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Merge branch 'master' into skylion007/classmethod

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Aaron Gokaslan 2022-11-08 12:27:42 -05:00 committed by GitHub
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21
.github/ISSUE_TEMPLATE/bug-report.yml vendored
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@ -6,7 +6,8 @@ body:
- type: markdown
attributes:
value: |
Maintainers will only make a best effort to triage PRs. Please do your best to make the issue as easy to act on as possible, and only open if clearly a problem with pybind11 (ask first if unsure).
Please do your best to make the issue as easy to act on as possible, and only submit here if there is clearly a problem with pybind11 (ask first if unsure). **Note that a reproducer in a PR is much more likely to get immediate attention.**
- type: checkboxes
id: steps
attributes:
@ -20,6 +21,12 @@ body:
- label: Consider asking first in the [Gitter chat room](https://gitter.im/pybind/Lobby) or in a [Discussion](https:/pybind/pybind11/discussions/new).
required: false
- type: Input
id: version
attributes:
label: What version (or hash if on master) of pybind11 are you using?
required: true
- type: textarea
id: description
attributes:
@ -40,6 +47,14 @@ body:
The code should be minimal, have no external dependencies, isolate the
function(s) that cause breakage. Submit matched and complete C++ and
Python snippets that can be easily compiled and run to diagnose the
issue. If possible, make a PR with a new, failing test to give us a
starting point to work on!
issue. — Note that a reproducer in a PR is much more likely to get
immediate attention: failing tests in the pybind11 CI are the best
starting point for working out fixes.
render: text
- type: Input
id: regression
attributes:
label: Is this a regression? Put the last known working version here if it is.
description: Put the last known working version here if this is a regression.
value: Not a regression

24
.github/workflows/ci.yml vendored
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@ -30,7 +30,7 @@ jobs:
- '3.6'
- '3.9'
- '3.10'
- '3.11-dev'
- '3.11'
- 'pypy-3.7'
- 'pypy-3.8'
- 'pypy-3.9'
@ -102,10 +102,12 @@ jobs:
run: python -m pip install pytest-github-actions-annotate-failures
# First build - C++11 mode and inplace
# More-or-less randomly adding -DPYBIND11_SIMPLE_GIL_MANAGEMENT=ON here.
- name: Configure C++11 ${{ matrix.args }}
run: >
cmake -S . -B .
-DPYBIND11_WERROR=ON
-DPYBIND11_SIMPLE_GIL_MANAGEMENT=ON
-DDOWNLOAD_CATCH=ON
-DDOWNLOAD_EIGEN=ON
-DCMAKE_CXX_STANDARD=11
@ -119,7 +121,7 @@ jobs:
- name: C++11 tests
# TODO: Figure out how to load the DLL on Python 3.8+
if: "!(runner.os == 'Windows' && (matrix.python == 3.8 || matrix.python == 3.9 || matrix.python == '3.10' || matrix.python == '3.11-dev' || matrix.python == 'pypy-3.8'))"
if: "!(runner.os == 'Windows' && (matrix.python == 3.8 || matrix.python == 3.9 || matrix.python == '3.10' || matrix.python == '3.11' || matrix.python == 'pypy-3.8'))"
run: cmake --build . --target cpptest -j 2
- name: Interface test C++11
@ -129,10 +131,12 @@ jobs:
run: git clean -fdx
# Second build - C++17 mode and in a build directory
# More-or-less randomly adding -DPYBIND11_SIMPLE_GIL_MANAGEMENT=OFF here.
- name: Configure C++17
run: >
cmake -S . -B build2
-DPYBIND11_WERROR=ON
-DPYBIND11_SIMPLE_GIL_MANAGEMENT=OFF
-DDOWNLOAD_CATCH=ON
-DDOWNLOAD_EIGEN=ON
-DCMAKE_CXX_STANDARD=17
@ -146,7 +150,7 @@ jobs:
- name: C++ tests
# TODO: Figure out how to load the DLL on Python 3.8+
if: "!(runner.os == 'Windows' && (matrix.python == 3.8 || matrix.python == 3.9 || matrix.python == '3.10' || matrix.python == '3.11-dev' || matrix.python == 'pypy-3.8'))"
if: "!(runner.os == 'Windows' && (matrix.python == 3.8 || matrix.python == 3.9 || matrix.python == '3.10' || matrix.python == '3.11' || matrix.python == 'pypy-3.8'))"
run: cmake --build build2 --target cpptest
# Third build - C++17 mode with unstable ABI
@ -186,7 +190,7 @@ jobs:
- python-version: "3.9"
python-debug: true
valgrind: true
- python-version: "3.11-dev"
- python-version: "3.11"
python-debug: false
name: "🐍 ${{ matrix.python-version }}${{ matrix.python-debug && '-dbg' || '' }} (deadsnakes)${{ matrix.valgrind && ' • Valgrind' || '' }} • x64"
@ -391,7 +395,7 @@ jobs:
# Testing on CentOS 7 + PGI compilers, which seems to require more workarounds
centos-nvhpc7:
runs-on: ubuntu-latest
name: "🐍 3 • CentOS7 / PGI 22.3 • x64"
name: "🐍 3 • CentOS7 / PGI 22.9 • x64"
container: centos:7
steps:
@ -401,7 +405,7 @@ jobs:
run: yum update -y && yum install -y epel-release && yum install -y git python3-devel make environment-modules cmake3 yum-utils
- name: Install NVidia HPC SDK
run: yum-config-manager --add-repo https://developer.download.nvidia.com/hpc-sdk/rhel/nvhpc.repo && yum -y install nvhpc-22.3
run: yum-config-manager --add-repo https://developer.download.nvidia.com/hpc-sdk/rhel/nvhpc.repo && yum -y install nvhpc-22.9
# On CentOS 7, we have to filter a few tests (compiler internal error)
# and allow deeper template recursion (not needed on CentOS 8 with a newer
@ -411,12 +415,12 @@ jobs:
shell: bash
run: |
source /etc/profile.d/modules.sh
module load /opt/nvidia/hpc_sdk/modulefiles/nvhpc/22.3
module load /opt/nvidia/hpc_sdk/modulefiles/nvhpc/22.9
cmake3 -S . -B build -DDOWNLOAD_CATCH=ON \
-DCMAKE_CXX_STANDARD=11 \
-DPYTHON_EXECUTABLE=$(python3 -c "import sys; print(sys.executable)") \
-DCMAKE_CXX_FLAGS="-Wc,--pending_instantiations=0" \
-DPYBIND11_TEST_FILTER="test_smart_ptr.cpp;test_virtual_functions.cpp"
-DPYBIND11_TEST_FILTER="test_smart_ptr.cpp"
# Building before installing Pip should produce a warning but not an error
- name: Build
@ -757,7 +761,7 @@ jobs:
uses: jwlawson/actions-setup-cmake@v1.13
- name: Prepare MSVC
uses: ilammy/msvc-dev-cmd@v1.11.0
uses: ilammy/msvc-dev-cmd@v1.12.0
with:
arch: x86
@ -810,7 +814,7 @@ jobs:
uses: jwlawson/actions-setup-cmake@v1.13
- name: Prepare MSVC
uses: ilammy/msvc-dev-cmd@v1.11.0
uses: ilammy/msvc-dev-cmd@v1.12.0
with:
arch: x86

6
.github/workflows/labeler.yml vendored
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@ -10,7 +10,11 @@ jobs:
steps:
- uses: actions/labeler@main
if: github.event.pull_request.merged == true
if: >
github.event.pull_request.merged == true &&
!startsWith(github.event.pull_request.title, 'chore(deps):') &&
!startsWith(github.event.pull_request.title, 'ci(fix):') &&
!startsWith(github.event.pull_request.title, 'docs(changelog):')
with:
repo-token: ${{ secrets.GITHUB_TOKEN }}
configuration-path: .github/labeler_merged.yml

1
.gitignore vendored
View File

@ -43,3 +43,4 @@ pybind11Targets.cmake
/pybind11/share/*
/docs/_build/*
.ipynb_checkpoints/
tests/main.cpp

12
.pre-commit-config.yaml
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@ -41,7 +41,7 @@ repos:
# Upgrade old Python syntax
- repo: https://github.com/asottile/pyupgrade
rev: "v2.38.2"
rev: "v3.2.0"
hooks:
- id: pyupgrade
args: [--py36-plus]
@ -54,7 +54,7 @@ repos:
# Black, the code formatter, natively supports pre-commit
- repo: https://github.com/psf/black
rev: "22.8.0" # Keep in sync with blacken-docs
rev: "22.10.0" # Keep in sync with blacken-docs
hooks:
- id: black
@ -64,7 +64,7 @@ repos:
hooks:
- id: blacken-docs
additional_dependencies:
- black==22.8.0 # keep in sync with black hook
- black==22.10.0 # keep in sync with black hook
# Changes tabs to spaces
- repo: https://github.com/Lucas-C/pre-commit-hooks
@ -116,7 +116,7 @@ repos:
# PyLint has native support - not always usable, but works for us
- repo: https://github.com/PyCQA/pylint
rev: "v2.15.3"
rev: "v2.15.5"
hooks:
- id: pylint
files: ^pybind11
@ -132,7 +132,7 @@ repos:
# Check static types with mypy
- repo: https://github.com/pre-commit/mirrors-mypy
rev: "v0.981"
rev: "v0.982"
hooks:
- id: mypy
args: []
@ -152,7 +152,7 @@ repos:
# Use tools/codespell_ignore_lines_from_errors.py
# to rebuild .codespell-ignore-lines
- repo: https://github.com/codespell-project/codespell
rev: "v2.2.1"
rev: "v2.2.2"
hooks:
- id: codespell
exclude: ".supp$"

8
CMakeLists.txt
View File

@ -91,10 +91,16 @@ endif()
option(PYBIND11_INSTALL "Install pybind11 header files?" ${PYBIND11_MASTER_PROJECT})
option(PYBIND11_TEST "Build pybind11 test suite?" ${PYBIND11_MASTER_PROJECT})
option(PYBIND11_NOPYTHON "Disable search for Python" OFF)
option(PYBIND11_SIMPLE_GIL_MANAGEMENT
"Use simpler GIL management logic that does not support disassociation" OFF)
set(PYBIND11_INTERNALS_VERSION
""
CACHE STRING "Override the ABI version, may be used to enable the unstable ABI.")
if(PYBIND11_SIMPLE_GIL_MANAGEMENT)
add_compile_definitions(PYBIND11_SIMPLE_GIL_MANAGEMENT)
endif()
cmake_dependent_option(
USE_PYTHON_INCLUDE_DIR
"Install pybind11 headers in Python include directory instead of default installation prefix"
@ -120,6 +126,8 @@ set(PYBIND11_HEADERS
include/pybind11/complex.h
include/pybind11/options.h
include/pybind11/eigen.h
include/pybind11/eigen/matrix.h
include/pybind11/eigen/tensor.h
include/pybind11/embed.h
include/pybind11/eval.h
include/pybind11/gil.h

9
docs/advanced/exceptions.rst
View File

@ -177,9 +177,12 @@ section.
may be explicitly (re-)thrown to delegate it to the other,
previously-declared existing exception translators.
Note that ``libc++`` and ``libstdc++`` `behave differently <https://stackoverflow.com/questions/19496643/using-clang-fvisibility-hidden-and-typeinfo-and-type-erasure/28827430>`_
with ``-fvisibility=hidden``. Therefore exceptions that are used across ABI boundaries need to be explicitly exported, as exercised in ``tests/test_exceptions.h``.
See also: "Problems with C++ exceptions" under `GCC Wiki <https://gcc.gnu.org/wiki/Visibility>`_.
Note that ``libc++`` and ``libstdc++`` `behave differently under macOS
<https://stackoverflow.com/questions/19496643/using-clang-fvisibility-hidden-and-typeinfo-and-type-erasure/28827430>`_
with ``-fvisibility=hidden``. Therefore exceptions that are used across ABI
boundaries need to be explicitly exported, as exercised in
``tests/test_exceptions.h``. See also:
"Problems with C++ exceptions" under `GCC Wiki <https://gcc.gnu.org/wiki/Visibility>`_.
Local vs Global Exception Translators

137
docs/changelog.rst
View File

@ -10,12 +10,147 @@ Changes will be added here periodically from the "Suggested changelog entry"
block in pull request descriptions.
IN DEVELOPMENT
--------------
Changes will be summarized here periodically.
Version 2.10.1 (Oct 31, 2022)
-----------------------------
This is the first version to fully support embedding the newly released Python 3.11.
Changes:
* Allow ``pybind11::capsule`` constructor to take null destructor pointers.
`#4221 <https://github.com/pybind/pybind11/pull/4221>`_
* ``embed.h`` was changed so that ``PYTHONPATH`` is used also with Python 3.11
(established behavior).
`#4119 <https://github.com/pybind/pybind11/pull/4119>`_
* A ``PYBIND11_SIMPLE_GIL_MANAGEMENT`` option was added (cmake, C++ define),
along with many additional tests in ``test_gil_scoped.py``. The option may be
useful to try when debugging GIL-related issues, to determine if the more
complex default implementation is or is not to blame. See #4216 for
background. WARNING: Please be careful to not create ODR violations when
using the option: everything that is linked together with mutual symbol
visibility needs to be rebuilt.
`#4216 <https://github.com/pybind/pybind11/pull/4216>`_
* ``PYBIND11_EXPORT_EXCEPTION`` was made non-empty only under macOS. This makes
Linux builds safer, and enables the removal of warning suppression pragmas for
Windows.
`#4298 <https://github.com/pybind/pybind11/pull/4298>`_
Bug fixes:
* Fixed a bug where ``UnicodeDecodeError`` was not propagated from various
``py::str`` ctors when decoding surrogate utf characters.
`#4294 <https://github.com/pybind/pybind11/pull/4294>`_
* Revert perfect forwarding for ``make_iterator``. This broke at least one
valid use case. May revisit later.
`#4234 <https://github.com/pybind/pybind11/pull/4234>`_
* Fix support for safe casts to ``void*`` (regression in 2.10.0).
`#4275 <https://github.com/pybind/pybind11/pull/4275>`_
* Fix ``char8_t`` support (regression in 2.9).
`#4278 <https://github.com/pybind/pybind11/pull/4278>`_
* Unicode surrogate character in Python exception message leads to process
termination in ``error_already_set::what()``.
`#4297 <https://github.com/pybind/pybind11/pull/4297>`_
* Fix MSVC 2019 v.1924 & C++14 mode error for ``overload_cast``.
`#4188 <https://github.com/pybind/pybind11/pull/4188>`_
* Make augmented assignment operators non-const for the object-api. Behavior
was previously broken for augmented assignment operators.
`#4065 <https://github.com/pybind/pybind11/pull/4065>`_
* Add proper error checking to C++ bindings for Python list append and insert.
`#4208 <https://github.com/pybind/pybind11/pull/4208>`_
* Work-around for Nvidia's CUDA nvcc compiler in versions 11.4.0 - 11.8.0.
`#4220 <https://github.com/pybind/pybind11/pull/4220>`_
* A workaround for PyPy was added in the ``py::error_already_set``
implementation, related to PR `#1895 <https://github.com/pybind/pybind11/pull/1895>`_
released with v2.10.0.
`#4079 <https://github.com/pybind/pybind11/pull/4079>`_
* Fixed compiler errors when C++23 ``std::forward_like`` is available.
`#4136 <https://github.com/pybind/pybind11/pull/4136>`_
* Properly raise exceptions in contains methods (like when an object in unhashable).
`#4209 <https://github.com/pybind/pybind11/pull/4209>`_
* Further improve another error in exception handling.
`#4232 <https://github.com/pybind/pybind11/pull/4232>`_
* ``get_local_internals()`` was made compatible with
``finalize_interpreter()``, fixing potential freezes during interpreter
finalization.
`#4192 <https://github.com/pybind/pybind11/pull/4192>`_
Performance and style:
* Reserve space in set and STL map casters if possible. This will prevent
unnecessary rehashing / resizing by knowing the number of keys ahead of time
for Python to C++ casting. This improvement will greatly speed up the casting
of large unordered maps and sets.
`#4194 <https://github.com/pybind/pybind11/pull/4194>`_
* GIL RAII scopes are non-copyable to avoid potential bugs.
`#4183 <https://github.com/pybind/pybind11/pull/4183>`_
* Explicitly default all relevant ctors for pytypes in the ``PYBIND11_OBJECT``
macros and enforce the clang-tidy checks ``modernize-use-equals-default`` in
macros as well.
`#4017 <https://github.com/pybind/pybind11/pull/4017>`_
* Optimize iterator advancement in C++ bindings.
`#4237 <https://github.com/pybind/pybind11/pull/4237>`_
* Use the modern ``PyObject_GenericGetDict`` and ``PyObject_GenericSetDict``
for handling dynamic attribute dictionaries.
`#4106 <https://github.com/pybind/pybind11/pull/4106>`_
* Document that users should use ``PYBIND11_NAMESPACE`` instead of using ``pybind11`` when
opening namespaces. Using namespace declarations and namespace qualification
remain the same as ``pybind11``. This is done to ensure consistent symbol
visibility.
`#4098 <https://github.com/pybind/pybind11/pull/4098>`_
* Mark ``detail::forward_like`` as constexpr.
`#4147 <https://github.com/pybind/pybind11/pull/4147>`_
* Optimize unpacking_collector when processing ``arg_v`` arguments.
`#4219 <https://github.com/pybind/pybind11/pull/4219>`_
* Optimize casting C++ object to ``None``.
`#4269 <https://github.com/pybind/pybind11/pull/4269>`_
Build system improvements:
* CMake: revert overwrite behavior, now opt-in with ``PYBIND11_PYTHONLIBS_OVERRWRITE OFF``.
`#4195 <https://github.com/pybind/pybind11/pull/4195>`_
* Include a pkg-config file when installing pybind11, such as in the Python
package.
`#4077 <https://github.com/pybind/pybind11/pull/4077>`_
* Avoid stripping debug symbols when ``CMAKE_BUILD_TYPE`` is set to ``DEBUG``
instead of ``Debug``.
`#4078 <https://github.com/pybind/pybind11/pull/4078>`_
* Followup to `#3948 <https://github.com/pybind/pybind11/pull/3948>`_, fixing vcpkg again.
`#4123 <https://github.com/pybind/pybind11/pull/4123>`_
Version 2.10.0 (Jul 15, 2022)
-----------------------------

12
include/pybind11/cast.h
View File

@ -248,7 +248,7 @@ public:
return false;
}
static handle cast(T, return_value_policy /* policy */, handle /* parent */) {
return none().inc_ref();
return none().release();
}
PYBIND11_TYPE_CASTER(T, const_name("None"));
};
@ -291,7 +291,7 @@ public:
if (ptr) {
return capsule(ptr).release();
}
return none().inc_ref();
return none().release();
}
template <typename T>
@ -537,7 +537,7 @@ public:
static handle cast(const CharT *src, return_value_policy policy, handle parent) {
if (src == nullptr) {
return pybind11::none().inc_ref();
return pybind11::none().release();
}
return StringCaster::cast(StringType(src), policy, parent);
}
@ -1179,11 +1179,9 @@ enable_if_t<cast_is_temporary_value_reference<T>::value, T> cast_safe(object &&)
pybind11_fail("Internal error: cast_safe fallback invoked");
}
template <typename T>
enable_if_t<std::is_same<void, intrinsic_t<T>>::value, void> cast_safe(object &&) {}
enable_if_t<std::is_void<T>::value, void> cast_safe(object &&) {}
template <typename T>
enable_if_t<detail::none_of<cast_is_temporary_value_reference<T>,
std::is_same<void, intrinsic_t<T>>>::value,
T>
enable_if_t<detail::none_of<cast_is_temporary_value_reference<T>, std::is_void<T>>::value, T>
cast_safe(object &&o) {
return pybind11::cast<T>(std::move(o));
}

32
include/pybind11/detail/common.h
View File

@ -96,13 +96,10 @@
#endif
#if !defined(PYBIND11_EXPORT_EXCEPTION)
# ifdef __MINGW32__
// workaround for:
// error: 'dllexport' implies default visibility, but xxx has already been declared with a
// different visibility
# define PYBIND11_EXPORT_EXCEPTION
# else
# if defined(__apple_build_version__)
# define PYBIND11_EXPORT_EXCEPTION PYBIND11_EXPORT
# else
# define PYBIND11_EXPORT_EXCEPTION
# endif
#endif
@ -205,11 +202,8 @@
# endif
#endif
#if defined(__cpp_lib_char8_t) && __cpp_lib_char8_t >= 201811L
# define PYBIND11_HAS_U8STRING
#endif
#include <Python.h>
// Reminder: WITH_THREAD is always defined if PY_VERSION_HEX >= 0x03070000
#if PY_VERSION_HEX < 0x03060000
# error "PYTHON < 3.6 IS UNSUPPORTED. pybind11 v2.9 was the last to support Python 2 and 3.5."
#endif
@ -233,6 +227,10 @@
# undef copysign
#endif
#if defined(PYPY_VERSION) && !defined(PYBIND11_SIMPLE_GIL_MANAGEMENT)
# define PYBIND11_SIMPLE_GIL_MANAGEMENT
#endif
#if defined(_MSC_VER)
# if defined(PYBIND11_DEBUG_MARKER)
# define _DEBUG
@ -259,6 +257,11 @@
# endif
#endif
// Must be after including <version> or one of the other headers specified by the standard
#if defined(__cpp_lib_char8_t) && __cpp_lib_char8_t >= 201811L
# define PYBIND11_HAS_U8STRING
#endif
// #define PYBIND11_STR_LEGACY_PERMISSIVE
// If DEFINED, pybind11::str can hold PyUnicodeObject or PyBytesObject
// (probably surprising and never documented, but this was the
@ -898,12 +901,6 @@ using expand_side_effects = bool[];
PYBIND11_NAMESPACE_END(detail)
#if defined(_MSC_VER)
# pragma warning(push)
# pragma warning(disable : 4275)
// warning C4275: An exported class was derived from a class that wasn't exported.
// Can be ignored when derived from a STL class.
#endif
/// C++ bindings of builtin Python exceptions
class PYBIND11_EXPORT_EXCEPTION builtin_exception : public std::runtime_error {
public:
@ -911,9 +908,6 @@ public:
/// Set the error using the Python C API
virtual void set_error() const = 0;
};
#if defined(_MSC_VER)
# pragma warning(pop)
#endif
#define PYBIND11_RUNTIME_EXCEPTION(name, type) \
class PYBIND11_EXPORT_EXCEPTION name : public builtin_exception { \

