ONLY
|
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char flags() const { return detail::array_descriptor_proxy(m_ptr)->flags; }
|
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#else
|
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std::uint64_t flags() const {
|
||||
if (detail::npy_api::get().PyArray_RUNTIME_VERSION_ < 0x12) {
|
||||
return (unsigned char) detail::array_descriptor1_proxy(m_ptr)->flags;
|
||||
}
|
||||
return detail::array_descriptor2_proxy(m_ptr)->flags;
|
||||
}
|
||||
#endif
|
||||
|
||||
private:
|
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static object &_dtype_from_pep3118() {
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||||
|
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@ -810,9 +919,7 @@ public:
|
|||
}
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||||
|
||||
/// Byte size of a single element
|
||||
ssize_t itemsize() const {
|
||||
return detail::array_descriptor_proxy(detail::array_proxy(m_ptr)->descr)->elsize;
|
||||
}
|
||||
ssize_t itemsize() const { return dtype().itemsize(); }
|
||||
|
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/// Total number of bytes
|
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ssize_t nbytes() const { return size() * itemsize(); }
|
||||
|
|
|
|||
|
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@ -218,4 +218,5 @@ def pytest_report_header(config):
|
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f" {pybind11_tests.cpp_std}"
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f" {pybind11_tests.PYBIND11_INTERNALS_ID}"
|
||||
f" PYBIND11_SIMPLE_GIL_MANAGEMENT={pybind11_tests.PYBIND11_SIMPLE_GIL_MANAGEMENT}"
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f" PYBIND11_NUMPY_1_ONLY={pybind11_tests.PYBIND11_NUMPY_1_ONLY}"
|
||||
)
|
||||
|
|
|
|||
|
|
@ -95,6 +95,12 @@ PYBIND11_MODULE(pybind11_tests, m) {
|
|||
#else
|
||||
false;
|
||||
#endif
|
||||
m.attr("PYBIND11_NUMPY_1_ONLY") =
|
||||
#if defined(PYBIND11_NUMPY_1_ONLY)
|
||||
true;
|
||||
#else
|
||||
false;
|
||||
#endif
|
||||
|
||||
bind_ConstructorStats(m);
|
||||
|
||||
|
|
|
|||
|
|
@ -608,7 +608,9 @@ def test_both_ref_mutators():
|
|||
def test_nocopy_wrapper():
|
||||
# get_elem requires a column-contiguous matrix reference, but should be
|
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# callable with other types of matrix (via copying):
|
||||
int_matrix_colmajor = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]], order="F")
|
||||
int_matrix_colmajor = np.array(
|
||||
[[1, 2, 3], [4, 5, 6], [7, 8, 9]], dtype="l", order="F"
|
||||
)
|
||||
dbl_matrix_colmajor = np.array(
|
||||
int_matrix_colmajor, dtype="double", order="F", copy=True
|
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)
|
||||
|
|
|
|||
|
|
@ -536,7 +536,12 @@ def test_format_descriptors_for_floating_point_types(test_func):
|
|||
@pytest.mark.parametrize("contiguity", [None, "C", "F"])
|
||||
@pytest.mark.parametrize("noconvert", [False, True])
|
||||
@pytest.mark.filterwarnings(
|
||||
"ignore:Casting complex values to real discards the imaginary part:numpy.ComplexWarning"
|
||||
"ignore:Casting complex values to real discards the imaginary part:"
|
||||
+ (
|
||||
"numpy.exceptions.ComplexWarning"
|
||||
if hasattr(np, "exceptions")
|
||||
else "numpy.ComplexWarning"
|
||||
)
|
||||
)
|
||||
def test_argument_conversions(forcecast, contiguity, noconvert):
|
||||
function_name = "accept_double"
|
||||
|
|
@ -583,7 +588,8 @@ def test_argument_conversions(forcecast, contiguity, noconvert):
|
|||
def test_dtype_refcount_leak():
|
||||
from sys import getrefcount
|
||||
|
||||
dtype = np.dtype(np.float_)
