mirror of
https://github.com/pybind/pybind11.git
synced 2024-11-22 13:15:12 +00:00
394 lines
14 KiB
C++
394 lines
14 KiB
C++
/*
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pybind11/numpy.h: Basic NumPy support, auto-vectorization support
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Copyright (c) 2015 Wenzel Jakob <wenzel@inf.ethz.ch>
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All rights reserved. Use of this source code is governed by a
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BSD-style license that can be found in the LICENSE file.
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*/
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#pragma once
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#include "pybind11.h"
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#include "complex.h"
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#include <numeric>
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#include <algorithm>
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#if defined(_MSC_VER)
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#pragma warning(push)
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#pragma warning(disable: 4127) // warning C4127: Conditional expression is constant
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#endif
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NAMESPACE_BEGIN(pybind11)
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template <typename type> struct npy_format_descriptor { };
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class array : public buffer {
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public:
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struct API {
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enum Entries {
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API_PyArray_Type = 2,
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API_PyArray_DescrFromType = 45,
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API_PyArray_FromAny = 69,
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API_PyArray_NewCopy = 85,
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API_PyArray_NewFromDescr = 94,
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NPY_C_CONTIGUOUS_ = 0x0001,
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NPY_F_CONTIGUOUS_ = 0x0002,
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NPY_ARRAY_FORCECAST_ = 0x0010,
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NPY_ENSURE_ARRAY_ = 0x0040,
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NPY_BOOL_ = 0,
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NPY_BYTE_, NPY_UBYTE_,
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NPY_SHORT_, NPY_USHORT_,
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NPY_INT_, NPY_UINT_,
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NPY_LONG_, NPY_ULONG_,
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NPY_LONGLONG_, NPY_ULONGLONG_,
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NPY_FLOAT_, NPY_DOUBLE_, NPY_LONGDOUBLE_,
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NPY_CFLOAT_, NPY_CDOUBLE_, NPY_CLONGDOUBLE_
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};
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static API lookup() {
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module m = module::import("numpy.core.multiarray");
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object c = (object) m.attr("_ARRAY_API");
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#if PY_MAJOR_VERSION >= 3
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void **api_ptr = (void **) (c ? PyCapsule_GetPointer(c.ptr(), NULL) : nullptr);
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#else
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void **api_ptr = (void **) (c ? PyCObject_AsVoidPtr(c.ptr()) : nullptr);
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#endif
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API api;
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api.PyArray_Type_ = (decltype(api.PyArray_Type_)) api_ptr[API_PyArray_Type];
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api.PyArray_DescrFromType_ = (decltype(api.PyArray_DescrFromType_)) api_ptr[API_PyArray_DescrFromType];
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api.PyArray_FromAny_ = (decltype(api.PyArray_FromAny_)) api_ptr[API_PyArray_FromAny];
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api.PyArray_NewCopy_ = (decltype(api.PyArray_NewCopy_)) api_ptr[API_PyArray_NewCopy];
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api.PyArray_NewFromDescr_ = (decltype(api.PyArray_NewFromDescr_)) api_ptr[API_PyArray_NewFromDescr];
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return api;
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}
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bool PyArray_Check_(PyObject *obj) const { return (bool) PyObject_TypeCheck(obj, PyArray_Type_); }
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PyObject *(*PyArray_DescrFromType_)(int);
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PyObject *(*PyArray_NewFromDescr_)
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(PyTypeObject *, PyObject *, int, Py_intptr_t *,
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Py_intptr_t *, void *, int, PyObject *);
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PyObject *(*PyArray_NewCopy_)(PyObject *, int);
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PyTypeObject *PyArray_Type_;
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PyObject *(*PyArray_FromAny_) (PyObject *, PyObject *, int, int, int, PyObject *);
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};
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PYBIND11_OBJECT_DEFAULT(array, buffer, lookup_api().PyArray_Check_)
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template <typename Type> array(size_t size, const Type *ptr) {
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API& api = lookup_api();
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PyObject *descr = api.PyArray_DescrFromType_(npy_format_descriptor<Type>::value);
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if (descr == nullptr)
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pybind11_fail("NumPy: unsupported buffer format!");
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Py_intptr_t shape = (Py_intptr_t) size;
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object tmp = object(api.PyArray_NewFromDescr_(
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api.PyArray_Type_, descr, 1, &shape, nullptr, (void *) ptr, 0, nullptr), false);
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if (ptr && tmp)
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tmp = object(api.PyArray_NewCopy_(tmp.ptr(), -1 /* any order */), false);
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if (!tmp)
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pybind11_fail("NumPy: unable to create array!");
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m_ptr = tmp.release().ptr();
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}
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array(const buffer_info &info) {
