| /* |
| pybind11/numpy.h: Basic NumPy support, vectorize() wrapper |
| |
| 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 "pybind11.h" |
| #include "complex.h" |
| #include <numeric> |
| #include <algorithm> |
| #include <array> |
| #include <cstdint> |
| #include <cstdlib> |
| #include <cstring> |
| #include <sstream> |
| #include <string> |
| #include <functional> |
| #include <type_traits> |
| #include <utility> |
| #include <vector> |
| #include <typeindex> |
| |
| /* 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 |
| upon the library user. */ |
| static_assert(sizeof(::pybind11::ssize_t) == sizeof(Py_intptr_t), "ssize_t != Py_intptr_t"); |
| static_assert(std::is_signed<Py_intptr_t>::value, "Py_intptr_t must be signed"); |
| // We now can reinterpret_cast between py::ssize_t and Py_intptr_t (MSVC + PyPy cares) |
| |
| PYBIND11_NAMESPACE_BEGIN(PYBIND11_NAMESPACE) |
| |
| class array; // Forward declaration |
| |
| PYBIND11_NAMESPACE_BEGIN(detail) |
| |
| template <> struct handle_type_name<array> { static constexpr auto name = _("numpy.ndarray"); }; |
| |
| template <typename type, typename SFINAE = void> struct npy_format_descriptor; |
| |
| struct PyArrayDescr_Proxy { |
| PyObject_HEAD |
| PyObject *typeobj; |
| char kind; |
| char type; |
| char byteorder; |
| char flags; |
| int type_num; |
| int elsize; |
| int alignment; |
| char *subarray; |
| PyObject *fields; |
| PyObject *names; |
| }; |
| |
| struct PyArray_Proxy { |
| PyObject_HEAD |
| char *data; |
| int nd; |
| ssize_t *dimensions; |
| ssize_t *strides; |
| PyObject *base; |
| PyObject *descr; |
| int flags; |
| }; |
| |
| struct PyVoidScalarObject_Proxy { |
| PyObject_VAR_HEAD |
| char *obval; |
| PyArrayDescr_Proxy *descr; |
| int flags; |
| PyObject *base; |
| }; |
| |
| struct numpy_type_info { |
| PyObject* dtype_ptr; |
| std::string format_str; |
| }; |
| |
| struct numpy_internals { |
| std::unordered_map<std::type_index, numpy_type_info> registered_dtypes; |
| |
| numpy_type_info *get_type_info(const std::type_info& tinfo, bool throw_if_missing = true) { |
| auto it = registered_dtypes.find(std::type_index(tinfo)); |
| if (it != registered_dtypes.end()) |
| return &(it->second); |
| if (throw_if_missing) |
| pybind11_fail(std::string("NumPy type info missing for ") + tinfo.name()); |
| return nullptr; |
| } |
| |
| template<typename T> numpy_type_info *get_type_info(bool throw_if_missing = true) { |
| return get_type_info(typeid(typename std::remove_cv<T>::type), throw_if_missing); |
| } |
| }; |
| |
| PYBIND11_NOINLINE void load_numpy_internals(numpy_internals* &ptr) { |
| ptr = &get_or_create_shared_data<numpy_internals>("_numpy_internals"); |
| } |
| |
| inline numpy_internals& get_numpy_internals() { |
| static numpy_internals* ptr = nullptr; |
| if (!ptr) |
| load_numpy_internals(ptr); |
| return *ptr; |
| } |
| |
| template <typename T> struct same_size { |
| template <typename U> using as = bool_constant<sizeof(T) == sizeof(U)>; |
| }; |
| |
| template <typename Concrete> constexpr int platform_lookup() { return -1; } |
| |
| // Lookup a type according to its size, and return a value corresponding to the NumPy typenum. |
| template <typename Concrete, typename T, typename... Ts, typename... Ints> |
| constexpr int platform_lookup(int I, Ints... Is) { |
| return sizeof(Concrete) == sizeof(T) ? I : platform_lookup<Concrete, Ts...>(Is...); |
| } |
| |
| struct npy_api { |
| enum constants { |
| NPY_ARRAY_C_CONTIGUOUS_ = 0x0001, |
| NPY_ARRAY_F_CONTIGUOUS_ = 0x0002, |
| NPY_ARRAY_OWNDATA_ = 0x0004, |
| NPY_ARRAY_FORCECAST_ = 0x0010, |
| NPY_ARRAY_ENSUREARRAY_ = 0x0040, |
| NPY_ARRAY_ALIGNED_ = 0x0100, |
| NPY_ARRAY_WRITEABLE_ = 0x0400, |
| NPY_BOOL_ = 0, |
| NPY_BYTE_, NPY_UBYTE_, |
| NPY_SHORT_, NPY_USHORT_, |
| NPY_INT_, NPY_UINT_, |
| NPY_LONG_, NPY_ULONG_, |
| NPY_LONGLONG_, NPY_ULONGLONG_, |
| NPY_FLOAT_, NPY_DOUBLE_, NPY_LONGDOUBLE_, |
| NPY_CFLOAT_, NPY_CDOUBLE_, NPY_CLONGDOUBLE_, |
| NPY_OBJECT_ = 17, |
| NPY_STRING_, NPY_UNICODE_, NPY_VOID_, |
| // Platform-dependent normalization |
| NPY_INT8_ = NPY_BYTE_, |
| NPY_UINT8_ = NPY_UBYTE_, |
| NPY_INT16_ = NPY_SHORT_, |
| NPY_UINT16_ = NPY_USHORT_, |
| // `npy_common.h` defines the integer aliases. In order, it checks: |
| // NPY_BITSOF_LONG, NPY_BITSOF_LONGLONG, NPY_BITSOF_INT, NPY_BITSOF_SHORT, NPY_BITSOF_CHAR |
| // and assigns the alias to the first matching size, so we should check in this order. |
| NPY_INT32_ = platform_lookup<std::int32_t, long, int, short>( |
| NPY_LONG_, NPY_INT_, NPY_SHORT_), |
| NPY_UINT32_ = platform_lookup<std::uint32_t, unsigned long, unsigned int, unsigned short>( |
| NPY_ULONG_, NPY_UINT_, NPY_USHORT_), |
| NPY_INT64_ = platform_lookup<std::int64_t, long, long long, int>( |
| NPY_LONG_, NPY_LONGLONG_, NPY_INT_), |
| NPY_UINT64_ = platform_lookup<std::uint64_t, unsigned long, unsigned long long, unsigned int>( |
| NPY_ULONG_, NPY_ULONGLONG_, NPY_UINT_), |
| }; |
| |
| struct PyArray_Dims { |
| Py_intptr_t *ptr; |
| int len; |
| }; |
| |
| static npy_api& get() { |
| static npy_api api = lookup(); |
| return api; |
| } |
| |
| bool PyArray_Check_(PyObject *obj) const { |
| return (bool) PyObject_TypeCheck(obj, PyArray_Type_); |
| } |
| bool PyArrayDescr_Check_(PyObject *obj) const { |
| return (bool) PyObject_TypeCheck(obj, PyArrayDescr_Type_); |
| } |
| |
| unsigned int (*PyArray_GetNDArrayCFeatureVersion_)(); |
| PyObject *(*PyArray_DescrFromType_)(int); |
| PyObject *(*PyArray_NewFromDescr_) |
| (PyTypeObject *, PyObject *, int, Py_intptr_t const *, |
| Py_intptr_t const *, void *, int, PyObject *); |
| // Unused. Not removed because that affects ABI of the class. |
| PyObject *(*PyArray_DescrNewFromType_)(int); |
| int (*PyArray_CopyInto_)(PyObject *, PyObject *); |
| PyObject *(*PyArray_NewCopy_)(PyObject *, int); |
| PyTypeObject *PyArray_Type_; |
| PyTypeObject *PyVoidArrType_Type_; |
| PyTypeObject *PyArrayDescr_Type_; |
| PyObject *(*PyArray_DescrFromScalar_)(PyObject *); |
| PyObject *(*PyArray_FromAny_) (PyObject *, PyObject *, int, int, int, PyObject *); |
| int (*PyArray_DescrConverter_) (PyObject *, PyObject **); |
| bool (*PyArray_EquivTypes_) (PyObject *, PyObject *); |
| int (*PyArray_GetArrayParamsFromObject_)(PyObject *, PyObject *, unsigned char, PyObject **, int *, |
| Py_intptr_t *, PyObject **, PyObject *); |
| PyObject *(*PyArray_Squeeze_)(PyObject *); |
| // 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, |
| API_PyArray_Type = 2, |
| API_PyArrayDescr_Type = 3, |
| API_PyVoidArrType_Type = 39, |
| API_PyArray_DescrFromType = 45, |
| API_PyArray_DescrFromScalar = 57, |
| API_PyArray_FromAny = 69, |
| API_PyArray_Resize = 80, |
| API_PyArray_CopyInto = 82, |
| 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_SetBaseObject = 282 |
| }; |
| |
| static npy_api lookup() { |
| module_ m = module_::import("numpy.core.multiarray"); |
| auto c = m.attr("_ARRAY_API"); |
| #if PY_MAJOR_VERSION >= 3 |
| void **api_ptr = (void **) PyCapsule_GetPointer(c.ptr(), NULL); |
| #else |
| void **api_ptr = (void **) PyCObject_AsVoidPtr(c.ptr()); |
| #endif |
| npy_api api; |
| #define DECL_NPY_API(Func) api.Func##_ = (decltype(api.Func##_)) api_ptr[API_##Func]; |
| DECL_NPY_API(PyArray_GetNDArrayCFeatureVersion); |
| if (api.PyArray_GetNDArrayCFeatureVersion_() < 0x7) |
| pybind11_fail("pybind11 numpy support requires numpy >= 1.7.0"); |
| DECL_NPY_API(PyArray_Type); |
| DECL_NPY_API(PyVoidArrType_Type); |
| DECL_NPY_API(PyArrayDescr_Type); |
| DECL_NPY_API(PyArray_DescrFromType); |
| DECL_NPY_API(PyArray_DescrFromScalar); |
| DECL_NPY_API(PyArray_FromAny); |
| DECL_NPY_API(PyArray_Resize); |
| DECL_NPY_API(PyArray_CopyInto); |
| 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_SetBaseObject); |
| |
| #undef DECL_NPY_API |
| return api; |
| } |
| }; |
| |
| inline PyArray_Proxy* array_proxy(void* ptr) { |
