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simplify installation procedure (#188) 

* postproc

* mv postproc of textdet in mmcv

* linting

* change deps mmcv 1.3.4

* update deps

* linting

* Update configs/textdet/panet/panet_r18_fpem_ffm_600e_icdar2015.py

* Update docs/changelog.md

* Update mmocr/models/textdet/postprocess/__init__.py

* Update mmocr/version.py

* resize&recompress jpg

* Update changelog.md

Co-authored-by: Hongbin Sun <hongbin306@gmail.com>
pull/193/head
jeffreykuang 2021-05-15 10:34:37 +08:00 committed by GitHub
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2
.github/workflows/build.yml vendored
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@ -56,7 +56,7 @@ jobs:
- name: Install PyTorch
run: pip install torch==${{matrix.torch}}+cpu torchvision==${{matrix.torchvision}}+cpu -f https://download.pytorch.org/whl/torch_stable.html
- name: Install MMCV
run: pip install mmcv-full==1.3.1 -f https://download.openmmlab.com/mmcv/dist/cpu/torch${{matrix.torch}}/index.html
run: pip install mmcv-full==1.3.4 -f https://download.openmmlab.com/mmcv/dist/cpu/torch${{matrix.torch}}/index.html
- name: Install MMDet
run: pip install mmdet==2.11.0
- name: Install other dependencies

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docker/Dockerfile
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@ -13,7 +13,7 @@ RUN apt-get update && apt-get install -y git ninja-build libglib2.0-0 libsm6 lib
&& rm -rf /var/lib/apt/lists/*
RUN conda clean --all
RUN pip install mmcv-full==1.3.1+torch1.5.0+cu101 -f https://download.openmmlab.com/mmcv/dist/index.html
RUN pip install mmcv-full==1.3.4+torch1.5.0+cu101 -f https://download.openmmlab.com/mmcv/dist/index.html
RUN pip install mmdet==2.11.0

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docs/changelog.md
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@ -1,4 +1,13 @@
# Changelog
## v0.2.0 (16/5/2021)
**Highlights**
- MMOCR is compiling-free via moving textdet postprocessing and ops to mmcv 1.3.4 or later.
- Add a new OCR downstream task-NER.
- Add two new text detection methods: DRRG and FCENet.
- Add a new text recognition method: TPS-CRNN.
- Add an end-to-end demo.
## v0.1.0 (7/4/2021)

7
docs/install.md
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@ -9,7 +9,7 @@
- CUDA 10.1
- NCCL 2
- GCC 5.4.0 or higher
- [MMCV](https://mmcv.readthedocs.io/en/latest/#installation) 1.3.1
- [MMCV](https://mmcv.readthedocs.io/en/latest/#installation) 1.3.4
- [MMDetection](https://mmdetection.readthedocs.io/en/latest/#installation) 2.11.0
We have tested the following versions of OS and softwares:
@ -17,7 +17,7 @@ We have tested the following versions of OS and softwares:
- OS: Ubuntu 16.04
- CUDA: 10.1
- GCC(G++): 5.4.0
- MMCV 1.3.1
- MMCV 1.3.4
- MMDetection 2.11.0
- PyTorch 1.5
- torchvision 0.6.0
@ -53,6 +53,7 @@ Please replace ``{cu_version}`` and ``{torch_version}`` in the url to your desir
```shell
pip install mmcv-full -f https://download.openmmlab.com/mmcv/dist/cu110/torch1.7.0/index.html
```
Note that mmocr 0.2.0 or later require mmcv 1.3.4 or later.
If it compiles during installation, then please check that the cuda version and pytorch version **exactly"" matches the version in the mmcv-full installation command. For example, pytorch 1.7.0 and 1.7.1 are treated differently.
@ -97,7 +98,7 @@ conda activate open-mmlab
conda install pytorch==1.5.0 torchvision==0.6.0 cudatoolkit=10.1 -c pytorch
# install the latest mmcv-full
pip install mmcv-full==1.3.1
pip install mmcv-full==1.3.4
# install mmdetection
pip install mmdet==2.11.0