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API& api = lookup_api();
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if ((info.format.size() < 1) || (info.format.size() > 2))
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pybind11_fail("Unsupported buffer format!");
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int fmt = (int) info.format[0];
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if (info.format == "Zd") fmt = API::NPY_CDOUBLE_;
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else if (info.format == "Zf") fmt = API::NPY_CFLOAT_;
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PyObject *descr = api.PyArray_DescrFromType_(fmt);
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if (descr == nullptr)
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pybind11_fail("NumPy: unsupported buffer format '" + info.format + "'!");
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object tmp(api.PyArray_NewFromDescr_(
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api.PyArray_Type_, descr, info.ndim, (Py_intptr_t *) &info.shape[0],
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(Py_intptr_t *) &info.strides[0], info.ptr, 0, nullptr), false);
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if (info.ptr && tmp)
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tmp = object(api.PyArray_NewCopy_(tmp.ptr(), -1 /* any order */), false);
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if (!tmp)
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pybind11_fail("NumPy: unable to create array!");
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m_ptr = tmp.release().ptr();
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}
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protected:
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static API &lookup_api() {
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static API api = API::lookup();
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return api;
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}
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};
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template <typename T> class array_t : public array {
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public:
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PYBIND11_OBJECT_CVT(array_t, array, is_non_null, m_ptr = ensure(m_ptr));
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array_t() : array() { }
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static bool is_non_null(PyObject *ptr) { return ptr != nullptr; }
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static PyObject *ensure(PyObject *ptr) {
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if (ptr == nullptr)
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return nullptr;
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API &api = lookup_api();
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PyObject *descr = api.PyArray_DescrFromType_(npy_format_descriptor<T>::value);
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PyObject *result = api.PyArray_FromAny_(
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ptr, descr, 0, 0, API::NPY_C_CONTIGUOUS_ | API::NPY_ENSURE_ARRAY_
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| API::NPY_ARRAY_FORCECAST_, nullptr);
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Py_DECREF(ptr);
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return result;
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}
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};
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#define DECL_FMT(t, n) template<> struct npy_format_descriptor<t> { enum { value = array::API::n }; }
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DECL_FMT(int8_t, NPY_BYTE_); DECL_FMT(uint8_t, NPY_UBYTE_); DECL_FMT(int16_t, NPY_SHORT_);
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DECL_FMT(uint16_t, NPY_USHORT_); DECL_FMT(int32_t, NPY_INT_); DECL_FMT(uint32_t, NPY_UINT_);
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DECL_FMT(int64_t, NPY_LONGLONG_); DECL_FMT(uint64_t, NPY_ULONGLONG_); DECL_FMT(float, NPY_FLOAT_);
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DECL_FMT(double, NPY_DOUBLE_); DECL_FMT(bool, NPY_BOOL_); DECL_FMT(std::complex<float>, NPY_CFLOAT_);
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DECL_FMT(std::complex<double>, NPY_CDOUBLE_);
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#undef DECL_FMT
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NAMESPACE_BEGIN(detail)
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template <class T>
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using array_iterator = typename std::add_pointer<T>::type;
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template <class T>
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array_iterator<T> array_begin(const buffer_info& buffer) {
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return array_iterator<T>(reinterpret_cast<T*>(buffer.ptr));
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}
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template <class T>
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array_iterator<T> array_end(const buffer_info& buffer) {
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return array_iterator<T>(reinterpret_cast<T*>(buffer.ptr) + buffer.size);
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}
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class common_iterator {
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public:
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using container_type = std::vector<size_t>;
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using value_type = container_type::value_type;
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using size_type = container_type::size_type;
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common_iterator() : p_ptr(0), m_strides() {}
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common_iterator(void* ptr, const container_type& strides, const std::vector<size_t>& shape)
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: p_ptr(reinterpret_cast<char*>(ptr)), m_strides(strides.size()) {
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m_strides.back() = static_cast<value_type>(strides.back());
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for (size_type i = m_strides.size() - 1; i != 0; --i) {
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size_type j = i - 1;
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value_type s = static_cast<value_type>(shape[i]);
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m_strides[j] = strides[j] + m_strides[i] - strides[i] * s;
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}
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}
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void increment(size_type dim) {
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p_ptr += m_strides[dim];
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}
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void* data() const {
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return p_ptr;