| return reinterpret_cast<PyArray_Proxy*>(ptr); |
| } |
| |
| inline const PyArray_Proxy* array_proxy(const void* ptr) { |
| return reinterpret_cast<const PyArray_Proxy*>(ptr); |
| } |
| |
| inline PyArrayDescr_Proxy* array_descriptor_proxy(PyObject* ptr) { |
| return reinterpret_cast<PyArrayDescr_Proxy*>(ptr); |
| } |
| |
| inline const PyArrayDescr_Proxy* array_descriptor_proxy(const PyObject* ptr) { |
| return reinterpret_cast<const PyArrayDescr_Proxy*>(ptr); |
| } |
| |
| inline bool check_flags(const void* ptr, int flag) { |
| return (flag == (array_proxy(ptr)->flags & flag)); |
| } |
| |
| template <typename T> struct is_std_array : std::false_type { }; |
| template <typename T, size_t N> struct is_std_array<std::array<T, N>> : std::true_type { }; |
| template <typename T> struct is_complex : std::false_type { }; |
| template <typename T> struct is_complex<std::complex<T>> : std::true_type { }; |
| |
| template <typename T> struct array_info_scalar { |
| using type = T; |
| static constexpr bool is_array = false; |
| static constexpr bool is_empty = false; |
| static constexpr auto extents = _(""); |
| static void append_extents(list& /* shape */) { } |
| }; |
| // Computes underlying type and a comma-separated list of extents for array |
| // types (any mix of std::array and built-in arrays). An array of char is |
| // treated as scalar because it gets special handling. |
| template <typename T> struct array_info : array_info_scalar<T> { }; |
| template <typename T, size_t N> struct array_info<std::array<T, N>> { |
| using type = typename array_info<T>::type; |
| static constexpr bool is_array = true; |
| static constexpr bool is_empty = (N == 0) || array_info<T>::is_empty; |
| static constexpr size_t extent = N; |
| |
| // appends the extents to shape |
| static void append_extents(list& shape) { |
| shape.append(N); |
| array_info<T>::append_extents(shape); |
| } |
| |
| static constexpr auto extents = _<array_info<T>::is_array>( |
| concat(_<N>(), array_info<T>::extents), _<N>() |
| ); |
| }; |
| // For numpy we have special handling for arrays of characters, so we don't include |
| // the size in the array extents. |
| template <size_t N> struct array_info<char[N]> : array_info_scalar<char[N]> { }; |
| template <size_t N> struct array_info<std::array<char, N>> : array_info_scalar<std::array<char, N>> { }; |
| template <typename T, size_t N> struct array_info<T[N]> : array_info<std::array<T, N>> { }; |
| 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(__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> |
| >; |
| |
| // Replacement for std::is_pod (deprecated in C++20) |
| template <typename T> using is_pod = all_of< |
| std::is_standard_layout<T>, |
| std::is_trivial<T> |
| >; |
| |
| template <ssize_t Dim = 0, typename Strides> ssize_t byte_offset_unsafe(const Strides &) { return 0; } |
| template <ssize_t Dim = 0, typename Strides, typename... Ix> |
| ssize_t byte_offset_unsafe(const Strides &strides, ssize_t i, Ix... index) { |
| return i * strides[Dim] + byte_offset_unsafe<Dim + 1>(strides, index...); |
| } |
| |
| /** |
| * Proxy class providing unsafe, unchecked const access to array data. This is constructed through |
| * the `unchecked<T, N>()` method of `array` or the `unchecked<N>()` method of `array_t<T>`. `Dims` |
| * will be -1 for dimensions determined at runtime. |
| */ |
| template <typename T, ssize_t Dims> |
| class unchecked_reference { |
| protected: |
| static constexpr bool Dynamic = Dims < 0; |
| const unsigned char *data_; |
| // Storing the shape & strides in local variables (i.e. these arrays) allows the compiler to |
| // make large performance gains on big, nested loops, but requires compile-time dimensions |
| conditional_t<Dynamic, const ssize_t *, std::array<ssize_t, (size_t) Dims>> |
| shape_, strides_; |
| const ssize_t dims_; |
| |
| friend class pybind11::array; |
| // Constructor for compile-time dimensions: |
| template <bool Dyn = Dynamic> |
| unchecked_reference(const void *data, const ssize_t *shape, const ssize_t *strides, enable_if_t<!Dyn, ssize_t>) |
| : data_{reinterpret_cast<const unsigned char *>(data)}, dims_{Dims} { |
| for (size_t i = 0; i < (size_t) dims_; i++) { |
| shape_[i] = shape[i]; |
| strides_[i] = strides[i]; |
| } |
| } |
| // Constructor for runtime dimensions: |
| template <bool Dyn = Dynamic> |
| unchecked_reference(const void *data, const ssize_t *shape, const ssize_t *strides, enable_if_t<Dyn, ssize_t> dims) |
| : data_{reinterpret_cast<const unsigned char *>(data)}, shape_{shape}, strides_{strides}, dims_{dims} {} |
| |
| public: |
| /** |
| * Unchecked const reference access to data at the given indices. For a compile-time known |
| * number of dimensions, this requires the correct number of arguments; for run-time |
| * dimensionality, this is not checked (and so is up to the caller to use safely). |
| */ |
| template <typename... Ix> const T &operator()(Ix... index) const { |
| static_assert(ssize_t{sizeof...(Ix)} == Dims || Dynamic, |
| "Invalid number of indices for unchecked array reference"); |
| return *reinterpret_cast<const T *>(data_ + byte_offset_unsafe(strides_, ssize_t(index)...)); |
| } |
| /** |
| * Unchecked const reference access to data; this operator only participates if the reference |
| * is to a 1-dimensional array. When present, this is exactly equivalent to `obj(index)`. |
| */ |
| template <ssize_t D = Dims, typename = enable_if_t<D == 1 || Dynamic>> |
| const T &operator[](ssize_t index) const { return operator()(index); } |
| |
| /// Pointer access to the data at the given indices. |
| template <typename... Ix> const T *data(Ix... ix) const { return &operator()(ssize_t(ix)...); } |
| |
| /// Returns the item size, i.e. sizeof(T) |
| constexpr static ssize_t itemsize() { return sizeof(T); } |
| |
| /// Returns the shape (i.e. size) of dimension `dim` |
| ssize_t shape(ssize_t dim) const { return shape_[(size_t) dim]; } |
| |
| /// Returns the number of dimensions of the array |
| ssize_t ndim() const { return dims_; } |
| |
| /// Returns the total number of elements in the referenced array, i.e. the product of the shapes |
| template <bool Dyn = Dynamic> |
| enable_if_t<!Dyn, ssize_t> size() const { |
| return std::accumulate(shape_.begin(), shape_.end(), (ssize_t) 1, std::multiplies<ssize_t>()); |
| } |
| template <bool Dyn = Dynamic> |
| enable_if_t<Dyn, ssize_t> size() const { |
| return std::accumulate(shape_, shape_ + ndim(), (ssize_t) 1, std::multiplies<ssize_t>()); |
| } |
| |
| /// Returns the total number of bytes used by the referenced data. Note that the actual span in |
| /// memory may be larger if the referenced array has non-contiguous strides (e.g. for a slice). |
| ssize_t nbytes() const { |
| return size() * itemsize(); |
| } |
| }; |
| |
| template <typename T, ssize_t Dims> |
| class unchecked_mutable_reference : public unchecked_reference<T, Dims> { |
| friend class pybind11::array; |
| using ConstBase = unchecked_reference<T, Dims>; |
| using ConstBase::ConstBase; |
| using ConstBase::Dynamic; |
| public: |
| // Bring in const-qualified versions from base class |
| using ConstBase::operator(); |
| using ConstBase::operator[]; |
| |
| /// Mutable, unchecked access to data at the given indices. |
| template <typename... Ix> T& operator()(Ix... index) { |
| static_assert(ssize_t{sizeof...(Ix)} == Dims || Dynamic, |
| "Invalid number of indices for unchecked array reference"); |
| return const_cast<T &>(ConstBase::operator()(index...)); |
| } |
| /** |
| * Mutable, unchecked access data at the given index; this operator only participates if the |
| * reference is to a 1-dimensional array (or has runtime dimensions). When present, this is |
| * exactly equivalent to `obj(index)`. |
| */ |
| template <ssize_t D = Dims, typename = enable_if_t<D == 1 || Dynamic>> |