47
include/pybind11/detail/internals.h
View File

@ -9,6 +9,12 @@
#pragma once
#include "common.h"
#if defined(WITH_THREAD) && defined(PYBIND11_SIMPLE_GIL_MANAGEMENT)
# include "../gil.h"
#endif
#include "../pytypes.h"
#include <exception>
@ -37,6 +43,8 @@ using ExceptionTranslator = void (*)(std::exception_ptr);
PYBIND11_NAMESPACE_BEGIN(detail)
constexpr const char *internals_function_record_capsule_name = "pybind11_function_record_capsule";
// Forward declarations
inline PyTypeObject *make_static_property_type();
inline PyTypeObject *make_default_metaclass();
@ -49,7 +57,7 @@ inline PyObject *make_object_base_type(PyTypeObject *metaclass);
// `Py_LIMITED_API` anyway.
# if PYBIND11_INTERNALS_VERSION > 4
# define PYBIND11_TLS_KEY_REF Py_tss_t &
# ifdef __GNUC__
# if defined(__GNUC__) && !defined(__INTEL_COMPILER)
// Clang on macOS warns due to `Py_tss_NEEDS_INIT` not specifying an initializer
// for every field.
# define PYBIND11_TLS_KEY_INIT(var) \
@ -169,11 +177,23 @@ struct internals {
PyTypeObject *default_metaclass;
PyObject *instance_base;
#if defined(WITH_THREAD)
// Unused if PYBIND11_SIMPLE_GIL_MANAGEMENT is defined:
PYBIND11_TLS_KEY_INIT(tstate)
# if PYBIND11_INTERNALS_VERSION > 4
PYBIND11_TLS_KEY_INIT(loader_life_support_tls_key)
# endif // PYBIND11_INTERNALS_VERSION > 4
// Unused if PYBIND11_SIMPLE_GIL_MANAGEMENT is defined:
PyInterpreterState *istate = nullptr;
# if PYBIND11_INTERNALS_VERSION > 4
// Note that we have to use a std::string to allocate memory to ensure a unique address
// We want unique addresses since we use pointer equality to compare function records
std::string function_record_capsule_name = internals_function_record_capsule_name;
# endif
internals() = default;
internals(const internals &other) = delete;
internals &operator=(const internals &other) = delete;
~internals() {
# if PYBIND11_INTERNALS_VERSION > 4
PYBIND11_TLS_FREE(loader_life_support_tls_key);
@ -408,6 +428,10 @@ PYBIND11_NOINLINE internals &get_internals() {
return **internals_pp;
}
#if defined(WITH_THREAD)
# if defined(PYBIND11_SIMPLE_GIL_MANAGEMENT)
gil_scoped_acquire gil;
# else
// Ensure that the GIL is held since we will need to make Python calls.
// Cannot use py::gil_scoped_acquire here since that constructor calls get_internals.
struct gil_scoped_acquire_local {
@ -417,6 +441,8 @@ PYBIND11_NOINLINE internals &get_internals() {
~gil_scoped_acquire_local() { PyGILState_Release(state); }
const PyGILState_STATE state;
} gil;
# endif
#endif
error_scope err_scope;
PYBIND11_STR_TYPE id(PYBIND11_INTERNALS_ID);
@ -534,6 +560,25 @@ const char *c_str(Args &&...args) {
return strings.front().c_str();
}
inline const char *get_function_record_capsule_name() {
#if PYBIND11_INTERNALS_VERSION > 4
return get_internals().function_record_capsule_name.c_str();
#else
return nullptr;
#endif
}
// Determine whether or not the following capsule contains a pybind11 function record.
// Note that we use `internals` to make sure that only ABI compatible records are touched.
//
// This check is currently used in two places:
// - An important optimization in functional.h to avoid overhead in C++ -> Python -> C++
// - The sibling feature of cpp_function to allow overloads
inline bool is_function_record_capsule(const capsule &cap) {
// Pointer equality as we rely on internals() to ensure unique pointers
return cap.name() == get_function_record_capsule_name();
}
PYBIND11_NAMESPACE_END(detail)
/// Returns a named pointer that is shared among all extension modules (using the same

703
include/pybind11/eigen.h
View File

@ -9,705 +9,4 @@
#pragma once
/* HINT: To suppress warnings originating from the Eigen headers, use -isystem.
See also:
https://stackoverflow.com/questions/2579576/i-dir-vs-isystem-dir
https://stackoverflow.com/questions/1741816/isystem-for-ms-visual-studio-c-compiler
*/
#include "numpy.h"
// The C4127 suppression was introduced for Eigen 3.4.0. In theory we could
// make it version specific, or even remove it later, but considering that
// 1. C4127 is generally far more distracting than useful for modern template code, and
// 2. we definitely want to ignore any MSVC warnings originating from Eigen code,
// it is probably best to keep this around indefinitely.
#if defined(_MSC_VER)
# pragma warning(push)
# pragma warning(disable : 4127) // C4127: conditional expression is constant
# pragma warning(disable : 5054) // https://github.com/pybind/pybind11/pull/3741
// C5054: operator '&': deprecated between enumerations of different types
#elif defined(__MINGW32__)
# pragma GCC diagnostic push
# pragma GCC diagnostic ignored "-Wmaybe-uninitialized"
#endif
#include <Eigen/Core>
#include <Eigen/SparseCore>
#if defined(_MSC_VER)
# pragma warning(pop)
#elif defined(__MINGW32__)
# pragma GCC diagnostic pop
#endif
// Eigen prior to 3.2.7 doesn't have proper move constructors--but worse, some classes get implicit
// move constructors that break things. We could detect this an explicitly copy, but an extra copy
// of matrices seems highly undesirable.
static_assert(EIGEN_VERSION_AT_LEAST(3, 2, 7),
"Eigen support in pybind11 requires Eigen >= 3.2.7");
PYBIND11_NAMESPACE_BEGIN(PYBIND11_NAMESPACE)
// Provide a convenience alias for easier pass-by-ref usage with fully dynamic strides:
using EigenDStride = Eigen::Stride<Eigen::Dynamic, Eigen::Dynamic>;
template <typename MatrixType>
using EigenDRef = Eigen::Ref<MatrixType, 0, EigenDStride>;
template <typename MatrixType>
using EigenDMap = Eigen::Map<MatrixType, 0, EigenDStride>;
PYBIND11_NAMESPACE_BEGIN(detail)
#if EIGEN_VERSION_AT_LEAST(3, 3, 0)
using EigenIndex = Eigen::Index;
template <typename Scalar, int Flags, typename StorageIndex>
using EigenMapSparseMatrix = Eigen::Map<Eigen::SparseMatrix<Scalar, Flags, StorageIndex>>;
#else
using EigenIndex = EIGEN_DEFAULT_DENSE_INDEX_TYPE;
template <typename Scalar, int Flags, typename StorageIndex>
using EigenMapSparseMatrix = Eigen::MappedSparseMatrix<Scalar, Flags, StorageIndex>;
#endif
// Matches Eigen::Map, Eigen::Ref, blocks, etc:
template <typename T>
using is_eigen_dense_map = all_of<is_template_base_of<Eigen::DenseBase, T>,
std::is_base_of<Eigen::MapBase<T, Eigen::ReadOnlyAccessors>, T>>;
template <typename T>
using is_eigen_mutable_map = std::is_base_of<Eigen::MapBase<T, Eigen::WriteAccessors>, T>;
template <typename T>
using is_eigen_dense_plain
= all_of<negation<is_eigen_dense_map<T>>, is_template_base_of<Eigen::PlainObjectBase, T>>;
template <typename T>
using is_eigen_sparse = is_template_base_of<Eigen::SparseMatrixBase, T>;
// Test for objects inheriting from EigenBase<Derived> that aren't captured by the above. This
// basically covers anything that can be assigned to a dense matrix but that don't have a typical
// matrix data layout that can be copied from their .data(). For example, DiagonalMatrix and
// SelfAdjointView fall into this category.
template <typename T>
using is_eigen_other
= all_of<is_template_base_of<Eigen::EigenBase, T>,
negation<any_of<is_eigen_dense_map<T>, is_eigen_dense_plain<T>, is_eigen_sparse<T>>>>;
// Captures numpy/eigen conformability status (returned by EigenProps::conformable()):
template <bool EigenRowMajor>
struct EigenConformable {
bool conformable = false;
EigenIndex rows = 0, cols = 0;
EigenDStride stride{0, 0}; // Only valid if negativestrides is false!
bool negativestrides = false; // If true, do not use stride!
// NOLINTNEXTLINE(google-explicit-constructor)
EigenConformable(bool fits = false) : conformable{fits} {}
// Matrix type:
EigenConformable(EigenIndex r, EigenIndex c, EigenIndex rstride, EigenIndex cstride)
: conformable{true}, rows{r}, cols{c},
// TODO: when Eigen bug #747 is fixed, remove the tests for non-negativity.
// http://eigen.tuxfamily.org/bz/show_bug.cgi?id=747
stride{EigenRowMajor ? (rstride > 0 ? rstride : 0)
: (cstride > 0 ? cstride : 0) /* outer stride */,
EigenRowMajor ? (cstride > 0 ? cstride : 0)
: (rstride > 0 ? rstride : 0) /* inner stride */},
negativestrides{rstride < 0 || cstride < 0} {}
// Vector type:
EigenConformable(EigenIndex r, EigenIndex c, EigenIndex stride)
: EigenConformable(r, c, r == 1 ? c * stride : stride, c == 1 ? r : r * stride) {}
template <typename props>
bool stride_compatible() const {
// To have compatible strides, we need (on both dimensions) one of fully dynamic strides,
// matching strides, or a dimension size of 1 (in which case the stride value is
// irrelevant). Alternatively, if any dimension size is 0, the strides are not relevant
// (and numpy ≥ 1.23 sets the strides to 0 in that case, so we need to check explicitly).
if (negativestrides) {
return false;
}
if (rows == 0 || cols == 0) {
return true;
}
return (props::inner_stride == Eigen::Dynamic || props::inner_stride == stride.inner()
|| (EigenRowMajor ? cols : rows) == 1)
&& (props::outer_stride == Eigen::Dynamic || props::outer_stride == stride.outer()
|| (EigenRowMajor ? rows : cols) == 1);
}
// NOLINTNEXTLINE(google-explicit-constructor)
operator bool() const { return conformable; }
};
template <typename Type>
struct eigen_extract_stride {
using type = Type;
};
template <typename PlainObjectType, int MapOptions, typename StrideType>
struct eigen_extract_stride<Eigen::Map<PlainObjectType, MapOptions, StrideType>> {
using type = StrideType;
};
template <typename PlainObjectType, int Options, typename StrideType>
struct eigen_extract_stride<Eigen::Ref<PlainObjectType, Options, StrideType>> {
using type = StrideType;
};
// Helper struct for extracting information from an Eigen type
template <typename Type_>
struct EigenProps {
using Type = Type_;
using Scalar = typename Type::Scalar;
using StrideType = typename eigen_extract_stride<Type>::type;
static constexpr EigenIndex rows = Type::RowsAtCompileTime, cols = Type::ColsAtCompileTime,
size = Type::SizeAtCompileTime;
static constexpr bool row_major = Type::IsRowMajor,
vector
= Type::IsVectorAtCompileTime, // At least one dimension has fixed size 1
fixed_rows = rows != Eigen::Dynamic, fixed_cols = cols != Eigen::Dynamic,
fixed = size != Eigen::Dynamic, // Fully-fixed size
dynamic = !fixed_rows && !fixed_cols; // Fully-dynamic size
template <EigenIndex i, EigenIndex ifzero>
using if_zero = std::integral_constant<EigenIndex, i == 0 ? ifzero : i>;
static constexpr EigenIndex inner_stride
= if_zero<StrideType::InnerStrideAtCompileTime, 1>::value,
outer_stride = if_zero < StrideType::OuterStrideAtCompileTime,
vector ? size
: row_major ? cols
: rows > ::value;
static constexpr bool dynamic_stride
= inner_stride == Eigen::Dynamic && outer_stride == Eigen::Dynamic;
static constexpr bool requires_row_major
= !dynamic_stride && !vector && (row_major ? inner_stride : outer_stride) == 1;
static constexpr bool requires_col_major
= !dynamic_stride && !vector && (row_major ? outer_stride : inner_stride) == 1;
// Takes an input array and determines whether we can make it fit into the Eigen type. If
// the array is a vector, we attempt to fit it into either an Eigen 1xN or Nx1 vector
// (preferring the latter if it will fit in either, i.e. for a fully dynamic matrix type).
static EigenConformable<row_major> conformable(const array &a) {
const auto dims = a.ndim();
if (dims < 1 || dims > 2) {
return false;
}
if (dims == 2) { // Matrix type: require exact match (or dynamic)
EigenIndex np_rows = a.shape(0), np_cols = a.shape(1),
np_rstride = a.strides(0) / static_cast<ssize_t>(sizeof(Scalar)),
np_cstride = a.strides(1) / static_cast<ssize_t>(sizeof(Scalar));
if ((PYBIND11_SILENCE_MSVC_C4127(fixed_rows) && np_rows != rows)
|| (PYBIND11_SILENCE_MSVC_C4127(fixed_cols) && np_cols != cols)) {
return false;
}
return {np_rows, np_cols, np_rstride, np_cstride};
}
// Otherwise we're storing an n-vector. Only one of the strides will be used, but
// whichever is used, we want the (single) numpy stride value.
const EigenIndex n = a.shape(0),
stride = a.strides(0) / static_cast<ssize_t>(sizeof(Scalar));
if (vector) { // Eigen type is a compile-time vector
if (PYBIND11_SILENCE_MSVC_C4127(fixed) && size != n) {
return false; // Vector size mismatch
}
return {rows == 1 ? 1 : n, cols == 1 ? 1 : n, stride};
}
if (fixed) {
// The type has a fixed size, but is not a vector: abort
return false;
}
if (fixed_cols) {
// Since this isn't a vector, cols must be != 1. We allow this only if it exactly
// equals the number of elements (rows is Dynamic, and so 1 row is allowed).
if (cols != n) {
return false;
}
return {1, n, stride};
} // Otherwise it's either fully dynamic, or column dynamic; both become a column vector
if (PYBIND11_SILENCE_MSVC_C4127(fixed_rows) && rows != n) {
return false;
}
return {n, 1, stride};
}
static constexpr bool show_writeable
= is_eigen_dense_map<Type>::value && is_eigen_mutable_map<Type>::value;
static constexpr bool show_order = is_eigen_dense_map<Type>::value;
static constexpr bool show_c_contiguous = show_order && requires_row_major;
static constexpr bool show_f_contiguous
= !show_c_contiguous && show_order && requires_col_major;
static constexpr auto descriptor
= const_name("numpy.ndarray[") + npy_format_descriptor<Scalar>::name + const_name("[")
+ const_name<fixed_rows>(const_name<(size_t) rows>(), const_name("m")) + const_name(", ")
+ const_name<fixed_cols>(const_name<(size_t) cols>(), const_name("n")) + const_name("]")
+
// For a reference type (e.g. Ref<MatrixXd>) we have other constraints that might need to
// be satisfied: writeable=True (for a mutable reference), and, depending on the map's
// stride options, possibly f_contiguous or c_contiguous. We include them in the
// descriptor output to provide some hint as to why a TypeError is occurring (otherwise
// it can be confusing to see that a function accepts a 'numpy.ndarray[float64[3,2]]' and
// an error message that you *gave* a numpy.ndarray of the right type and dimensions.
const_name<show_writeable>(", flags.writeable", "")
+ const_name<show_c_contiguous>(", flags.c_contiguous", "")
+ const_name<show_f_contiguous>(", flags.f_contiguous", "") + const_name("]");
};
// Casts an Eigen type to numpy array. If given a base, the numpy array references the src data,
// otherwise it'll make a copy. writeable lets you turn off the writeable flag for the array.
template <typename props>
handle
eigen_array_cast(typename props::Type const &src, handle base = handle(), bool writeable = true) {
constexpr ssize_t elem_size = sizeof(typename props::Scalar);
array a;
if (props::vector) {
a = array({src.size()}, {elem_size * src.innerStride()}, src.data(), base);
} else {
a = array({src.rows(), src.cols()},
{elem_size * src.rowStride(), elem_size * src.colStride()},
src.data(),
base);
}
if (!writeable) {
array_proxy(a.ptr())->flags &= ~detail::npy_api::NPY_ARRAY_WRITEABLE_;
}
return a.release();
}
// Takes an lvalue ref to some Eigen type and a (python) base object, creating a numpy array that
// reference the Eigen object's data with `base` as the python-registered base class (if omitted,
// the base will be set to None, and lifetime management is up to the caller). The numpy array is
// non-writeable if the given type is const.
template <typename props, typename Type>
handle eigen_ref_array(Type &src, handle parent = none()) {
// none here is to get past array's should-we-copy detection, which currently always
// copies when there is no base. Setting the base to None should be harmless.
