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ext: Update pybind11 to v2.8.1

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Change-Id: Ia1c7081377f53fd470addf35526f8b28a949a7b0
Signed-off-by: Jason Lowe-Power <jason@lowepower.com>
Reviewed-on: https://gem5-review.googlesource.com/c/public/gem5/+/52523
Maintainer: Bobby R. Bruce <bbruce@ucdavis.edu>
Tested-by: kokoro <noreply+kokoro@google.com>
Reviewed-by: Gabe Black <gabe.black@gmail.com>
This commit is contained in:
Jason Lowe-Power
2021-11-06 13:16:21 -07:00
committed by Jason Lowe-Power
parent ba5f68db3d
commit 1e8aeee698
161 changed files with 7820 additions and 3191 deletions
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146
ext/pybind11/include/pybind11/numpy.h
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@@ -25,11 +25,6 @@
#include <vector>
#include <typeindex>
#if defined(_MSC_VER)
# pragma warning(push)
# pragma warning(disable: 4127) // warning C4127: Conditional expression is constant
#endif
/* This will be true on all flat address space platforms and allows us to reduce the
whole npy_intp / ssize_t / Py_intptr_t business down to just ssize_t for all size
and dimension types (e.g. shape, strides, indexing), instead of inflicting this
@@ -104,7 +99,7 @@ struct numpy_internals {
}
};
inline PYBIND11_NOINLINE void load_numpy_internals(numpy_internals* &ptr) {
PYBIND11_NOINLINE void load_numpy_internals(numpy_internals* &ptr) {
ptr = &get_or_create_shared_data<numpy_internals>("_numpy_internals");
}
@@ -164,10 +159,10 @@ struct npy_api {
NPY_ULONG_, NPY_ULONGLONG_, NPY_UINT_),
};
typedef struct {
struct PyArray_Dims {
Py_intptr_t *ptr;
int len;
} PyArray_Dims;
};
static npy_api& get() {
static npy_api api = lookup();
@@ -203,6 +198,9 @@ struct npy_api {
// Unused. Not removed because that affects ABI of the class.
int (*PyArray_SetBaseObject_)(PyObject *, PyObject *);
PyObject* (*PyArray_Resize_)(PyObject*, PyArray_Dims*, int, int);
PyObject* (*PyArray_Newshape_)(PyObject*, PyArray_Dims*, int);
PyObject* (*PyArray_View_)(PyObject*, PyObject*, PyObject*);
private:
enum functions {
API_PyArray_GetNDArrayCFeatureVersion = 211,
@@ -217,10 +215,12 @@ private:
API_PyArray_NewCopy = 85,
API_PyArray_NewFromDescr = 94,
API_PyArray_DescrNewFromType = 96,
API_PyArray_Newshape = 135,
API_PyArray_Squeeze = 136,
API_PyArray_View = 137,
API_PyArray_DescrConverter = 174,
API_PyArray_EquivTypes = 182,
API_PyArray_GetArrayParamsFromObject = 278,
API_PyArray_Squeeze = 136,
API_PyArray_SetBaseObject = 282
};
@@ -248,11 +248,14 @@ private:
DECL_NPY_API(PyArray_NewCopy);
DECL_NPY_API(PyArray_NewFromDescr);
DECL_NPY_API(PyArray_DescrNewFromType);
DECL_NPY_API(PyArray_Newshape);
DECL_NPY_API(PyArray_Squeeze);
DECL_NPY_API(PyArray_View);
DECL_NPY_API(PyArray_DescrConverter);
DECL_NPY_API(PyArray_EquivTypes);
DECL_NPY_API(PyArray_GetArrayParamsFromObject);
DECL_NPY_API(PyArray_Squeeze);
DECL_NPY_API(PyArray_SetBaseObject);
#undef DECL_NPY_API
return api;
}
@@ -319,14 +322,13 @@ template <typename T> using remove_all_extents_t = typename array_info<T>::type;
template <typename T> using is_pod_struct = all_of<
std::is_standard_layout<T>, // since we're accessing directly in memory we need a standard layout type
#if !defined(__GNUG__) || defined(_LIBCPP_VERSION) || defined(_GLIBCXX_USE_CXX11_ABI)
// _GLIBCXX_USE_CXX11_ABI indicates that we're using libstdc++ from GCC 5 or newer, independent
// of the actual compiler (Clang can also use libstdc++, but it always defines __GNUC__ == 4).