| T &operator[](ssize_t index) { return operator()(index); } |
| |
| /// Mutable pointer access to the data at the given indices. |
| template <typename... Ix> T *mutable_data(Ix... ix) { return &operator()(ssize_t(ix)...); } |
| }; |
| |
| template <typename T, ssize_t Dim> |
| struct type_caster<unchecked_reference<T, Dim>> { |
| static_assert(Dim == 0 && Dim > 0 /* always fail */, "unchecked array proxy object is not castable"); |
| }; |
| template <typename T, ssize_t Dim> |
| struct type_caster<unchecked_mutable_reference<T, Dim>> : type_caster<unchecked_reference<T, Dim>> {}; |
| |
| PYBIND11_NAMESPACE_END(detail) |
| |
| class dtype : public object { |
| public: |
| PYBIND11_OBJECT_DEFAULT(dtype, object, detail::npy_api::get().PyArrayDescr_Check_); |
| |
| 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 != 0 ? info.itemsize : descr.itemsize()) |
| .release() |
| .ptr(); |
| } |
| |
| explicit dtype(const std::string &format) { |
| m_ptr = from_args(pybind11::str(format)).release().ptr(); |
| } |
| |
| explicit dtype(const char *format) : dtype(std::string(format)) {} |
| |
| dtype(list names, list formats, list offsets, ssize_t itemsize) { |
| dict args; |
| args["names"] = std::move(names); |
| args["formats"] = std::move(formats); |
| args["offsets"] = std::move(offsets); |
| args["itemsize"] = pybind11::int_(itemsize); |
| 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) == 0) || !ptr) |
| throw error_already_set(); |
| return reinterpret_steal<dtype>(ptr); |
| } |
| |
| /// Return dtype associated with a C++ type. |
| template <typename T> static dtype of() { |
| return detail::npy_format_descriptor<typename std::remove_cv<T>::type>::dtype(); |
| } |
| |
| /// Size of the data type in bytes. |
| ssize_t itemsize() const { |
| return detail::array_descriptor_proxy(m_ptr)->elsize; |
| } |
| |
| /// Returns true for structured data types. |
| bool has_fields() const { |
| return detail::array_descriptor_proxy(m_ptr)->names != nullptr; |
| } |
| |
| /// 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") |
| .attr("_dtype_from_pep3118").cast<object>().release().ptr(); |
| return reinterpret_borrow<object>(obj); |
| } |
| |
| dtype strip_padding(ssize_t itemsize) { |
| // Recursively strip all void fields with empty names that are generated for |
| // padding fields (as of NumPy v1.11). |
| if (!has_fields()) |
| return *this; |
| |
| struct field_descr { PYBIND11_STR_TYPE name; object format; pybind11::int_ offset; }; |
| std::vector<field_descr> field_descriptors; |
| |
| for (auto field : attr("fields").attr("items")()) { |
| auto spec = field.cast<tuple>(); |
| 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) == 0u) && format.kind() == 'V') |
| continue; |
| field_descriptors.push_back({(PYBIND11_STR_TYPE) name, format.strip_padding(format.itemsize()), offset}); |
| } |
| |
| std::sort(field_descriptors.begin(), field_descriptors.end(), |
| [](const field_descr& a, const field_descr& b) { |
| return a.offset.cast<int>() < b.offset.cast<int>(); |
| }); |
| |
| list names, formats, offsets; |
| for (auto& descr : field_descriptors) { |
| names.append(descr.name); |
| formats.append(descr.format); |
| offsets.append(descr.offset); |
| } |
| return dtype(std::move(names), std::move(formats), std::move(offsets), itemsize); |
| } |
| }; |
| |
| class array : public buffer { |
| public: |
| PYBIND11_OBJECT_CVT(array, buffer, detail::npy_api::get().PyArray_Check_, raw_array) |
| |
| enum { |
| c_style = detail::npy_api::NPY_ARRAY_C_CONTIGUOUS_, |
| f_style = detail::npy_api::NPY_ARRAY_F_CONTIGUOUS_, |
| forcecast = detail::npy_api::NPY_ARRAY_FORCECAST_ |
| }; |
| |
| array() : array(0, static_cast<const double *>(nullptr)) {} |
| |
| using ShapeContainer = detail::any_container<ssize_t>; |
| using StridesContainer = detail::any_container<ssize_t>; |
| |
| // Constructs an array taking shape/strides from arbitrary container types |
| array(const pybind11::dtype &dt, ShapeContainer shape, StridesContainer strides, |
| const void *ptr = nullptr, handle base = handle()) { |
| |
| if (strides->empty()) |
| *strides = detail::c_strides(*shape, dt.itemsize()); |
| |
| auto ndim = shape->size(); |
| if (ndim != strides->size()) |
| pybind11_fail("NumPy: shape ndim doesn't match strides ndim"); |
| auto descr = dt; |
| |
| int flags = 0; |
| if (base && ptr) { |
| if (isinstance<array>(base)) |
| /* Copy flags from base (except ownership bit) */ |
| flags = reinterpret_borrow<array>(base).flags() & ~detail::npy_api::NPY_ARRAY_OWNDATA_; |
| else |
| /* Writable by default, easy to downgrade later on if needed */ |
| flags = detail::npy_api::NPY_ARRAY_WRITEABLE_; |
| } |
| |
| auto &api = detail::npy_api::get(); |
| auto tmp = reinterpret_steal<object>(api.PyArray_NewFromDescr_( |
| api.PyArray_Type_, descr.release().ptr(), (int) ndim, |
| // Use reinterpret_cast for PyPy on Windows (remove if fixed, checked on 7.3.1) |
| reinterpret_cast<Py_intptr_t*>(shape->data()), |
| reinterpret_cast<Py_intptr_t*>(strides->data()), |
| const_cast<void *>(ptr), flags, nullptr)); |
| if (!tmp) |
| throw error_already_set(); |
| if (ptr) { |
| if (base) { |
| api.PyArray_SetBaseObject_(tmp.ptr(), base.inc_ref().ptr()); |
| } else { |
| tmp = reinterpret_steal<object>(api.PyArray_NewCopy_(tmp.ptr(), -1 /* any order */)); |
| } |
| } |
| m_ptr = tmp.release().ptr(); |
| } |
| |
| array(const pybind11::dtype &dt, ShapeContainer shape, const void *ptr = nullptr, handle base = handle()) |
| : array(dt, std::move(shape), {}, ptr, base) { } |
| |
| template <typename T, typename = detail::enable_if_t<std::is_integral<T>::value && !std::is_same<bool, T>::value>> |
| array(const pybind11::dtype &dt, T count, const void *ptr = nullptr, handle base = handle()) |
| : array(dt, {{count}}, ptr, base) { } |
| |
| template <typename T> |
| array(ShapeContainer shape, StridesContainer strides, const T *ptr, handle base = handle()) |
| : array(pybind11::dtype::of<T>(), std::move(shape), std::move(strides), ptr, base) { } |
| |
| template <typename T> |
| array(ShapeContainer shape, const T *ptr, handle base = handle()) |
| : array(std::move(shape), {}, ptr, base) { } |
| |
| template <typename T> |
| explicit array(ssize_t count, const T *ptr, handle base = handle()) : array({count}, {}, ptr, base) { } |
| |
| explicit array(const buffer_info &info, handle base = handle()) |
| : array(pybind11::dtype(info), info.shape, info.strides, info.ptr, base) { } |
| |
| /// Array descriptor (dtype) |
| pybind11::dtype dtype() const { |
| return reinterpret_borrow<pybind11::dtype>(detail::array_proxy(m_ptr)->descr); |
| } |
| |
| /// Total number of elements |
| ssize_t size() const { |
| return std::accumulate(shape(), shape() + ndim(), (ssize_t) 1, std::multiplies<ssize_t>()); |
| } |
| |
| /// Byte size of a single element |
| ssize_t itemsize() const { |
| return detail::array_descriptor_proxy(detail::array_proxy(m_ptr)->descr)->elsize; |
| } |
| |
| /// Total number of bytes |
| ssize_t nbytes() const { |
| return size() * itemsize(); |
| } |
| |
| /// Number of dimensions |
| ssize_t ndim() const { |
| return detail::array_proxy(m_ptr)->nd; |
| } |
| |
| /// Base object |
| object base() const { |
| return reinterpret_borrow<object>(detail::array_proxy(m_ptr)->base); |
| } |
| |
| /// Dimensions of the array |
| const ssize_t* shape() const { |
| return detail::array_proxy(m_ptr)->dimensions; |
| } |
| |
| /// Dimension along a given axis |
| ssize_t shape(ssize_t dim) const { |
| if (dim >= ndim()) |
| fail_dim_check(dim, "invalid axis"); |
| return shape()[dim]; |
| } |
| |
| /// Strides of the array |
| const ssize_t* strides() const { |
| return detail::array_proxy(m_ptr)->strides; |
| } |
| |
| /// Stride along a given axis |
| ssize_t strides(ssize_t dim) const { |
| if (dim >= ndim()) |