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mmocr/models/textdet/postprocess/include/clipper/clipper.cpp
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mmocr/models/textdet/postprocess/include/clipper/clipper.hpp
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/*******************************************************************************
* *
* Author : Angus Johnson *
* Version : 6.4.0 *
* Date : 2 July 2015 *
* Website : http://www.angusj.com *
* Copyright : Angus Johnson 2010-2015 *
* *
* License: *
* Use, modification & distribution is subject to Boost Software License Ver 1. *
* http://www.boost.org/LICENSE_1_0.txt *
* *
* Attributions: *
* The code in this library is an extension of Bala Vatti's clipping algorithm: *
* "A generic solution to polygon clipping" *
* Communications of the ACM, Vol 35, Issue 7 (July 1992) pp 56-63. *
* http://portal.acm.org/citation.cfm?id=129906 *
* *
* Computer graphics and geometric modeling: implementation and algorithms *
* By Max K. Agoston *
* Springer; 1 edition (January 4, 2005) *
* http://books.google.com/books?q=vatti+clipping+agoston *
* *
* See also: *
* "Polygon Offsetting by Computing Winding Numbers" *
* Paper no. DETC2005-85513 pp. 565-575 *
* ASME 2005 International Design Engineering Technical Conferences *
* and Computers and Information in Engineering Conference (IDETC/CIE2005) *
* September 24-28, 2005 , Long Beach, California, USA *
* http://www.me.berkeley.edu/~mcmains/pubs/DAC05OffsetPolygon.pdf *
* *
*******************************************************************************/
#ifndef clipper_hpp
#define clipper_hpp
#define CLIPPER_VERSION "6.2.6"
//use_int32: When enabled 32bit ints are used instead of 64bit ints. This
//improve performance but coordinate values are limited to the range +/- 46340
//#define use_int32
//use_xyz: adds a Z member to IntPoint. Adds a minor cost to perfomance.
//#define use_xyz
//use_lines: Enables line clipping. Adds a very minor cost to performance.
#define use_lines
//use_deprecated: Enables temporary support for the obsolete functions
//#define use_deprecated
#include <vector>
#include <list>
#include <set>
#include <stdexcept>
#include <cstring>
#include <cstdlib>
#include <ostream>
#include <functional>
#include <queue>
namespace ClipperLib {
enum ClipType { ctIntersection, ctUnion, ctDifference, ctXor };
enum PolyType { ptSubject, ptClip };
//By far the most widely used winding rules for polygon filling are
//EvenOdd & NonZero (GDI, GDI+, XLib, OpenGL, Cairo, AGG, Quartz, SVG, Gr32)
//Others rules include Positive, Negative and ABS_GTR_EQ_TWO (only in OpenGL)
//see http://glprogramming.com/red/chapter11.html
enum PolyFillType { pftEvenOdd, pftNonZero, pftPositive, pftNegative };
#ifdef use_int32
typedef int cInt;
static cInt const loRange = 0x7FFF;
static cInt const hiRange = 0x7FFF;
#else
typedef signed long long cInt;
static cInt const loRange = 0x3FFFFFFF;
static cInt const hiRange = 0x3FFFFFFFFFFFFFFFLL;
typedef signed long long long64; //used by Int128 class
typedef unsigned long long ulong64;
#endif
struct IntPoint {
cInt X;
cInt Y;
#ifdef use_xyz
cInt Z;
IntPoint(cInt x = 0, cInt y = 0, cInt z = 0): X(x), Y(y), Z(z) {};
#else
IntPoint(cInt x = 0, cInt y = 0): X(x), Y(y) {};
#endif
friend inline bool operator== (const IntPoint& a, const IntPoint& b)
{
return a.X == b.X && a.Y == b.Y;
}
friend inline bool operator!= (const IntPoint& a, const IntPoint& b)
{
return a.X != b.X || a.Y != b.Y;
}
};
//------------------------------------------------------------------------------
typedef std::vector< IntPoint > Path;
typedef std::vector< Path > Paths;
inline Path& operator <<(Path& poly, const IntPoint& p) {poly.push_back(p); return poly;}
inline Paths& operator <<(Paths& polys, const Path& p) {polys.push_back(p); return polys;}
std::ostream& operator <<(std::ostream &s, const IntPoint &p);
std::ostream& operator <<(std::ostream &s, const Path &p);
std::ostream& operator <<(std::ostream &s, const Paths &p);
struct DoublePoint
{
double X;
double Y;
DoublePoint(double x = 0, double y = 0) : X(x), Y(y) {}
DoublePoint(IntPoint ip) : X((double)ip.X), Y((double)ip.Y) {}
};
//------------------------------------------------------------------------------
#ifdef use_xyz
typedef void (*ZFillCallback)(IntPoint& e1bot, IntPoint& e1top, IntPoint& e2bot, IntPoint& e2top, IntPoint& pt);
#endif
enum InitOptions {ioReverseSolution = 1, ioStrictlySimple = 2, ioPreserveCollinear = 4};
enum JoinType {jtSquare, jtRound, jtMiter};
enum EndType {etClosedPolygon, etClosedLine, etOpenButt, etOpenSquare, etOpenRound};
class PolyNode;
typedef std::vector< PolyNode* > PolyNodes;
class PolyNode
{
public:
PolyNode();
virtual ~PolyNode(){};
Path Contour;
PolyNodes Childs;
PolyNode* Parent;
PolyNode* GetNext() const;
bool IsHole() const;
bool IsOpen() const;
int ChildCount() const;
private:
unsigned Index; //node index in Parent.Childs
bool m_IsOpen;
JoinType m_jointype;
EndType m_endtype;
PolyNode* GetNextSiblingUp() const;
void AddChild(PolyNode& child);
friend class Clipper; //to access Index
friend class ClipperOffset;
};
class PolyTree: public PolyNode
{
public:
~PolyTree(){Clear();};
PolyNode* GetFirst() const;
void Clear();
int Total() const;
private:
PolyNodes AllNodes;
friend class Clipper; //to access AllNodes
};
bool Orientation(const Path &poly);
double Area(const Path &poly);
int PointInPolygon(const IntPoint &pt, const Path &path);
void SimplifyPolygon(const Path &in_poly, Paths &out_polys, PolyFillType fillType = pftEvenOdd);
void SimplifyPolygons(const Paths &in_polys, Paths &out_polys, PolyFillType fillType = pftEvenOdd);
void SimplifyPolygons(Paths &polys, PolyFillType fillType = pftEvenOdd);
void CleanPolygon(const Path& in_poly, Path& out_poly, double distance = 1.415);
void CleanPolygon(Path& poly, double distance = 1.415);
void CleanPolygons(const Paths& in_polys, Paths& out_polys, double distance = 1.415);
void CleanPolygons(Paths& polys, double distance = 1.415);
void MinkowskiSum(const Path& pattern, const Path& path, Paths& solution, bool pathIsClosed);
void MinkowskiSum(const Path& pattern, const Paths& paths, Paths& solution, bool pathIsClosed);
void MinkowskiDiff(const Path& poly1, const Path& poly2, Paths& solution);
void PolyTreeToPaths(const PolyTree& polytree, Paths& paths);
void ClosedPathsFromPolyTree(const PolyTree& polytree, Paths& paths);
void OpenPathsFromPolyTree(PolyTree& polytree, Paths& paths);
void ReversePath(Path& p);
void ReversePaths(Paths& p);
struct IntRect { cInt left; cInt top; cInt right; cInt bottom; };
//enums that are used internally ...
enum EdgeSide { esLeft = 1, esRight = 2};
//forward declarations (for stuff used internally) ...
struct TEdge;
struct IntersectNode;
struct LocalMinimum;
struct OutPt;
struct OutRec;
struct Join;
typedef std::vector < OutRec* > PolyOutList;
typedef std::vector < TEdge* > EdgeList;
typedef std::vector < Join* > JoinList;
typedef std::vector < IntersectNode* > IntersectList;
//------------------------------------------------------------------------------
//ClipperBase is the ancestor to the Clipper class. It should not be
//instantiated directly. This class simply abstracts the conversion of sets of
//polygon coordinates into edge objects that are stored in a LocalMinima list.
class ClipperBase
{
public:
ClipperBase();
virtual ~ClipperBase();
virtual bool AddPath(const Path &pg, PolyType PolyTyp, bool Closed);
bool AddPaths(const Paths &ppg, PolyType PolyTyp, bool Closed);
virtual void Clear();
IntRect GetBounds();
bool PreserveCollinear() {return m_PreserveCollinear;};
void PreserveCollinear(bool value) {m_PreserveCollinear = value;};
protected:
void DisposeLocalMinimaList();
TEdge* AddBoundsToLML(TEdge *e, bool IsClosed);
virtual void Reset();
TEdge* ProcessBound(TEdge* E, bool IsClockwise);
void InsertScanbeam(const cInt Y);
bool PopScanbeam(cInt &Y);
bool LocalMinimaPending();
bool PopLocalMinima(cInt Y, const LocalMinimum *&locMin);
OutRec* CreateOutRec();
void DisposeAllOutRecs();
void DisposeOutRec(PolyOutList::size_type index);
void SwapPositionsInAEL(TEdge *edge1, TEdge *edge2);
void DeleteFromAEL(TEdge *e);
void UpdateEdgeIntoAEL(TEdge *&e);
typedef std::vector<LocalMinimum> MinimaList;
MinimaList::iterator m_CurrentLM;
MinimaList m_MinimaList;
bool m_UseFullRange;
EdgeList m_edges;
bool m_PreserveCollinear;
bool m_HasOpenPaths;
PolyOutList m_PolyOuts;
TEdge *m_ActiveEdges;
typedef std::priority_queue<cInt> ScanbeamList;
ScanbeamList m_Scanbeam;
};
//------------------------------------------------------------------------------
class Clipper : public virtual ClipperBase
{
public:
Clipper(int initOptions = 0);
bool Execute(ClipType clipType,
Paths &solution,
PolyFillType fillType = pftEvenOdd);
bool Execute(ClipType clipType,
Paths &solution,
PolyFillType subjFillType,
PolyFillType clipFillType);
bool Execute(ClipType clipType,
PolyTree &polytree,
PolyFillType fillType = pftEvenOdd);
bool Execute(ClipType clipType,
PolyTree &polytree,
PolyFillType subjFillType,
PolyFillType clipFillType);
bool ReverseSolution() { return m_ReverseOutput; };
void ReverseSolution(bool value) {m_ReverseOutput = value;};
bool StrictlySimple() {return m_StrictSimple;};
void StrictlySimple(bool value) {m_StrictSimple = value;};
//set the callback function for z value filling on intersections (otherwise Z is 0)
#ifdef use_xyz
void ZFillFunction(ZFillCallback zFillFunc);
#endif
protected:
virtual bool ExecuteInternal();
private:
JoinList m_Joins;
JoinList m_GhostJoins;
IntersectList m_IntersectList;
ClipType m_ClipType;
typedef std::list<cInt> MaximaList;
MaximaList m_Maxima;
TEdge *m_SortedEdges;
bool m_ExecuteLocked;
PolyFillType m_ClipFillType;
PolyFillType m_SubjFillType;
bool m_ReverseOutput;
bool m_UsingPolyTree;
bool m_StrictSimple;
#ifdef use_xyz
ZFillCallback m_ZFill; //custom callback
#endif
void SetWindingCount(TEdge& edge);
bool IsEvenOddFillType(const TEdge& edge) const;
bool IsEvenOddAltFillType(const TEdge& edge) const;
void InsertLocalMinimaIntoAEL(const cInt botY);
void InsertEdgeIntoAEL(TEdge *edge, TEdge* startEdge);
void AddEdgeToSEL(TEdge *edge);
bool PopEdgeFromSEL(TEdge *&edge);
void CopyAELToSEL();
void DeleteFromSEL(TEdge *e);
void SwapPositionsInSEL(TEdge *edge1, TEdge *edge2);
bool IsContributing(const TEdge& edge) const;
bool IsTopHorz(const cInt XPos);
void DoMaxima(TEdge *e);
void ProcessHorizontals();
void ProcessHorizontal(TEdge *horzEdge);
void AddLocalMaxPoly(TEdge *e1, TEdge *e2, const IntPoint &pt);
OutPt* AddLocalMinPoly(TEdge *e1, TEdge *e2, const IntPoint &pt);
OutRec* GetOutRec(int idx);
void AppendPolygon(TEdge *e1, TEdge *e2);
void IntersectEdges(TEdge *e1, TEdge *e2, IntPoint &pt);
OutPt* AddOutPt(TEdge *e, const IntPoint &pt);
OutPt* GetLastOutPt(TEdge *e);
bool ProcessIntersections(const cInt topY);
void BuildIntersectList(const cInt topY);
void ProcessIntersectList();
void ProcessEdgesAtTopOfScanbeam(const cInt topY);
void BuildResult(Paths& polys);
void BuildResult2(PolyTree& polytree);
void SetHoleState(TEdge *e, OutRec *outrec);
void DisposeIntersectNodes();
bool FixupIntersectionOrder();
void FixupOutPolygon(OutRec &outrec);
void FixupOutPolyline(OutRec &outrec);
bool IsHole(TEdge *e);
bool FindOwnerFromSplitRecs(OutRec &outRec, OutRec *&currOrfl);
void FixHoleLinkage(OutRec &outrec);
void AddJoin(OutPt *op1, OutPt *op2, const IntPoint offPt);
void ClearJoins();
void ClearGhostJoins();
void AddGhostJoin(OutPt *op, const IntPoint offPt);
bool JoinPoints(Join *j, OutRec* outRec1, OutRec* outRec2);
void JoinCommonEdges();
void DoSimplePolygons();
void FixupFirstLefts1(OutRec* OldOutRec, OutRec* NewOutRec);
void FixupFirstLefts2(OutRec* InnerOutRec, OutRec* OuterOutRec);
void FixupFirstLefts3(OutRec* OldOutRec, OutRec* NewOutRec);
#ifdef use_xyz
void SetZ(IntPoint& pt, TEdge& e1, TEdge& e2);
#endif
};
//------------------------------------------------------------------------------
class ClipperOffset
{
public:
ClipperOffset(double miterLimit = 2.0, double roundPrecision = 0.25);
~ClipperOffset();
void AddPath(const Path& path, JoinType joinType, EndType endType);
void AddPaths(const Paths& paths, JoinType joinType, EndType endType);
void Execute(Paths& solution, double delta);
void Execute(PolyTree& solution, double delta);
void Clear();
double MiterLimit;
double ArcTolerance;
private:
Paths m_destPolys;
Path m_srcPoly;
Path m_destPoly;
std::vector<DoublePoint> m_normals;
double m_delta, m_sinA, m_sin, m_cos;
double m_miterLim, m_StepsPerRad;
IntPoint m_lowest;
PolyNode m_polyNodes;
void FixOrientations();
void DoOffset(double delta);
void OffsetPoint(int j, int& k, JoinType jointype);
void DoSquare(int j, int k);
void DoMiter(int j, int k, double r);
void DoRound(int j, int k);
};
//------------------------------------------------------------------------------
class clipperException : public std::exception
{
public:
clipperException(const char* description): m_descr(description) {}
virtual ~clipperException() throw() {}
virtual const char* what() const throw() {return m_descr.c_str();}
private:
std::string m_descr;
};
//------------------------------------------------------------------------------
} //ClipperLib namespace
#endif //clipper_hpp