std::is_trivially_copyable<T>,
#else
// GCC 4 doesn't implement is_trivially_copyable, so approximate it
#if defined(__GLIBCXX__) && (__GLIBCXX__ < 20150422 || __GLIBCXX__ == 20150426 || __GLIBCXX__ == 20150623 || __GLIBCXX__ == 20150626 || __GLIBCXX__ == 20160803)
// libstdc++ < 5 (including versions 4.8.5, 4.9.3 and 4.9.4 which were released after 5)
// don't implement is_trivially_copyable, so approximate it
std::is_trivially_destructible<T>,
satisfies_any_of<T, std::has_trivial_copy_constructor, std::has_trivial_copy_assign>,
#else
std::is_trivially_copyable<T>,
#endif
satisfies_none_of<T, std::is_reference, std::is_array, is_std_array, std::is_arithmetic, is_complex, std::is_enum>
>;
@@ -466,28 +468,30 @@ public:
explicit dtype(const buffer_info &info) {
dtype descr(_dtype_from_pep3118()(PYBIND11_STR_TYPE(info.format)));
// If info.itemsize == 0, use the value calculated from the format string
m_ptr = descr.strip_padding(info.itemsize ? info.itemsize : descr.itemsize()).release().ptr();
m_ptr = descr.strip_padding(info.itemsize != 0 ? info.itemsize : descr.itemsize())
.release()
.ptr();
}
explicit dtype(const std::string &format) {
m_ptr = from_args(pybind11::str(format)).release().ptr();
}
dtype(const char *format) : dtype(std::string(format)) { }
explicit dtype(const char *format) : dtype(std::string(format)) {}
dtype(list names, list formats, list offsets, ssize_t itemsize) {
dict args;
args["names"] = names;
args["formats"] = formats;
args["offsets"] = offsets;
args["names"] = std::move(names);
args["formats"] = std::move(formats);
args["offsets"] = std::move(offsets);
args["itemsize"] = pybind11::int_(itemsize);
m_ptr = from_args(args).release().ptr();
m_ptr = from_args(std::move(args)).release().ptr();
}
/// This is essentially the same as calling numpy.dtype(args) in Python.
static dtype from_args(object args) {
PyObject *ptr = nullptr;
if (!detail::npy_api::get().PyArray_DescrConverter_(args.ptr(), &ptr) || !ptr)
if ((detail::npy_api::get().PyArray_DescrConverter_(args.ptr(), &ptr) == 0) || !ptr)
throw error_already_set();
return reinterpret_steal<dtype>(ptr);
}
@@ -507,11 +511,21 @@ public:
return detail::array_descriptor_proxy(m_ptr)->names != nullptr;
}
/// Single-character type code.
/// Single-character code for dtype's kind.
/// For example, floating point types are 'f' and integral types are 'i'.
char kind() const {
return detail::array_descriptor_proxy(m_ptr)->kind;
}
/// Single-character for dtype's type.
/// For example, ``float`` is 'f', ``double`` 'd', ``int`` 'i', and ``long`` 'l'.
char char_() const {
// Note: The signature, `dtype::char_` follows the naming of NumPy's
// public Python API (i.e., ``dtype.char``), rather than its internal
// C API (``PyArray_Descr::type``).
return detail::array_descriptor_proxy(m_ptr)->type;
}
private:
static object _dtype_from_pep3118() {
static PyObject *obj = module_::import("numpy.core._internal")
@@ -533,7 +547,7 @@ private:
auto name = spec[0].cast<pybind11::str>();
auto format = spec[1].cast<tuple>()[0].cast<dtype>();
auto offset = spec[1].cast<tuple>()[1].cast<pybind11::int_>();
if (!len(name) && format.kind() == 'V')
if ((len(name) == 0u) && format.kind() == 'V')
continue;
field_descriptors.push_back({(PYBIND11_STR_TYPE) name, format.strip_padding(format.itemsize()), offset});
}
@@ -549,7 +563,7 @@ private:
formats.append(descr.format);
offsets.append(descr.offset);
}
return dtype(names, formats, offsets, itemsize);
return dtype(std::move(names), std::move(formats), std::move(offsets), itemsize);
}
};
@@ -736,7 +750,7 @@ public:
* and the caller must take care not to access invalid dimensions or dimension indices.