| fail_dim_check(dim, "invalid axis"); |
| return strides()[dim]; |
| } |
| |
| /// Return the NumPy array flags |
| int flags() const { |
| return detail::array_proxy(m_ptr)->flags; |
| } |
| |
| /// If set, the array is writeable (otherwise the buffer is read-only) |
| bool writeable() const { |
| return detail::check_flags(m_ptr, detail::npy_api::NPY_ARRAY_WRITEABLE_); |
| } |
| |
| /// If set, the array owns the data (will be freed when the array is deleted) |
| bool owndata() const { |
| return detail::check_flags(m_ptr, detail::npy_api::NPY_ARRAY_OWNDATA_); |
| } |
| |
| /// Pointer to the contained data. If index is not provided, points to the |
| /// beginning of the buffer. May throw if the index would lead to out of bounds access. |
| template<typename... Ix> const void* data(Ix... index) const { |
| return static_cast<const void *>(detail::array_proxy(m_ptr)->data + offset_at(index...)); |
| } |
| |
| /// Mutable pointer to the contained data. If index is not provided, points to the |
| /// beginning of the buffer. May throw if the index would lead to out of bounds access. |
| /// May throw if the array is not writeable. |
| template<typename... Ix> void* mutable_data(Ix... index) { |
| check_writeable(); |
| return static_cast<void *>(detail::array_proxy(m_ptr)->data + offset_at(index...)); |
| } |
| |
| /// Byte offset from beginning of the array to a given index (full or partial). |
| /// May throw if the index would lead to out of bounds access. |
| template<typename... Ix> ssize_t offset_at(Ix... index) const { |
| if ((ssize_t) sizeof...(index) > ndim()) |
| fail_dim_check(sizeof...(index), "too many indices for an array"); |
| return byte_offset(ssize_t(index)...); |
| } |
| |
| ssize_t offset_at() const { return 0; } |
| |
| /// Item count from beginning of the array to a given index (full or partial). |
| /// May throw if the index would lead to out of bounds access. |
| template<typename... Ix> ssize_t index_at(Ix... index) const { |
| return offset_at(index...) / itemsize(); |
| } |
| |
| /** |
| * Returns a proxy object that provides access to the array's data without bounds or |
| * dimensionality checking. Will throw if the array is missing the `writeable` flag. Use with |
| * care: the array must not be destroyed or reshaped for the duration of the returned object, |
| * 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 (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()); |
| } |
| |
| /** |
| * Returns a proxy object that provides const access to the array's data without bounds or |
| * dimensionality checking. Unlike `mutable_unchecked()`, this does not require that the |
| * underlying array have the `writable` flag. Use with care: the array must not be destroyed or |
| * reshaped for the duration of the returned object, and the caller must take care not to access |
| * invalid dimensions or dimension indices. |
| */ |
| template <typename T, ssize_t Dims = -1> detail::unchecked_reference<T, Dims> unchecked() const & { |
| 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()); |
| } |
| |
| /// Return a new view with all of the dimensions of length 1 removed |
| array squeeze() { |
| auto& api = detail::npy_api::get(); |
| return reinterpret_steal<array>(api.PyArray_Squeeze_(m_ptr)); |
| } |
| |
| /// Resize array to given shape |
| /// If refcheck is true and more that one reference exist to this array |
| /// then resize will succeed only if it makes a reshape, i.e. original size doesn't change |
| void resize(ShapeContainer new_shape, bool refcheck = true) { |
| detail::npy_api::PyArray_Dims d = { |
| // Use reinterpret_cast for PyPy on Windows (remove if fixed, checked on 7.3.1) |
| reinterpret_cast<Py_intptr_t*>(new_shape->data()), |
| int(new_shape->size()) |
| }; |
| // try to resize, set ordering param to -1 cause it's not used anyway |
| auto new_array = reinterpret_steal<object>( |
| detail::npy_api::get().PyArray_Resize_(m_ptr, &d, int(refcheck), -1) |
| ); |
| if (!new_array) throw error_already_set(); |
| 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) { |
| auto result = reinterpret_steal<array>(raw_array(h.ptr(), ExtraFlags)); |
| if (!result) |
| PyErr_Clear(); |
| return result; |
| } |
| |
| protected: |
| template<typename, typename> friend struct detail::npy_format_descriptor; |
| |
| void fail_dim_check(ssize_t dim, const std::string& msg) const { |
| throw index_error(msg + ": " + std::to_string(dim) + |
| " (ndim = " + std::to_string(ndim()) + ")"); |
| } |
| |
| template<typename... Ix> ssize_t byte_offset(Ix... index) const { |
| check_dimensions(index...); |
| return detail::byte_offset_unsafe(strides(), ssize_t(index)...); |
| } |
| |
| void check_writeable() const { |
| if (!writeable()) |
| throw std::domain_error("array is not writeable"); |
| } |
| |
| template<typename... Ix> void check_dimensions(Ix... index) const { |
| check_dimensions_impl(ssize_t(0), shape(), ssize_t(index)...); |
| } |
| |
| void check_dimensions_impl(ssize_t, const ssize_t*) const { } |
| |
| template<typename... Ix> void check_dimensions_impl(ssize_t axis, const ssize_t* shape, ssize_t i, Ix... index) const { |
| if (i >= *shape) { |
| throw index_error(std::string("index ") + std::to_string(i) + |
| " is out of bounds for axis " + std::to_string(axis) + |
| " with size " + std::to_string(*shape)); |
| } |
| check_dimensions_impl(axis + 1, shape + 1, index...); |
| } |
| |
| /// Create array from any object -- always returns a new reference |
| static PyObject *raw_array(PyObject *ptr, int ExtraFlags = 0) { |
| if (ptr == nullptr) { |
| PyErr_SetString(PyExc_ValueError, "cannot create a pybind11::array from a nullptr"); |
| return nullptr; |
| } |
| return detail::npy_api::get().PyArray_FromAny_( |
| ptr, nullptr, 0, 0, detail::npy_api::NPY_ARRAY_ENSUREARRAY_ | ExtraFlags, nullptr); |
| } |
| }; |
| |
| template <typename T, int ExtraFlags = array::forcecast> class array_t : public array { |
| private: |
| struct private_ctor {}; |
| // Delegating constructor needed when both moving and accessing in the same constructor |
| array_t(private_ctor, ShapeContainer &&shape, StridesContainer &&strides, const T *ptr, handle base) |
| : array(std::move(shape), std::move(strides), ptr, base) {} |
| public: |
| static_assert(!detail::array_info<T>::is_array, "Array types cannot be used with array_t"); |
| |
| using value_type = T; |
| |
| array_t() : array(0, static_cast<const T *>(nullptr)) {} |
| array_t(handle h, borrowed_t) : array(h, borrowed_t{}) { } |
| array_t(handle h, stolen_t) : array(h, stolen_t{}) { } |
| |
| PYBIND11_DEPRECATED("Use array_t<T>::ensure() instead") |
| array_t(handle h, bool is_borrowed) : array(raw_array_t(h.ptr()), stolen_t{}) { |
| if (!m_ptr) PyErr_Clear(); |
| 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(); |
| } |
| |
| explicit array_t(const buffer_info& info, handle base = handle()) : array(info, base) { } |
| |
| array_t(ShapeContainer shape, StridesContainer strides, const T *ptr = nullptr, handle base = handle()) |
| : 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) != 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) { } |
| |
| constexpr ssize_t itemsize() const { |
| return sizeof(T); |
| } |
| |
| template<typename... Ix> ssize_t index_at(Ix... index) const { |
| return offset_at(index...) / itemsize(); |
| } |
| |
| template<typename... Ix> const T* data(Ix... index) const { |
| return static_cast<const T*>(array::data(index...)); |
| } |
| |
| template<typename... Ix> T* mutable_data(Ix... index) { |
| return static_cast<T*>(array::mutable_data(index...)); |
| } |
| |
| // Reference to element at a given index |
| template<typename... Ix> const T& at(Ix... index) const { |
| if ((ssize_t) sizeof...(index) != ndim()) |
| fail_dim_check(sizeof...(index), "index dimension mismatch"); |