|
||||
# Was np.float_ but that alias for float64 was removed in NumPy 2.
|
||||
dtype = np.dtype(np.float64)
|
||||
a = np.array([1], dtype=dtype)
|
||||
before = getrefcount(dtype)
|
||||
m.ndim(a)
|
||||
|
|
|
|||
|
|
@ -405,10 +405,35 @@ TEST_SUBMODULE(numpy_dtypes, m) {
|
|||
});
|
||||
|
||||
// test_dtype
|
||||
// Below we use `L` for unsigned long as unfortunately the only name that
|
||||
// works reliably on Both NumPy 2.x and old NumPy 1.x.
|
||||
std::vector<const char *> dtype_names{
|
||||
"byte", "short", "intc", "int_", "longlong", "ubyte", "ushort",
|
||||
"uintc", "uint", "ulonglong", "half", "single", "double", "longdouble",
|
||||
"csingle", "cdouble", "clongdouble", "bool_", "datetime64", "timedelta64", "object_"};
|
||||
"byte",
|
||||
"short",
|
||||
"intc",
|
||||
"long",
|
||||
"longlong",
|
||||
"ubyte",
|
||||
"ushort",
|
||||
"uintc",
|
||||
"L",
|
||||
"ulonglong",
|
||||
"half",
|
||||
"single",
|
||||
"double",
|
||||
"longdouble",
|
||||
"csingle",
|
||||
"cdouble",
|
||||
"clongdouble",
|
||||
"bool_",
|
||||
"datetime64",
|
||||
"timedelta64",
|
||||
"object_",
|
||||
// platform dependent aliases (int_ and uint are also NumPy version dependent on windows)
|
||||
"int_",
|
||||
"uint",
|
||||
"intp",
|
||||
"uintp"};
|
||||
|
||||
m.def("print_dtypes", []() {
|
||||
py::list l;
|
||||
|
|
|
|||
|
|
@ -3,6 +3,7 @@ import re
|
|||
import pytest
|
||||
|
||||
import env # noqa: F401
|
||||
from pybind11_tests import PYBIND11_NUMPY_1_ONLY
|
||||
from pybind11_tests import numpy_dtypes as m
|
||||
|
||||
np = pytest.importorskip("numpy")
|
||||
|
|
@ -172,13 +173,20 @@ def test_dtype(simple_dtype):
|
|||
np.zeros(1, m.trailing_padding_dtype())
|
||||
)
|
||||
|
||||
expected_chars = "bhilqBHILQefdgFDG?MmO"
|
||||
assert m.test_dtype_kind() == list("iiiiiuuuuuffffcccbMmO")
|
||||
expected_chars = list("bhilqBHILQefdgFDG?MmO")
|
||||
# Note that int_ and uint size and mapping is NumPy version dependent:
|
||||
expected_chars += [np.dtype(_).char for _ in ("int_", "uint", "intp", "uintp")]
|
||||
assert m.test_dtype_kind() == list("iiiiiuuuuuffffcccbMmOiuiu")
|
||||
assert m.test_dtype_char_() == list(expected_chars)
|
||||
assert m.test_dtype_num() == [np.dtype(ch).num for ch in expected_chars]
|
||||
assert m.test_dtype_byteorder() == [np.dtype(ch).byteorder for ch in expected_chars]
|
||||
assert m.test_dtype_alignment() == [np.dtype(ch).alignment for ch in expected_chars]
|
||||
assert m.test_dtype_flags() == [chr(np.dtype(ch).flags) for ch in expected_chars]
|
||||
if not PYBIND11_NUMPY_1_ONLY:
|
||||
assert m.test_dtype_flags() == [np.dtype(ch).flags for ch in expected_chars]
|
||||
else:
|
||||
assert m.test_dtype_flags() == [
|
||||
chr(np.dtype(ch).flags) for ch in expected_chars
|
||||
]
|
||||
|
||||
|
||||
def test_recarray(simple_dtype, packed_dtype):
|
||||
|
|
|
|||
Loading…
Reference in New Issue