*/
template <typename T, ssize_t Dims = -1> detail::unchecked_mutable_reference<T, Dims> mutable_unchecked() & {
if (Dims >= 0 && ndim() != Dims)
if (PYBIND11_SILENCE_MSVC_C4127(Dims >= 0) && ndim() != Dims)
throw std::domain_error("array has incorrect number of dimensions: " + std::to_string(ndim()) +
"; expected " + std::to_string(Dims));
return detail::unchecked_mutable_reference<T, Dims>(mutable_data(), shape(), strides(), ndim());
@@ -750,7 +764,7 @@ public:
* invalid dimensions or dimension indices.
*/
template <typename T, ssize_t Dims = -1> detail::unchecked_reference<T, Dims> unchecked() const & {
if (Dims >= 0 && ndim() != Dims)
if (PYBIND11_SILENCE_MSVC_C4127(Dims >= 0) && ndim() != Dims)
throw std::domain_error("array has incorrect number of dimensions: " + std::to_string(ndim()) +
"; expected " + std::to_string(Dims));
return detail::unchecked_reference<T, Dims>(data(), shape(), strides(), ndim());
@@ -779,6 +793,33 @@ public:
if (isinstance<array>(new_array)) { *this = std::move(new_array); }
}
/// Optional `order` parameter omitted, to be added as needed.
array reshape(ShapeContainer new_shape) {
detail::npy_api::PyArray_Dims d
= {reinterpret_cast<Py_intptr_t *>(new_shape->data()), int(new_shape->size())};
auto new_array
= reinterpret_steal<array>(detail::npy_api::get().PyArray_Newshape_(m_ptr, &d, 0));
if (!new_array) {
throw error_already_set();
}
return new_array;
}
/// Create a view of an array in a different data type.
/// This function may fundamentally reinterpret the data in the array.
/// It is the responsibility of the caller to ensure that this is safe.
/// Only supports the `dtype` argument, the `type` argument is omitted,
/// to be added as needed.
array view(const std::string &dtype) {
auto &api = detail::npy_api::get();
auto new_view = reinterpret_steal<array>(api.PyArray_View_(
m_ptr, dtype::from_args(pybind11::str(dtype)).release().ptr(), nullptr));
if (!new_view) {
throw error_already_set();
}
return new_view;
}
/// Ensure that the argument is a NumPy array
/// In case of an error, nullptr is returned and the Python error is cleared.
static array ensure(handle h, int ExtraFlags = 0) {
@@ -853,6 +894,7 @@ public:
if (!is_borrowed) Py_XDECREF(h.ptr());
}
// NOLINTNEXTLINE(google-explicit-constructor)
array_t(const object &o) : array(raw_array_t(o.ptr()), stolen_t{}) {
if (!m_ptr) throw error_already_set();
}
@@ -863,11 +905,12 @@ public:
: array(std::move(shape), std::move(strides), ptr, base) { }
explicit array_t(ShapeContainer shape, const T *ptr = nullptr, handle base = handle())
: array_t(private_ctor{}, std::move(shape),
ExtraFlags & f_style
? detail::f_strides(*shape, itemsize())
: detail::c_strides(*shape, itemsize()),
ptr, base) { }
: array_t(private_ctor{},
std::move(shape),
(ExtraFlags & f_style) != 0 ? detail::f_strides(*shape, itemsize())
: detail::c_strides(*shape, itemsize()),
ptr,
base) {}
explicit array_t(ssize_t count, const T *ptr = nullptr, handle base = handle())
: array({count}, {}, ptr, base) { }
@@ -1020,7 +1063,10 @@ struct npy_format_descriptor_name<T, enable_if_t<std::is_integral<T>::value>> {
template <typename T>
struct npy_format_descriptor_name<T, enable_if_t<std::is_floating_point<T>::value>> {
static constexpr auto name = _<std::is_same<T, float>::value || std::is_same<T, double>::value>(