| return *(static_cast<const T*>(array::data()) + byte_offset(ssize_t(index)...) / itemsize()); |
| } |
| |
| // Mutable reference to element at a given index |
| template<typename... Ix> T& mutable_at(Ix... index) { |
| if ((ssize_t) sizeof...(index) != ndim()) |
| fail_dim_check(sizeof...(index), "index dimension mismatch"); |
| return *(static_cast<T*>(array::mutable_data()) + byte_offset(ssize_t(index)...) / itemsize()); |
| } |
| |
| /** |
| * Returns a proxy object that provides access to the array's data without bounds or |
| * dimensionality checking. Will throw if the array is missing the `writeable` flag. Use with |
| * care: the array must not be destroyed or reshaped for the duration of the returned object, |
| * and the caller must take care not to access invalid dimensions or dimension indices. |
| */ |
| template <ssize_t Dims = -1> detail::unchecked_mutable_reference<T, Dims> mutable_unchecked() & { |
| return array::mutable_unchecked<T, Dims>(); |
| } |
| |
| /** |
| * Returns a proxy object that provides const access to the array's data without bounds or |
| * dimensionality checking. Unlike `unchecked()`, this does not require that the underlying |
| * array have the `writable` flag. Use with care: the array must not be destroyed or reshaped |
| * for the duration of the returned object, and the caller must take care not to access invalid |
| * dimensions or dimension indices. |
| */ |
| template <ssize_t Dims = -1> detail::unchecked_reference<T, Dims> unchecked() const & { |
| return array::unchecked<T, Dims>(); |
| } |
| |
| /// Ensure that the argument is a NumPy array of the correct dtype (and if not, try to convert |
| /// it). In case of an error, nullptr is returned and the Python error is cleared. |
| static array_t ensure(handle h) { |
| auto result = reinterpret_steal<array_t>(raw_array_t(h.ptr())); |
| if (!result) |
| PyErr_Clear(); |
| return result; |
| } |
| |
| static bool check_(handle h) { |
| const auto &api = detail::npy_api::get(); |
| return api.PyArray_Check_(h.ptr()) |
| && api.PyArray_EquivTypes_(detail::array_proxy(h.ptr())->descr, dtype::of<T>().ptr()) |
| && detail::check_flags(h.ptr(), ExtraFlags & (array::c_style | array::f_style)); |
| } |
| |
| protected: |
| /// Create array from any object -- always returns a new reference |
| static PyObject *raw_array_t(PyObject *ptr) { |
| if (ptr == nullptr) { |
| PyErr_SetString(PyExc_ValueError, "cannot create a pybind11::array_t from a nullptr"); |
| return nullptr; |
| } |
| return detail::npy_api::get().PyArray_FromAny_( |
| ptr, dtype::of<T>().release().ptr(), 0, 0, |
| detail::npy_api::NPY_ARRAY_ENSUREARRAY_ | ExtraFlags, nullptr); |
| } |
| }; |
| |
| template <typename T> |
| struct format_descriptor<T, detail::enable_if_t<detail::is_pod_struct<T>::value>> { |
| static std::string format() { |
| return detail::npy_format_descriptor<typename std::remove_cv<T>::type>::format(); |
| } |
| }; |
| |
| template <size_t N> struct format_descriptor<char[N]> { |
| static std::string format() { return std::to_string(N) + "s"; } |
| }; |
| template <size_t N> struct format_descriptor<std::array<char, N>> { |
| static std::string format() { return std::to_string(N) + "s"; } |
| }; |
| |
| template <typename T> |
| struct format_descriptor<T, detail::enable_if_t<std::is_enum<T>::value>> { |
| static std::string format() { |
| return format_descriptor< |
| typename std::remove_cv<typename std::underlying_type<T>::type>::type>::format(); |
| } |
| }; |
| |
| template <typename T> |
| struct format_descriptor<T, detail::enable_if_t<detail::array_info<T>::is_array>> { |
| static std::string format() { |
| using namespace detail; |
| static constexpr auto extents = _("(") + array_info<T>::extents + _(")"); |
| return extents.text + format_descriptor<remove_all_extents_t<T>>::format(); |
| } |
| }; |
| |
| PYBIND11_NAMESPACE_BEGIN(detail) |
| template <typename T, int ExtraFlags> |
| struct pyobject_caster<array_t<T, ExtraFlags>> { |
| using type = array_t<T, ExtraFlags>; |
| |
| bool load(handle src, bool convert) { |
| if (!convert && !type::check_(src)) |
| return false; |
| value = type::ensure(src); |
| return static_cast<bool>(value); |
| } |
| |
| static handle cast(const handle &src, return_value_policy /* policy */, handle /* parent */) { |
| return src.inc_ref(); |
| } |
| PYBIND11_TYPE_CASTER(type, handle_type_name<type>::name); |
| }; |
| |
| template <typename T> |
| struct compare_buffer_info<T, detail::enable_if_t<detail::is_pod_struct<T>::value>> { |
| static bool compare(const buffer_info& b) { |
| return npy_api::get().PyArray_EquivTypes_(dtype::of<T>().ptr(), dtype(b).ptr()); |
| } |
| }; |
| |
| template <typename T, typename = void> |
| struct npy_format_descriptor_name; |
| |
| template <typename T> |
| struct npy_format_descriptor_name<T, enable_if_t<std::is_integral<T>::value>> { |
| static constexpr auto name = _<std::is_same<T, bool>::value>( |
| _("bool"), _<std::is_signed<T>::value>("numpy.int", "numpy.uint") + _<sizeof(T)*8>() |
| ); |
| }; |
| |
| 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, const float>::value |
| || std::is_same<T, double>::value |
| || std::is_same<T, const double>::value>( |
| _("numpy.float") + _<sizeof(T)*8>(), _("numpy.longdouble") |
| ); |
| }; |
| |
| 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, 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") |
| ); |
| }; |
| |
| template <typename T> |
| struct npy_format_descriptor<T, enable_if_t<satisfies_any_of<T, std::is_arithmetic, is_complex>::value>> |
| : npy_format_descriptor_name<T> { |
| private: |
| // NB: the order here must match the one in common.h |
| constexpr static const int values[15] = { |
| npy_api::NPY_BOOL_, |
| npy_api::NPY_BYTE_, npy_api::NPY_UBYTE_, npy_api::NPY_INT16_, npy_api::NPY_UINT16_, |
| npy_api::NPY_INT32_, npy_api::NPY_UINT32_, npy_api::NPY_INT64_, npy_api::NPY_UINT64_, |
| npy_api::NPY_FLOAT_, npy_api::NPY_DOUBLE_, npy_api::NPY_LONGDOUBLE_, |
| npy_api::NPY_CFLOAT_, npy_api::NPY_CDOUBLE_, npy_api::NPY_CLONGDOUBLE_ |
| }; |
| |
| public: |
| static constexpr int value = values[detail::is_fmt_numeric<T>::index]; |
| |
| static pybind11::dtype dtype() { |
| if (auto ptr = npy_api::get().PyArray_DescrFromType_(value)) |
| return reinterpret_steal<pybind11::dtype>(ptr); |
| pybind11_fail("Unsupported buffer format!"); |
| } |
| }; |
| |
| #define PYBIND11_DECL_CHAR_FMT \ |
| static constexpr auto name = _("S") + _<N>(); \ |
| static pybind11::dtype dtype() { return pybind11::dtype(std::string("S") + std::to_string(N)); } |
| template <size_t N> struct npy_format_descriptor<char[N]> { PYBIND11_DECL_CHAR_FMT }; |
| template <size_t N> struct npy_format_descriptor<std::array<char, N>> { PYBIND11_DECL_CHAR_FMT }; |
| #undef PYBIND11_DECL_CHAR_FMT |
| |
| template<typename T> struct npy_format_descriptor<T, enable_if_t<array_info<T>::is_array>> { |
| private: |
| using base_descr = npy_format_descriptor<typename array_info<T>::type>; |
| public: |
| static_assert(!array_info<T>::is_empty, "Zero-sized arrays are not supported"); |
| |
| static constexpr auto name = _("(") + array_info<T>::extents + _(")") + base_descr::name; |
| static pybind11::dtype dtype() { |
| list shape; |
| array_info<T>::append_extents(shape); |
| return pybind11::dtype::from_args(pybind11::make_tuple(base_descr::dtype(), shape)); |
| } |
| }; |
| |
| template<typename T> struct npy_format_descriptor<T, enable_if_t<std::is_enum<T>::value>> { |
| private: |
| using base_descr = npy_format_descriptor<typename std::underlying_type<T>::type>; |
| public: |
| static constexpr auto name = base_descr::name; |
| static pybind11::dtype dtype() { return base_descr::dtype(); } |
| }; |
| |
| struct field_descriptor { |
| const char *name; |
| ssize_t offset; |
| ssize_t size; |
| std::string format; |
| dtype descr; |