return eigen_array_cast<props>(src, parent, !std::is_const<Type>::value);
}
// Takes a pointer to some dense, plain Eigen type, builds a capsule around it, then returns a
// numpy array that references the encapsulated data with a python-side reference to the capsule to
// tie its destruction to that of any dependent python objects. Const-ness is determined by
// whether or not the Type of the pointer given is const.
template <typename props, typename Type, typename = enable_if_t<is_eigen_dense_plain<Type>::value>>
handle eigen_encapsulate(Type *src) {
capsule base(src, [](void *o) { delete static_cast<Type *>(o); });
return eigen_ref_array<props>(*src, base);
}
// Type caster for regular, dense matrix types (e.g. MatrixXd), but not maps/refs/etc. of dense
// types.
template <typename Type>
struct type_caster<Type, enable_if_t<is_eigen_dense_plain<Type>::value>> {
using Scalar = typename Type::Scalar;
using props = EigenProps<Type>;
bool load(handle src, bool convert) {
// If we're in no-convert mode, only load if given an array of the correct type
if (!convert && !isinstance<array_t<Scalar>>(src)) {
return false;
}
// Coerce into an array, but don't do type conversion yet; the copy below handles it.
auto buf = array::ensure(src);
if (!buf) {
return false;
}
auto dims = buf.ndim();
if (dims < 1 || dims > 2) {
return false;
}
auto fits = props::conformable(buf);
if (!fits) {
return false;
}
// Allocate the new type, then build a numpy reference into it
value = Type(fits.rows, fits.cols);
auto ref = reinterpret_steal<array>(eigen_ref_array<props>(value));
if (dims == 1) {
ref = ref.squeeze();
} else if (ref.ndim() == 1) {
buf = buf.squeeze();
}
int result = detail::npy_api::get().PyArray_CopyInto_(ref.ptr(), buf.ptr());
if (result < 0) { // Copy failed!
PyErr_Clear();
return false;
}
return true;
}
private:
// Cast implementation
template <typename CType>
static handle cast_impl(CType *src, return_value_policy policy, handle parent) {
switch (policy) {
case return_value_policy::take_ownership:
case return_value_policy::automatic:
return eigen_encapsulate<props>(src);
case return_value_policy::move:
return eigen_encapsulate<props>(new CType(std::move(*src)));
case return_value_policy::copy:
return eigen_array_cast<props>(*src);
case return_value_policy::reference:
case return_value_policy::automatic_reference:
return eigen_ref_array<props>(*src);
case return_value_policy::reference_internal:
return eigen_ref_array<props>(*src, parent);
default:
throw cast_error("unhandled return_value_policy: should not happen!");
};
}
public:
// Normal returned non-reference, non-const value:
static handle cast(Type &&src, return_value_policy /* policy */, handle parent) {
return cast_impl(&src, return_value_policy::move, parent);
}
// If you return a non-reference const, we mark the numpy array readonly:
static handle cast(const Type &&src, return_value_policy /* policy */, handle parent) {
return cast_impl(&src, return_value_policy::move, parent);
}
// lvalue reference return; default (automatic) becomes copy
static handle cast(Type &src, return_value_policy policy, handle parent) {
if (policy == return_value_policy::automatic
|| policy == return_value_policy::automatic_reference) {
policy = return_value_policy::copy;
}
return cast_impl(&src, policy, parent);
}
// const lvalue reference return; default (automatic) becomes copy
static handle cast(const Type &src, return_value_policy policy, handle parent) {
if (policy == return_value_policy::automatic
|| policy == return_value_policy::automatic_reference) {
policy = return_value_policy::copy;
}
return cast(&src, policy, parent);
}
// non-const pointer return
static handle cast(Type *src, return_value_policy policy, handle parent) {
return cast_impl(src, policy, parent);
}
// const pointer return
static handle cast(const Type *src, return_value_policy policy, handle parent) {
return cast_impl(src, policy, parent);
}
static constexpr auto name = props::descriptor;
// NOLINTNEXTLINE(google-explicit-constructor)
operator Type *() { return &value; }
// NOLINTNEXTLINE(google-explicit-constructor)
operator Type &() { return value; }
// NOLINTNEXTLINE(google-explicit-constructor)
operator Type &&() && { return std::move(value); }
template <typename T>
using cast_op_type = movable_cast_op_type<T>;
private:
Type value;
};
// Base class for casting reference/map/block/etc. objects back to python.
template <typename MapType>
struct eigen_map_caster {
private:
using props = EigenProps<MapType>;
public:
// Directly referencing a ref/map's data is a bit dangerous (whatever the map/ref points to has
// to stay around), but we'll allow it under the assumption that you know what you're doing
// (and have an appropriate keep_alive in place). We return a numpy array pointing directly at
// the ref's data (The numpy array ends up read-only if the ref was to a const matrix type.)
// Note that this means you need to ensure you don't destroy the object in some other way (e.g.
// with an appropriate keep_alive, or with a reference to a statically allocated matrix).
static handle cast(const MapType &src, return_value_policy policy, handle parent) {
switch (policy) {
case return_value_policy::copy:
return eigen_array_cast<props>(src);
case return_value_policy::reference_internal:
return eigen_array_cast<props>(src, parent, is_eigen_mutable_map<MapType>::value);
case return_value_policy::reference:
case return_value_policy::automatic:
case return_value_policy::automatic_reference:
return eigen_array_cast<props>(src, none(), is_eigen_mutable_map<MapType>::value);
default:
// move, take_ownership don't make any sense for a ref/map:
pybind11_fail("Invalid return_value_policy for Eigen Map/Ref/Block type");
}
}
static constexpr auto name = props::descriptor;
// Explicitly delete these: support python -> C++ conversion on these (i.e. these can be return
// types but not bound arguments). We still provide them (with an explicitly delete) so that
// you end up here if you try anyway.
bool load(handle, bool) = delete;
operator MapType() = delete;
template <typename>
using cast_op_type = MapType;
};
// We can return any map-like object (but can only load Refs, specialized next):
template <typename Type>
struct type_caster<Type, enable_if_t<is_eigen_dense_map<Type>::value>> : eigen_map_caster<Type> {};
// Loader for Ref<...> arguments. See the documentation for info on how to make this work without
// copying (it requires some extra effort in many cases).
template <typename PlainObjectType, typename StrideType>
struct type_caster<
Eigen::Ref<PlainObjectType, 0, StrideType>,
enable_if_t<is_eigen_dense_map<Eigen::Ref<PlainObjectType, 0, StrideType>>::value>>
: public eigen_map_caster<Eigen::Ref<PlainObjectType, 0, StrideType>> {
private:
using Type = Eigen::Ref<PlainObjectType, 0, StrideType>;
using props = EigenProps<Type>;
using Scalar = typename props::Scalar;
using MapType = Eigen::Map<PlainObjectType, 0, StrideType>;
using Array
= array_t<Scalar,
array::forcecast
| ((props::row_major ? props::inner_stride : props::outer_stride) == 1
? array::c_style
: (props::row_major ? props::outer_stride : props::inner_stride) == 1
? array::f_style
: 0)>;
static constexpr bool need_writeable = is_eigen_mutable_map<Type>::value;
// Delay construction (these have no default constructor)
std::unique_ptr<MapType> map;
std::unique_ptr<Type> ref;
// Our array. When possible, this is just a numpy array pointing to the source data, but
// sometimes we can't avoid copying (e.g. input is not a numpy array at all, has an
// incompatible layout, or is an array of a type that needs to be converted). Using a numpy
// temporary (rather than an Eigen temporary) saves an extra copy when we need both type
// conversion and storage order conversion. (Note that we refuse to use this temporary copy
// when loading an argument for a Ref<M> with M non-const, i.e. a read-write reference).
Array copy_or_ref;
public:
bool load(handle src, bool convert) {
// First check whether what we have is already an array of the right type. If not, we
// can't avoid a copy (because the copy is also going to do type conversion).
bool need_copy = !isinstance<Array>(src);
EigenConformable<props::row_major> fits;
if (!need_copy) {
// We don't need a converting copy, but we also need to check whether the strides are
// compatible with the Ref's stride requirements
auto aref = reinterpret_borrow<Array>(src);
if (aref && (!need_writeable || aref.writeable())) {
fits = props::conformable(aref);
if (!fits) {
return false; // Incompatible dimensions
}
if (!fits.template stride_compatible<props>()) {
need_copy = true;
} else {
copy_or_ref = std::move(aref);
}
} else {
need_copy = true;
}
}
if (need_copy) {
// We need to copy: If we need a mutable reference, or we're not supposed to convert
// (either because we're in the no-convert overload pass, or because we're explicitly
// instructed not to copy (via `py::arg().noconvert()`) we have to fail loading.
if (!convert || need_writeable) {
return false;
}
Array copy = Array::ensure(src);
if (!copy) {
return false;
}
fits = props::conformable(copy);
if (!fits || !fits.template stride_compatible<props>()) {
return false;
}
copy_or_ref = std::move(copy);
loader_life_support::add_patient(copy_or_ref);
}
ref.reset();
map.reset(new MapType(data(copy_or_ref),
fits.rows,
fits.cols,
make_stride(fits.stride.outer(), fits.stride.inner())));
ref.reset(new Type(*map));
return true;
}
// NOLINTNEXTLINE(google-explicit-constructor)
operator Type *() { return ref.get(); }
// NOLINTNEXTLINE(google-explicit-constructor)
operator Type &() { return *ref; }
template <typename _T>
using cast_op_type = pybind11::detail::cast_op_type<_T>;
private:
template <typename T = Type, enable_if_t<is_eigen_mutable_map<T>::value, int> = 0>
Scalar *data(Array &a) {
return a.mutable_data();
}
template <typename T = Type, enable_if_t<!is_eigen_mutable_map<T>::value, int> = 0>
const Scalar *data(Array &a) {
return a.data();
}
// Attempt to figure out a constructor of `Stride` that will work.
// If both strides are fixed, use a default constructor:
template <typename S>
using stride_ctor_default = bool_constant<S::InnerStrideAtCompileTime != Eigen::Dynamic
&& S::OuterStrideAtCompileTime != Eigen::Dynamic
&& std::is_default_constructible<S>::value>;
// Otherwise, if there is a two-index constructor, assume it is (outer,inner) like
// Eigen::Stride, and use it:
template <typename S>
using stride_ctor_dual
= bool_constant<!stride_ctor_default<S>::value
&& std::is_constructible<S, EigenIndex, EigenIndex>::value>;
// Otherwise, if there is a one-index constructor, and just one of the strides is dynamic, use
// it (passing whichever stride is dynamic).
template <typename S>
using stride_ctor_outer
= bool_constant<!any_of<stride_ctor_default<S>, stride_ctor_dual<S>>::value
&& S::OuterStrideAtCompileTime == Eigen::Dynamic
&& S::InnerStrideAtCompileTime != Eigen::Dynamic
&& std::is_constructible<S, EigenIndex>::value>;
template <typename S>
using stride_ctor_inner
= bool_constant<!any_of<stride_ctor_default<S>, stride_ctor_dual<S>>::value
&& S::InnerStrideAtCompileTime == Eigen::Dynamic
&& S::OuterStrideAtCompileTime != Eigen::Dynamic
&& std::is_constructible<S, EigenIndex>::value>;
template <typename S = StrideType, enable_if_t<stride_ctor_default<S>::value, int> = 0>
static S make_stride(EigenIndex, EigenIndex) {
return S();
}
template <typename S = StrideType, enable_if_t<stride_ctor_dual<S>::value, int> = 0>
static S make_stride(EigenIndex outer, EigenIndex inner) {
return S(outer, inner);
}
template <typename S = StrideType, enable_if_t<stride_ctor_outer<S>::value, int> = 0>
static S make_stride(EigenIndex outer, EigenIndex) {
return S(outer);
}
template <typename S = StrideType, enable_if_t<stride_ctor_inner<S>::value, int> = 0>
static S make_stride(EigenIndex, EigenIndex inner) {
return S(inner);
}
};
// type_caster for special matrix types (e.g. DiagonalMatrix), which are EigenBase, but not
// EigenDense (i.e. they don't have a data(), at least not with the usual matrix layout).
// load() is not supported, but we can cast them into the python domain by first copying to a
// regular Eigen::Matrix, then casting that.
template <typename Type>
struct type_caster<Type, enable_if_t<is_eigen_other<Type>::value>> {
protected:
using Matrix
= Eigen::Matrix<typename Type::Scalar, Type::RowsAtCompileTime, Type::ColsAtCompileTime>;
using props = EigenProps<Matrix>;
public:
static handle cast(const Type &src, return_value_policy /* policy */, handle /* parent */) {
handle h = eigen_encapsulate<props>(new Matrix(src));
return h;
}
static handle cast(const Type *src, return_value_policy policy, handle parent) {
return cast(*src, policy, parent);
}
static constexpr auto name = props::descriptor;
// Explicitly delete these: support python -> C++ conversion on these (i.e. these can be return
// types but not bound arguments). We still provide them (with an explicitly delete) so that
// you end up here if you try anyway.
bool load(handle, bool) = delete;
operator Type() = delete;
template <typename>
using cast_op_type = Type;
};
template <typename Type>
struct type_caster<Type, enable_if_t<is_eigen_sparse<Type>::value>> {
using Scalar = typename Type::Scalar;
using StorageIndex = remove_reference_t<decltype(*std::declval<Type>().outerIndexPtr())>;
using Index = typename Type::Index;
static constexpr bool rowMajor = Type::IsRowMajor;
bool load(handle src, bool) {
if (!src) {
return false;
}
auto obj = reinterpret_borrow<object>(src);
object sparse_module = module_::import("scipy.sparse");
object matrix_type = sparse_module.attr(rowMajor ? "csr_matrix" : "csc_matrix");
if (!type::handle_of(obj).is(matrix_type)) {
try {
obj = matrix_type(obj);
} catch (const error_already_set &) {
return false;
}
}
auto values = array_t<Scalar>((object) obj.attr("data"));
auto innerIndices = array_t<StorageIndex>((object) obj.attr("indices"));
auto outerIndices = array_t<StorageIndex>((object) obj.attr("indptr"));
auto shape = pybind11::tuple((pybind11::object) obj.attr("shape"));
auto nnz = obj.attr("nnz").cast<Index>();
if (!values || !innerIndices || !outerIndices) {
return false;
}
value = EigenMapSparseMatrix<Scalar,
Type::Flags &(Eigen::RowMajor | Eigen::ColMajor),
StorageIndex>(shape[0].cast<Index>(),
shape[1].cast<Index>(),
std::move(nnz),
outerIndices.mutable_data(),
innerIndices.mutable_data(),
values.mutable_data());
return true;
}
static handle cast(const Type &src, return_value_policy /* policy */, handle /* parent */) {
const_cast<Type &>(src).makeCompressed();
object matrix_type
= module_::import("scipy.sparse").attr(rowMajor ? "csr_matrix" : "csc_matrix");
array data(src.nonZeros(), src.valuePtr());
array outerIndices((rowMajor ? src.rows() : src.cols()) + 1, src.outerIndexPtr());
array innerIndices(src.nonZeros(), src.innerIndexPtr());
return matrix_type(pybind11::make_tuple(
std::move(data), std::move(innerIndices), std::move(outerIndices)),
pybind11::make_tuple(src.rows(), src.cols()))
.release();
}
PYBIND11_TYPE_CASTER(Type,
const_name<(Type::IsRowMajor) != 0>("scipy.sparse.csr_matrix[",
"scipy.sparse.csc_matrix[")
+ npy_format_descriptor<Scalar>::name + const_name("]"));
};
PYBIND11_NAMESPACE_END(detail)
PYBIND11_NAMESPACE_END(PYBIND11_NAMESPACE)
#include "eigen/matrix.h"