static constexpr auto name = _<std::is_same<T, float>::value
|| std::is_same<T, const float>::value
|| std::is_same<T, double>::value
|| std::is_same<T, const double>::value>(
_("numpy.float") + _<sizeof(T)*8>(), _("numpy.longdouble")
);
};
@@ -1028,7 +1074,9 @@ struct npy_format_descriptor_name<T, enable_if_t<std::is_floating_point<T>::valu
template <typename T>
struct npy_format_descriptor_name<T, enable_if_t<is_complex<T>::value>> {
static constexpr auto name = _<std::is_same<typename T::value_type, float>::value
|| std::is_same<typename T::value_type, double>::value>(
|| std::is_same<typename T::value_type, const float>::value
|| std::is_same<typename T::value_type, double>::value
|| std::is_same<typename T::value_type, const double>::value>(
_("numpy.complex") + _<sizeof(typename T::value_type)*16>(), _("numpy.longcomplex")
);
};
@@ -1093,7 +1141,7 @@ struct field_descriptor {
dtype descr;
};
inline PYBIND11_NOINLINE void register_structured_dtype(
PYBIND11_NOINLINE void register_structured_dtype(
any_container<field_descriptor> fields,
const std::type_info& tinfo, ssize_t itemsize,
bool (*direct_converter)(PyObject *, void *&)) {
@@ -1117,7 +1165,10 @@ inline PYBIND11_NOINLINE void register_structured_dtype(
formats.append(field.descr);
offsets.append(pybind11::int_(field.offset));
}
auto dtype_ptr = pybind11::dtype(names, formats, offsets, itemsize).release().ptr();
auto dtype_ptr
= pybind11::dtype(std::move(names), std::move(formats), std::move(offsets), itemsize)
.release()
.ptr();
// There is an existing bug in NumPy (as of v1.11): trailing bytes are
// not encoded explicitly into the format string. This will supposedly
@@ -1277,7 +1328,7 @@ public:
using value_type = container_type::value_type;
using size_type = container_type::size_type;
common_iterator() : p_ptr(0), m_strides() {}
common_iterator() : m_strides() {}
common_iterator(void* ptr, const container_type& strides, const container_type& shape)
: p_ptr(reinterpret_cast<char*>(ptr)), m_strides(strides.size()) {
@@ -1298,7 +1349,7 @@ public:
}
private:
char* p_ptr;
char *p_ptr{0};
container_type m_strides;
};
@@ -1326,9 +1377,8 @@ public:
if (++m_index[i] != m_shape[i]) {
increment_common_iterator(i);
break;
} else {
m_index[i] = 0;
}
m_index[i] = 0;
}
return *this;
}
@@ -1479,8 +1529,7 @@ struct vectorize_returned_array {
static Type create(broadcast_trivial trivial, const std::vector<ssize_t> &shape) {
if (trivial == broadcast_trivial::f_trivial)
return array_t<Return, array::f_style>(shape);
else
return array_t<Return>(shape);
return array_t<Return>(shape);
}
static Return *mutable_data(Type &array) {
@@ -1536,8 +1585,11 @@ private:
"pybind11::vectorize(...) requires a function with at least one vectorizable argument");
public:
template <typename T>
explicit vectorize_helper(T &&f) : f(std::forward<T>(f)) { }
template <typename T,
// SFINAE to prevent shadowing the copy constructor.
typename = detail::enable_if_t<
!std::is_same<vectorize_helper, typename std::decay<T>::type>::value>>
explicit vectorize_helper(T &&f) : f(std::forward<T>(f)) {}
object operator()(typename vectorize_arg<Args>::type... args) {
return run(args...,
@@ -1687,7 +1739,3 @@ Helper vectorize(Return (Class::*f)(Args...) const) {
}
PYBIND11_NAMESPACE_END(PYBIND11_NAMESPACE)
#if defined(_MSC_VER)
#pragma warning(pop)
#endif