| }; |
| |
| PYBIND11_NOINLINE void register_structured_dtype( |
| any_container<field_descriptor> fields, |
| const std::type_info& tinfo, ssize_t itemsize, |
| bool (*direct_converter)(PyObject *, void *&)) { |
| |
| auto& numpy_internals = get_numpy_internals(); |
| if (numpy_internals.get_type_info(tinfo, false)) |
| pybind11_fail("NumPy: dtype is already registered"); |
| |
| // Use ordered fields because order matters as of NumPy 1.14: |
| // https://docs.scipy.org/doc/numpy/release.html#multiple-field-indexing-assignment-of-structured-arrays |
| std::vector<field_descriptor> ordered_fields(std::move(fields)); |
| std::sort(ordered_fields.begin(), ordered_fields.end(), |
| [](const field_descriptor &a, const field_descriptor &b) { return a.offset < b.offset; }); |
| |
| list names, formats, offsets; |
| for (auto& field : ordered_fields) { |
| if (!field.descr) |
| pybind11_fail(std::string("NumPy: unsupported field dtype: `") + |
| field.name + "` @ " + tinfo.name()); |
| names.append(PYBIND11_STR_TYPE(field.name)); |
| formats.append(field.descr); |
| offsets.append(pybind11::int_(field.offset)); |
| } |
| 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 |
| // get fixed in v1.12; for further details, see these: |
| // - https://github.com/numpy/numpy/issues/7797 |
| // - https://github.com/numpy/numpy/pull/7798 |
| // Because of this, we won't use numpy's logic to generate buffer format |
| // strings and will just do it ourselves. |
| ssize_t offset = 0; |
| std::ostringstream oss; |
| // mark the structure as unaligned with '^', because numpy and C++ don't |
| // always agree about alignment (particularly for complex), and we're |
| // explicitly listing all our padding. This depends on none of the fields |
| // overriding the endianness. Putting the ^ in front of individual fields |
| // isn't guaranteed to work due to https://github.com/numpy/numpy/issues/9049 |
| oss << "^T{"; |
| for (auto& field : ordered_fields) { |
| if (field.offset > offset) |
| oss << (field.offset - offset) << 'x'; |
| oss << field.format << ':' << field.name << ':'; |
| offset = field.offset + field.size; |
| } |
| if (itemsize > offset) |
| oss << (itemsize - offset) << 'x'; |
| oss << '}'; |
| auto format_str = oss.str(); |
| |
| // Sanity check: verify that NumPy properly parses our buffer format string |
| auto& api = npy_api::get(); |
| auto arr = array(buffer_info(nullptr, itemsize, format_str, 1)); |
| if (!api.PyArray_EquivTypes_(dtype_ptr, arr.dtype().ptr())) |
| pybind11_fail("NumPy: invalid buffer descriptor!"); |
| |
| auto tindex = std::type_index(tinfo); |
| numpy_internals.registered_dtypes[tindex] = { dtype_ptr, format_str }; |
| get_internals().direct_conversions[tindex].push_back(direct_converter); |
| } |
| |
| template <typename T, typename SFINAE> struct npy_format_descriptor { |
| static_assert(is_pod_struct<T>::value, "Attempt to use a non-POD or unimplemented POD type as a numpy dtype"); |
| |
| static constexpr auto name = make_caster<T>::name; |
| |
| static pybind11::dtype dtype() { |
| return reinterpret_borrow<pybind11::dtype>(dtype_ptr()); |
| } |
| |
| static std::string format() { |
| static auto format_str = get_numpy_internals().get_type_info<T>(true)->format_str; |
| return format_str; |
| } |
| |
| static void register_dtype(any_container<field_descriptor> fields) { |
| register_structured_dtype(std::move(fields), typeid(typename std::remove_cv<T>::type), |
| sizeof(T), &direct_converter); |
| } |
| |
| private: |
| static PyObject* dtype_ptr() { |
| static PyObject* ptr = get_numpy_internals().get_type_info<T>(true)->dtype_ptr; |
| return ptr; |
| } |
| |
| static bool direct_converter(PyObject *obj, void*& value) { |
| auto& api = npy_api::get(); |
| if (!PyObject_TypeCheck(obj, api.PyVoidArrType_Type_)) |
| return false; |
| if (auto descr = reinterpret_steal<object>(api.PyArray_DescrFromScalar_(obj))) { |
| if (api.PyArray_EquivTypes_(dtype_ptr(), descr.ptr())) { |
| value = ((PyVoidScalarObject_Proxy *) obj)->obval; |
| return true; |
| } |
| } |
| return false; |
| } |
| }; |
| |
| #ifdef __CLION_IDE__ // replace heavy macro with dummy code for the IDE (doesn't affect code) |
| # define PYBIND11_NUMPY_DTYPE(Type, ...) ((void)0) |
| # define PYBIND11_NUMPY_DTYPE_EX(Type, ...) ((void)0) |
| #else |
| |
| #define PYBIND11_FIELD_DESCRIPTOR_EX(T, Field, Name) \ |
| ::pybind11::detail::field_descriptor { \ |
| Name, offsetof(T, Field), sizeof(decltype(std::declval<T>().Field)), \ |
| ::pybind11::format_descriptor<decltype(std::declval<T>().Field)>::format(), \ |
| ::pybind11::detail::npy_format_descriptor<decltype(std::declval<T>().Field)>::dtype() \ |
| } |
| |
| // Extract name, offset and format descriptor for a struct field |
| #define PYBIND11_FIELD_DESCRIPTOR(T, Field) PYBIND11_FIELD_DESCRIPTOR_EX(T, Field, #Field) |
| |
| // The main idea of this macro is borrowed from https://github.com/swansontec/map-macro |
| // (C) William Swanson, Paul Fultz |
| #define PYBIND11_EVAL0(...) __VA_ARGS__ |
| #define PYBIND11_EVAL1(...) PYBIND11_EVAL0 (PYBIND11_EVAL0 (PYBIND11_EVAL0 (__VA_ARGS__))) |
| #define PYBIND11_EVAL2(...) PYBIND11_EVAL1 (PYBIND11_EVAL1 (PYBIND11_EVAL1 (__VA_ARGS__))) |
| #define PYBIND11_EVAL3(...) PYBIND11_EVAL2 (PYBIND11_EVAL2 (PYBIND11_EVAL2 (__VA_ARGS__))) |
| #define PYBIND11_EVAL4(...) PYBIND11_EVAL3 (PYBIND11_EVAL3 (PYBIND11_EVAL3 (__VA_ARGS__))) |
| #define PYBIND11_EVAL(...) PYBIND11_EVAL4 (PYBIND11_EVAL4 (PYBIND11_EVAL4 (__VA_ARGS__))) |
| #define PYBIND11_MAP_END(...) |
| #define PYBIND11_MAP_OUT |
| #define PYBIND11_MAP_COMMA , |
| #define PYBIND11_MAP_GET_END() 0, PYBIND11_MAP_END |
| #define PYBIND11_MAP_NEXT0(test, next, ...) next PYBIND11_MAP_OUT |
| #define PYBIND11_MAP_NEXT1(test, next) PYBIND11_MAP_NEXT0 (test, next, 0) |
| #define PYBIND11_MAP_NEXT(test, next) PYBIND11_MAP_NEXT1 (PYBIND11_MAP_GET_END test, next) |
| #if defined(_MSC_VER) && !defined(__clang__) // MSVC is not as eager to expand macros, hence this workaround |
| #define PYBIND11_MAP_LIST_NEXT1(test, next) \ |
| PYBIND11_EVAL0 (PYBIND11_MAP_NEXT0 (test, PYBIND11_MAP_COMMA next, 0)) |
| #else |
| #define PYBIND11_MAP_LIST_NEXT1(test, next) \ |
| PYBIND11_MAP_NEXT0 (test, PYBIND11_MAP_COMMA next, 0) |
| #endif |
| #define PYBIND11_MAP_LIST_NEXT(test, next) \ |
| PYBIND11_MAP_LIST_NEXT1 (PYBIND11_MAP_GET_END test, next) |
| #define PYBIND11_MAP_LIST0(f, t, x, peek, ...) \ |
| f(t, x) PYBIND11_MAP_LIST_NEXT (peek, PYBIND11_MAP_LIST1) (f, t, peek, __VA_ARGS__) |
| #define PYBIND11_MAP_LIST1(f, t, x, peek, ...) \ |
| f(t, x) PYBIND11_MAP_LIST_NEXT (peek, PYBIND11_MAP_LIST0) (f, t, peek, __VA_ARGS__) |
| // PYBIND11_MAP_LIST(f, t, a1, a2, ...) expands to f(t, a1), f(t, a2), ... |
| #define PYBIND11_MAP_LIST(f, t, ...) \ |
| PYBIND11_EVAL (PYBIND11_MAP_LIST1 (f, t, __VA_ARGS__, (), 0)) |
| |
| #define PYBIND11_NUMPY_DTYPE(Type, ...) \ |
| ::pybind11::detail::npy_format_descriptor<Type>::register_dtype \ |
| (::std::vector<::pybind11::detail::field_descriptor> \ |
| {PYBIND11_MAP_LIST (PYBIND11_FIELD_DESCRIPTOR, Type, __VA_ARGS__)}) |
| |
| #if defined(_MSC_VER) && !defined(__clang__) |
| #define PYBIND11_MAP2_LIST_NEXT1(test, next) \ |
| PYBIND11_EVAL0 (PYBIND11_MAP_NEXT0 (test, PYBIND11_MAP_COMMA next, 0)) |
| #else |
| #define PYBIND11_MAP2_LIST_NEXT1(test, next) \ |
| PYBIND11_MAP_NEXT0 (test, PYBIND11_MAP_COMMA next, 0) |
| #endif |
| #define PYBIND11_MAP2_LIST_NEXT(test, next) \ |
| PYBIND11_MAP2_LIST_NEXT1 (PYBIND11_MAP_GET_END test, next) |
| #define PYBIND11_MAP2_LIST0(f, t, x1, x2, peek, ...) \ |
| f(t, x1, x2) PYBIND11_MAP2_LIST_NEXT (peek, PYBIND11_MAP2_LIST1) (f, t, peek, __VA_ARGS__) |
| #define PYBIND11_MAP2_LIST1(f, t, x1, x2, peek, ...) \ |
| f(t, x1, x2) PYBIND11_MAP2_LIST_NEXT (peek, PYBIND11_MAP2_LIST0) (f, t, peek, __VA_ARGS__) |