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/*
pybind11/eigen/matrix.h: Transparent conversion for dense and sparse Eigen matrices
Copyright (c) 2016 Wenzel Jakob <wenzel.jakob@epfl.ch>
All rights reserved. Use of this source code is governed by a
BSD-style license that can be found in the LICENSE file.
*/
#pragma once
#include "../numpy.h"
/* HINT: To suppress warnings originating from the Eigen headers, use -isystem.
See also:
https://stackoverflow.com/questions/2579576/i-dir-vs-isystem-dir
https://stackoverflow.com/questions/1741816/isystem-for-ms-visual-studio-c-compiler
*/
// The C4127 suppression was introduced for Eigen 3.4.0. In theory we could
// make it version specific, or even remove it later, but considering that
// 1. C4127 is generally far more distracting than useful for modern template code, and
// 2. we definitely want to ignore any MSVC warnings originating from Eigen code,
// it is probably best to keep this around indefinitely.
#if defined(_MSC_VER)
# pragma warning(push)
# pragma warning(disable : 4127) // C4127: conditional expression is constant
# pragma warning(disable : 5054) // https://github.com/pybind/pybind11/pull/3741
// C5054: operator '&': deprecated between enumerations of different types
#elif defined(__MINGW32__)
# pragma GCC diagnostic push
# pragma GCC diagnostic ignored "-Wmaybe-uninitialized"
#endif
#include <Eigen/Core>
#include <Eigen/SparseCore>
#if defined(_MSC_VER)
# pragma warning(pop)
#elif defined(__MINGW32__)
# pragma GCC diagnostic pop
#endif
// Eigen prior to 3.2.7 doesn't have proper move constructors--but worse, some classes get implicit
// move constructors that break things. We could detect this an explicitly copy, but an extra copy
// of matrices seems highly undesirable.
static_assert(EIGEN_VERSION_AT_LEAST(3, 2, 7),
"Eigen matrix support in pybind11 requires Eigen >= 3.2.7");
PYBIND11_NAMESPACE_BEGIN(PYBIND11_NAMESPACE)
// Provide a convenience alias for easier pass-by-ref usage with fully dynamic strides:
using EigenDStride = Eigen::Stride<Eigen::Dynamic, Eigen::Dynamic>;
template <typename MatrixType>
using EigenDRef = Eigen::Ref<MatrixType, 0, EigenDStride>;
template <typename MatrixType>
using EigenDMap = Eigen::Map<MatrixType, 0, EigenDStride>;
PYBIND11_NAMESPACE_BEGIN(detail)
#if EIGEN_VERSION_AT_LEAST(3, 3, 0)
using EigenIndex = Eigen::Index;
template <typename Scalar, int Flags, typename StorageIndex>
using EigenMapSparseMatrix = Eigen::Map<Eigen::SparseMatrix<Scalar, Flags, StorageIndex>>;
#else
using EigenIndex = EIGEN_DEFAULT_DENSE_INDEX_TYPE;
template <typename Scalar, int Flags, typename StorageIndex>
using EigenMapSparseMatrix = Eigen::MappedSparseMatrix<Scalar, Flags, StorageIndex>;
#endif
// Matches Eigen::Map, Eigen::Ref, blocks, etc:
template <typename T>
using is_eigen_dense_map = all_of<is_template_base_of<Eigen::DenseBase, T>,
std::is_base_of<Eigen::MapBase<T, Eigen::ReadOnlyAccessors>, T>>;
template <typename T>
using is_eigen_mutable_map = std::is_base_of<Eigen::MapBase<T, Eigen::WriteAccessors>, T>;
template <typename T>
using is_eigen_dense_plain
= all_of<negation<is_eigen_dense_map<T>>, is_template_base_of<Eigen::PlainObjectBase, T>>;
template <typename T>
using is_eigen_sparse = is_template_base_of<Eigen::SparseMatrixBase, T>;
// Test for objects inheriting from EigenBase<Derived> that aren't captured by the above. This
// basically covers anything that can be assigned to a dense matrix but that don't have a typical
// matrix data layout that can be copied from their .data(). For example, DiagonalMatrix and
// SelfAdjointView fall into this category.
template <typename T>
using is_eigen_other
= all_of<is_template_base_of<Eigen::EigenBase, T>,
negation<any_of<is_eigen_dense_map<T>, is_eigen_dense_plain<T>, is_eigen_sparse<T>>>>;
// Captures numpy/eigen conformability status (returned by EigenProps::conformable()):
template <bool EigenRowMajor>
struct EigenConformable {
bool conformable = false;
EigenIndex rows = 0, cols = 0;
EigenDStride stride{0, 0}; // Only valid if negativestrides is false!
bool negativestrides = false; // If true, do not use stride!
// NOLINTNEXTLINE(google-explicit-constructor)
EigenConformable(bool fits = false) : conformable{fits} {}
// Matrix type:
EigenConformable(EigenIndex r, EigenIndex c, EigenIndex rstride, EigenIndex cstride)
: conformable{true}, rows{r}, cols{c},
// TODO: when Eigen bug #747 is fixed, remove the tests for non-negativity.
// http://eigen.tuxfamily.org/bz/show_bug.cgi?id=747
stride{EigenRowMajor ? (rstride > 0 ? rstride : 0)
: (cstride > 0 ? cstride : 0) /* outer stride */,
EigenRowMajor ? (cstride > 0 ? cstride : 0)
: (rstride > 0 ? rstride : 0) /* inner stride */},
negativestrides{rstride < 0 || cstride < 0} {}
// Vector type:
EigenConformable(EigenIndex r, EigenIndex c, EigenIndex stride)
: EigenConformable(r, c, r == 1 ? c * stride : stride, c == 1 ? r : r * stride) {}
template <typename props>
bool stride_compatible() const {
// To have compatible strides, we need (on both dimensions) one of fully dynamic strides,
// matching strides, or a dimension size of 1 (in which case the stride value is
// irrelevant). Alternatively, if any dimension size is 0, the strides are not relevant
// (and numpy ≥ 1.23 sets the strides to 0 in that case, so we need to check explicitly).
if (negativestrides) {
return false;
}
if (rows == 0 || cols == 0) {
return true;
}
return (props::inner_stride == Eigen::Dynamic || props::inner_stride == stride.inner()
|| (EigenRowMajor ? cols : rows) == 1)
&& (props::outer_stride == Eigen::Dynamic || props::outer_stride == stride.outer()
|| (EigenRowMajor ? rows : cols) == 1);
}
// NOLINTNEXTLINE(google-explicit-constructor)
operator bool() const { return conformable; }
};
template <typename Type>
struct eigen_extract_stride {
using type = Type;
};
template <typename PlainObjectType, int MapOptions, typename StrideType>
struct eigen_extract_stride<Eigen::Map<PlainObjectType, MapOptions, StrideType>> {
using type = StrideType;
};
template <typename PlainObjectType, int Options, typename StrideType>
struct eigen_extract_stride<Eigen::Ref<PlainObjectType, Options, StrideType>> {
using type = StrideType;
};
// Helper struct for extracting information from an Eigen type
template <typename Type_>
struct EigenProps {
using Type = Type_;
using Scalar = typename Type::Scalar;
using StrideType = typename eigen_extract_stride<Type>::type;
static constexpr EigenIndex rows = Type::RowsAtCompileTime, cols = Type::ColsAtCompileTime,
size = Type::SizeAtCompileTime;
static constexpr bool row_major = Type::IsRowMajor,
vector
= Type::IsVectorAtCompileTime, // At least one dimension has fixed size 1
fixed_rows = rows != Eigen::Dynamic, fixed_cols = cols != Eigen::Dynamic,
fixed = size != Eigen::Dynamic, // Fully-fixed size
dynamic = !fixed_rows && !fixed_cols; // Fully-dynamic size
template <EigenIndex i, EigenIndex ifzero>
using if_zero = std::integral_constant<EigenIndex, i == 0 ? ifzero : i>;
static constexpr EigenIndex inner_stride
= if_zero<StrideType::InnerStrideAtCompileTime, 1>::value,
outer_stride = if_zero < StrideType::OuterStrideAtCompileTime,
vector ? size
: row_major ? cols
: rows > ::value;
static constexpr bool dynamic_stride
= inner_stride == Eigen::Dynamic && outer_stride == Eigen::Dynamic;
static constexpr bool requires_row_major
= !dynamic_stride && !vector && (row_major ? inner_stride : outer_stride) == 1;
static constexpr bool requires_col_major
= !dynamic_stride && !vector && (row_major ? outer_stride : inner_stride) == 1;
// Takes an input array and determines whether we can make it fit into the Eigen type. If
// the array is a vector, we attempt to fit it into either an Eigen 1xN or Nx1 vector
// (preferring the latter if it will fit in either, i.e. for a fully dynamic matrix type).
static EigenConformable<row_major> conformable(const array &a) {
const auto dims = a.ndim();
if (dims < 1 || dims > 2) {
return false;
}
if (dims == 2) { // Matrix type: require exact match (or dynamic)
EigenIndex np_rows = a.shape(0), np_cols = a.shape(1),
np_rstride = a.strides(0) / static_cast<ssize_t>(sizeof(Scalar)),
np_cstride = a.strides(1) / static_cast<ssize_t>(sizeof(Scalar));
if ((PYBIND11_SILENCE_MSVC_C4127(fixed_rows) && np_rows != rows)
|| (PYBIND11_SILENCE_MSVC_C4127(fixed_cols) && np_cols != cols)) {
return false;
}
return {np_rows, np_cols, np_rstride, np_cstride};
}
// Otherwise we're storing an n-vector. Only one of the strides will be used, but
// whichever is used, we want the (single) numpy stride value.
const EigenIndex n = a.shape(0),
stride = a.strides(0) / static_cast<ssize_t>(sizeof(Scalar));
if (vector) { // Eigen type is a compile-time vector
if (PYBIND11_SILENCE_MSVC_C4127(fixed) && size != n) {
return false; // Vector size mismatch
}
return {rows == 1 ? 1 : n, cols == 1 ? 1 : n, stride};
}
if (fixed) {
// The type has a fixed size, but is not a vector: abort
return false;
}
if (fixed_cols) {
// Since this isn't a vector, cols must be != 1. We allow this only if it exactly
// equals the number of elements (rows is Dynamic, and so 1 row is allowed).
if (cols != n) {
return false;
}
return {1, n, stride};
} // Otherwise it's either fully dynamic, or column dynamic; both become a column vector
if (PYBIND11_SILENCE_MSVC_C4127(fixed_rows) && rows != n) {
return false;
}
return {n, 1, stride};
}
static constexpr bool show_writeable
= is_eigen_dense_map<Type>::value && is_eigen_mutable_map<Type>::value;
static constexpr bool show_order = is_eigen_dense_map<Type>::value;
static constexpr bool show_c_contiguous = show_order && requires_row_major;
static constexpr bool show_f_contiguous
= !show_c_contiguous && show_order && requires_col_major;
static constexpr auto descriptor
= const_name("numpy.ndarray[") + npy_format_descriptor<Scalar>::name + const_name("[")
+ const_name<fixed_rows>(const_name<(size_t) rows>(), const_name("m")) + const_name(", ")
+ const_name<fixed_cols>(const_name<(size_t) cols>(), const_name("n")) + const_name("]")
+
// For a reference type (e.g. Ref<MatrixXd>) we have other constraints that might need to
// be satisfied: writeable=True (for a mutable reference), and, depending on the map's
// stride options, possibly f_contiguous or c_contiguous. We include them in the
// descriptor output to provide some hint as to why a TypeError is occurring (otherwise
// it can be confusing to see that a function accepts a 'numpy.ndarray[float64[3,2]]' and
// an error message that you *gave* a numpy.ndarray of the right type and dimensions.
const_name<show_writeable>(", flags.writeable", "")
+ const_name<show_c_contiguous>(", flags.c_contiguous", "")
+ const_name<show_f_contiguous>(", flags.f_contiguous", "") + const_name("]");
};
// Casts an Eigen type to numpy array. If given a base, the numpy array references the src data,
// otherwise it'll make a copy. writeable lets you turn off the writeable flag for the array.
template <typename props>
handle
eigen_array_cast(typename props::Type const &src, handle base = handle(), bool writeable = true) {
constexpr ssize_t elem_size = sizeof(typename props::Scalar);
array a;
if (props::vector) {
a = array({src.size()}, {elem_size * src.innerStride()}, src.data(), base);
} else {
a = array({src.rows(), src.cols()},
{elem_size * src.rowStride(), elem_size * src.colStride()},
src.data(),
base);
}
if (!writeable) {
array_proxy(a.ptr())->flags &= ~detail::npy_api::NPY_ARRAY_WRITEABLE_;
}
return a.release();
}
// Takes an lvalue ref to some Eigen type and a (python) base object, creating a numpy array that
// reference the Eigen object's data with `base` as the python-registered base class (if omitted,
// the base will be set to None, and lifetime management is up to the caller). The numpy array is
// non-writeable if the given type is const.
template <typename props, typename Type>
handle eigen_ref_array(Type &src, handle parent = none()) {
// none here is to get past array's should-we-copy detection, which currently always
// copies when there is no base. Setting the base to None should be harmless.
return eigen_array_cast<props>(src, parent, !std::is_const<Type>::value);
}
// Takes a pointer to some dense, plain Eigen type, builds a capsule around it, then returns a
// numpy array that references the encapsulated data with a python-side reference to the capsule to
// tie its destruction to that of any dependent python objects. Const-ness is determined by
// whether or not the Type of the pointer given is const.
template <typename props, typename Type, typename = enable_if_t<is_eigen_dense_plain<Type>::value>>
handle eigen_encapsulate(Type *src) {
capsule base(src, [](void *o) { delete static_cast<Type *>(o); });
return eigen_ref_array<props>(*src, base);
}
// Type caster for regular, dense matrix types (e.g. MatrixXd), but not maps/refs/etc. of dense
// types.
template <typename Type>
struct type_caster<Type, enable_if_t<is_eigen_dense_plain<Type>::value>> {
using Scalar = typename Type::Scalar;
using props = EigenProps<Type>;
bool load(handle src, bool convert) {
// If we're in no-convert mode, only load if given an array of the correct type
if (!convert && !isinstance<array_t<Scalar>>(src)) {
return false;
}
// Coerce into an array, but don't do type conversion yet; the copy below handles it.
auto buf = array::ensure(src);
if (!buf) {
return false;
}
auto dims = buf.ndim();
if (dims < 1 || dims > 2) {
return false;
}
auto fits = props::conformable(buf);
if (!fits) {
return false;
}
// Allocate the new type, then build a numpy reference into it
value = Type(fits.rows, fits.cols);
auto ref = reinterpret_steal<array>(eigen_ref_array<props>(value));
if (dims == 1) {
ref = ref.squeeze();
} else if (ref.ndim() == 1) {
buf = buf.squeeze();
}
int result = detail::npy_api::get().PyArray_CopyInto_(ref.ptr(), buf.ptr());
if (result < 0) { // Copy failed!
PyErr_Clear();
return false;
}
return true;
}
private:
// Cast implementation
template <typename CType>
static handle cast_impl(CType *src, return_value_policy policy, handle parent) {
switch (policy) {
case return_value_policy::take_ownership:
case return_value_policy::automatic:
return eigen_encapsulate<props>(src);
case return_value_policy::move:
return eigen_encapsulate<props>(new CType(std::move(*src)));
case return_value_policy::copy:
return eigen_array_cast<props>(*src);
case return_value_policy::reference:
case return_value_policy::automatic_reference:
return eigen_ref_array<props>(*src);
case return_value_policy::reference_internal:
return eigen_ref_array<props>(*src, parent);
default:
throw cast_error("unhandled return_value_policy: should not happen!");
};
}
public:
// Normal returned non-reference, non-const value:
static handle cast(Type &&src, return_value_policy /* policy */, handle parent) {
return cast_impl(&src, return_value_policy::move, parent);
}
// If you return a non-reference const, we mark the numpy array readonly:
static handle cast(const Type &&src, return_value_policy /* policy */, handle parent) {
return cast_impl(&src, return_value_policy::move, parent);
}
// lvalue reference return; default (automatic) becomes copy
static handle cast(Type &src, return_value_policy policy, handle parent) {
if (policy == return_value_policy::automatic
|| policy == return_value_policy::automatic_reference) {
policy = return_value_policy::copy;
}
return cast_impl(&src, policy, parent);
}
// const lvalue reference return; default (automatic) becomes copy
static handle cast(const Type &src, return_value_policy policy, handle parent) {
if (policy == return_value_policy::automatic
|| policy == return_value_policy::automatic_reference) {
policy = return_value_policy::copy;
}
return cast(&src, policy, parent);
}
// non-const pointer return
static handle cast(Type *src, return_value_policy policy, handle parent) {
return cast_impl(src, policy, parent);
}
// const pointer return
static handle cast(const Type *src, return_value_policy policy, handle parent) {
return cast_impl(src, policy, parent);
}
static constexpr auto name = props::descriptor;
// NOLINTNEXTLINE(google-explicit-constructor)
operator Type *() { return &value; }
// NOLINTNEXTLINE(google-explicit-constructor)
operator Type &() { return value; }
// NOLINTNEXTLINE(google-explicit-constructor)
operator Type &&() && { return std::move(value); }
template <typename T>
using cast_op_type = movable_cast_op_type<T>;
private:
Type value;
};
// Base class for casting reference/map/block/etc. objects back to python.
template <typename MapType>
struct eigen_map_caster {
private:
using props = EigenProps<MapType>;
public:
// Directly referencing a ref/map's data is a bit dangerous (whatever the map/ref points to has
// to stay around), but we'll allow it under the assumption that you know what you're doing
// (and have an appropriate keep_alive in place). We return a numpy array pointing directly at
// the ref's data (The numpy array ends up read-only if the ref was to a const matrix type.)
// Note that this means you need to ensure you don't destroy the object in some other way (e.g.
// with an appropriate keep_alive, or with a reference to a statically allocated matrix).
static handle cast(const MapType &src, return_value_policy policy, handle parent) {
switch (policy) {
case return_value_policy::copy:
return eigen_array_cast<props>(src);
case return_value_policy::reference_internal:
return eigen_array_cast<props>(src, parent, is_eigen_mutable_map<MapType>::value);
case return_value_policy::reference:
case return_value_policy::automatic:
case return_value_policy::automatic_reference:
return eigen_array_cast<props>(src, none(), is_eigen_mutable_map<MapType>::value);
default:
// move, take_ownership don't make any sense for a ref/map:
pybind11_fail("Invalid return_value_policy for Eigen Map/Ref/Block type");
}
}
static constexpr auto name = props::descriptor;
// Explicitly delete these: support python -> C++ conversion on these (i.e. these can be return
// types but not bound arguments). We still provide them (with an explicitly delete) so that
// you end up here if you try anyway.
bool load(handle, bool) = delete;
operator MapType() = delete;
template <typename>
using cast_op_type = MapType;
};
// We can return any map-like object (but can only load Refs, specialized next):
template <typename Type>
struct type_caster<Type, enable_if_t<is_eigen_dense_map<Type>::value>> : eigen_map_caster<Type> {};
// Loader for Ref<...> arguments. See the documentation for info on how to make this work without
// copying (it requires some extra effort in many cases).
template <typename PlainObjectType, typename StrideType>
struct type_caster<
Eigen::Ref<PlainObjectType, 0, StrideType>,
enable_if_t<is_eigen_dense_map<Eigen::Ref<PlainObjectType, 0, StrideType>>::value>>
: public eigen_map_caster<Eigen::Ref<PlainObjectType, 0, StrideType>> {
private:
using Type = Eigen::Ref<PlainObjectType, 0, StrideType>;
using props = EigenProps<Type>;
using Scalar = typename props::Scalar;
using MapType = Eigen::Map<PlainObjectType, 0, StrideType>;
using Array
= array_t<Scalar,
array::forcecast
| ((props::row_major ? props::inner_stride : props::outer_stride) == 1
? array::c_style
: (props::row_major ? props::outer_stride : props::inner_stride) == 1
? array::f_style
: 0)>;
static constexpr bool need_writeable = is_eigen_mutable_map<Type>::value;
// Delay construction (these have no default constructor)
std::unique_ptr<MapType> map;
std::unique_ptr<Type> ref;
// Our array. When possible, this is just a numpy array pointing to the source data, but
// sometimes we can't avoid copying (e.g. input is not a numpy array at all, has an
// incompatible layout, or is an array of a type that needs to be converted). Using a numpy
// temporary (rather than an Eigen temporary) saves an extra copy when we need both type
// conversion and storage order conversion. (Note that we refuse to use this temporary copy
// when loading an argument for a Ref<M> with M non-const, i.e. a read-write reference).
Array copy_or_ref;
public:
bool load(handle src, bool convert) {
// First check whether what we have is already an array of the right type. If not, we
// can't avoid a copy (because the copy is also going to do type conversion).
bool need_copy = !isinstance<Array>(src);
EigenConformable<props::row_major> fits;
if (!need_copy) {
// We don't need a converting copy, but we also need to check whether the strides are
// compatible with the Ref's stride requirements
auto aref = reinterpret_borrow<Array>(src);
if (aref && (!need_writeable || aref.writeable())) {
fits = props::conformable(aref);
if (!fits) {
return false; // Incompatible dimensions
}
if (!fits.template stride_compatible<props>()) {
need_copy = true;
} else {
copy_or_ref = std::move(aref);
}
} else {
need_copy = true;
}
}
if (need_copy) {
// We need to copy: If we need a mutable reference, or we're not supposed to convert
// (either because we're in the no-convert overload pass, or because we're explicitly
// instructed not to copy (via `py::arg().noconvert()`) we have to fail loading.
if (!convert || need_writeable) {
return false;
}
Array copy = Array::ensure(src);
if (!copy) {
return false;
}
fits = props::conformable(copy);
if (!fits || !fits.template stride_compatible<props>()) {
return false;
}
copy_or_ref = std::move(copy);
loader_life_support::add_patient(copy_or_ref);
}
ref.reset();
map.reset(new MapType(data(copy_or_ref),
fits.rows,
fits.cols,
make_stride(fits.stride.outer(), fits.stride.inner())));
ref.reset(new Type(*map));
return true;
}
// NOLINTNEXTLINE(google-explicit-constructor)
operator Type *() { return ref.get(); }
// NOLINTNEXTLINE(google-explicit-constructor)
operator Type &() { return *ref; }
template <typename _T>
using cast_op_type = pybind11::detail::cast_op_type<_T>;
private:
template <typename T = Type, enable_if_t<is_eigen_mutable_map<T>::value, int> = 0>
Scalar *data(Array &a) {
return a.mutable_data();
}
template <typename T = Type, enable_if_t<!is_eigen_mutable_map<T>::value, int> = 0>
const Scalar *data(Array &a) {
return a.data();
}
// Attempt to figure out a constructor of `Stride` that will work.
// If both strides are fixed, use a default constructor:
template <typename S>
using stride_ctor_default = bool_constant<S::InnerStrideAtCompileTime != Eigen::Dynamic
&& S::OuterStrideAtCompileTime != Eigen::Dynamic
&& std::is_default_constructible<S>::value>;
// Otherwise, if there is a two-index constructor, assume it is (outer,inner) like
// Eigen::Stride, and use it:
template <typename S>
using stride_ctor_dual
= bool_constant<!stride_ctor_default<S>::value
&& std::is_constructible<S, EigenIndex, EigenIndex>::value>;
// Otherwise, if there is a one-index constructor, and just one of the strides is dynamic, use
// it (passing whichever stride is dynamic).
template <typename S>
using stride_ctor_outer
= bool_constant<!any_of<stride_ctor_default<S>, stride_ctor_dual<S>>::value
&& S::OuterStrideAtCompileTime == Eigen::Dynamic
&& S::InnerStrideAtCompileTime != Eigen::Dynamic
&& std::is_constructible<S, EigenIndex>::value>;
template <typename S>
using stride_ctor_inner
= bool_constant<!any_of<stride_ctor_default<S>, stride_ctor_dual<S>>::value
&& S::InnerStrideAtCompileTime == Eigen::Dynamic
&& S::OuterStrideAtCompileTime != Eigen::Dynamic
&& std::is_constructible<S, EigenIndex>::value>;
template <typename S = StrideType, enable_if_t<stride_ctor_default<S>::value, int> = 0>
static S make_stride(EigenIndex, EigenIndex) {
return S();
}
template <typename S = StrideType, enable_if_t<stride_ctor_dual<S>::value, int> = 0>
static S make_stride(EigenIndex outer, EigenIndex inner) {
return S(outer, inner);
}
template <typename S = StrideType, enable_if_t<stride_ctor_outer<S>::value, int> = 0>
static S make_stride(EigenIndex outer, EigenIndex) {
return S(outer);
}
template <typename S = StrideType, enable_if_t<stride_ctor_inner<S>::value, int> = 0>
static S make_stride(EigenIndex, EigenIndex inner) {
return S(inner);
}
};
// type_caster for special matrix types (e.g. DiagonalMatrix), which are EigenBase, but not
// EigenDense (i.e. they don't have a data(), at least not with the usual matrix layout).
// load() is not supported, but we can cast them into the python domain by first copying to a
// regular Eigen::Matrix, then casting that.
template <typename Type>
struct type_caster<Type, enable_if_t<is_eigen_other<Type>::value>> {
protected:
using Matrix
= Eigen::Matrix<typename Type::Scalar, Type::RowsAtCompileTime, Type::ColsAtCompileTime>;
using props = EigenProps<Matrix>;
public:
static handle cast(const Type &src, return_value_policy /* policy */, handle /* parent */) {
handle h = eigen_encapsulate<props>(new Matrix(src));
return h;
}
static handle cast(const Type *src, return_value_policy policy, handle parent) {
return cast(*src, policy, parent);
}
static constexpr auto name = props::descriptor;
// Explicitly delete these: support python -> C++ conversion on these (i.e. these can be return
// types but not bound arguments). We still provide them (with an explicitly delete) so that
// you end up here if you try anyway.
bool load(handle, bool) = delete;
operator Type() = delete;
template <typename>
using cast_op_type = Type;
};
template <typename Type>
struct type_caster<Type, enable_if_t<is_eigen_sparse<Type>::value>> {
using Scalar = typename Type::Scalar;
using StorageIndex = remove_reference_t<decltype(*std::declval<Type>().outerIndexPtr())>;
using Index = typename Type::Index;
static constexpr bool rowMajor = Type::IsRowMajor;
bool load(handle src, bool) {
if (!src) {
return false;
}
auto obj = reinterpret_borrow<object>(src);
object sparse_module = module_::import("scipy.sparse");
object matrix_type = sparse_module.attr(rowMajor ? "csr_matrix" : "csc_matrix");
if (!type::handle_of(obj).is(matrix_type)) {
try {
obj = matrix_type(obj);
} catch (const error_already_set &) {
return false;
}
}
auto values = array_t<Scalar>((object) obj.attr("data"));
auto innerIndices = array_t<StorageIndex>((object) obj.attr("indices"));
auto outerIndices = array_t<StorageIndex>((object) obj.attr("indptr"));
auto shape = pybind11::tuple((pybind11::object) obj.attr("shape"));
auto nnz = obj.attr("nnz").cast<Index>();
if (!values || !innerIndices || !outerIndices) {
return false;
}
value = EigenMapSparseMatrix<Scalar,
Type::Flags &(Eigen::RowMajor | Eigen::ColMajor),
StorageIndex>(shape[0].cast<Index>(),
shape[1].cast<Index>(),
std::move(nnz),
outerIndices.mutable_data(),
innerIndices.mutable_data(),
values.mutable_data());
return true;
}
static handle cast(const Type &src, return_value_policy /* policy */, handle /* parent */) {
const_cast<Type &>(src).makeCompressed();
object matrix_type
= module_::import("scipy.sparse").attr(rowMajor ? "csr_matrix" : "csc_matrix");
array data(src.nonZeros(), src.valuePtr());
array outerIndices((rowMajor ? src.rows() : src.cols()) + 1, src.outerIndexPtr());
array innerIndices(src.nonZeros(), src.innerIndexPtr());
return matrix_type(pybind11::make_tuple(
std::move(data), std::move(innerIndices), std::move(outerIndices)),
pybind11::make_tuple(src.rows(), src.cols()))
.release();
}
PYBIND11_TYPE_CASTER(Type,
const_name<(Type::IsRowMajor) != 0>("scipy.sparse.csr_matrix[",
"scipy.sparse.csc_matrix[")
+ npy_format_descriptor<Scalar>::name + const_name("]"));
};
PYBIND11_NAMESPACE_END(detail)
PYBIND11_NAMESPACE_END(PYBIND11_NAMESPACE)