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}
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private:
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char* p_ptr;
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container_type m_strides;
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};
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template <size_t N> class multi_array_iterator {
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public:
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using container_type = std::vector<size_t>;
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multi_array_iterator(const std::array<buffer_info, N> &buffers,
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const std::vector<size_t> &shape)
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: m_shape(shape.size()), m_index(shape.size(), 0),
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m_common_iterator() {
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// Manual copy to avoid conversion warning if using std::copy
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for (size_t i = 0; i < shape.size(); ++i)
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m_shape[i] = static_cast<container_type::value_type>(shape[i]);
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container_type strides(shape.size());
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for (size_t i = 0; i < N; ++i)
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init_common_iterator(buffers[i], shape, m_common_iterator[i], strides);
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}
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multi_array_iterator& operator++() {
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for (size_t j = m_index.size(); j != 0; --j) {
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size_t i = j - 1;
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if (++m_index[i] != m_shape[i]) {
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increment_common_iterator(i);
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break;
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} else {
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m_index[i] = 0;
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}
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}
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return *this;
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}
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template <size_t K, class T> const T& data() const {
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return *reinterpret_cast<T*>(m_common_iterator[K].data());
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}
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private:
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using common_iter = common_iterator;
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void init_common_iterator(const buffer_info &buffer,
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const std::vector<size_t> &shape,
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common_iter &iterator, container_type &strides) {
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auto buffer_shape_iter = buffer.shape.rbegin();
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auto buffer_strides_iter = buffer.strides.rbegin();
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auto shape_iter = shape.rbegin();
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auto strides_iter = strides.rbegin();
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while (buffer_shape_iter != buffer.shape.rend()) {
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if (*shape_iter == *buffer_shape_iter)
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*strides_iter = static_cast<int>(*buffer_strides_iter);
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else
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*strides_iter = 0;
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++buffer_shape_iter;
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++buffer_strides_iter;
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++shape_iter;
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++strides_iter;
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}
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std::fill(strides_iter, strides.rend(), 0);
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iterator = common_iter(buffer.ptr, strides, shape);
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}
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void increment_common_iterator(size_t dim) {
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for (auto &iter : m_common_iterator)
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iter.increment(dim);
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}
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container_type m_shape;
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container_type m_index;
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std::array<common_iter, N> m_common_iterator;
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};
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template <size_t N>
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bool broadcast(const std::array<buffer_info, N>& buffers, int& ndim, std::vector<size_t>& shape) {
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ndim = std::accumulate(buffers.begin(), buffers.end(), 0, [](int res, const buffer_info& buf) {
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return std::max(res, buf.ndim);
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});
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shape = std::vector<size_t>(static_cast<size_t>(ndim), 1);
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bool trivial_broadcast = true;
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for (size_t i = 0; i < N; ++i) {
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auto res_iter = shape.rbegin();
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bool i_trivial_broadcast = (buffers[i].size == 1) || (buffers[i].ndim == ndim);
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for (auto shape_iter = buffers[i].shape.rbegin();
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shape_iter != buffers[i].shape.rend(); ++shape_iter, ++res_iter) {
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if (*res_iter == 1)
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*res_iter = *shape_iter;
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else if ((*shape_iter != 1) && (*res_iter != *shape_iter))
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pybind11_fail("pybind11::vectorize: incompatible size/dimension of inputs!");
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i_trivial_broadcast = i_trivial_broadcast && (*res_iter == *shape_iter);
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}
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trivial_broadcast = trivial_broadcast && i_trivial_broadcast;
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}
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return trivial_broadcast;