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mmocr/models/textdet/postprocess/include/pybind11/attr.h
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/*
pybind11/attr.h: Infrastructure for processing custom
type and function attributes
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 "cast.h"
NAMESPACE_BEGIN(PYBIND11_NAMESPACE)
/// \addtogroup annotations
/// @{
/// Annotation for methods
struct is_method { handle class_; is_method(const handle &c) : class_(c) { } };
/// Annotation for operators
struct is_operator { };
/// Annotation for parent scope
struct scope { handle value; scope(const handle &s) : value(s) { } };
/// Annotation for documentation
struct doc { const char *value; doc(const char *value) : value(value) { } };
/// Annotation for function names
struct name { const char *value; name(const char *value) : value(value) { } };
/// Annotation indicating that a function is an overload associated with a given "sibling"
struct sibling { handle value; sibling(const handle &value) : value(value.ptr()) { } };
/// Annotation indicating that a class derives from another given type
template <typename T> struct base {
PYBIND11_DEPRECATED("base<T>() was deprecated in favor of specifying 'T' as a template argument to class_")
base() { }
};
/// Keep patient alive while nurse lives
template <size_t Nurse, size_t Patient> struct keep_alive { };
/// Annotation indicating that a class is involved in a multiple inheritance relationship
struct multiple_inheritance { };
/// Annotation which enables dynamic attributes, i.e. adds `__dict__` to a class
struct dynamic_attr { };
/// Annotation which enables the buffer protocol for a type
struct buffer_protocol { };
/// Annotation which requests that a special metaclass is created for a type
struct metaclass {
handle value;
PYBIND11_DEPRECATED("py::metaclass() is no longer required. It's turned on by default now.")
metaclass() {}
/// Override pybind11's default metaclass
explicit metaclass(handle value) : value(value) { }
};
/// Annotation that marks a class as local to the module:
struct module_local { const bool value; constexpr module_local(bool v = true) : value(v) { } };
/// Annotation to mark enums as an arithmetic type
struct arithmetic { };
/** \rst
A call policy which places one or more guard variables (``Ts...``) around the function call.
For example, this definition:
.. code-block:: cpp
m.def("foo", foo, py::call_guard<T>());
is equivalent to the following pseudocode:
.. code-block:: cpp
m.def("foo", [](args...) {
T scope_guard;
return foo(args...); // forwarded arguments
});
\endrst */
template <typename... Ts> struct call_guard;
template <> struct call_guard<> { using type = detail::void_type; };
template <typename T>
struct call_guard<T> {
static_assert(std::is_default_constructible<T>::value,
"The guard type must be default constructible");
using type = T;
};
template <typename T, typename... Ts>
struct call_guard<T, Ts...> {
struct type {
T guard{}; // Compose multiple guard types with left-to-right default-constructor order
typename call_guard<Ts...>::type next{};
};
};
/// @} annotations
NAMESPACE_BEGIN(detail)
/* Forward declarations */
enum op_id : int;
enum op_type : int;
struct undefined_t;
template <op_id id, op_type ot, typename L = undefined_t, typename R = undefined_t> struct op_;
inline void keep_alive_impl(size_t Nurse, size_t Patient, function_call &call, handle ret);
/// Internal data structure which holds metadata about a keyword argument
struct argument_record {
const char *name; ///< Argument name
const char *descr; ///< Human-readable version of the argument value
handle value; ///< Associated Python object
bool convert : 1; ///< True if the argument is allowed to convert when loading
bool none : 1; ///< True if None is allowed when loading
argument_record(const char *name, const char *descr, handle value, bool convert, bool none)
: name(name), descr(descr), value(value), convert(convert), none(none) { }
};
/// Internal data structure which holds metadata about a bound function (signature, overloads, etc.)
struct function_record {
function_record()
: is_constructor(false), is_new_style_constructor(false), is_stateless(false),
is_operator(false), has_args(false), has_kwargs(false), is_method(false) { }
/// Function name
char *name = nullptr; /* why no C++ strings? They generate heavier code.. */
// User-specified documentation string
char *doc = nullptr;
/// Human-readable version of the function signature
char *signature = nullptr;
/// List of registered keyword arguments
std::vector<argument_record> args;
/// Pointer to lambda function which converts arguments and performs the actual call
handle (*impl) (function_call &) = nullptr;
/// Storage for the wrapped function pointer and captured data, if any
void *data[3] = { };
/// Pointer to custom destructor for 'data' (if needed)
void (*free_data) (function_record *ptr) = nullptr;
/// Return value policy associated with this function
return_value_policy policy = return_value_policy::automatic;
/// True if name == '__init__'
bool is_constructor : 1;
/// True if this is a new-style `__init__` defined in `detail/init.h`
bool is_new_style_constructor : 1;
/// True if this is a stateless function pointer
bool is_stateless : 1;
/// True if this is an operator (__add__), etc.
bool is_operator : 1;
/// True if the function has a '*args' argument
bool has_args : 1;
/// True if the function has a '**kwargs' argument
bool has_kwargs : 1;
/// True if this is a method
bool is_method : 1;
/// Number of arguments (including py::args and/or py::kwargs, if present)
std::uint16_t nargs;
/// Python method object
PyMethodDef *def = nullptr;
/// Python handle to the parent scope (a class or a module)
handle scope;
/// Python handle to the sibling function representing an overload chain
handle sibling;
/// Pointer to next overload
function_record *next = nullptr;
};
/// Special data structure which (temporarily) holds metadata about a bound class
struct type_record {
PYBIND11_NOINLINE type_record()
: multiple_inheritance(false), dynamic_attr(false), buffer_protocol(false), module_local(false) { }
/// Handle to the parent scope
handle scope;
/// Name of the class
const char *name = nullptr;
// Pointer to RTTI type_info data structure
const std::type_info *type = nullptr;
/// How large is the underlying C++ type?
size_t type_size = 0;
/// What is the alignment of the underlying C++ type?
size_t type_align = 0;
/// How large is the type's holder?
size_t holder_size = 0;
/// The global operator new can be overridden with a class-specific variant
void *(*operator_new)(size_t) = nullptr;
/// Function pointer to class_<..>::init_instance
void (*init_instance)(instance *, const void *) = nullptr;
/// Function pointer to class_<..>::dealloc
void (*dealloc)(detail::value_and_holder &) = nullptr;
/// List of base classes of the newly created type
list bases;
/// Optional docstring
const char *doc = nullptr;
/// Custom metaclass (optional)
handle metaclass;
/// Multiple inheritance marker
bool multiple_inheritance : 1;
/// Does the class manage a __dict__?
bool dynamic_attr : 1;
/// Does the class implement the buffer protocol?
bool buffer_protocol : 1;
/// Is the default (unique_ptr) holder type used?
bool default_holder : 1;
/// Is the class definition local to the module shared object?
bool module_local : 1;
PYBIND11_NOINLINE void add_base(const std::type_info &base, void *(*caster)(void *)) {
auto base_info = detail::get_type_info(base, false);
if (!base_info) {
std::string tname(base.name());
detail::clean_type_id(tname);
pybind11_fail("generic_type: type \"" + std::string(name) +
"\" referenced unknown base type \"" + tname + "\"");
}
if (default_holder != base_info->default_holder) {
std::string tname(base.name());
detail::clean_type_id(tname);
pybind11_fail("generic_type: type \"" + std::string(name) + "\" " +
(default_holder ? "does not have" : "has") +
" a non-default holder type while its base \"" + tname + "\" " +
(base_info->default_holder ? "does not" : "does"));
}
bases.append((PyObject *) base_info->type);
if (base_info->type->tp_dictoffset != 0)
dynamic_attr = true;
if (caster)
base_info->implicit_casts.emplace_back(type, caster);
}
};
inline function_call::function_call(const function_record &f, handle p) :
func(f), parent(p) {
args.reserve(f.nargs);
args_convert.reserve(f.nargs);
}
/// Tag for a new-style `__init__` defined in `detail/init.h`
struct is_new_style_constructor { };
/**
* Partial template specializations to process custom attributes provided to
* cpp_function_ and class_. These are either used to initialize the respective
* fields in the type_record and function_record data structures or executed at
* runtime to deal with custom call policies (e.g. keep_alive).
*/