518
include/pybind11/eigen/tensor.h Normal file
View File

@ -0,0 +1,518 @@
/*
pybind11/eigen/tensor.h: Transparent conversion for Eigen tensors
All rights reserved. Use of this source code is governed by a
BSD-style license that can be found in the LICENSE file.
*/
#pragma once
#include "../numpy.h"
#if defined(__GNUC__) && !defined(__clang__) && !defined(__INTEL_COMPILER)
static_assert(__GNUC__ > 5, "Eigen Tensor support in pybind11 requires GCC > 5.0");
#endif
#if defined(_MSC_VER)
# pragma warning(push)
# pragma warning(disable : 4554) // Tensor.h warning
# pragma warning(disable : 4127) // Tensor.h warning
#elif defined(__MINGW32__)
# pragma GCC diagnostic push
# pragma GCC diagnostic ignored "-Wmaybe-uninitialized"
#endif
#include <unsupported/Eigen/CXX11/Tensor>
#if defined(_MSC_VER)
# pragma warning(pop)
#elif defined(__MINGW32__)
# pragma GCC diagnostic pop
#endif
static_assert(EIGEN_VERSION_AT_LEAST(3, 3, 0),
"Eigen Tensor support in pybind11 requires Eigen >= 3.3.0");
PYBIND11_NAMESPACE_BEGIN(PYBIND11_NAMESPACE)
PYBIND11_NAMESPACE_BEGIN(detail)
inline bool is_tensor_aligned(const void *data) {
return (reinterpret_cast<std::size_t>(data) % EIGEN_DEFAULT_ALIGN_BYTES) == 0;
}
template <typename T>
constexpr int compute_array_flag_from_tensor() {
static_assert((static_cast<int>(T::Layout) == static_cast<int>(Eigen::RowMajor))
|| (static_cast<int>(T::Layout) == static_cast<int>(Eigen::ColMajor)),
"Layout must be row or column major");
return (static_cast<int>(T::Layout) == static_cast<int>(Eigen::RowMajor)) ? array::c_style
: array::f_style;
}
template <typename T>
struct eigen_tensor_helper {};
template <typename Scalar_, int NumIndices_, int Options_, typename IndexType>
struct eigen_tensor_helper<Eigen::Tensor<Scalar_, NumIndices_, Options_, IndexType>> {
using Type = Eigen::Tensor<Scalar_, NumIndices_, Options_, IndexType>;
using ValidType = void;
static Eigen::DSizes<typename Type::Index, Type::NumIndices> get_shape(const Type &f) {
return f.dimensions();
}
static constexpr bool
is_correct_shape(const Eigen::DSizes<typename Type::Index, Type::NumIndices> & /*shape*/) {
return true;
}
template <typename T>
struct helper {};
template <size_t... Is>
struct helper<index_sequence<Is...>> {
static constexpr auto value = concat(const_name(((void) Is, "?"))...);
};
static constexpr auto dimensions_descriptor
= helper<decltype(make_index_sequence<Type::NumIndices>())>::value;
template <typename... Args>
static Type *alloc(Args &&...args) {
return new Type(std::forward<Args>(args)...);
}
static void free(Type *tensor) { delete tensor; }
};
template <typename Scalar_, typename std::ptrdiff_t... Indices, int Options_, typename IndexType>
struct eigen_tensor_helper<
Eigen::TensorFixedSize<Scalar_, Eigen::Sizes<Indices...>, Options_, IndexType>> {
using Type = Eigen::TensorFixedSize<Scalar_, Eigen::Sizes<Indices...>, Options_, IndexType>;
using ValidType = void;
static constexpr Eigen::DSizes<typename Type::Index, Type::NumIndices>
get_shape(const Type & /*f*/) {
return get_shape();
}
static constexpr Eigen::DSizes<typename Type::Index, Type::NumIndices> get_shape() {
return Eigen::DSizes<typename Type::Index, Type::NumIndices>(Indices...);
}
static bool
is_correct_shape(const Eigen::DSizes<typename Type::Index, Type::NumIndices> &shape) {
return get_shape() == shape;
}
static constexpr auto dimensions_descriptor = concat(const_name<Indices>()...);
template <typename... Args>
static Type *alloc(Args &&...args) {
Eigen::aligned_allocator<Type> allocator;
return ::new (allocator.allocate(1)) Type(std::forward<Args>(args)...);
}
static void free(Type *tensor) {
Eigen::aligned_allocator<Type> allocator;
tensor->~Type();
allocator.deallocate(tensor, 1);
}
};
template <typename Type, bool ShowDetails, bool NeedsWriteable = false>
struct get_tensor_descriptor {
static constexpr auto details
= const_name<NeedsWriteable>(", flags.writeable", "")
+ const_name<static_cast<int>(Type::Layout) == static_cast<int>(Eigen::RowMajor)>(
", flags.c_contiguous", ", flags.f_contiguous");
static constexpr auto value
= const_name("numpy.ndarray[") + npy_format_descriptor<typename Type::Scalar>::name
+ const_name("[") + eigen_tensor_helper<remove_cv_t<Type>>::dimensions_descriptor
+ const_name("]") + const_name<ShowDetails>(details, const_name("")) + const_name("]");
};
// When EIGEN_AVOID_STL_ARRAY is defined, Eigen::DSizes<T, 0> does not have the begin() member
// function. Falling back to a simple loop works around this issue.
//
// We need to disable the type-limits warning for the inner loop when size = 0.
#if defined(__GNUC__)
# pragma GCC diagnostic push
# pragma GCC diagnostic ignored "-Wtype-limits"
#endif
template <typename T, int size>
std::vector<T> convert_dsizes_to_vector(const Eigen::DSizes<T, size> &arr) {
std::vector<T> result(size);
for (size_t i = 0; i < size; i++) {
result[i] = arr[i];
}
return result;
}
template <typename T, int size>
Eigen::DSizes<T, size> get_shape_for_array(const array &arr) {
Eigen::DSizes<T, size> result;
const T *shape = arr.shape();
for (size_t i = 0; i < size; i++) {
result[i] = shape[i];
}
return result;
}
#if defined(__GNUC__)
# pragma GCC diagnostic pop
#endif
template <typename Type>
struct type_caster<Type, typename eigen_tensor_helper<Type>::ValidType> {
using Helper = eigen_tensor_helper<Type>;
static constexpr auto temp_name = get_tensor_descriptor<Type, false>::value;
PYBIND11_TYPE_CASTER(Type, temp_name);
bool load(handle src, bool convert) {
if (!convert) {
if (!isinstance<array>(src)) {
return false;
}
array temp = array::ensure(src);
if (!temp) {
return false;
}
if (!convert && !temp.dtype().is(dtype::of<typename Type::Scalar>())) {
return false;
}
}
array_t<typename Type::Scalar, compute_array_flag_from_tensor<Type>()> arr(
reinterpret_borrow<object>(src));
if (arr.ndim() != Type::NumIndices) {
return false;
}
auto shape = get_shape_for_array<typename Type::Index, Type::NumIndices>(arr);
if (!Helper::is_correct_shape(shape)) {
return false;
}
#if EIGEN_VERSION_AT_LEAST(3, 4, 0)
auto data_pointer = arr.data();
#else
// Handle Eigen bug
auto data_pointer = const_cast<typename Type::Scalar *>(arr.data());
#endif
if (is_tensor_aligned(arr.data())) {
value = Eigen::TensorMap<const Type, Eigen::Aligned>(data_pointer, shape);
} else {
value = Eigen::TensorMap<const Type>(data_pointer, shape);
}
return true;
}
static handle cast(Type &&src, return_value_policy policy, handle parent) {
if (policy == return_value_policy::reference
|| policy == return_value_policy::reference_internal) {
pybind11_fail("Cannot use a reference return value policy for an rvalue");
}
return cast_impl(&src, return_value_policy::move, parent);
}
static handle cast(const Type &&src, return_value_policy policy, handle parent) {
if (policy == return_value_policy::reference
|| policy == return_value_policy::reference_internal) {
pybind11_fail("Cannot use a reference return value policy for an rvalue");
}
return cast_impl(&src, return_value_policy::move, parent);
}
static handle cast(Type &src, return_value_policy policy, handle parent) {
if (policy == return_value_policy::automatic
|| policy == return_value_policy::automatic_reference) {
policy = return_value_policy::copy;
}
return cast_impl(&src, policy, parent);
}
static handle cast(const Type &src, return_value_policy policy, handle parent) {
if (policy == return_value_policy::automatic
|| policy == return_value_policy::automatic_reference) {
policy = return_value_policy::copy;
}
return cast(&src, policy, parent);
}
static handle cast(Type *src, return_value_policy policy, handle parent) {
if (policy == return_value_policy::automatic) {
policy = return_value_policy::take_ownership;
} else if (policy == return_value_policy::automatic_reference) {
policy = return_value_policy::reference;
}
return cast_impl(src, policy, parent);
}
static handle cast(const Type *src, return_value_policy policy, handle parent) {
if (policy == return_value_policy::automatic) {
policy = return_value_policy::take_ownership;
} else if (policy == return_value_policy::automatic_reference) {
policy = return_value_policy::reference;
}
return cast_impl(src, policy, parent);
}
template <typename C>
static handle cast_impl(C *src, return_value_policy policy, handle parent) {
object parent_object;
bool writeable = false;
switch (policy) {
case return_value_policy::move:
if (std::is_const<C>::value) {
pybind11_fail("Cannot move from a constant reference");
}
src = Helper::alloc(std::move(*src));
parent_object
= capsule(src, [](void *ptr) { Helper::free(reinterpret_cast<Type *>(ptr)); });
writeable = true;
break;
case return_value_policy::take_ownership:
if (std::is_const<C>::value) {
// This cast is ugly, and might be UB in some cases, but we don't have an
// alterantive here as we must free that memory
Helper::free(const_cast<Type *>(src));
pybind11_fail("Cannot take ownership of a const reference");
}
parent_object
= capsule(src, [](void *ptr) { Helper::free(reinterpret_cast<Type *>(ptr)); });
writeable = true;
break;
case return_value_policy::copy:
writeable = true;
break;
case return_value_policy::reference:
parent_object = none();
writeable = !std::is_const<C>::value;
break;
case return_value_policy::reference_internal:
// Default should do the right thing
if (!parent) {
pybind11_fail("Cannot use reference internal when there is no parent");
}
parent_object = reinterpret_borrow<object>(parent);
writeable = !std::is_const<C>::value;
break;
default:
pybind11_fail("pybind11 bug in eigen.h, please file a bug report");
}
auto result = array_t<typename Type::Scalar, compute_array_flag_from_tensor<Type>()>(
convert_dsizes_to_vector(Helper::get_shape(*src)), src->data(), parent_object);
if (!writeable) {
array_proxy(result.ptr())->flags &= ~detail::npy_api::NPY_ARRAY_WRITEABLE_;
}
return result.release();
}
};
template <typename StoragePointerType,
bool needs_writeable,
enable_if_t<!needs_writeable, bool> = true>
StoragePointerType get_array_data_for_type(array &arr) {
#if EIGEN_VERSION_AT_LEAST(3, 4, 0)
return reinterpret_cast<StoragePointerType>(arr.data());
#else
// Handle Eigen bug
return reinterpret_cast<StoragePointerType>(const_cast<void *>(arr.data()));
#endif
}
template <typename StoragePointerType,
bool needs_writeable,
enable_if_t<needs_writeable, bool> = true>
StoragePointerType get_array_data_for_type(array &arr) {
return reinterpret_cast<StoragePointerType>(arr.mutable_data());
}
template <typename T, typename = void>
struct get_storage_pointer_type;
template <typename MapType>
struct get_storage_pointer_type<MapType, void_t<typename MapType::StoragePointerType>> {
using SPT = typename MapType::StoragePointerType;
};
template <typename MapType>
struct get_storage_pointer_type<MapType, void_t<typename MapType::PointerArgType>> {
using SPT = typename MapType::PointerArgType;
};
template <typename Type, int Options>
struct type_caster<Eigen::TensorMap<Type, Options>,
typename eigen_tensor_helper<remove_cv_t<Type>>::ValidType> {
using MapType = Eigen::TensorMap<Type, Options>;
using Helper = eigen_tensor_helper<remove_cv_t<Type>>;
bool load(handle src, bool /*convert*/) {
// Note that we have a lot more checks here as we want to make sure to avoid copies
if (!isinstance<array>(src)) {
return false;
}
auto arr = reinterpret_borrow<array>(src);
if ((arr.flags() & compute_array_flag_from_tensor<Type>()) == 0) {
return false;
}
if (!arr.dtype().is(dtype::of<typename Type::Scalar>())) {
return false;
}
if (arr.ndim() != Type::NumIndices) {
return false;
}
constexpr bool is_aligned = (Options & Eigen::Aligned) != 0;
if (PYBIND11_SILENCE_MSVC_C4127(is_aligned) && !is_tensor_aligned(arr.data())) {
return false;
}
auto shape = get_shape_for_array<typename Type::Index, Type::NumIndices>(arr);
if (!Helper::is_correct_shape(shape)) {
return false;
}
if (PYBIND11_SILENCE_MSVC_C4127(needs_writeable) && !arr.writeable()) {
return false;
}
auto result = get_array_data_for_type<typename get_storage_pointer_type<MapType>::SPT,
needs_writeable>(arr);
value.reset(new MapType(std::move(result), std::move(shape)));
return true;
}
static handle cast(MapType &&src, return_value_policy policy, handle parent) {
return cast_impl(&src, policy, parent);
}
static handle cast(const MapType &&src, return_value_policy policy, handle parent) {
return cast_impl(&src, policy, parent);
}
static handle cast(MapType &src, return_value_policy policy, handle parent) {
if (policy == return_value_policy::automatic
|| policy == return_value_policy::automatic_reference) {
policy = return_value_policy::copy;
}
return cast_impl(&src, policy, parent);
}
static handle cast(const MapType &src, return_value_policy policy, handle parent) {
if (policy == return_value_policy::automatic
|| policy == return_value_policy::automatic_reference) {
policy = return_value_policy::copy;
}
return cast(&src, policy, parent);
}
static handle cast(MapType *src, return_value_policy policy, handle parent) {
if (policy == return_value_policy::automatic) {
policy = return_value_policy::take_ownership;
} else if (policy == return_value_policy::automatic_reference) {
policy = return_value_policy::reference;
}
return cast_impl(src, policy, parent);
}
static handle cast(const MapType *src, return_value_policy policy, handle parent) {
if (policy == return_value_policy::automatic) {
policy = return_value_policy::take_ownership;
} else if (policy == return_value_policy::automatic_reference) {
policy = return_value_policy::reference;
}
return cast_impl(src, policy, parent);
}
template <typename C>
static handle cast_impl(C *src, return_value_policy policy, handle parent) {
object parent_object;
constexpr bool writeable = !std::is_const<C>::value;
switch (policy) {
case return_value_policy::reference:
parent_object = none();
break;
case return_value_policy::reference_internal:
// Default should do the right thing
if (!parent) {
pybind11_fail("Cannot use reference internal when there is no parent");
}
parent_object = reinterpret_borrow<object>(parent);
break;
case return_value_policy::take_ownership:
delete src;
// fallthrough
default:
// move, take_ownership don't make any sense for a ref/map:
pybind11_fail("Invalid return_value_policy for Eigen Map type, must be either "
"reference or reference_internal");
}
auto result = array_t<typename Type::Scalar, compute_array_flag_from_tensor<Type>()>(
convert_dsizes_to_vector(Helper::get_shape(*src)),
src->data(),
std::move(parent_object));
if (!writeable) {
array_proxy(result.ptr())->flags &= ~detail::npy_api::NPY_ARRAY_WRITEABLE_;
}
return result.release();
}
#if EIGEN_VERSION_AT_LEAST(3, 4, 0)
static constexpr bool needs_writeable = !std::is_const<typename std::remove_pointer<
typename get_storage_pointer_type<MapType>::SPT>::type>::value;
#else
// Handle Eigen bug
static constexpr bool needs_writeable = !std::is_const<Type>::value;
#endif
protected:
// TODO: Move to std::optional once std::optional has more support
std::unique_ptr<MapType> value;
public:
static constexpr auto name = get_tensor_descriptor<Type, true, needs_writeable>::value;
explicit operator MapType *() { return value.get(); }
explicit operator MapType &() { return *value; }
explicit operator MapType &&() && { return std::move(*value); }
template <typename T_>
using cast_op_type = ::pybind11::detail::movable_cast_op_type<T_>;
};
PYBIND11_NAMESPACE_END(detail)
PYBIND11_NAMESPACE_END(PYBIND11_NAMESPACE)

13
include/pybind11/functional.h
View File

@ -48,9 +48,16 @@ public:
*/
if (auto cfunc = func.cpp_function()) {
auto *cfunc_self = PyCFunction_GET_SELF(cfunc.ptr());
if (isinstance<capsule>(cfunc_self)) {
if (cfunc_self == nullptr) {
PyErr_Clear();
} else if (isinstance<capsule>(cfunc_self)) {
auto c = reinterpret_borrow<capsule>(cfunc_self);
auto *rec = (function_record *) c;
function_record *rec = nullptr;
// Check that we can safely reinterpret the capsule into a function_record
if (detail::is_function_record_capsule(c)) {
rec = c.get_pointer<function_record>();
}
while (rec != nullptr) {
if (rec->is_stateless
@ -110,7 +117,7 @@ public:
template <typename Func>
static handle cast(Func &&f_, return_value_policy policy, handle /* parent */) {
if (!f_) {
return none().inc_ref();
return none().release();
}
auto result = f_.template target<function_type>();

39
include/pybind11/gil.h
View File

@ -10,7 +10,10 @@
#pragma once
#include "detail/common.h"
#if defined(WITH_THREAD) && !defined(PYBIND11_SIMPLE_GIL_MANAGEMENT)
# include "detail/internals.h"
#endif
PYBIND11_NAMESPACE_BEGIN(PYBIND11_NAMESPACE)
@ -21,7 +24,9 @@ PyThreadState *get_thread_state_unchecked();
PYBIND11_NAMESPACE_END(detail)
#if defined(WITH_THREAD) && !defined(PYPY_VERSION)
#if defined(WITH_THREAD)
# if !defined(PYBIND11_SIMPLE_GIL_MANAGEMENT)
/* The functions below essentially reproduce the PyGILState_* API using a RAII
* pattern, but there are a few important differences:
@ -178,12 +183,14 @@ private:
bool disassoc;
bool active = true;
};
#elif defined(PYPY_VERSION)
# else // PYBIND11_SIMPLE_GIL_MANAGEMENT
class gil_scoped_acquire {
PyGILState_STATE state;
public:
gil_scoped_acquire() { state = PyGILState_Ensure(); }
gil_scoped_acquire() : state{PyGILState_Ensure()} {}
gil_scoped_acquire(const gil_scoped_acquire &) = delete;
gil_scoped_acquire &operator=(const gil_scoped_acquire &) = delete;
~gil_scoped_acquire() { PyGILState_Release(state); }
@ -194,19 +201,39 @@ class gil_scoped_release {
PyThreadState *state;
public:
gil_scoped_release() { state = PyEval_SaveThread(); }
gil_scoped_release() : state{PyEval_SaveThread()} {}
gil_scoped_release(const gil_scoped_release &) = delete;
gil_scoped_release &operator=(const gil_scoped_acquire &) = delete;
~gil_scoped_release() { PyEval_RestoreThread(state); }
void disarm() {}
};
#else
# endif // PYBIND11_SIMPLE_GIL_MANAGEMENT
#else // WITH_THREAD
class gil_scoped_acquire {
public:
gil_scoped_acquire() {
// Trick to suppress `unused variable` error messages (at call sites).
(void) (this != (this + 1));
}
gil_scoped_acquire(const gil_scoped_acquire &) = delete;
gil_scoped_acquire &operator=(const gil_scoped_acquire &) = delete;
void disarm() {}
};
class gil_scoped_release {
public:
gil_scoped_release() {
// Trick to suppress `unused variable` error messages (at call sites).
(void) (this != (this + 1));
}
gil_scoped_release(const gil_scoped_release &) = delete;
gil_scoped_release &operator=(const gil_scoped_acquire &) = delete;
void disarm() {}
};
#endif
#endif // WITH_THREAD
PYBIND11_NAMESPACE_END(PYBIND11_NAMESPACE)

60
include/pybind11/pybind11.h
View File

@ -468,14 +468,21 @@ protected:
if (rec->sibling) {
if (PyCFunction_Check(rec->sibling.ptr())) {
auto *self = PyCFunction_GET_SELF(rec->sibling.ptr());
capsule rec_capsule = isinstance<capsule>(self) ? reinterpret_borrow<capsule>(self)
: capsule(self);
chain = (detail::function_record *) rec_capsule;
if (!isinstance<capsule>(self)) {
chain = nullptr;
} else {
auto rec_capsule = reinterpret_borrow<capsule>(self);
if (detail::is_function_record_capsule(rec_capsule)) {
chain = rec_capsule.get_pointer<detail::function_record>();
/* Never append a method to an overload chain of a parent class;
instead, hide the parent's overloads in this case */
if (!chain->scope.is(rec->scope)) {
chain = nullptr;
}
} else {
chain = nullptr;
}
}
}
// Don't trigger for things like the default __init__, which are wrapper_descriptors
// that we are intentionally replacing
@ -496,6 +503,7 @@ protected:
capsule rec_capsule(unique_rec.release(),
[](void *ptr) { destruct((detail::function_record *) ptr); });
rec_capsule.set_name(detail::get_function_record_capsule_name());
guarded_strdup.release();
object scope_module;
@ -661,10 +669,13 @@ protected:
/// Main dispatch logic for calls to functions bound using pybind11
static PyObject *dispatcher(PyObject *self, PyObject *args_in, PyObject *kwargs_in) {
using namespace detail;
assert(isinstance<capsule>(self));
/* Iterator over the list of potentially admissible overloads */
const function_record *overloads = (function_record *) PyCapsule_GetPointer(self, nullptr),
const function_record *overloads = reinterpret_cast<function_record *>(
PyCapsule_GetPointer(self, get_function_record_capsule_name())),
*it = overloads;
assert(overloads != nullptr);
/* Need to know how many arguments + keyword arguments there are to pick the right
overload */
@ -1883,9 +1894,22 @@ private:
static detail::function_record *get_function_record(handle h) {
h = detail::get_function(h);
return h ? (detail::function_record *) reinterpret_borrow<capsule>(
PyCFunction_GET_SELF(h.ptr()))
: nullptr;
if (!h) {
return nullptr;
}
handle func_self = PyCFunction_GET_SELF(h.ptr());
if (!func_self) {
throw error_already_set();
}
if (!isinstance<capsule>(func_self)) {
return nullptr;
}
auto cap = reinterpret_borrow<capsule>(func_self);
if (!detail::is_function_record_capsule(cap)) {
return nullptr;
}
return cap.get_pointer<detail::function_record>();
}
};
@ -2345,7 +2369,7 @@ template <typename Access,
typename Sentinel,
typename ValueType,
typename... Extra>
iterator make_iterator_impl(Iterator &&first, Sentinel &&last, Extra &&...extra) {
iterator make_iterator_impl(Iterator first, Sentinel last, Extra &&...extra) {
using state = detail::iterator_state<Access, Policy, Iterator, Sentinel, ValueType, Extra...>;
// TODO: state captures only the types of Extra, not the values
@ -2371,7 +2395,7 @@ iterator make_iterator_impl(Iterator &&first, Sentinel &&last, Extra &&...extra)
Policy);
}
return cast(state{std::forward<Iterator>(first), std::forward<Sentinel>(last), true});
return cast(state{first, last, true});
}
PYBIND11_NAMESPACE_END(detail)
@ -2382,15 +2406,13 @@ template <return_value_policy Policy = return_value_policy::reference_internal,
typename Sentinel,
typename ValueType = typename detail::iterator_access<Iterator>::result_type,
typename... Extra>
iterator make_iterator(Iterator &&first, Sentinel &&last, Extra &&...extra) {
iterator make_iterator(Iterator first, Sentinel last, Extra &&...extra) {
return detail::make_iterator_impl<detail::iterator_access<Iterator>,
Policy,
Iterator,
Sentinel,
ValueType,
Extra...>(std::forward<Iterator>(first),
std::forward<Sentinel>(last),
std::forward<Extra>(extra)...);
Extra...>(first, last, std::forward<Extra>(extra)...);
}
/// Makes a python iterator over the keys (`.first`) of a iterator over pairs from a
@ -2400,15 +2422,13 @@ template <return_value_policy Policy = return_value_policy::reference_internal,
typename Sentinel,
typename KeyType = typename detail::iterator_key_access<Iterator>::result_type,
typename... Extra>
iterator make_key_iterator(Iterator &&first, Sentinel &&last, Extra &&...extra) {
iterator make_key_iterator(Iterator first, Sentinel last, Extra &&...extra) {
return detail::make_iterator_impl<detail::iterator_key_access<Iterator>,
Policy,
Iterator,
Sentinel,
KeyType,
Extra...>(std::forward<Iterator>(first),
std::forward<Sentinel>(last),
std::forward<Extra>(extra)...);
Extra...>(first, last, std::forward<Extra>(extra)...);
}
/// Makes a python iterator over the values (`.second`) of a iterator over pairs from a
@ -2418,15 +2438,13 @@ template <return_value_policy Policy = return_value_policy::reference_internal,
typename Sentinel,
typename ValueType = typename detail::iterator_value_access<Iterator>::result_type,
typename... Extra>
iterator make_value_iterator(Iterator &&first, Sentinel &&last, Extra &&...extra) {
iterator make_value_iterator(Iterator first, Sentinel last, Extra &&...extra) {
return detail::make_iterator_impl<detail::iterator_value_access<Iterator>,
Policy,
Iterator,
Sentinel,
ValueType,
Extra...>(std::forward<Iterator>(first),
std::forward<Sentinel>(last),
std::forward<Extra>(extra)...);
Extra...>(first, last, std::forward<Extra>(extra)...);
}
/// Makes an iterator over values of an stl container or other container supporting