| // PYBIND11_MAP2_LIST(f, t, a1, a2, ...) expands to f(t, a1, a2), f(t, a3, a4), ... |
| #define PYBIND11_MAP2_LIST(f, t, ...) \ |
| PYBIND11_EVAL (PYBIND11_MAP2_LIST1 (f, t, __VA_ARGS__, (), 0)) |
| |
| #define PYBIND11_NUMPY_DTYPE_EX(Type, ...) \ |
| ::pybind11::detail::npy_format_descriptor<Type>::register_dtype \ |
| (::std::vector<::pybind11::detail::field_descriptor> \ |
| {PYBIND11_MAP2_LIST (PYBIND11_FIELD_DESCRIPTOR_EX, Type, __VA_ARGS__)}) |
| |
| #endif // __CLION_IDE__ |
| |
| class common_iterator { |
| public: |
| using container_type = std::vector<ssize_t>; |
| using value_type = container_type::value_type; |
| using size_type = container_type::size_type; |
| |
| 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()) { |
| m_strides.back() = static_cast<value_type>(strides.back()); |
| for (size_type i = m_strides.size() - 1; i != 0; --i) { |
| size_type j = i - 1; |
| auto s = static_cast<value_type>(shape[i]); |
| m_strides[j] = strides[j] + m_strides[i] - strides[i] * s; |
| } |
| } |
| |
| void increment(size_type dim) { |
| p_ptr += m_strides[dim]; |
| } |
| |
| void* data() const { |
| return p_ptr; |
| } |
| |
| private: |
| char *p_ptr{0}; |
| container_type m_strides; |
| }; |
| |
| template <size_t N> class multi_array_iterator { |
| public: |
| using container_type = std::vector<ssize_t>; |
| |
| multi_array_iterator(const std::array<buffer_info, N> &buffers, |
| const container_type &shape) |
| : m_shape(shape.size()), m_index(shape.size(), 0), |
| m_common_iterator() { |
| |
| // Manual copy to avoid conversion warning if using std::copy |
| for (size_t i = 0; i < shape.size(); ++i) |
| m_shape[i] = shape[i]; |
| |
| container_type strides(shape.size()); |
| for (size_t i = 0; i < N; ++i) |
| init_common_iterator(buffers[i], shape, m_common_iterator[i], strides); |
| } |
| |
| multi_array_iterator& operator++() { |
| for (size_t j = m_index.size(); j != 0; --j) { |
| size_t i = j - 1; |
| if (++m_index[i] != m_shape[i]) { |
| increment_common_iterator(i); |
| break; |
| } |
| m_index[i] = 0; |
| } |
| return *this; |
| } |
| |
| template <size_t K, class T = void> T* data() const { |
| return reinterpret_cast<T*>(m_common_iterator[K].data()); |
| } |
| |
| private: |
| |
| using common_iter = common_iterator; |
| |
| void init_common_iterator(const buffer_info &buffer, |
| const container_type &shape, |
| common_iter &iterator, |
| container_type &strides) { |
| auto buffer_shape_iter = buffer.shape.rbegin(); |
| auto buffer_strides_iter = buffer.strides.rbegin(); |
| auto shape_iter = shape.rbegin(); |
| auto strides_iter = strides.rbegin(); |
| |
| while (buffer_shape_iter != buffer.shape.rend()) { |
| if (*shape_iter == *buffer_shape_iter) |
| *strides_iter = *buffer_strides_iter; |
| else |
| *strides_iter = 0; |
| |
| ++buffer_shape_iter; |
| ++buffer_strides_iter; |
| ++shape_iter; |
| ++strides_iter; |
| } |
| |
| std::fill(strides_iter, strides.rend(), 0); |
| iterator = common_iter(buffer.ptr, strides, shape); |
| } |
| |
| void increment_common_iterator(size_t dim) { |
| for (auto &iter : m_common_iterator) |
| iter.increment(dim); |
| } |
| |
| container_type m_shape; |
| container_type m_index; |
| std::array<common_iter, N> m_common_iterator; |
| }; |
| |
| enum class broadcast_trivial { non_trivial, c_trivial, f_trivial }; |
| |
| // Populates the shape and number of dimensions for the set of buffers. Returns a broadcast_trivial |
| // enum value indicating whether the broadcast is "trivial"--that is, has each buffer being either a |
| // singleton or a full-size, C-contiguous (`c_trivial`) or Fortran-contiguous (`f_trivial`) storage |
| // buffer; returns `non_trivial` otherwise. |
| template <size_t N> |
| broadcast_trivial broadcast(const std::array<buffer_info, N> &buffers, ssize_t &ndim, std::vector<ssize_t> &shape) { |
| ndim = std::accumulate(buffers.begin(), buffers.end(), ssize_t(0), [](ssize_t res, const buffer_info &buf) { |
| return std::max(res, buf.ndim); |
| }); |
| |
| shape.clear(); |
| shape.resize((size_t) ndim, 1); |
| |
| // Figure out the output size, and make sure all input arrays conform (i.e. are either size 1 or |
| // the full size). |
| for (size_t i = 0; i < N; ++i) { |
| auto res_iter = shape.rbegin(); |
| auto end = buffers[i].shape.rend(); |
| for (auto shape_iter = buffers[i].shape.rbegin(); shape_iter != end; ++shape_iter, ++res_iter) { |
| const auto &dim_size_in = *shape_iter; |
| auto &dim_size_out = *res_iter; |
| |
| // Each input dimension can either be 1 or `n`, but `n` values must match across buffers |
| if (dim_size_out == 1) |
| dim_size_out = dim_size_in; |
| else if (dim_size_in != 1 && dim_size_in != dim_size_out) |
| pybind11_fail("pybind11::vectorize: incompatible size/dimension of inputs!"); |
| } |
| } |
| |
| bool trivial_broadcast_c = true; |
| bool trivial_broadcast_f = true; |
| for (size_t i = 0; i < N && (trivial_broadcast_c || trivial_broadcast_f); ++i) { |
| if (buffers[i].size == 1) |
| continue; |
| |
| // Require the same number of dimensions: |
| if (buffers[i].ndim != ndim) |
| return broadcast_trivial::non_trivial; |
| |
| // Require all dimensions be full-size: |
| if (!std::equal(buffers[i].shape.cbegin(), buffers[i].shape.cend(), shape.cbegin())) |
| return broadcast_trivial::non_trivial; |
| |
| // Check for C contiguity (but only if previous inputs were also C contiguous) |
| if (trivial_broadcast_c) { |
| ssize_t expect_stride = buffers[i].itemsize; |
| auto end = buffers[i].shape.crend(); |
| for (auto shape_iter = buffers[i].shape.crbegin(), stride_iter = buffers[i].strides.crbegin(); |
| trivial_broadcast_c && shape_iter != end; ++shape_iter, ++stride_iter) { |
| if (expect_stride == *stride_iter) |
| expect_stride *= *shape_iter; |
| else |
| trivial_broadcast_c = false; |
| } |
| } |
| |
| // Check for Fortran contiguity (if previous inputs were also F contiguous) |
| if (trivial_broadcast_f) { |
| ssize_t expect_stride = buffers[i].itemsize; |
| auto end = buffers[i].shape.cend(); |
| for (auto shape_iter = buffers[i].shape.cbegin(), stride_iter = buffers[i].strides.cbegin(); |
| trivial_broadcast_f && shape_iter != end; ++shape_iter, ++stride_iter) { |
| if (expect_stride == *stride_iter) |
| expect_stride *= *shape_iter; |
| else |
| trivial_broadcast_f = false; |
| } |
| } |
| } |
| |
| return |
| trivial_broadcast_c ? broadcast_trivial::c_trivial : |
| trivial_broadcast_f ? broadcast_trivial::f_trivial : |
| broadcast_trivial::non_trivial; |
| } |
| |
| template <typename T> |
| struct vectorize_arg { |
| static_assert(!std::is_rvalue_reference<T>::value, "Functions with rvalue reference arguments cannot be vectorized"); |
| // The wrapped function gets called with this type: |
| using call_type = remove_reference_t<T>; |
| // Is this a vectorized argument? |
| static constexpr bool vectorize = |
| satisfies_any_of<call_type, std::is_arithmetic, is_complex, is_pod>::value && |
| satisfies_none_of<call_type, std::is_pointer, std::is_array, is_std_array, std::is_enum>::value && |
| (!std::is_reference<T>::value || |
| (std::is_lvalue_reference<T>::value && std::is_const<call_type>::value)); |
| // Accept this type: an array for vectorized types, otherwise the type as-is: |
| using type = conditional_t<vectorize, array_t<remove_cv_t<call_type>, array::forcecast>, T>; |
| }; |
| |
| |
| // py::vectorize when a return type is present |
| template <typename Func, typename Return, typename... Args> |
| struct vectorize_returned_array { |
| using Type = array_t<Return>; |
| |
| 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); |
| return array_t<Return>(shape); |
| } |
| |
| static Return *mutable_data(Type &array) { |
| return array.mutable_data(); |
| } |
| |
| static Return call(Func &f, Args &... args) { |
| return f(args...); |
| } |
| |
| static void call(Return *out, size_t i, Func &f, Args &... args) { |