template <typename T, typename SFINAE = void> struct process_attribute;
template <typename T> struct process_attribute_default {
/// Default implementation: do nothing
static void init(const T &, function_record *) { }
static void init(const T &, type_record *) { }
static void precall(function_call &) { }
static void postcall(function_call &, handle) { }
};
/// Process an attribute specifying the function's name
template <> struct process_attribute<name> : process_attribute_default<name> {
static void init(const name &n, function_record *r) { r->name = const_cast<char *>(n.value); }
};
/// Process an attribute specifying the function's docstring
template <> struct process_attribute<doc> : process_attribute_default<doc> {
static void init(const doc &n, function_record *r) { r->doc = const_cast<char *>(n.value); }
};
/// Process an attribute specifying the function's docstring (provided as a C-style string)
template <> struct process_attribute<const char *> : process_attribute_default<const char *> {
static void init(const char *d, function_record *r) { r->doc = const_cast<char *>(d); }
static void init(const char *d, type_record *r) { r->doc = const_cast<char *>(d); }
};
template <> struct process_attribute<char *> : process_attribute<const char *> { };
/// Process an attribute indicating the function's return value policy
template <> struct process_attribute<return_value_policy> : process_attribute_default<return_value_policy> {
static void init(const return_value_policy &p, function_record *r) { r->policy = p; }
};
/// Process an attribute which indicates that this is an overloaded function associated with a given sibling
template <> struct process_attribute<sibling> : process_attribute_default<sibling> {
static void init(const sibling &s, function_record *r) { r->sibling = s.value; }
};
/// Process an attribute which indicates that this function is a method
template <> struct process_attribute<is_method> : process_attribute_default<is_method> {
static void init(const is_method &s, function_record *r) { r->is_method = true; r->scope = s.class_; }
};
/// Process an attribute which indicates the parent scope of a method
template <> struct process_attribute<scope> : process_attribute_default<scope> {
static void init(const scope &s, function_record *r) { r->scope = s.value; }
};
/// Process an attribute which indicates that this function is an operator
template <> struct process_attribute<is_operator> : process_attribute_default<is_operator> {
static void init(const is_operator &, function_record *r) { r->is_operator = true; }
};
template <> struct process_attribute<is_new_style_constructor> : process_attribute_default<is_new_style_constructor> {
static void init(const is_new_style_constructor &, function_record *r) { r->is_new_style_constructor = true; }
};
/// Process a keyword argument attribute (*without* a default value)
template <> struct process_attribute<arg> : process_attribute_default<arg> {
static void init(const arg &a, function_record *r) {
if (r->is_method && r->args.empty())
r->args.emplace_back("self", nullptr, handle(), true /*convert*/, false /*none not allowed*/);
r->args.emplace_back(a.name, nullptr, handle(), !a.flag_noconvert, a.flag_none);
}
};
/// Process a keyword argument attribute (*with* a default value)
template <> struct process_attribute<arg_v> : process_attribute_default<arg_v> {
static void init(const arg_v &a, function_record *r) {
if (r->is_method && r->args.empty())
r->args.emplace_back("self", nullptr /*descr*/, handle() /*parent*/, true /*convert*/, false /*none not allowed*/);
if (!a.value) {
#if !defined(NDEBUG)
std::string descr("'");
if (a.name) descr += std::string(a.name) + ": ";
descr += a.type + "'";
if (r->is_method) {
if (r->name)
descr += " in method '" + (std::string) str(r->scope) + "." + (std::string) r->name + "'";
else
descr += " in method of '" + (std::string) str(r->scope) + "'";
} else if (r->name) {
descr += " in function '" + (std::string) r->name + "'";
}
pybind11_fail("arg(): could not convert default argument "
+ descr + " into a Python object (type not registered yet?)");
#else
pybind11_fail("arg(): could not convert default argument "
"into a Python object (type not registered yet?). "
"Compile in debug mode for more information.");
#endif
}
r->args.emplace_back(a.name, a.descr, a.value.inc_ref(), !a.flag_noconvert, a.flag_none);
}
};
/// Process a parent class attribute. Single inheritance only (class_ itself already guarantees that)
template <typename T>
struct process_attribute<T, enable_if_t<is_pyobject<T>::value>> : process_attribute_default<handle> {
static void init(const handle &h, type_record *r) { r->bases.append(h); }
};
/// Process a parent class attribute (deprecated, does not support multiple inheritance)
template <typename T>
struct process_attribute<base<T>> : process_attribute_default<base<T>> {
static void init(const base<T> &, type_record *r) { r->add_base(typeid(T), nullptr); }
};
/// Process a multiple inheritance attribute
template <>
struct process_attribute<multiple_inheritance> : process_attribute_default<multiple_inheritance> {
static void init(const multiple_inheritance &, type_record *r) { r->multiple_inheritance = true; }
};
template <>
struct process_attribute<dynamic_attr> : process_attribute_default<dynamic_attr> {
static void init(const dynamic_attr &, type_record *r) { r->dynamic_attr = true; }
};
template <>
struct process_attribute<buffer_protocol> : process_attribute_default<buffer_protocol> {
static void init(const buffer_protocol &, type_record *r) { r->buffer_protocol = true; }
};
template <>
struct process_attribute<metaclass> : process_attribute_default<metaclass> {
static void init(const metaclass &m, type_record *r) { r->metaclass = m.value; }
};
template <>
struct process_attribute<module_local> : process_attribute_default<module_local> {
static void init(const module_local &l, type_record *r) { r->module_local = l.value; }
};
/// Process an 'arithmetic' attribute for enums (does nothing here)
template <>
struct process_attribute<arithmetic> : process_attribute_default<arithmetic> {};
template <typename... Ts>
struct process_attribute<call_guard<Ts...>> : process_attribute_default<call_guard<Ts...>> { };
/**
* Process a keep_alive call policy -- invokes keep_alive_impl during the
* pre-call handler if both Nurse, Patient != 0 and use the post-call handler
* otherwise
*/
template <size_t Nurse, size_t Patient> struct process_attribute<keep_alive<Nurse, Patient>> : public process_attribute_default<keep_alive<Nurse, Patient>> {
template <size_t N = Nurse, size_t P = Patient, enable_if_t<N != 0 && P != 0, int> = 0>
static void precall(function_call &call) { keep_alive_impl(Nurse, Patient, call, handle()); }
template <size_t N = Nurse, size_t P = Patient, enable_if_t<N != 0 && P != 0, int> = 0>
static void postcall(function_call &, handle) { }
template <size_t N = Nurse, size_t P = Patient, enable_if_t<N == 0 || P == 0, int> = 0>
static void precall(function_call &) { }
template <size_t N = Nurse, size_t P = Patient, enable_if_t<N == 0 || P == 0, int> = 0>
static void postcall(function_call &call, handle ret) { keep_alive_impl(Nurse, Patient, call, ret); }
};
/// Recursively iterate over variadic template arguments
template <typename... Args> struct process_attributes {
static void init(const Args&... args, function_record *r) {
int unused[] = { 0, (process_attribute<typename std::decay<Args>::type>::init(args, r), 0) ... };
ignore_unused(unused);
}
static void init(const Args&... args, type_record *r) {
int unused[] = { 0, (process_attribute<typename std::decay<Args>::type>::init(args, r), 0) ... };
ignore_unused(unused);
}
static void precall(function_call &call) {
int unused[] = { 0, (process_attribute<typename std::decay<Args>::type>::precall(call), 0) ... };
ignore_unused(unused);
}
static void postcall(function_call &call, handle fn_ret) {
int unused[] = { 0, (process_attribute<typename std::decay<Args>::type>::postcall(call, fn_ret), 0) ... };
ignore_unused(unused);
}
};
template <typename T>
using is_call_guard = is_instantiation<call_guard, T>;
/// Extract the ``type`` from the first `call_guard` in `Extras...` (or `void_type` if none found)
template <typename... Extra>
using extract_guard_t = typename exactly_one_t<is_call_guard, call_guard<>, Extra...>::type;
/// Check the number of named arguments at compile time
template <typename... Extra,
size_t named = constexpr_sum(std::is_base_of<arg, Extra>::value...),
size_t self = constexpr_sum(std::is_same<is_method, Extra>::value...)>
constexpr bool expected_num_args(size_t nargs, bool has_args, bool has_kwargs) {
return named == 0 || (self + named + has_args + has_kwargs) == nargs;
}
NAMESPACE_END(detail)
NAMESPACE_END(PYBIND11_NAMESPACE)