66
include/pybind11/pytypes.h
View File

@ -501,11 +501,29 @@ struct error_fetch_and_normalize {
std::string message_error_string;
if (m_value) {
auto value_str = reinterpret_steal<object>(PyObject_Str(m_value.ptr()));
constexpr const char *message_unavailable_exc
= "<MESSAGE UNAVAILABLE DUE TO ANOTHER EXCEPTION>";
if (!value_str) {
message_error_string = detail::error_string();
result = "<MESSAGE UNAVAILABLE DUE TO ANOTHER EXCEPTION>";
result = message_unavailable_exc;
} else {
result = value_str.cast<std::string>();
// Not using `value_str.cast<std::string>()`, to not potentially throw a secondary
// error_already_set that will then result in process termination (#4288).
auto value_bytes = reinterpret_steal<object>(
PyUnicode_AsEncodedString(value_str.ptr(), "utf-8", "backslashreplace"));
if (!value_bytes) {
message_error_string = detail::error_string();
result = message_unavailable_exc;
} else {
char *buffer = nullptr;
Py_ssize_t length = 0;
if (PyBytes_AsStringAndSize(value_bytes.ptr(), &buffer, &length) == -1) {
message_error_string = detail::error_string();
result = message_unavailable_exc;
} else {
result = std::string(buffer, static_cast<std::size_t>(length));
}
}
}
} else {
result = "<MESSAGE UNAVAILABLE>";
@ -605,12 +623,6 @@ inline std::string error_string() {
PYBIND11_NAMESPACE_END(detail)
#if defined(_MSC_VER)
# pragma warning(push)
# pragma warning(disable : 4275 4251)
// warning C4275: An exported class was derived from a class that wasn't exported.
// Can be ignored when derived from a STL class.
#endif
/// Fetch and hold an error which was already set in Python. An instance of this is typically
/// thrown to propagate python-side errors back through C++ which can either be caught manually or
/// else falls back to the function dispatcher (which then raises the captured error back to
@ -670,9 +682,6 @@ private:
/// crashes (undefined behavior) if the Python interpreter is finalizing.
static void m_fetched_error_deleter(detail::error_fetch_and_normalize *raw_ptr);
};
#if defined(_MSC_VER)
# pragma warning(pop)
#endif
/// Replaces the current Python error indicator with the chosen error, performing a
/// 'raise from' to indicate that the chosen error was caused by the original error.
@ -1383,7 +1392,7 @@ public:
private:
void advance() {
value = reinterpret_steal<object>(PyIter_Next(m_ptr));
if (PyErr_Occurred()) {
if (value.ptr() == nullptr && PyErr_Occurred()) {
throw error_already_set();
}
}
@ -1433,6 +1442,9 @@ public:
str(const char *c, const SzType &n)
: object(PyUnicode_FromStringAndSize(c, ssize_t_cast(n)), stolen_t{}) {
if (!m_ptr) {
if (PyErr_Occurred()) {
throw error_already_set();
}
pybind11_fail("Could not allocate string object!");
}
}
@ -1442,6 +1454,9 @@ public:
// NOLINTNEXTLINE(google-explicit-constructor)
str(const char *c = "") : object(PyUnicode_FromString(c), stolen_t{}) {
if (!m_ptr) {
if (PyErr_Occurred()) {
throw error_already_set();
}
pybind11_fail("Could not allocate string object!");
}
}
@ -1599,6 +1614,9 @@ inline str::str(const bytes &b) {
}
auto obj = reinterpret_steal<object>(PyUnicode_FromStringAndSize(buffer, length));
if (!obj) {
if (PyErr_Occurred()) {
throw error_already_set();
}
pybind11_fail("Could not allocate string object!");
}
m_ptr = obj.release().ptr();
@ -1810,16 +1828,16 @@ public:
explicit capsule(const void *value,
const char *name = nullptr,
void (*destructor)(PyObject *) = nullptr)
PyCapsule_Destructor destructor = nullptr)
: object(PyCapsule_New(const_cast<void *>(value), name, destructor), stolen_t{}) {
if (!m_ptr) {
throw error_already_set();
}
}
PYBIND11_DEPRECATED("Please pass a destructor that takes a void pointer as input")
capsule(const void *value, void (*destruct)(PyObject *))
: object(PyCapsule_New(const_cast<void *>(value), nullptr, destruct), stolen_t{}) {
PYBIND11_DEPRECATED("Please use the ctor with value, name, destructor args")
capsule(const void *value, PyCapsule_Destructor destructor)
: object(PyCapsule_New(const_cast<void *>(value), nullptr, destructor), stolen_t{}) {
if (!m_ptr) {
throw error_already_set();
}
@ -1830,7 +1848,7 @@ public:
// guard if destructor called while err indicator is set
error_scope error_guard;
auto destructor = reinterpret_cast<void (*)(void *)>(PyCapsule_GetContext(o));
if (PyErr_Occurred()) {
if (destructor == nullptr && PyErr_Occurred()) {
throw error_already_set();
}
const char *name = get_name_in_error_scope(o);
@ -1844,7 +1862,7 @@ public:
}
});
if (!m_ptr || PyCapsule_SetContext(m_ptr, (void *) destructor) != 0) {
if (!m_ptr || PyCapsule_SetContext(m_ptr, reinterpret_cast<void *>(destructor)) != 0) {
throw error_already_set();
}
}
@ -1968,7 +1986,11 @@ public:
void clear() /* py-non-const */ { PyDict_Clear(ptr()); }
template <typename T>
bool contains(T &&key) const {
return PyDict_Contains(m_ptr, detail::object_or_cast(std::forward<T>(key)).ptr()) == 1;
auto result = PyDict_Contains(m_ptr, detail::object_or_cast(std::forward<T>(key)).ptr());
if (result == -1) {
throw error_already_set();
}
return result == 1;
}
private:
@ -2054,7 +2076,11 @@ public:
bool empty() const { return size() == 0; }
template <typename T>
bool contains(T &&val) const {
return PySet_Contains(m_ptr, detail::object_or_cast(std::forward<T>(val)).ptr()) == 1;
auto result = PySet_Contains(m_ptr, detail::object_or_cast(std::forward<T>(val)).ptr());
if (result == -1) {
throw error_already_set();
}
return result == 1;
}
};

2
include/pybind11/stl.h
View File

@ -311,7 +311,7 @@ struct optional_caster {
template <typename T>
static handle cast(T &&src, return_value_policy policy, handle parent) {
if (!src) {
return none().inc_ref();
return none().release();
}
if (!std::is_lvalue_reference<T>::value) {
policy = return_value_policy_override<Value>::policy(policy);

34
tests/CMakeLists.txt
View File

@ -128,7 +128,9 @@ set(PYBIND11_TEST_FILES
test_custom_type_casters
test_custom_type_setup
test_docstring_options
test_eigen
test_eigen_matrix
test_eigen_tensor
test_eigen_tensor_avoid_stl_array.cpp
test_enum
test_eval
test_exceptions
@ -233,7 +235,10 @@ list(GET PYBIND11_EIGEN_VERSION_AND_HASH 1 PYBIND11_EIGEN_VERSION_HASH)
# Check if Eigen is available; if not, remove from PYBIND11_TEST_FILES (but
# keep it in PYBIND11_PYTEST_FILES, so that we get the "eigen is not installed"
# skip message).
list(FIND PYBIND11_TEST_FILES test_eigen.cpp PYBIND11_TEST_FILES_EIGEN_I)
list(FIND PYBIND11_TEST_FILES test_eigen_matrix.cpp PYBIND11_TEST_FILES_EIGEN_I)
if(PYBIND11_TEST_FILES_EIGEN_I EQUAL -1)
list(FIND PYBIND11_TEST_FILES test_eigen_tensor.cpp PYBIND11_TEST_FILES_EIGEN_I)
endif()
if(PYBIND11_TEST_FILES_EIGEN_I GREATER -1)
# Try loading via newer Eigen's Eigen3Config first (bypassing tools/FindEigen3.cmake).
# Eigen 3.3.1+ exports a cmake 3.0+ target for handling dependency requirements, but also
@ -289,12 +294,37 @@ if(PYBIND11_TEST_FILES_EIGEN_I GREATER -1)
endif()
message(STATUS "Building tests with Eigen v${EIGEN3_VERSION}")
else()
list(FIND PYBIND11_TEST_FILES test_eigen_matrix.cpp PYBIND11_TEST_FILES_EIGEN_I)
if(PYBIND11_TEST_FILES_EIGEN_I GREATER -1)
list(REMOVE_AT PYBIND11_TEST_FILES ${PYBIND11_TEST_FILES_EIGEN_I})
endif()
list(FIND PYBIND11_TEST_FILES test_eigen_tensor.cpp PYBIND11_TEST_FILES_EIGEN_I)
if(PYBIND11_TEST_FILES_EIGEN_I GREATER -1)
list(REMOVE_AT PYBIND11_TEST_FILES ${PYBIND11_TEST_FILES_EIGEN_I})
endif()
list(FIND PYBIND11_TEST_FILES test_eigen_tensor_avoid_stl_array.cpp
PYBIND11_TEST_FILES_EIGEN_I)
if(PYBIND11_TEST_FILES_EIGEN_I GREATER -1)
list(REMOVE_AT PYBIND11_TEST_FILES ${PYBIND11_TEST_FILES_EIGEN_I})
endif()
message(
STATUS "Building tests WITHOUT Eigen, use -DDOWNLOAD_EIGEN=ON on CMake 3.11+ to download")
endif()
endif()
# Some code doesn't support gcc 4
if(CMAKE_CXX_COMPILER_ID STREQUAL "GNU" AND CMAKE_CXX_COMPILER_VERSION VERSION_LESS 5.0)
list(FIND PYBIND11_TEST_FILES test_eigen_tensor.cpp PYBIND11_TEST_FILES_EIGEN_I)
if(PYBIND11_TEST_FILES_EIGEN_I GREATER -1)
list(REMOVE_AT PYBIND11_TEST_FILES ${PYBIND11_TEST_FILES_EIGEN_I})
endif()
list(FIND PYBIND11_TEST_FILES test_eigen_tensor_avoid_stl_array.cpp PYBIND11_TEST_FILES_EIGEN_I)
if(PYBIND11_TEST_FILES_EIGEN_I GREATER -1)
list(REMOVE_AT PYBIND11_TEST_FILES ${PYBIND11_TEST_FILES_EIGEN_I})
endif()
endif()
# Optional dependency for some tests (boost::variant is only supported with version >= 1.56)
find_package(Boost 1.56)

1
tests/conftest.py
View File

@ -210,4 +210,5 @@ def pytest_report_header(config):
f" {pybind11_tests.compiler_info}"
f" {pybind11_tests.cpp_std}"
f" {pybind11_tests.PYBIND11_INTERNALS_ID}"
f" PYBIND11_SIMPLE_GIL_MANAGEMENT={pybind11_tests.PYBIND11_SIMPLE_GIL_MANAGEMENT}"
)

67
tests/cross_module_gil_utils.cpp
View File

@ -6,9 +6,15 @@
All rights reserved. Use of this source code is governed by a
BSD-style license that can be found in the LICENSE file.
*/
#if defined(PYBIND11_INTERNALS_VERSION)
# undef PYBIND11_INTERNALS_VERSION
#endif
#define PYBIND11_INTERNALS_VERSION 21814642 // Ensure this module has its own `internals` instance.
#include <pybind11/pybind11.h>
#include <cstdint>
#include <string>
#include <thread>
// This file mimics a DSO that makes pybind11 calls but does not define a
// PYBIND11_MODULE. The purpose is to test that such a DSO can create a
@ -21,8 +27,54 @@
namespace {
namespace py = pybind11;
void gil_acquire() { py::gil_scoped_acquire gil; }
std::string gil_multi_acquire_release(unsigned bits) {
if ((bits & 0x1u) != 0u) {
py::gil_scoped_acquire gil;
}
if ((bits & 0x2u) != 0u) {
py::gil_scoped_release gil;
}
if ((bits & 0x4u) != 0u) {
py::gil_scoped_acquire gil;
}
if ((bits & 0x8u) != 0u) {
py::gil_scoped_release gil;
}
return PYBIND11_INTERNALS_ID;
}
struct CustomAutoGIL {
CustomAutoGIL() : gstate(PyGILState_Ensure()) {}
~CustomAutoGIL() { PyGILState_Release(gstate); }
PyGILState_STATE gstate;
};
struct CustomAutoNoGIL {
CustomAutoNoGIL() : save(PyEval_SaveThread()) {}
~CustomAutoNoGIL() { PyEval_RestoreThread(save); }
PyThreadState *save;
};
template <typename Acquire, typename Release>
void gil_acquire_inner() {
Acquire acquire_outer;
Acquire acquire_inner;
Release release;
}
template <typename Acquire, typename Release>
void gil_acquire_nested() {
Acquire acquire_outer;
Acquire acquire_inner;
Release release;
auto thread = std::thread(&gil_acquire_inner<Acquire, Release>);
thread.join();
}
constexpr char kModuleName[] = "cross_module_gil_utils";
struct PyModuleDef moduledef = {
@ -30,6 +82,9 @@ struct PyModuleDef moduledef = {
} // namespace
#define ADD_FUNCTION(Name, ...) \
PyModule_AddObject(m, Name, PyLong_FromVoidPtr(reinterpret_cast<void *>(&__VA_ARGS__)));
extern "C" PYBIND11_EXPORT PyObject *PyInit_cross_module_gil_utils() {
PyObject *m = PyModule_Create(&moduledef);
@ -37,8 +92,16 @@ extern "C" PYBIND11_EXPORT PyObject *PyInit_cross_module_gil_utils() {
if (m != nullptr) {
static_assert(sizeof(&gil_acquire) == sizeof(void *),
"Function pointer must have the same size as void*");
PyModule_AddObject(
m, "gil_acquire_funcaddr", PyLong_FromVoidPtr(reinterpret_cast<void *>(&gil_acquire)));
ADD_FUNCTION("gil_acquire_funcaddr", gil_acquire)
ADD_FUNCTION("gil_multi_acquire_release_funcaddr", gil_multi_acquire_release)
ADD_FUNCTION("gil_acquire_inner_custom_funcaddr",
gil_acquire_inner<CustomAutoGIL, CustomAutoNoGIL>)
ADD_FUNCTION("gil_acquire_nested_custom_funcaddr",
gil_acquire_nested<CustomAutoGIL, CustomAutoNoGIL>)
ADD_FUNCTION("gil_acquire_inner_pybind11_funcaddr",
gil_acquire_inner<py::gil_scoped_acquire, py::gil_scoped_release>)
ADD_FUNCTION("gil_acquire_nested_pybind11_funcaddr",
gil_acquire_nested<py::gil_scoped_acquire, py::gil_scoped_release>)
}
return m;

8
tests/extra_python_package/test_files.py
View File

@ -55,6 +55,11 @@ detail_headers = {
"include/pybind11/detail/typeid.h",
}
eigen_headers = {
"include/pybind11/eigen/matrix.h",
"include/pybind11/eigen/tensor.h",
}
stl_headers = {
"include/pybind11/stl/filesystem.h",
}
@ -82,7 +87,7 @@ py_files = {
"setup_helpers.py",
}
headers = main_headers | detail_headers | stl_headers
headers = main_headers | detail_headers | eigen_headers | stl_headers
src_files = headers | cmake_files | pkgconfig_files
all_files = src_files | py_files
@ -92,6 +97,7 @@ sdist_files = {
"pybind11/include",
"pybind11/include/pybind11",
"pybind11/include/pybind11/detail",
"pybind11/include/pybind11/eigen",
"pybind11/include/pybind11/stl",
"pybind11/share",
"pybind11/share/cmake",

6
tests/pybind11_tests.cpp
View File

@ -89,6 +89,12 @@ PYBIND11_MODULE(pybind11_tests, m) {
#endif
m.attr("cpp_std") = cpp_std();
m.attr("PYBIND11_INTERNALS_ID") = PYBIND11_INTERNALS_ID;
m.attr("PYBIND11_SIMPLE_GIL_MANAGEMENT") =
#if defined(PYBIND11_SIMPLE_GIL_MANAGEMENT)
true;
#else
false;
#endif
bind_ConstructorStats(m);

37
tests/test_callbacks.cpp
View File

@ -240,4 +240,41 @@ TEST_SUBMODULE(callbacks, m) {
f();
}
});
auto *custom_def = []() {
static PyMethodDef def;
def.ml_name = "example_name";
def.ml_doc = "Example doc";
def.ml_meth = [](PyObject *, PyObject *args) -> PyObject * {
if (PyTuple_Size(args) != 1) {
throw std::runtime_error("Invalid number of arguments for example_name");
}
PyObject *first = PyTuple_GetItem(args, 0);
if (!PyLong_Check(first)) {
throw std::runtime_error("Invalid argument to example_name");
}
auto result = py::cast(PyLong_AsLong(first) * 9);
return result.release().ptr();
};
def.ml_flags = METH_VARARGS;
return &def;
}();
// rec_capsule with name that has the same value (but not pointer) as our internal one
// This capsule should be detected by our code as foreign and not inspected as the pointers
// shouldn't match
constexpr const char *rec_capsule_name
= pybind11::detail::internals_function_record_capsule_name;
py::capsule rec_capsule(std::malloc(1), [](void *data) { std::free(data); });
rec_capsule.set_name(rec_capsule_name);
m.add_object("custom_function", PyCFunction_New(custom_def, rec_capsule.ptr()));
// This test requires a new ABI version to pass
#if PYBIND11_INTERNALS_VERSION > 4
// rec_capsule with nullptr name
py::capsule rec_capsule2(std::malloc(1), [](void *data) { std::free(data); });
m.add_object("custom_function2", PyCFunction_New(custom_def, rec_capsule2.ptr()));
#else
m.add_object("custom_function2", py::none());
#endif
}

13
tests/test_callbacks.py
View File

@ -193,3 +193,16 @@ def test_callback_num_times():
if len(rates) > 1:
print("Min Mean Max")
print(f"{min(rates):6.3f} {sum(rates) / len(rates):6.3f} {max(rates):6.3f}")
def test_custom_func():
assert m.custom_function(4) == 36
assert m.roundtrip(m.custom_function)(4) == 36
@pytest.mark.skipif(
m.custom_function2 is None, reason="Current PYBIND11_INTERNALS_VERSION too low"
)
def test_custom_func2():
assert m.custom_function2(3) == 27
assert m.roundtrip(m.custom_function2)(3) == 27

18
tests/test_class.cpp
View File

@ -392,6 +392,8 @@ TEST_SUBMODULE(class_, m) {
protected:
virtual int foo() const { return value; }
virtual void *void_foo() { return static_cast<void *>(&value); }
virtual void *get_self() { return static_cast<void *>(this); }
private:
int value = 42;
@ -400,6 +402,8 @@ TEST_SUBMODULE(class_, m) {
class TrampolineB : public ProtectedB {
public:
int foo() const override { PYBIND11_OVERRIDE(int, ProtectedB, foo, ); }
void *void_foo() override { PYBIND11_OVERRIDE(void *, ProtectedB, void_foo, ); }
void *get_self() override { PYBIND11_OVERRIDE(void *, ProtectedB, get_self, ); }
};
class PublicistB : public ProtectedB {
@ -409,11 +413,23 @@ TEST_SUBMODULE(class_, m) {
// (in Debug builds only, tested with icpc (ICC) 2021.1 Beta 20200827)
~PublicistB() override{}; // NOLINT(modernize-use-equals-default)
using ProtectedB::foo;
using ProtectedB::get_self;
using ProtectedB::void_foo;
};
m.def("read_foo", [](const void *original) {
const int *ptr = reinterpret_cast<const int *>(original);
return *ptr;
});
m.def("pointers_equal",
[](const void *original, const void *comparison) { return original == comparison; });
py::class_<ProtectedB, TrampolineB>(m, "ProtectedB")
.def(py::init<>())
.def("foo", &PublicistB::foo);
.def("foo", &PublicistB::foo)
.def("void_foo", &PublicistB::void_foo)
.def("get_self", &PublicistB::get_self);
// test_brace_initialization
struct BraceInitialization {

2
tests/test_class.py
View File

@ -320,6 +320,8 @@ def test_bind_protected_functions():
b = m.ProtectedB()
assert b.foo() == 42
assert m.read_foo(b.void_foo()) == 42
assert m.pointers_equal(b.get_self(), b)
class C(m.ProtectedB):
def __init__(self):

4
tests/test_eigen.cpp → tests/test_eigen_matrix.cpp
View File

@ -7,7 +7,7 @@
BSD-style license that can be found in the LICENSE file.
*/
#include <pybind11/eigen.h>
#include <pybind11/eigen/matrix.h>
#include <pybind11/stl.h>
#include "constructor_stats.h"
@ -81,7 +81,7 @@ struct CustomOperatorNew {
EIGEN_MAKE_ALIGNED_OPERATOR_NEW;
};
TEST_SUBMODULE(eigen, m) {
TEST_SUBMODULE(eigen_matrix, m) {
using FixedMatrixR = Eigen::Matrix<float, 5, 6, Eigen::RowMajor>;
using FixedMatrixC = Eigen::Matrix<float, 5, 6>;
using DenseMatrixR = Eigen::Matrix<float, Eigen::Dynamic, Eigen::Dynamic, Eigen::RowMajor>;

2
tests/test_eigen.py → tests/test_eigen_matrix.py
View File

@ -3,7 +3,7 @@ import pytest
from pybind11_tests import ConstructorStats
np = pytest.importorskip("numpy")
m = pytest.importorskip("pybind11_tests.eigen")
m = pytest.importorskip("pybind11_tests.eigen_matrix")
ref = np.array(

16
tests/test_eigen_tensor.cpp Normal file
View File

@ -0,0 +1,16 @@
/*
tests/eigen_tensor.cpp -- automatic conversion of Eigen Tensor
All rights reserved. Use of this source code is governed by a
BSD-style license that can be found in the LICENSE file.
*/
constexpr const char *test_eigen_tensor_module_name = "eigen_tensor";
#define PYBIND11_TEST_EIGEN_TENSOR_NAMESPACE eigen_tensor
#ifdef EIGEN_AVOID_STL_ARRAY
# undef EIGEN_AVOID_STL_ARRAY
#endif
#include "test_eigen_tensor.inl"