| out[i] = f(args...); |
| } |
| }; |
| |
| // py::vectorize when a return type is not present |
| template <typename Func, typename... Args> |
| struct vectorize_returned_array<Func, void, Args...> { |
| using Type = none; |
| |
| static Type create(broadcast_trivial, const std::vector<ssize_t> &) { |
| return none(); |
| } |
| |
| static void *mutable_data(Type &) { |
| return nullptr; |
| } |
| |
| static detail::void_type call(Func &f, Args &... args) { |
| f(args...); |
| return {}; |
| } |
| |
| static void call(void *, size_t, Func &f, Args &... args) { |
| f(args...); |
| } |
| }; |
| |
| |
| template <typename Func, typename Return, typename... Args> |
| struct vectorize_helper { |
| |
| // NVCC for some reason breaks if NVectorized is private |
| #ifdef __CUDACC__ |
| public: |
| #else |
| private: |
| #endif |
| |
| static constexpr size_t N = sizeof...(Args); |
| static constexpr size_t NVectorized = constexpr_sum(vectorize_arg<Args>::vectorize...); |
| static_assert(NVectorized >= 1, |
| "pybind11::vectorize(...) requires a function with at least one vectorizable argument"); |
| |
| public: |
| 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..., |
| make_index_sequence<N>(), |
| select_indices<vectorize_arg<Args>::vectorize...>(), |
| make_index_sequence<NVectorized>()); |
| } |
| |
| private: |
| remove_reference_t<Func> f; |
| |
| // Internal compiler error in MSVC 19.16.27025.1 (Visual Studio 2017 15.9.4), when compiling with "/permissive-" flag |
| // when arg_call_types is manually inlined. |
| using arg_call_types = std::tuple<typename vectorize_arg<Args>::call_type...>; |
| template <size_t Index> using param_n_t = typename std::tuple_element<Index, arg_call_types>::type; |
| |
| using returned_array = vectorize_returned_array<Func, Return, Args...>; |
| |
| // Runs a vectorized function given arguments tuple and three index sequences: |
| // - Index is the full set of 0 ... (N-1) argument indices; |
| // - VIndex is the subset of argument indices with vectorized parameters, letting us access |
| // vectorized arguments (anything not in this sequence is passed through) |
| // - BIndex is a incremental sequence (beginning at 0) of the same size as VIndex, so that |
| // we can store vectorized buffer_infos in an array (argument VIndex has its buffer at |
| // index BIndex in the array). |
| template <size_t... Index, size_t... VIndex, size_t... BIndex> object run( |
| typename vectorize_arg<Args>::type &...args, |
| index_sequence<Index...> i_seq, index_sequence<VIndex...> vi_seq, index_sequence<BIndex...> bi_seq) { |
| |
| // Pointers to values the function was called with; the vectorized ones set here will start |
| // out as array_t<T> pointers, but they will be changed them to T pointers before we make |
| // call the wrapped function. Non-vectorized pointers are left as-is. |
| std::array<void *, N> params{{ &args... }}; |
| |
| // The array of `buffer_info`s of vectorized arguments: |
| std::array<buffer_info, NVectorized> buffers{{ reinterpret_cast<array *>(params[VIndex])->request()... }}; |
| |
| /* Determine dimensions parameters of output array */ |
| ssize_t nd = 0; |
| std::vector<ssize_t> shape(0); |
| auto trivial = broadcast(buffers, nd, shape); |
| auto ndim = (size_t) nd; |
| |
| size_t size = std::accumulate(shape.begin(), shape.end(), (size_t) 1, std::multiplies<size_t>()); |
| |
| // If all arguments are 0-dimension arrays (i.e. single values) return a plain value (i.e. |
| // not wrapped in an array). |
| if (size == 1 && ndim == 0) { |
| PYBIND11_EXPAND_SIDE_EFFECTS(params[VIndex] = buffers[BIndex].ptr); |
| return cast(returned_array::call(f, *reinterpret_cast<param_n_t<Index> *>(params[Index])...)); |
| } |
| |
| auto result = returned_array::create(trivial, shape); |
| |
| if (size == 0) return std::move(result); |
| |
| /* Call the function */ |
| auto mutable_data = returned_array::mutable_data(result); |
| if (trivial == broadcast_trivial::non_trivial) |
| apply_broadcast(buffers, params, mutable_data, size, shape, i_seq, vi_seq, bi_seq); |
| else |
| apply_trivial(buffers, params, mutable_data, size, i_seq, vi_seq, bi_seq); |
| |
| return std::move(result); |
| } |
| |
| template <size_t... Index, size_t... VIndex, size_t... BIndex> |
| void apply_trivial(std::array<buffer_info, NVectorized> &buffers, |
| std::array<void *, N> ¶ms, |
| Return *out, |
| size_t size, |
| index_sequence<Index...>, index_sequence<VIndex...>, index_sequence<BIndex...>) { |
| |
| // Initialize an array of mutable byte references and sizes with references set to the |
| // appropriate pointer in `params`; as we iterate, we'll increment each pointer by its size |
| // (except for singletons, which get an increment of 0). |
| std::array<std::pair<unsigned char *&, const size_t>, NVectorized> vecparams{{ |
| std::pair<unsigned char *&, const size_t>( |
| reinterpret_cast<unsigned char *&>(params[VIndex] = buffers[BIndex].ptr), |
| buffers[BIndex].size == 1 ? 0 : sizeof(param_n_t<VIndex>) |
| )... |
| }}; |
| |
| for (size_t i = 0; i < size; ++i) { |
| returned_array::call(out, i, f, *reinterpret_cast<param_n_t<Index> *>(params[Index])...); |
| for (auto &x : vecparams) x.first += x.second; |
| } |
| } |
| |
| template <size_t... Index, size_t... VIndex, size_t... BIndex> |
| void apply_broadcast(std::array<buffer_info, NVectorized> &buffers, |
| std::array<void *, N> ¶ms, |
| Return *out, |
| size_t size, |
| const std::vector<ssize_t> &output_shape, |
| index_sequence<Index...>, index_sequence<VIndex...>, index_sequence<BIndex...>) { |
| |
| multi_array_iterator<NVectorized> input_iter(buffers, output_shape); |
| |
| for (size_t i = 0; i < size; ++i, ++input_iter) { |
| PYBIND11_EXPAND_SIDE_EFFECTS(( |
| params[VIndex] = input_iter.template data<BIndex>() |
| )); |
| returned_array::call(out, i, f, *reinterpret_cast<param_n_t<Index> *>(std::get<Index>(params))...); |
| } |
| } |
| }; |
| |
| template <typename Func, typename Return, typename... Args> |
| vectorize_helper<Func, Return, Args...> |
| vectorize_extractor(const Func &f, Return (*) (Args ...)) { |
| return detail::vectorize_helper<Func, Return, Args...>(f); |
| } |
| |
| template <typename T, int Flags> struct handle_type_name<array_t<T, Flags>> { |
| static constexpr auto name = _("numpy.ndarray[") + npy_format_descriptor<T>::name + _("]"); |
| }; |
| |
| PYBIND11_NAMESPACE_END(detail) |
| |
| // Vanilla pointer vectorizer: |
| template <typename Return, typename... Args> |
| detail::vectorize_helper<Return (*)(Args...), Return, Args...> |
| vectorize(Return (*f) (Args ...)) { |
| return detail::vectorize_helper<Return (*)(Args...), Return, Args...>(f); |
| } |
| |
| // lambda vectorizer: |
| template <typename Func, detail::enable_if_t<detail::is_lambda<Func>::value, int> = 0> |
| auto vectorize(Func &&f) -> decltype( |
| detail::vectorize_extractor(std::forward<Func>(f), (detail::function_signature_t<Func> *) nullptr)) { |
| return detail::vectorize_extractor(std::forward<Func>(f), (detail::function_signature_t<Func> *) nullptr); |
| } |
| |
| // Vectorize a class method (non-const): |
| template <typename Return, typename Class, typename... Args, |
| typename Helper = detail::vectorize_helper<decltype(std::mem_fn(std::declval<Return (Class::*)(Args...)>())), Return, Class *, Args...>> |
| Helper vectorize(Return (Class::*f)(Args...)) { |
| return Helper(std::mem_fn(f)); |
| } |
| |
| // Vectorize a class method (const): |
| template <typename Return, typename Class, typename... Args, |
| typename Helper = detail::vectorize_helper<decltype(std::mem_fn(std::declval<Return (Class::*)(Args...) const>())), Return, const Class *, Args...>> |
| Helper vectorize(Return (Class::*f)(Args...) const) { |
| return Helper(std::mem_fn(f)); |
| } |
| |
| PYBIND11_NAMESPACE_END(PYBIND11_NAMESPACE) |