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/*
pybind11/buffer_info.h: Python buffer object interface
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 "detail/common.h"
NAMESPACE_BEGIN(PYBIND11_NAMESPACE)
/// Information record describing a Python buffer object
struct buffer_info {
void *ptr = nullptr; // Pointer to the underlying storage
ssize_t itemsize = 0; // Size of individual items in bytes
ssize_t size = 0; // Total number of entries
std::string format; // For homogeneous buffers, this should be set to format_descriptor<T>::format()
ssize_t ndim = 0; // Number of dimensions
std::vector<ssize_t> shape; // Shape of the tensor (1 entry per dimension)
std::vector<ssize_t> strides; // Number of entries between adjacent entries (for each per dimension)
buffer_info() { }
buffer_info(void *ptr, ssize_t itemsize, const std::string &format, ssize_t ndim,
detail::any_container<ssize_t> shape_in, detail::any_container<ssize_t> strides_in)
: ptr(ptr), itemsize(itemsize), size(1), format(format), ndim(ndim),
shape(std::move(shape_in)), strides(std::move(strides_in)) {
if (ndim != (ssize_t) shape.size() || ndim != (ssize_t) strides.size())
pybind11_fail("buffer_info: ndim doesn't match shape and/or strides length");
for (size_t i = 0; i < (size_t) ndim; ++i)
size *= shape[i];
}
template <typename T>
buffer_info(T *ptr, detail::any_container<ssize_t> shape_in, detail::any_container<ssize_t> strides_in)
: buffer_info(private_ctr_tag(), ptr, sizeof(T), format_descriptor<T>::format(), static_cast<ssize_t>(shape_in->size()), std::move(shape_in), std::move(strides_in)) { }
buffer_info(void *ptr, ssize_t itemsize, const std::string &format, ssize_t size)
: buffer_info(ptr, itemsize, format, 1, {size}, {itemsize}) { }
template <typename T>
buffer_info(T *ptr, ssize_t size)
: buffer_info(ptr, sizeof(T), format_descriptor<T>::format(), size) { }
explicit buffer_info(Py_buffer *view, bool ownview = true)
: buffer_info(view->buf, view->itemsize, view->format, view->ndim,
{view->shape, view->shape + view->ndim}, {view->strides, view->strides + view->ndim}) {
this->view = view;
this->ownview = ownview;
}
buffer_info(const buffer_info &) = delete;
buffer_info& operator=(const buffer_info &) = delete;
buffer_info(buffer_info &&other) {
(*this) = std::move(other);
}
buffer_info& operator=(buffer_info &&rhs) {
ptr = rhs.ptr;
itemsize = rhs.itemsize;
size = rhs.size;
format = std::move(rhs.format);
ndim = rhs.ndim;
shape = std::move(rhs.shape);
strides = std::move(rhs.strides);
std::swap(view, rhs.view);
std::swap(ownview, rhs.ownview);
return *this;
}
~buffer_info() {
if (view && ownview) { PyBuffer_Release(view); delete view; }
}
private:
struct private_ctr_tag { };
buffer_info(private_ctr_tag, void *ptr, ssize_t itemsize, const std::string &format, ssize_t ndim,
detail::any_container<ssize_t> &&shape_in, detail::any_container<ssize_t> &&strides_in)
: buffer_info(ptr, itemsize, format, ndim, std::move(shape_in), std::move(strides_in)) { }
Py_buffer *view = nullptr;
bool ownview = false;
};
NAMESPACE_BEGIN(detail)
template <typename T, typename SFINAE = void> struct compare_buffer_info {
static bool compare(const buffer_info& b) {
return b.format == format_descriptor<T>::format() && b.itemsize == (ssize_t) sizeof(T);
}
};
template <typename T> struct compare_buffer_info<T, detail::enable_if_t<std::is_integral<T>::value>> {
static bool compare(const buffer_info& b) {
return (size_t) b.itemsize == sizeof(T) && (b.format == format_descriptor<T>::value ||
((sizeof(T) == sizeof(long)) && b.format == (std::is_unsigned<T>::value ? "L" : "l")) ||
((sizeof(T) == sizeof(size_t)) && b.format == (std::is_unsigned<T>::value ? "N" : "n")));
}
};
NAMESPACE_END(detail)
NAMESPACE_END(PYBIND11_NAMESPACE)