333
tests/test_eigen_tensor.inl Normal file
View File

@ -0,0 +1,333 @@
/*
tests/eigen_tensor.cpp -- automatic conversion of Eigen Tensor
All rights reserved. Use of this source code is governed by a
BSD-style license that can be found in the LICENSE file.
*/
#include <pybind11/eigen/tensor.h>
#include "pybind11_tests.h"
namespace PYBIND11_TEST_EIGEN_TENSOR_NAMESPACE {
template <typename M>
void reset_tensor(M &x) {
for (int i = 0; i < x.dimension(0); i++) {
for (int j = 0; j < x.dimension(1); j++) {
for (int k = 0; k < x.dimension(2); k++) {
x(i, j, k) = i * (5 * 2) + j * 2 + k;
}
}
}
}
template <typename M>
bool check_tensor(M &x) {
for (int i = 0; i < x.dimension(0); i++) {
for (int j = 0; j < x.dimension(1); j++) {
for (int k = 0; k < x.dimension(2); k++) {
if (x(i, j, k) != (i * (5 * 2) + j * 2 + k)) {
return false;
}
}
}
}
return true;
}
template <int Options>
Eigen::Tensor<double, 3, Options> &get_tensor() {
static Eigen::Tensor<double, 3, Options> *x;
if (!x) {
x = new Eigen::Tensor<double, 3, Options>(3, 5, 2);
reset_tensor(*x);
}
return *x;
}
template <int Options>
Eigen::TensorMap<Eigen::Tensor<double, 3, Options>> &get_tensor_map() {
static Eigen::TensorMap<Eigen::Tensor<double, 3, Options>> *x;
if (!x) {
x = new Eigen::TensorMap<Eigen::Tensor<double, 3, Options>>(get_tensor<Options>());
}
return *x;
}
template <int Options>
Eigen::TensorFixedSize<double, Eigen::Sizes<3, 5, 2>, Options> &get_fixed_tensor() {
static Eigen::TensorFixedSize<double, Eigen::Sizes<3, 5, 2>, Options> *x;
if (!x) {
Eigen::aligned_allocator<Eigen::TensorFixedSize<double, Eigen::Sizes<3, 5, 2>, Options>>
allocator;
x = new (allocator.allocate(1))
Eigen::TensorFixedSize<double, Eigen::Sizes<3, 5, 2>, Options>();
reset_tensor(*x);
}
return *x;
}
template <int Options>
const Eigen::Tensor<double, 3, Options> &get_const_tensor() {
return get_tensor<Options>();
}
template <int Options>
struct CustomExample {
CustomExample() : member(get_tensor<Options>()), view_member(member) {}
Eigen::Tensor<double, 3, Options> member;
Eigen::TensorMap<Eigen::Tensor<double, 3, Options>> view_member;
};
template <int Options>
void init_tensor_module(pybind11::module &m) {
const char *needed_options = "";
if (PYBIND11_SILENCE_MSVC_C4127(Options == Eigen::ColMajor)) {
needed_options = "F";
} else {
needed_options = "C";
}
m.attr("needed_options") = needed_options;
m.def("setup", []() {
reset_tensor(get_tensor<Options>());
reset_tensor(get_fixed_tensor<Options>());
});
m.def("is_ok", []() {
return check_tensor(get_tensor<Options>()) && check_tensor(get_fixed_tensor<Options>());
});
py::class_<CustomExample<Options>>(m, "CustomExample")
.def(py::init<>())
.def_readonly(
"member", &CustomExample<Options>::member, py::return_value_policy::reference_internal)
.def_readonly("member_view",
&CustomExample<Options>::view_member,
py::return_value_policy::reference_internal);
m.def(
"copy_fixed_tensor",
[]() { return &get_fixed_tensor<Options>(); },
py::return_value_policy::copy);
m.def(
"copy_tensor", []() { return &get_tensor<Options>(); }, py::return_value_policy::copy);
m.def(
"copy_const_tensor",
[]() { return &get_const_tensor<Options>(); },
py::return_value_policy::copy);
m.def(
"move_fixed_tensor_copy",
[]() -> Eigen::TensorFixedSize<double, Eigen::Sizes<3, 5, 2>, Options> {
return get_fixed_tensor<Options>();
},
py::return_value_policy::move);
m.def(
"move_tensor_copy",
[]() -> Eigen::Tensor<double, 3, Options> { return get_tensor<Options>(); },
py::return_value_policy::move);
m.def(
"move_const_tensor",
[]() -> const Eigen::Tensor<double, 3, Options> & { return get_const_tensor<Options>(); },
py::return_value_policy::move);
m.def(
"take_fixed_tensor",
[]() {
Eigen::aligned_allocator<
Eigen::TensorFixedSize<double, Eigen::Sizes<3, 5, 2>, Options>>
allocator;
return new (allocator.allocate(1))
Eigen::TensorFixedSize<double, Eigen::Sizes<3, 5, 2>, Options>(
get_fixed_tensor<Options>());
},
py::return_value_policy::take_ownership);
m.def(
"take_tensor",
[]() { return new Eigen::Tensor<double, 3, Options>(get_tensor<Options>()); },
py::return_value_policy::take_ownership);
m.def(
"take_const_tensor",
[]() -> const Eigen::Tensor<double, 3, Options> * {
return new Eigen::Tensor<double, 3, Options>(get_tensor<Options>());
},
py::return_value_policy::take_ownership);
m.def(
"take_view_tensor",
[]() -> const Eigen::TensorMap<Eigen::Tensor<double, 3, Options>> * {
return new Eigen::TensorMap<Eigen::Tensor<double, 3, Options>>(get_tensor<Options>());
},
py::return_value_policy::take_ownership);
m.def(
"reference_tensor",
[]() { return &get_tensor<Options>(); },
py::return_value_policy::reference);
m.def(
"reference_tensor_v2",
[]() -> Eigen::Tensor<double, 3, Options> & { return get_tensor<Options>(); },
py::return_value_policy::reference);
m.def(
"reference_tensor_internal",
[]() { return &get_tensor<Options>(); },
py::return_value_policy::reference_internal);
m.def(
"reference_fixed_tensor",
[]() { return &get_tensor<Options>(); },
py::return_value_policy::reference);
m.def(
"reference_const_tensor",
[]() { return &get_const_tensor<Options>(); },
py::return_value_policy::reference);
m.def(
"reference_const_tensor_v2",
[]() -> const Eigen::Tensor<double, 3, Options> & { return get_const_tensor<Options>(); },
py::return_value_policy::reference);
m.def(
"reference_view_of_tensor",
[]() -> Eigen::TensorMap<Eigen::Tensor<double, 3, Options>> {
return get_tensor_map<Options>();
},
py::return_value_policy::reference);
m.def(
"reference_view_of_tensor_v2",
// NOLINTNEXTLINE(readability-const-return-type)
[]() -> const Eigen::TensorMap<Eigen::Tensor<double, 3, Options>> {
return get_tensor_map<Options>(); // NOLINT(readability-const-return-type)
}, // NOLINT(readability-const-return-type)
py::return_value_policy::reference);
m.def(
"reference_view_of_tensor_v3",
[]() -> Eigen::TensorMap<Eigen::Tensor<double, 3, Options>> * {
return &get_tensor_map<Options>();
},
py::return_value_policy::reference);
m.def(
"reference_view_of_tensor_v4",
[]() -> const Eigen::TensorMap<Eigen::Tensor<double, 3, Options>> * {
return &get_tensor_map<Options>();
},
py::return_value_policy::reference);
m.def(
"reference_view_of_tensor_v5",
[]() -> Eigen::TensorMap<Eigen::Tensor<double, 3, Options>> & {
return get_tensor_map<Options>();
},
py::return_value_policy::reference);
m.def(
"reference_view_of_tensor_v6",
[]() -> const Eigen::TensorMap<Eigen::Tensor<double, 3, Options>> & {
return get_tensor_map<Options>();
},
py::return_value_policy::reference);
m.def(
"reference_view_of_fixed_tensor",
[]() {
return Eigen::TensorMap<
Eigen::TensorFixedSize<double, Eigen::Sizes<3, 5, 2>, Options>>(
get_fixed_tensor<Options>());
},
py::return_value_policy::reference);
m.def("round_trip_tensor",
[](const Eigen::Tensor<double, 3, Options> &tensor) { return tensor; });
m.def(
"round_trip_tensor_noconvert",
[](const Eigen::Tensor<double, 3, Options> &tensor) { return tensor; },
py::arg("tensor").noconvert());
m.def("round_trip_tensor2",
[](const Eigen::Tensor<int32_t, 3, Options> &tensor) { return tensor; });
m.def("round_trip_fixed_tensor",
[](const Eigen::TensorFixedSize<double, Eigen::Sizes<3, 5, 2>, Options> &tensor) {
return tensor;
});
m.def(
"round_trip_view_tensor",
[](Eigen::TensorMap<Eigen::Tensor<double, 3, Options>> view) { return view; },
py::return_value_policy::reference);
m.def(
"round_trip_view_tensor_ref",
[](Eigen::TensorMap<Eigen::Tensor<double, 3, Options>> &view) { return view; },
py::return_value_policy::reference);
m.def(
"round_trip_view_tensor_ptr",
[](Eigen::TensorMap<Eigen::Tensor<double, 3, Options>> *view) { return view; },
py::return_value_policy::reference);
m.def(
"round_trip_aligned_view_tensor",
[](Eigen::TensorMap<Eigen::Tensor<double, 3, Options>, Eigen::Aligned> view) {
return view;
},
py::return_value_policy::reference);
m.def(
"round_trip_const_view_tensor",
[](Eigen::TensorMap<const Eigen::Tensor<double, 3, Options>> view) {
return Eigen::Tensor<double, 3, Options>(view);
},
py::return_value_policy::move);
m.def(
"round_trip_rank_0",
[](const Eigen::Tensor<double, 0, Options> &tensor) { return tensor; },
py::return_value_policy::move);
m.def(
"round_trip_rank_0_noconvert",
[](const Eigen::Tensor<double, 0, Options> &tensor) { return tensor; },
py::arg("tensor").noconvert(),
py::return_value_policy::move);
m.def(
"round_trip_rank_0_view",
[](Eigen::TensorMap<Eigen::Tensor<double, 0, Options>> &tensor) { return tensor; },
py::return_value_policy::reference);
}
void test_module(py::module_ &);
test_initializer name(test_eigen_tensor_module_name, test_module);
void test_module(py::module_ &m) {
auto f_style = m.def_submodule("f_style");
auto c_style = m.def_submodule("c_style");
init_tensor_module<Eigen::ColMajor>(f_style);
init_tensor_module<Eigen::RowMajor>(c_style);
}
} // namespace PYBIND11_TEST_EIGEN_TENSOR_NAMESPACE

296
tests/test_eigen_tensor.py Normal file
View File

@ -0,0 +1,296 @@
import sys
import pytest
np = pytest.importorskip("numpy")
eigen_tensor = pytest.importorskip("pybind11_tests.eigen_tensor")
submodules = [eigen_tensor.c_style, eigen_tensor.f_style]
try:
from pybind11_tests import eigen_tensor_avoid_stl_array as avoid
submodules += [avoid.c_style, avoid.f_style]
except ImportError as e:
# Ensure config, build, toolchain, etc. issues are not masked here:
raise RuntimeError(
"import pybind11_tests.eigen_tensor_avoid_stl_array FAILED, while "
"import pybind11_tests.eigen_tensor succeeded. "
"Please ensure that "
"test_eigen_tensor.cpp & "
"test_eigen_tensor_avoid_stl_array.cpp "
"are built together (or both are not built if Eigen is not available)."
) from e
tensor_ref = np.empty((3, 5, 2), dtype=np.int64)
for i in range(tensor_ref.shape[0]):
for j in range(tensor_ref.shape[1]):
for k in range(tensor_ref.shape[2]):
tensor_ref[i, j, k] = i * (5 * 2) + j * 2 + k
indices = (2, 3, 1)
@pytest.fixture(autouse=True)
def cleanup():
for module in submodules:
module.setup()
yield
for module in submodules:
assert module.is_ok()
def test_import_avoid_stl_array():
pytest.importorskip("pybind11_tests.eigen_tensor_avoid_stl_array")
assert len(submodules) == 4
def assert_equal_tensor_ref(mat, writeable=True, modified=None):
assert mat.flags.writeable == writeable
copy = np.array(tensor_ref)
if modified is not None:
copy[indices] = modified
np.testing.assert_array_equal(mat, copy)
@pytest.mark.parametrize("m", submodules)
@pytest.mark.parametrize("member_name", ["member", "member_view"])
def test_reference_internal(m, member_name):
if not hasattr(sys, "getrefcount"):
pytest.skip("No reference counting")
foo = m.CustomExample()
counts = sys.getrefcount(foo)
mem = getattr(foo, member_name)
assert_equal_tensor_ref(mem, writeable=False)
new_counts = sys.getrefcount(foo)
assert new_counts == counts + 1
assert_equal_tensor_ref(mem, writeable=False)
del mem
assert sys.getrefcount(foo) == counts
assert_equal_funcs = [
"copy_tensor",
"copy_fixed_tensor",
"copy_const_tensor",
"move_tensor_copy",
"move_fixed_tensor_copy",
"take_tensor",
"take_fixed_tensor",
"reference_tensor",
"reference_tensor_v2",
"reference_fixed_tensor",
"reference_view_of_tensor",
"reference_view_of_tensor_v3",
"reference_view_of_tensor_v5",
"reference_view_of_fixed_tensor",
]
assert_equal_const_funcs = [
"reference_view_of_tensor_v2",
"reference_view_of_tensor_v4",
"reference_view_of_tensor_v6",
"reference_const_tensor",
"reference_const_tensor_v2",
]
@pytest.mark.parametrize("m", submodules)
@pytest.mark.parametrize("func_name", assert_equal_funcs + assert_equal_const_funcs)
def test_convert_tensor_to_py(m, func_name):
writeable = func_name in assert_equal_funcs
assert_equal_tensor_ref(getattr(m, func_name)(), writeable=writeable)
@pytest.mark.parametrize("m", submodules)
def test_bad_cpp_to_python_casts(m):
with pytest.raises(
RuntimeError, match="Cannot use reference internal when there is no parent"
):
m.reference_tensor_internal()
with pytest.raises(RuntimeError, match="Cannot move from a constant reference"):
m.move_const_tensor()
with pytest.raises(
RuntimeError, match="Cannot take ownership of a const reference"
):
m.take_const_tensor()
with pytest.raises(
RuntimeError,
match="Invalid return_value_policy for Eigen Map type, must be either reference or reference_internal",
):
m.take_view_tensor()
@pytest.mark.parametrize("m", submodules)
def test_bad_python_to_cpp_casts(m):
with pytest.raises(
TypeError, match=r"^round_trip_tensor\(\): incompatible function arguments"
):
m.round_trip_tensor(np.zeros((2, 3)))
with pytest.raises(TypeError, match=r"^Cannot cast array data from dtype"):
m.round_trip_tensor(np.zeros(dtype=np.str_, shape=(2, 3, 1)))
with pytest.raises(
TypeError,
match=r"^round_trip_tensor_noconvert\(\): incompatible function arguments",
):
m.round_trip_tensor_noconvert(tensor_ref)
assert_equal_tensor_ref(
m.round_trip_tensor_noconvert(tensor_ref.astype(np.float64))
)
if m.needed_options == "F":
bad_options = "C"
else:
bad_options = "F"
# Shape, dtype and the order need to be correct for a TensorMap cast
with pytest.raises(
TypeError, match=r"^round_trip_view_tensor\(\): incompatible function arguments"
):
m.round_trip_view_tensor(
np.zeros((3, 5, 2), dtype=np.float64, order=bad_options)
)
with pytest.raises(
TypeError, match=r"^round_trip_view_tensor\(\): incompatible function arguments"
):
m.round_trip_view_tensor(
np.zeros((3, 5, 2), dtype=np.float32, order=m.needed_options)
)
with pytest.raises(
TypeError, match=r"^round_trip_view_tensor\(\): incompatible function arguments"
):
m.round_trip_view_tensor(
np.zeros((3, 5), dtype=np.float64, order=m.needed_options)
)
with pytest.raises(
TypeError, match=r"^round_trip_view_tensor\(\): incompatible function arguments"
):
temp = np.zeros((3, 5, 2), dtype=np.float64, order=m.needed_options)
m.round_trip_view_tensor(
temp[:, ::-1, :],
)
with pytest.raises(
TypeError, match=r"^round_trip_view_tensor\(\): incompatible function arguments"
):
temp = np.zeros((3, 5, 2), dtype=np.float64, order=m.needed_options)
temp.setflags(write=False)
m.round_trip_view_tensor(temp)
@pytest.mark.parametrize("m", submodules)
def test_references_actually_refer(m):
a = m.reference_tensor()
temp = a[indices]
a[indices] = 100
assert_equal_tensor_ref(m.copy_const_tensor(), modified=100)
a[indices] = temp
assert_equal_tensor_ref(m.copy_const_tensor())
a = m.reference_view_of_tensor()
a[indices] = 100
assert_equal_tensor_ref(m.copy_const_tensor(), modified=100)
a[indices] = temp
assert_equal_tensor_ref(m.copy_const_tensor())
@pytest.mark.parametrize("m", submodules)
def test_round_trip(m):
assert_equal_tensor_ref(m.round_trip_tensor(tensor_ref))
with pytest.raises(TypeError, match="^Cannot cast array data from"):
assert_equal_tensor_ref(m.round_trip_tensor2(tensor_ref))
assert_equal_tensor_ref(m.round_trip_tensor2(np.array(tensor_ref, dtype=np.int32)))
assert_equal_tensor_ref(m.round_trip_fixed_tensor(tensor_ref))
assert_equal_tensor_ref(m.round_trip_aligned_view_tensor(m.reference_tensor()))
copy = np.array(tensor_ref, dtype=np.float64, order=m.needed_options)
assert_equal_tensor_ref(m.round_trip_view_tensor(copy))
assert_equal_tensor_ref(m.round_trip_view_tensor_ref(copy))
assert_equal_tensor_ref(m.round_trip_view_tensor_ptr(copy))
copy.setflags(write=False)
assert_equal_tensor_ref(m.round_trip_const_view_tensor(copy))
np.testing.assert_array_equal(
tensor_ref[:, ::-1, :], m.round_trip_tensor(tensor_ref[:, ::-1, :])
)
assert m.round_trip_rank_0(np.float64(3.5)) == 3.5
assert m.round_trip_rank_0(3.5) == 3.5
with pytest.raises(
TypeError,
match=r"^round_trip_rank_0_noconvert\(\): incompatible function arguments",
):
m.round_trip_rank_0_noconvert(np.float64(3.5))
with pytest.raises(
TypeError,
match=r"^round_trip_rank_0_noconvert\(\): incompatible function arguments",
):
m.round_trip_rank_0_noconvert(3.5)
with pytest.raises(
TypeError, match=r"^round_trip_rank_0_view\(\): incompatible function arguments"
):
m.round_trip_rank_0_view(np.float64(3.5))
with pytest.raises(
TypeError, match=r"^round_trip_rank_0_view\(\): incompatible function arguments"
):
m.round_trip_rank_0_view(3.5)
@pytest.mark.parametrize("m", submodules)
def test_round_trip_references_actually_refer(m):
# Need to create a copy that matches the type on the C side
copy = np.array(tensor_ref, dtype=np.float64, order=m.needed_options)
a = m.round_trip_view_tensor(copy)
temp = a[indices]
a[indices] = 100
assert_equal_tensor_ref(copy, modified=100)
a[indices] = temp
assert_equal_tensor_ref(copy)
@pytest.mark.parametrize("m", submodules)
def test_doc_string(m, doc):
assert (
doc(m.copy_tensor) == "copy_tensor() -> numpy.ndarray[numpy.float64[?, ?, ?]]"
)
assert (
doc(m.copy_fixed_tensor)
== "copy_fixed_tensor() -> numpy.ndarray[numpy.float64[3, 5, 2]]"
)
assert (
doc(m.reference_const_tensor)
== "reference_const_tensor() -> numpy.ndarray[numpy.float64[?, ?, ?]]"
)
order_flag = f"flags.{m.needed_options.lower()}_contiguous"
assert doc(m.round_trip_view_tensor) == (
f"round_trip_view_tensor(arg0: numpy.ndarray[numpy.float64[?, ?, ?], flags.writeable, {order_flag}])"
+ f" -> numpy.ndarray[numpy.float64[?, ?, ?], flags.writeable, {order_flag}]"
)
assert doc(m.round_trip_const_view_tensor) == (
f"round_trip_const_view_tensor(arg0: numpy.ndarray[numpy.float64[?, ?, ?], {order_flag}])"
+ " -> numpy.ndarray[numpy.float64[?, ?, ?]]"
)

16
tests/test_eigen_tensor_avoid_stl_array.cpp Normal file
View File

@ -0,0 +1,16 @@
/*
tests/eigen_tensor.cpp -- automatic conversion of Eigen Tensor
All rights reserved. Use of this source code is governed by a
BSD-style license that can be found in the LICENSE file.
*/
constexpr const char *test_eigen_tensor_module_name = "eigen_tensor_avoid_stl_array";
#ifndef EIGEN_AVOID_STL_ARRAY
# define EIGEN_AVOID_STL_ARRAY
#endif
#define PYBIND11_TEST_EIGEN_TENSOR_NAMESPACE eigen_tensor_avoid_stl_array
#include "test_eigen_tensor.inl"

1
tests/test_embed/test_interpreter.cpp
View File

@ -293,7 +293,6 @@ TEST_CASE("Threads") {
{
py::gil_scoped_release gil_release{};
REQUIRE(has_pybind11_internals_static());
auto threads = std::vector<std::thread>();
for (auto i = 0; i < num_threads; ++i) {

5
tests/test_exceptions.cpp
View File

@ -105,11 +105,6 @@ struct PythonAlreadySetInDestructor {
py::str s;
};
std::string error_already_set_what(const py::object &exc_type, const py::object &exc_value) {
PyErr_SetObject(exc_type.ptr(), exc_value.ptr());
return py::error_already_set().what();
}
TEST_SUBMODULE(exceptions, m) {
m.def("throw_std_exception",
[]() { throw std::runtime_error("This exception was intentionally thrown."); });

14
tests/test_exceptions.py
View File

@ -275,6 +275,20 @@ def test_local_translator(msg):
assert msg(excinfo.value) == "this mod"
def test_error_already_set_message_with_unicode_surrogate(): # Issue #4288
assert m.error_already_set_what(RuntimeError, "\ud927") == (
"RuntimeError: \\ud927",
False,
)
def test_error_already_set_message_with_malformed_utf8():
assert m.error_already_set_what(RuntimeError, b"\x80") == (
"RuntimeError: b'\\x80'",
False,
)
class FlakyException(Exception):
def __init__(self, failure_point):
if failure_point == "failure_point_init":