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}
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template <typename Func, typename Return, typename... Args>
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struct vectorize_helper {
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typename std::remove_reference<Func>::type f;
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template <typename T>
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vectorize_helper(T&&f) : f(std::forward<T>(f)) { }
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object operator()(array_t<Args>... args) {
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return run(args..., typename make_index_sequence<sizeof...(Args)>::type());
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}
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template <size_t ... Index> object run(array_t<Args>&... args, index_sequence<Index...> index) {
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/* Request buffers from all parameters */
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const size_t N = sizeof...(Args);
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std::array<buffer_info, N> buffers {{ args.request()... }};
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/* Determine dimensions parameters of output array */
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int ndim = 0;
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std::vector<size_t> shape(0);
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bool trivial_broadcast = broadcast(buffers, ndim, shape);
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size_t size = 1;
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std::vector<size_t> strides(ndim);
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if (ndim > 0) {
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strides[ndim-1] = sizeof(Return);
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for (int i = ndim - 1; i > 0; --i) {
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strides[i - 1] = strides[i] * shape[i];
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size *= shape[i];
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}
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size *= shape[0];
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}
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if (size == 1)
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return cast(f(*((Args *) buffers[Index].ptr)...));
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array result(buffer_info(nullptr, sizeof(Return),
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format_descriptor<Return>::value(),
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ndim, shape, strides));
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buffer_info buf = result.request();
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Return *output = (Return *) buf.ptr;
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if(trivial_broadcast) {
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/* Call the function */
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for (size_t i=0; i<size; ++i) {
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output[i] = f((buffers[Index].size == 1
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? *((Args *) buffers[Index].ptr)
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: ((Args *) buffers[Index].ptr)[i])...);
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}
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} else {
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apply_broadcast<N, Index...>(buffers, buf, index);
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}
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return result;
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}
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template <size_t N, size_t... Index>
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void apply_broadcast(const std::array<buffer_info, N> &buffers,
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buffer_info &output, index_sequence<Index...>) {
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using input_iterator = multi_array_iterator<N>;
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using output_iterator = array_iterator<Return>;
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input_iterator input_iter(buffers, output.shape);
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output_iterator output_end = array_end<Return>(output);
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for (output_iterator iter = array_begin<Return>(output);
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iter != output_end; ++iter, ++input_iter) {
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*iter = f((input_iter.template data<Index, Args>())...);
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}
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}
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};
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template <typename T> struct handle_type_name<array_t<T>> {
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static PYBIND11_DESCR name() { return _("array[") + type_caster<T>::name() + _("]"); }
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};
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NAMESPACE_END(detail)
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template <typename Func, typename Return, typename... Args>
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detail::vectorize_helper<Func, Return, Args...> vectorize(const Func &f, Return (*) (Args ...)) {
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return detail::vectorize_helper<Func, Return, Args...>(f);
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}
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template <typename Return, typename... Args>
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detail::vectorize_helper<Return (*) (Args ...), Return, Args...> vectorize(Return (*f) (Args ...)) {
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return vectorize<Return (*) (Args ...), Return, Args...>(f, f);
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}
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template <typename func> auto vectorize(func &&f) -> decltype(
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vectorize(std::forward<func>(f), (typename detail::remove_class<decltype(&std::remove_reference<func>::type::operator())>::type *) nullptr)) {
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return vectorize(std::forward<func>(f), (typename detail::remove_class<decltype(
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&std::remove_reference<func>::type::operator())>::type *) nullptr);
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}
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NAMESPACE_END(pybind11)
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#if defined(_MSC_VER)
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#pragma warning(pop)
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#endif
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