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/*
pybind11/chrono.h: Transparent conversion between std::chrono and python's datetime
Copyright (c) 2016 Trent Houliston <trent@houliston.me> and
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 <cmath>
#include <ctime>
#include <chrono>
#include <datetime.h>
// Backport the PyDateTime_DELTA functions from Python3.3 if required
#ifndef PyDateTime_DELTA_GET_DAYS
#define PyDateTime_DELTA_GET_DAYS(o) (((PyDateTime_Delta*)o)->days)
#endif
#ifndef PyDateTime_DELTA_GET_SECONDS
#define PyDateTime_DELTA_GET_SECONDS(o) (((PyDateTime_Delta*)o)->seconds)
#endif
#ifndef PyDateTime_DELTA_GET_MICROSECONDS
#define PyDateTime_DELTA_GET_MICROSECONDS(o) (((PyDateTime_Delta*)o)->microseconds)
#endif
NAMESPACE_BEGIN(PYBIND11_NAMESPACE)
NAMESPACE_BEGIN(detail)
template <typename type> class duration_caster {
public:
typedef typename type::rep rep;
typedef typename type::period period;
typedef std::chrono::duration<uint_fast32_t, std::ratio<86400>> days;
bool load(handle src, bool) {
using namespace std::chrono;
// Lazy initialise the PyDateTime import
if (!PyDateTimeAPI) { PyDateTime_IMPORT; }
if (!src) return false;
// If invoked with datetime.delta object
if (PyDelta_Check(src.ptr())) {
value = type(duration_cast<duration<rep, period>>(
days(PyDateTime_DELTA_GET_DAYS(src.ptr()))
+ seconds(PyDateTime_DELTA_GET_SECONDS(src.ptr()))
+ microseconds(PyDateTime_DELTA_GET_MICROSECONDS(src.ptr()))));
return true;
}
// If invoked with a float we assume it is seconds and convert
else if (PyFloat_Check(src.ptr())) {
value = type(duration_cast<duration<rep, period>>(duration<double>(PyFloat_AsDouble(src.ptr()))));
return true;
}
else return false;
}
// If this is a duration just return it back
static const std::chrono::duration<rep, period>& get_duration(const std::chrono::duration<rep, period> &src) {
return src;
}
// If this is a time_point get the time_since_epoch
template <typename Clock> static std::chrono::duration<rep, period> get_duration(const std::chrono::time_point<Clock, std::chrono::duration<rep, period>> &src) {
return src.time_since_epoch();
}
static handle cast(const type &src, return_value_policy /* policy */, handle /* parent */) {
using namespace std::chrono;
// Use overloaded function to get our duration from our source
// Works out if it is a duration or time_point and get the duration
auto d = get_duration(src);
// Lazy initialise the PyDateTime import
if (!PyDateTimeAPI) { PyDateTime_IMPORT; }
// Declare these special duration types so the conversions happen with the correct primitive types (int)
using dd_t = duration<int, std::ratio<86400>>;
using ss_t = duration<int, std::ratio<1>>;
using us_t = duration<int, std::micro>;
auto dd = duration_cast<dd_t>(d);
auto subd = d - dd;
auto ss = duration_cast<ss_t>(subd);
auto us = duration_cast<us_t>(subd - ss);
return PyDelta_FromDSU(dd.count(), ss.count(), us.count());
}
PYBIND11_TYPE_CASTER(type, _("datetime.timedelta"));
};
// This is for casting times on the system clock into datetime.datetime instances
template <typename Duration> class type_caster<std::chrono::time_point<std::chrono::system_clock, Duration>> {
public:
typedef std::chrono::time_point<std::chrono::system_clock, Duration> type;
bool load(handle src, bool) {
using namespace std::chrono;
// Lazy initialise the PyDateTime import
if (!PyDateTimeAPI) { PyDateTime_IMPORT; }
if (!src) return false;
if (PyDateTime_Check(src.ptr())) {
std::tm cal;
cal.tm_sec = PyDateTime_DATE_GET_SECOND(src.ptr());
cal.tm_min = PyDateTime_DATE_GET_MINUTE(src.ptr());
cal.tm_hour = PyDateTime_DATE_GET_HOUR(src.ptr());
cal.tm_mday = PyDateTime_GET_DAY(src.ptr());
cal.tm_mon = PyDateTime_GET_MONTH(src.ptr()) - 1;
cal.tm_year = PyDateTime_GET_YEAR(src.ptr()) - 1900;
cal.tm_isdst = -1;
value = system_clock::from_time_t(std::mktime(&cal)) + microseconds(PyDateTime_DATE_GET_MICROSECOND(src.ptr()));
return true;
}
else return false;
}
static handle cast(const std::chrono::time_point<std::chrono::system_clock, Duration> &src, return_value_policy /* policy */, handle /* parent */) {
using namespace std::chrono;
// Lazy initialise the PyDateTime import
if (!PyDateTimeAPI) { PyDateTime_IMPORT; }
std::time_t tt = system_clock::to_time_t(src);
// this function uses static memory so it's best to copy it out asap just in case
// otherwise other code that is using localtime may break this (not just python code)
std::tm localtime = *std::localtime(&tt);
// Declare these special duration types so the conversions happen with the correct primitive types (int)
using us_t = duration<int, std::micro>;
return PyDateTime_FromDateAndTime(localtime.tm_year + 1900,
localtime.tm_mon + 1,
localtime.tm_mday,
localtime.tm_hour,
localtime.tm_min,
localtime.tm_sec,
(duration_cast<us_t>(src.time_since_epoch() % seconds(1))).count());
}
PYBIND11_TYPE_CASTER(type, _("datetime.datetime"));
};
// Other clocks that are not the system clock are not measured as datetime.datetime objects
// since they are not measured on calendar time. So instead we just make them timedeltas
// Or if they have passed us a time as a float we convert that
template <typename Clock, typename Duration> class type_caster<std::chrono::time_point<Clock, Duration>>
: public duration_caster<std::chrono::time_point<Clock, Duration>> {
};
template <typename Rep, typename Period> class type_caster<std::chrono::duration<Rep, Period>>
: public duration_caster<std::chrono::duration<Rep, Period>> {
};
NAMESPACE_END(detail)
NAMESPACE_END(PYBIND11_NAMESPACE)