107
tests/test_gil_scoped.cpp
View File

@ -11,6 +11,13 @@
#include "pybind11_tests.h"
#include <string>
#include <thread>
#define CROSS_MODULE(Function) \
auto cm = py::module_::import("cross_module_gil_utils"); \
auto target = reinterpret_cast<void (*)()>(PyLong_AsVoidPtr(cm.attr(Function).ptr()));
class VirtClass {
public:
virtual ~VirtClass() = default;
@ -28,6 +35,16 @@ class PyVirtClass : public VirtClass {
};
TEST_SUBMODULE(gil_scoped, m) {
m.attr("defined_THREAD_SANITIZER") =
#if defined(THREAD_SANITIZER)
true;
#else
false;
#endif
m.def("intentional_deadlock",
[]() { std::thread([]() { py::gil_scoped_acquire gil_acquired; }).join(); });
py::class_<VirtClass, PyVirtClass>(m, "VirtClass")
.def(py::init<>())
.def("virtual_func", &VirtClass::virtual_func)
@ -37,11 +54,91 @@ TEST_SUBMODULE(gil_scoped, m) {
m.def("test_callback_std_func", [](const std::function<void()> &func) { func(); });
m.def("test_callback_virtual_func", [](VirtClass &virt) { virt.virtual_func(); });
m.def("test_callback_pure_virtual_func", [](VirtClass &virt) { virt.pure_virtual_func(); });
m.def("test_cross_module_gil", []() {
auto cm = py::module_::import("cross_module_gil_utils");
auto gil_acquire = reinterpret_cast<void (*)()>(
PyLong_AsVoidPtr(cm.attr("gil_acquire_funcaddr").ptr()));
m.def("test_cross_module_gil_released", []() {
CROSS_MODULE("gil_acquire_funcaddr")
py::gil_scoped_release gil_release;
gil_acquire();
target();
});
m.def("test_cross_module_gil_acquired", []() {
CROSS_MODULE("gil_acquire_funcaddr")
py::gil_scoped_acquire gil_acquire;
target();
});
m.def("test_cross_module_gil_inner_custom_released", []() {
CROSS_MODULE("gil_acquire_inner_custom_funcaddr")
py::gil_scoped_release gil_release;
target();
});
m.def("test_cross_module_gil_inner_custom_acquired", []() {
CROSS_MODULE("gil_acquire_inner_custom_funcaddr")
py::gil_scoped_acquire gil_acquire;
target();
});
m.def("test_cross_module_gil_inner_pybind11_released", []() {
CROSS_MODULE("gil_acquire_inner_pybind11_funcaddr")
py::gil_scoped_release gil_release;
target();
});
m.def("test_cross_module_gil_inner_pybind11_acquired", []() {
CROSS_MODULE("gil_acquire_inner_pybind11_funcaddr")
py::gil_scoped_acquire gil_acquire;
target();
});
m.def("test_cross_module_gil_nested_custom_released", []() {
CROSS_MODULE("gil_acquire_nested_custom_funcaddr")
py::gil_scoped_release gil_release;
target();
});
m.def("test_cross_module_gil_nested_custom_acquired", []() {
CROSS_MODULE("gil_acquire_nested_custom_funcaddr")
py::gil_scoped_acquire gil_acquire;
target();
});
m.def("test_cross_module_gil_nested_pybind11_released", []() {
CROSS_MODULE("gil_acquire_nested_pybind11_funcaddr")
py::gil_scoped_release gil_release;
target();
});
m.def("test_cross_module_gil_nested_pybind11_acquired", []() {
CROSS_MODULE("gil_acquire_nested_pybind11_funcaddr")
py::gil_scoped_acquire gil_acquire;
target();
});
m.def("test_release_acquire", [](const py::object &obj) {
py::gil_scoped_release gil_released;
py::gil_scoped_acquire gil_acquired;
return py::str(obj);
});
m.def("test_nested_acquire", [](const py::object &obj) {
py::gil_scoped_release gil_released;
py::gil_scoped_acquire gil_acquired_outer;
py::gil_scoped_acquire gil_acquired_inner;
return py::str(obj);
});
m.def("test_multi_acquire_release_cross_module", [](unsigned bits) {
py::set internals_ids;
internals_ids.add(PYBIND11_INTERNALS_ID);
{
py::gil_scoped_release gil_released;
auto thread_f = [bits, &internals_ids]() {
py::gil_scoped_acquire gil_acquired;
auto cm = py::module_::import("cross_module_gil_utils");
auto target = reinterpret_cast<std::string (*)(unsigned)>(
PyLong_AsVoidPtr(cm.attr("gil_multi_acquire_release_funcaddr").ptr()));
std::string cm_internals_id = target(bits >> 3);
internals_ids.add(cm_internals_id);
};
if ((bits & 0x1u) != 0u) {
thread_f();
}
if ((bits & 0x2u) != 0u) {
std::thread non_python_thread(thread_f);
non_python_thread.join();
}
if ((bits & 0x4u) != 0u) {
thread_f();
}
}
return internals_ids;
});
}

223
tests/test_gil_scoped.py
View File

@ -1,26 +1,13 @@
import multiprocessing
import sys
import threading
import time
import pytest
from pybind11_tests import gil_scoped as m
def _run_in_process(target, *args, **kwargs):
"""Runs target in process and returns its exitcode after 10s (None if still alive)."""
process = multiprocessing.Process(target=target, args=args, kwargs=kwargs)
process.daemon = True
try:
process.start()
# Do not need to wait much, 10s should be more than enough.
process.join(timeout=10)
return process.exitcode
finally:
if process.is_alive():
process.terminate()
def _python_to_cpp_to_python():
"""Calls different C++ functions that come back to Python."""
class ExtendedVirtClass(m.VirtClass):
def virtual_func(self):
pass
@ -28,18 +15,185 @@ def _python_to_cpp_to_python():
def pure_virtual_func(self):
pass
extended = ExtendedVirtClass()
def test_callback_py_obj():
m.test_callback_py_obj(lambda: None)
def test_callback_std_func():
m.test_callback_std_func(lambda: None)
def test_callback_virtual_func():
extended = ExtendedVirtClass()
m.test_callback_virtual_func(extended)
def test_callback_pure_virtual_func():
extended = ExtendedVirtClass()
m.test_callback_pure_virtual_func(extended)
def _python_to_cpp_to_python_from_threads(num_threads, parallel=False):
"""Calls different C++ functions that come back to Python, from Python threads."""
def test_cross_module_gil_released():
"""Makes sure that the GIL can be acquired by another module from a GIL-released state."""
m.test_cross_module_gil_released() # Should not raise a SIGSEGV
def test_cross_module_gil_acquired():
"""Makes sure that the GIL can be acquired by another module from a GIL-acquired state."""
m.test_cross_module_gil_acquired() # Should not raise a SIGSEGV
def test_cross_module_gil_inner_custom_released():
"""Makes sure that the GIL can be acquired/released by another module
from a GIL-released state using custom locking logic."""
m.test_cross_module_gil_inner_custom_released()
def test_cross_module_gil_inner_custom_acquired():
"""Makes sure that the GIL can be acquired/acquired by another module
from a GIL-acquired state using custom locking logic."""
m.test_cross_module_gil_inner_custom_acquired()
def test_cross_module_gil_inner_pybind11_released():
"""Makes sure that the GIL can be acquired/released by another module
from a GIL-released state using pybind11 locking logic."""
m.test_cross_module_gil_inner_pybind11_released()
def test_cross_module_gil_inner_pybind11_acquired():
"""Makes sure that the GIL can be acquired/acquired by another module
from a GIL-acquired state using pybind11 locking logic."""
m.test_cross_module_gil_inner_pybind11_acquired()
def test_cross_module_gil_nested_custom_released():
"""Makes sure that the GIL can be nested acquired/released by another module
from a GIL-released state using custom locking logic."""
m.test_cross_module_gil_nested_custom_released()
def test_cross_module_gil_nested_custom_acquired():
"""Makes sure that the GIL can be nested acquired/acquired by another module
from a GIL-acquired state using custom locking logic."""
m.test_cross_module_gil_nested_custom_acquired()
def test_cross_module_gil_nested_pybind11_released():
"""Makes sure that the GIL can be nested acquired/released by another module
from a GIL-released state using pybind11 locking logic."""
m.test_cross_module_gil_nested_pybind11_released()
def test_cross_module_gil_nested_pybind11_acquired():
"""Makes sure that the GIL can be nested acquired/acquired by another module
from a GIL-acquired state using pybind11 locking logic."""
m.test_cross_module_gil_nested_pybind11_acquired()
def test_release_acquire():
assert m.test_release_acquire(0xAB) == "171"
def test_nested_acquire():
assert m.test_nested_acquire(0xAB) == "171"
def test_multi_acquire_release_cross_module():
for bits in range(16 * 8):
internals_ids = m.test_multi_acquire_release_cross_module(bits)
assert len(internals_ids) == 2 if bits % 8 else 1
# Intentionally putting human review in the loop here, to guard against accidents.
VARS_BEFORE_ALL_BASIC_TESTS = dict(vars()) # Make a copy of the dict (critical).
ALL_BASIC_TESTS = (
test_callback_py_obj,
test_callback_std_func,
test_callback_virtual_func,
test_callback_pure_virtual_func,
test_cross_module_gil_released,
test_cross_module_gil_acquired,
test_cross_module_gil_inner_custom_released,
test_cross_module_gil_inner_custom_acquired,
test_cross_module_gil_inner_pybind11_released,
test_cross_module_gil_inner_pybind11_acquired,
test_cross_module_gil_nested_custom_released,
test_cross_module_gil_nested_custom_acquired,
test_cross_module_gil_nested_pybind11_released,
test_cross_module_gil_nested_pybind11_acquired,
test_release_acquire,
test_nested_acquire,
test_multi_acquire_release_cross_module,
)
def test_all_basic_tests_completeness():
num_found = 0
for key, value in VARS_BEFORE_ALL_BASIC_TESTS.items():
if not key.startswith("test_"):
continue
assert value in ALL_BASIC_TESTS
num_found += 1
assert len(ALL_BASIC_TESTS) == num_found
def _intentional_deadlock():
m.intentional_deadlock()
ALL_BASIC_TESTS_PLUS_INTENTIONAL_DEADLOCK = ALL_BASIC_TESTS + (_intentional_deadlock,)
SKIP_IF_DEADLOCK = True # See PR #4216
def _run_in_process(target, *args, **kwargs):
if len(args) == 0:
test_fn = target
else:
test_fn = args[0]
# Do not need to wait much, 10s should be more than enough.
timeout = 0.1 if test_fn is _intentional_deadlock else 10
process = multiprocessing.Process(target=target, args=args, kwargs=kwargs)
process.daemon = True
try:
t_start = time.time()
process.start()
if timeout >= 100: # For debugging.
print(
"\nprocess.pid STARTED", process.pid, (sys.argv, target, args, kwargs)
)
print(f"COPY-PASTE-THIS: gdb {sys.argv[0]} -p {process.pid}", flush=True)
process.join(timeout=timeout)
if timeout >= 100:
print("\nprocess.pid JOINED", process.pid, flush=True)
t_delta = time.time() - t_start
if process.exitcode == 66 and m.defined_THREAD_SANITIZER: # Issue #2754
# WOULD-BE-NICE-TO-HAVE: Check that the message below is actually in the output.
# Maybe this could work:
# https://gist.github.com/alexeygrigorev/01ce847f2e721b513b42ea4a6c96905e
pytest.skip(
"ThreadSanitizer: starting new threads after multi-threaded fork is not supported."
)
elif test_fn is _intentional_deadlock:
assert process.exitcode is None
return 0
elif process.exitcode is None:
assert t_delta > 0.9 * timeout
msg = "DEADLOCK, most likely, exactly what this test is meant to detect."
if SKIP_IF_DEADLOCK:
pytest.skip(msg)
raise RuntimeError(msg)
return process.exitcode
finally:
if process.is_alive():
process.terminate()
def _run_in_threads(test_fn, num_threads, parallel):
threads = []
for _ in range(num_threads):
thread = threading.Thread(target=_python_to_cpp_to_python)
thread = threading.Thread(target=test_fn)
thread.daemon = True
thread.start()
if parallel:
@ -51,43 +205,40 @@ def _python_to_cpp_to_python_from_threads(num_threads, parallel=False):
# TODO: FIXME, sometimes returns -11 (segfault) instead of 0 on macOS Python 3.9
def test_python_to_cpp_to_python_from_thread():
@pytest.mark.parametrize("test_fn", ALL_BASIC_TESTS_PLUS_INTENTIONAL_DEADLOCK)
def test_run_in_process_one_thread(test_fn):
"""Makes sure there is no GIL deadlock when running in a thread.
It runs in a separate process to be able to stop and assert if it deadlocks.
"""
assert _run_in_process(_python_to_cpp_to_python_from_threads, 1) == 0
assert _run_in_process(_run_in_threads, test_fn, num_threads=1, parallel=False) == 0
# TODO: FIXME on macOS Python 3.9
def test_python_to_cpp_to_python_from_thread_multiple_parallel():
@pytest.mark.parametrize("test_fn", ALL_BASIC_TESTS_PLUS_INTENTIONAL_DEADLOCK)
def test_run_in_process_multiple_threads_parallel(test_fn):
"""Makes sure there is no GIL deadlock when running in a thread multiple times in parallel.
It runs in a separate process to be able to stop and assert if it deadlocks.
"""
assert _run_in_process(_python_to_cpp_to_python_from_threads, 8, parallel=True) == 0
assert _run_in_process(_run_in_threads, test_fn, num_threads=8, parallel=True) == 0
# TODO: FIXME on macOS Python 3.9
def test_python_to_cpp_to_python_from_thread_multiple_sequential():
@pytest.mark.parametrize("test_fn", ALL_BASIC_TESTS_PLUS_INTENTIONAL_DEADLOCK)
def test_run_in_process_multiple_threads_sequential(test_fn):
"""Makes sure there is no GIL deadlock when running in a thread multiple times sequentially.
It runs in a separate process to be able to stop and assert if it deadlocks.
"""
assert (
_run_in_process(_python_to_cpp_to_python_from_threads, 8, parallel=False) == 0
)
assert _run_in_process(_run_in_threads, test_fn, num_threads=8, parallel=False) == 0
# TODO: FIXME on macOS Python 3.9
def test_python_to_cpp_to_python_from_process():
@pytest.mark.parametrize("test_fn", ALL_BASIC_TESTS_PLUS_INTENTIONAL_DEADLOCK)
def test_run_in_process_direct(test_fn):
"""Makes sure there is no GIL deadlock when using processes.
This test is for completion, but it was never an issue.
"""
assert _run_in_process(_python_to_cpp_to_python) == 0
def test_cross_module_gil():
"""Makes sure that the GIL can be acquired by another module from a GIL-released state."""
m.test_cross_module_gil() # Should not raise a SIGSEGV
assert _run_in_process(test_fn) == 0

2
tests/test_numpy_array.cpp
View File

@ -521,4 +521,6 @@ TEST_SUBMODULE(numpy_array, sm) {
sm.def("test_fmt_desc_double", [](const py::array_t<double> &) {});
sm.def("test_fmt_desc_const_float", [](const py::array_t<const float> &) {});
sm.def("test_fmt_desc_const_double", [](const py::array_t<const double> &) {});
sm.def("round_trip_float", [](double d) { return d; });
}

6
tests/test_numpy_array.py
View File

@ -585,3 +585,9 @@ def test_dtype_refcount_leak():
m.ndim(a)
after = getrefcount(dtype)
assert after == before
def test_round_trip_float():
arr = np.zeros((), np.float64)
arr[()] = 37.2
assert m.round_trip_float(arr) == 37.2

10
tests/test_pytypes.cpp
View File

@ -183,7 +183,7 @@ TEST_SUBMODULE(pytypes, m) {
return d2;
});
m.def("dict_contains",
[](const py::dict &dict, py::object val) { return dict.contains(val); });
[](const py::dict &dict, const py::object &val) { return dict.contains(val); });
m.def("dict_contains",
[](const py::dict &dict, const char *val) { return dict.contains(val); });
@ -206,7 +206,12 @@ TEST_SUBMODULE(pytypes, m) {
m.def("str_from_char_ssize_t", []() { return py::str{"red", (py::ssize_t) 3}; });
m.def("str_from_char_size_t", []() { return py::str{"blue", (py::size_t) 4}; });
m.def("str_from_string", []() { return py::str(std::string("baz")); });
m.def("str_from_std_string_input", [](const std::string &stri) { return py::str(stri); });
m.def("str_from_cstr_input", [](const char *c_str) { return py::str(c_str); });
m.def("str_from_bytes", []() { return py::str(py::bytes("boo", 3)); });
m.def("str_from_bytes_input",
[](const py::bytes &encoded_str) { return py::str(encoded_str); });
m.def("str_from_object", [](const py::object &obj) { return py::str(obj); });
m.def("repr_from_object", [](const py::object &obj) { return py::repr(obj); });
m.def("str_from_handle", [](py::handle h) { return py::str(h); });
@ -538,6 +543,9 @@ TEST_SUBMODULE(pytypes, m) {
m.def("hash_function", [](py::object obj) { return py::hash(std::move(obj)); });
m.def("obj_contains",
[](py::object &obj, const py::object &key) { return obj.contains(key); });
m.def("test_number_protocol", [](const py::object &a, const py::object &b) {
py::list l;
l.append(a.equal(b));

39
tests/test_pytypes.py
View File

@ -168,6 +168,31 @@ def test_dict(capture, doc):
assert m.dict_keyword_constructor() == {"x": 1, "y": 2, "z": 3}
class CustomContains:
d = {"key": None}
def __contains__(self, m):
return m in self.d
@pytest.mark.parametrize(
"arg,func",
[
(set(), m.anyset_contains),
(dict(), m.dict_contains),
(CustomContains(), m.obj_contains),
],
)
@pytest.mark.xfail("env.PYPY and sys.pypy_version_info < (7, 3, 10)", strict=False)
def test_unhashable_exceptions(arg, func):
class Unhashable:
__hash__ = None
with pytest.raises(TypeError) as exc_info:
func(arg, Unhashable())
assert "unhashable type:" in str(exc_info.value)
def test_tuple():
assert m.tuple_no_args() == ()
assert m.tuple_ssize_t() == ()
@ -219,6 +244,20 @@ def test_str(doc):
m.str_from_string_from_str(ucs_surrogates_str)
@pytest.mark.parametrize(
"func",
[
m.str_from_bytes_input,
m.str_from_cstr_input,
m.str_from_std_string_input,
],
)
def test_surrogate_pairs_unicode_error(func):
input_str = "\ud83d\ude4f".encode("utf-8", "surrogatepass")
with pytest.raises(UnicodeDecodeError):
func(input_str)
def test_bytes(doc):
assert m.bytes_from_char_ssize_t().decode() == "green"
assert m.bytes_from_char_size_t().decode() == "purple"

19
tests/test_sequences_and_iterators.cpp
View File

@ -559,4 +559,23 @@ TEST_SUBMODULE(sequences_and_iterators, m) {
[]() { return py::make_iterator<py::return_value_policy::copy>(list); });
m.def("make_iterator_2",
[]() { return py::make_iterator<py::return_value_policy::automatic>(list); });
// test_iterator on c arrays
// #4100: ensure lvalue required as increment operand
class CArrayHolder {
public:
CArrayHolder(double x, double y, double z) {
values[0] = x;
values[1] = y;
values[2] = z;
};
double values[3];
};
py::class_<CArrayHolder>(m, "CArrayHolder")
.def(py::init<double, double, double>())
.def(
"__iter__",
[](const CArrayHolder &v) { return py::make_iterator(v.values, v.values + 3); },
py::keep_alive<0, 1>());
}

8
tests/test_sequences_and_iterators.py
View File

@ -241,3 +241,11 @@ def test_iterator_rvp():
assert list(m.make_iterator_1()) == [1, 2, 3]
assert list(m.make_iterator_2()) == [1, 2, 3]
assert not isinstance(m.make_iterator_1(), type(m.make_iterator_2()))
def test_carray_iterator():
"""#4100: Check for proper iterator overload with C-Arrays"""
args_gt = list(float(i) for i in range(3))
arr_h = m.CArrayHolder(*args_gt)
args = list(arr_h)
assert args_gt == args

6
tools/FindPythonLibsNew.cmake
View File

@ -151,9 +151,13 @@ if(NOT _PYTHON_SUCCESS MATCHES 0)
return()
endif()
option(
PYBIND11_PYTHONLIBS_OVERWRITE
"Overwrite cached values read from Python library (classic search). Turn off if cross-compiling and manually setting these values."
ON)
# Can manually set values when cross-compiling
macro(_PYBIND11_GET_IF_UNDEF lst index name)
if(NOT DEFINED "${name}")
if(PYBIND11_PYTHONLIBS_OVERWRITE OR NOT DEFINED "${name}")
list(GET "${lst}" "${index}" "${name}")
endif()
endmacro()

4
tools/setup_global.py.in
View File

@ -27,10 +27,11 @@ class InstallHeadersNested(install_headers):
main_headers = glob.glob("pybind11/include/pybind11/*.h")
detail_headers = glob.glob("pybind11/include/pybind11/detail/*.h")
eigen_headers = glob.glob("pybind11/include/pybind11/eigen/*.h")
stl_headers = glob.glob("pybind11/include/pybind11/stl/*.h")
cmake_files = glob.glob("pybind11/share/cmake/pybind11/*.cmake")
pkgconfig_files = glob.glob("pybind11/share/pkgconfig/*.pc")
headers = main_headers + detail_headers + stl_headers
headers = main_headers + detail_headers + stl_headers + eigen_headers
cmdclass = {"install_headers": InstallHeadersNested}
$extra_cmd
@ -55,6 +56,7 @@ setup(
(base + "share/pkgconfig", pkgconfig_files),
(base + "include/pybind11", main_headers),
(base + "include/pybind11/detail", detail_headers),
(base + "include/pybind11/eigen", eigen_headers),
(base + "include/pybind11/stl", stl_headers),
],
cmdclass=cmdclass,

2
tools/setup_main.py.in
View File

@ -15,6 +15,7 @@ setup(
"pybind11",
"pybind11.include.pybind11",
"pybind11.include.pybind11.detail",
"pybind11.include.pybind11.eigen",
"pybind11.include.pybind11.stl",
"pybind11.share.cmake.pybind11",
"pybind11.share.pkgconfig",
@ -23,6 +24,7 @@ setup(
"pybind11": ["py.typed"],
"pybind11.include.pybind11": ["*.h"],
"pybind11.include.pybind11.detail": ["*.h"],
"pybind11.include.pybind11.eigen": ["*.h"],
"pybind11.include.pybind11.stl": ["*.h"],
"pybind11.share.cmake.pybind11": ["*.cmake"],
"pybind11.share.pkgconfig": ["*.pc"],