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/*
pybind11/class_support.h: Python C API implementation details for py::class_
Copyright (c) 2017 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 "attr.h"
NAMESPACE_BEGIN(pybind11)
NAMESPACE_BEGIN(detail)
inline PyTypeObject *type_incref(PyTypeObject *type) {
Py_INCREF(type);
return type;
}
#if !defined(PYPY_VERSION)
/// `pybind11_static_property.__get__()`: Always pass the class instead of the instance.
extern "C" inline PyObject *pybind11_static_get(PyObject *self, PyObject * /*ob*/, PyObject *cls) {
return PyProperty_Type.tp_descr_get(self, cls, cls);
}
/// `pybind11_static_property.__set__()`: Just like the above `__get__()`.
extern "C" inline int pybind11_static_set(PyObject *self, PyObject *obj, PyObject *value) {
PyObject *cls = PyType_Check(obj) ? obj : (PyObject *) Py_TYPE(obj);
return PyProperty_Type.tp_descr_set(self, cls, value);
}
/** A `static_property` is the same as a `property` but the `__get__()` and `__set__()`
methods are modified to always use the object type instead of a concrete instance.
Return value: New reference. */
inline PyTypeObject *make_static_property_type() {
constexpr auto *name = "pybind11_static_property";
auto name_obj = reinterpret_steal<object>(PYBIND11_FROM_STRING(name));
/* Danger zone: from now (and until PyType_Ready), make sure to
issue no Python C API calls which could potentially invoke the
garbage collector (the GC will call type_traverse(), which will in
turn find the newly constructed type in an invalid state) */
auto heap_type = (PyHeapTypeObject *) PyType_Type.tp_alloc(&PyType_Type, 0);
if (!heap_type)
pybind11_fail("make_static_property_type(): error allocating type!");
heap_type->ht_name = name_obj.inc_ref().ptr();
#if PY_MAJOR_VERSION >= 3 && PY_MINOR_VERSION >= 3
heap_type->ht_qualname = name_obj.inc_ref().ptr();
#endif
auto type = &heap_type->ht_type;
type->tp_name = name;
type->tp_base = type_incref(&PyProperty_Type);
type->tp_flags = Py_TPFLAGS_DEFAULT | Py_TPFLAGS_BASETYPE | Py_TPFLAGS_HEAPTYPE;
type->tp_descr_get = pybind11_static_get;
type->tp_descr_set = pybind11_static_set;
if (PyType_Ready(type) < 0)
pybind11_fail("make_static_property_type(): failure in PyType_Ready()!");
setattr((PyObject *) type, "__module__", str("pybind11_builtins"));
return type;
}
#else // PYPY
/** PyPy has some issues with the above C API, so we evaluate Python code instead.
This function will only be called once so performance isn't really a concern.
Return value: New reference. */
inline PyTypeObject *make_static_property_type() {
auto d = dict();
PyObject *result = PyRun_String(R"(\
class pybind11_static_property(property):
def __get__(self, obj, cls):
return property.__get__(self, cls, cls)
def __set__(self, obj, value):
cls = obj if isinstance(obj, type) else type(obj)
property.__set__(self, cls, value)
)", Py_file_input, d.ptr(), d.ptr()
);
if (result == nullptr)
throw error_already_set();
Py_DECREF(result);
return (PyTypeObject *) d["pybind11_static_property"].cast<object>().release().ptr();
}
#endif // PYPY
/** Types with static properties need to handle `Type.static_prop = x` in a specific way.
By default, Python replaces the `static_property` itself, but for wrapped C++ types
we need to call `static_property.__set__()` in order to propagate the new value to
the underlying C++ data structure. */
extern "C" inline int pybind11_meta_setattro(PyObject* obj, PyObject* name, PyObject* value) {
// Use `_PyType_Lookup()` instead of `PyObject_GetAttr()` in order to get the raw
// descriptor (`property`) instead of calling `tp_descr_get` (`property.__get__()`).
PyObject *descr = _PyType_Lookup((PyTypeObject *) obj, name);
// The following assignment combinations are possible:
// 1. `Type.static_prop = value` --> descr_set: `Type.static_prop.__set__(value)`
// 2. `Type.static_prop = other_static_prop` --> setattro: replace existing `static_prop`
// 3. `Type.regular_attribute = value` --> setattro: regular attribute assignment
const auto static_prop = (PyObject *) get_internals().static_property_type;
const auto call_descr_set = descr && PyObject_IsInstance(descr, static_prop)
&& !PyObject_IsInstance(value, static_prop);
if (call_descr_set) {
// Call `static_property.__set__()` instead of replacing the `static_property`.
#if !defined(PYPY_VERSION)
return Py_TYPE(descr)->tp_descr_set(descr, obj, value);
#else
if (PyObject *result = PyObject_CallMethod(descr, "__set__", "OO", obj, value)) {
Py_DECREF(result);
return 0;
} else {
return -1;
}
#endif
} else {
// Replace existing attribute.
return PyType_Type.tp_setattro(obj, name, value);
}
}
#if PY_MAJOR_VERSION >= 3
/**
* Python 3's PyInstanceMethod_Type hides itself via its tp_descr_get, which prevents aliasing
* methods via cls.attr("m2") = cls.attr("m1"): instead the tp_descr_get returns a plain function,
* when called on a class, or a PyMethod, when called on an instance. Override that behaviour here
* to do a special case bypass for PyInstanceMethod_Types.
*/
extern "C" inline PyObject *pybind11_meta_getattro(PyObject *obj, PyObject *name) {
PyObject *descr = _PyType_Lookup((PyTypeObject *) obj, name);
if (descr && PyInstanceMethod_Check(descr)) {
Py_INCREF(descr);
return descr;
}
else {
return PyType_Type.tp_getattro(obj, name);
}
}
#endif
/** This metaclass is assigned by default to all pybind11 types and is required in order
for static properties to function correctly. Users may override this using `py::metaclass`.
Return value: New reference. */
inline PyTypeObject* make_default_metaclass() {
constexpr auto *name = "pybind11_type";
auto name_obj = reinterpret_steal<object>(PYBIND11_FROM_STRING(name));
/* Danger zone: from now (and until PyType_Ready), make sure to
issue no Python C API calls which could potentially invoke the
garbage collector (the GC will call type_traverse(), which will in
turn find the newly constructed type in an invalid state) */
auto heap_type = (PyHeapTypeObject *) PyType_Type.tp_alloc(&PyType_Type, 0);
if (!heap_type)
pybind11_fail("make_default_metaclass(): error allocating metaclass!");
heap_type->ht_name = name_obj.inc_ref().ptr();
#if PY_MAJOR_VERSION >= 3 && PY_MINOR_VERSION >= 3
heap_type->ht_qualname = name_obj.inc_ref().ptr();
#endif
auto type = &heap_type->ht_type;
type->tp_name = name;
type->tp_base = type_incref(&PyType_Type);
type->tp_flags = Py_TPFLAGS_DEFAULT | Py_TPFLAGS_BASETYPE | Py_TPFLAGS_HEAPTYPE;
type->tp_setattro = pybind11_meta_setattro;
#if PY_MAJOR_VERSION >= 3
type->tp_getattro = pybind11_meta_getattro;
#endif
if (PyType_Ready(type) < 0)
pybind11_fail("make_default_metaclass(): failure in PyType_Ready()!");
setattr((PyObject *) type, "__module__", str("pybind11_builtins"));
return type;
}
/// For multiple inheritance types we need to recursively register/deregister base pointers for any
/// base classes with pointers that are difference from the instance value pointer so that we can
/// correctly recognize an offset base class pointer. This calls a function with any offset base ptrs.
inline void traverse_offset_bases(void *valueptr, const detail::type_info *tinfo, instance *self,
bool (*f)(void * /*parentptr*/, instance * /*self*/)) {
for (handle h : reinterpret_borrow<tuple>(tinfo->type->tp_bases)) {
if (auto parent_tinfo = get_type_info((PyTypeObject *) h.ptr())) {
for (auto &c : parent_tinfo->implicit_casts) {
if (c.first == tinfo->cpptype) {
auto *parentptr = c.second(valueptr);
if (parentptr != valueptr)
f(parentptr, self);
traverse_offset_bases(parentptr, parent_tinfo, self, f);
break;
}
}
}
}
}
inline bool register_instance_impl(void *ptr, instance *self) {
get_internals().registered_instances.emplace(ptr, self);
return true; // unused, but gives the same signature as the deregister func
}
inline bool deregister_instance_impl(void *ptr, instance *self) {
auto &registered_instances = get_internals().registered_instances;
auto range = registered_instances.equal_range(ptr);
for (auto it = range.first; it != range.second; ++it) {
if (Py_TYPE(self) == Py_TYPE(it->second)) {
registered_instances.erase(it);
return true;
}
}
return false;
}
inline void register_instance(instance *self, void *valptr, const type_info *tinfo) {
register_instance_impl(valptr, self);
if (!tinfo->simple_ancestors)
traverse_offset_bases(valptr, tinfo, self, register_instance_impl);
}
inline bool deregister_instance(instance *self, void *valptr, const type_info *tinfo) {
bool ret = deregister_instance_impl(valptr, self);
if (!tinfo->simple_ancestors)
traverse_offset_bases(valptr, tinfo, self, deregister_instance_impl);
return ret;
}
/// Instance creation function for all pybind11 types. It only allocates space for the C++ object
/// (or multiple objects, for Python-side inheritance from multiple pybind11 types), but doesn't
/// call the constructor -- an `__init__` function must do that (followed by an `init_instance`
/// to set up the holder and register the instance).
inline PyObject *make_new_instance(PyTypeObject *type, bool allocate_value /*= true (in cast.h)*/) {
#if defined(PYPY_VERSION)
// PyPy gets tp_basicsize wrong (issue 2482) under multiple inheritance when the first inherited
// object is a a plain Python type (i.e. not derived from an extension type). Fix it.
ssize_t instance_size = static_cast<ssize_t>(sizeof(instance));
if (type->tp_basicsize < instance_size) {
type->tp_basicsize = instance_size;
}
#endif
PyObject *self = type->tp_alloc(type, 0);
auto inst = reinterpret_cast<instance *>(self);
// Allocate the value/holder internals:
inst->allocate_layout();
inst->owned = true;
// Allocate (if requested) the value pointers; otherwise leave them as nullptr
if (allocate_value) {
for (auto &v_h : values_and_holders(inst)) {
void *&vptr = v_h.value_ptr();
vptr = v_h.type->operator_new(v_h.type->type_size);
}
}
return self;
}
/// Instance creation function for all pybind11 types. It only allocates space for the
/// C++ object, but doesn't call the constructor -- an `__init__` function must do that.
extern "C" inline PyObject *pybind11_object_new(PyTypeObject *type, PyObject *, PyObject *) {
return make_new_instance(type);
}
/// An `__init__` function constructs the C++ object. Users should provide at least one
/// of these using `py::init` or directly with `.def(__init__, ...)`. Otherwise, the
/// following default function will be used which simply throws an exception.
extern "C" inline int pybind11_object_init(PyObject *self, PyObject *, PyObject *) {
PyTypeObject *type = Py_TYPE(self);
std::string msg;
#if defined(PYPY_VERSION)
msg += handle((PyObject *) type).attr("__module__").cast<std::string>() + ".";
#endif
msg += type->tp_name;
msg += ": No constructor defined!";
PyErr_SetString(PyExc_TypeError, msg.c_str());
return -1;
}
inline void add_patient(PyObject *nurse, PyObject *patient) {
auto &internals = get_internals();
auto instance = reinterpret_cast<detail::instance *>(nurse);
instance->has_patients = true;
Py_INCREF(patient);
internals.patients[nurse].push_back(patient);
}
inline void clear_patients(PyObject *self) {
auto instance = reinterpret_cast<detail::instance *>(self);
auto &internals = get_internals();
auto pos = internals.patients.find(self);
assert(pos != internals.patients.end());
// Clearing the patients can cause more Python code to run, which
// can invalidate the iterator. Extract the vector of patients
// from the unordered_map first.
auto patients = std::move(pos->second);
internals.patients.erase(pos);
instance->has_patients = false;
for (PyObject *&patient : patients)
Py_CLEAR(patient);
}
/// Clears all internal data from the instance and removes it from registered instances in
/// preparation for deallocation.
inline void clear_instance(PyObject *self) {
auto instance = reinterpret_cast<detail::instance *>(self);
// Deallocate any values/holders, if present:
for (auto &v_h : values_and_holders(instance)) {
if (v_h) {
// We have to deregister before we call dealloc because, for virtual MI types, we still
// need to be able to get the parent pointers.
if (v_h.instance_registered() && !deregister_instance(instance, v_h.value_ptr(), v_h.type))
pybind11_fail("pybind11_object_dealloc(): Tried to deallocate unregistered instance!");
if (instance->owned || v_h.holder_constructed())
v_h.type->dealloc(v_h);
}
}
// Deallocate the value/holder layout internals:
instance->deallocate_layout();
if (instance->weakrefs)
PyObject_ClearWeakRefs(self);
PyObject **dict_ptr = _PyObject_GetDictPtr(self);
if (dict_ptr)
Py_CLEAR(*dict_ptr);
if (instance->has_patients)
clear_patients(self);
}
/// Instance destructor function for all pybind11 types. It calls `type_info.dealloc`
/// to destroy the C++ object itself, while the rest is Python bookkeeping.
extern "C" inline void pybind11_object_dealloc(PyObject *self) {
clear_instance(self);
Py_TYPE(self)->tp_free(self);
}
/** Create the type which can be used as a common base for all classes. This is
needed in order to satisfy Python's requirements for multiple inheritance.
Return value: New reference. */
inline PyObject *make_object_base_type(PyTypeObject *metaclass) {
constexpr auto *name = "pybind11_object";
auto name_obj = reinterpret_steal<object>(PYBIND11_FROM_STRING(name));
/* Danger zone: from now (and until PyType_Ready), make sure to
issue no Python C API calls which could potentially invoke the
garbage collector (the GC will call type_traverse(), which will in
turn find the newly constructed type in an invalid state) */
auto heap_type = (PyHeapTypeObject *) metaclass->tp_alloc(metaclass, 0);
if (!heap_type)
pybind11_fail("make_object_base_type(): error allocating type!");
heap_type->ht_name = name_obj.inc_ref().ptr();
#if PY_MAJOR_VERSION >= 3 && PY_MINOR_VERSION >= 3
heap_type->ht_qualname = name_obj.inc_ref().ptr();
#endif
auto type = &heap_type->ht_type;
type->tp_name = name;
type->tp_base = type_incref(&PyBaseObject_Type);
type->tp_basicsize = static_cast<ssize_t>(sizeof(instance));
type->tp_flags = Py_TPFLAGS_DEFAULT | Py_TPFLAGS_BASETYPE | Py_TPFLAGS_HEAPTYPE;
type->tp_new = pybind11_object_new;
type->tp_init = pybind11_object_init;
type->tp_dealloc = pybind11_object_dealloc;
/* Support weak references (needed for the keep_alive feature) */
type->tp_weaklistoffset = offsetof(instance, weakrefs);
if (PyType_Ready(type) < 0)
pybind11_fail("PyType_Ready failed in make_object_base_type():" + error_string());
setattr((PyObject *) type, "__module__", str("pybind11_builtins"));
assert(!PyType_HasFeature(type, Py_TPFLAGS_HAVE_GC));
return (PyObject *) heap_type;
}
/// dynamic_attr: Support for `d = instance.__dict__`.
extern "C" inline PyObject *pybind11_get_dict(PyObject *self, void *) {
PyObject *&dict = *_PyObject_GetDictPtr(self);
if (!dict)
dict = PyDict_New();
Py_XINCREF(dict);
return dict;
}
/// dynamic_attr: Support for `instance.__dict__ = dict()`.
extern "C" inline int pybind11_set_dict(PyObject *self, PyObject *new_dict, void *) {
if (!PyDict_Check(new_dict)) {
PyErr_Format(PyExc_TypeError, "__dict__ must be set to a dictionary, not a '%.200s'",
Py_TYPE(new_dict)->tp_name);
return -1;
}
PyObject *&dict = *_PyObject_GetDictPtr(self);
Py_INCREF(new_dict);
Py_CLEAR(dict);
dict = new_dict;
return 0;
}
/// dynamic_attr: Allow the garbage collector to traverse the internal instance `__dict__`.
extern "C" inline int pybind11_traverse(PyObject *self, visitproc visit, void *arg) {
PyObject *&dict = *_PyObject_GetDictPtr(self);
Py_VISIT(dict);
return 0;
}
/// dynamic_attr: Allow the GC to clear the dictionary.
extern "C" inline int pybind11_clear(PyObject *self) {
PyObject *&dict = *_PyObject_GetDictPtr(self);
Py_CLEAR(dict);
return 0;
}
/// Give instances of this type a `__dict__` and opt into garbage collection.
inline void enable_dynamic_attributes(PyHeapTypeObject *heap_type) {
auto type = &heap_type->ht_type;
#if defined(PYPY_VERSION)
pybind11_fail(std::string(type->tp_name) + ": dynamic attributes are "
"currently not supported in "
"conjunction with PyPy!");
#endif
type->tp_flags |= Py_TPFLAGS_HAVE_GC;
type->tp_dictoffset = type->tp_basicsize; // place dict at the end
type->tp_basicsize += (ssize_t)sizeof(PyObject *); // and allocate enough space for it
type->tp_traverse = pybind11_traverse;
type->tp_clear = pybind11_clear;
static PyGetSetDef getset[] = {
{const_cast<char*>("__dict__"), pybind11_get_dict, pybind11_set_dict, nullptr, nullptr},
{nullptr, nullptr, nullptr, nullptr, nullptr}
};
type->tp_getset = getset;
}
/// buffer_protocol: Fill in the view as specified by flags.
extern "C" inline int pybind11_getbuffer(PyObject *obj, Py_buffer *view, int flags) {
// Look for a `get_buffer` implementation in this type's info or any bases (following MRO).
type_info *tinfo = nullptr;
for (auto type : reinterpret_borrow<tuple>(Py_TYPE(obj)->tp_mro)) {
tinfo = get_type_info((PyTypeObject *) type.ptr());
if (tinfo && tinfo->get_buffer)
break;
}
if (view == nullptr || obj == nullptr || !tinfo || !tinfo->get_buffer) {
if (view)
view->obj = nullptr;
PyErr_SetString(PyExc_BufferError, "pybind11_getbuffer(): Internal error");
return -1;
}
std::memset(view, 0, sizeof(Py_buffer));
buffer_info *info = tinfo->get_buffer(obj, tinfo->get_buffer_data);
view->obj = obj;
view->ndim = 1;
view->internal = info;
view->buf = info->ptr;
view->itemsize = info->itemsize;
view->len = view->itemsize;
for (auto s : info->shape)
view->len *= s;
if ((flags & PyBUF_FORMAT) == PyBUF_FORMAT)
view->format = const_cast<char *>(info->format.c_str());
if ((flags & PyBUF_STRIDES) == PyBUF_STRIDES) {
view->ndim = (int) info->ndim;
view->strides = &info->strides[0];
view->shape = &info->shape[0];
}
Py_INCREF(view->obj);
return 0;
}
/// buffer_protocol: Release the resources of the buffer.
extern "C" inline void pybind11_releasebuffer(PyObject *, Py_buffer *view) {
delete (buffer_info *) view->internal;
}
/// Give this type a buffer interface.
inline void enable_buffer_protocol(PyHeapTypeObject *heap_type) {
heap_type->ht_type.tp_as_buffer = &heap_type->as_buffer;
#if PY_MAJOR_VERSION < 3
heap_type->ht_type.tp_flags |= Py_TPFLAGS_HAVE_NEWBUFFER;
#endif
heap_type->as_buffer.bf_getbuffer = pybind11_getbuffer;
heap_type->as_buffer.bf_releasebuffer = pybind11_releasebuffer;
}
/** Create a brand new Python type according to the `type_record` specification.
Return value: New reference. */
inline PyObject* make_new_python_type(const type_record &rec) {
auto name = reinterpret_steal<object>(PYBIND11_FROM_STRING(rec.name));
#if PY_MAJOR_VERSION >= 3 && PY_MINOR_VERSION >= 3
auto ht_qualname = name;
if (rec.scope && hasattr(rec.scope, "__qualname__")) {
ht_qualname = reinterpret_steal<object>(
PyUnicode_FromFormat("%U.%U", rec.scope.attr("__qualname__").ptr(), name.ptr()));
}
#endif
object module;
if (rec.scope) {
if (hasattr(rec.scope, "__module__"))
module = rec.scope.attr("__module__");
else if (hasattr(rec.scope, "__name__"))
module = rec.scope.attr("__name__");
}
#if !defined(PYPY_VERSION)
const auto full_name = module ? str(module).cast<std::string>() + "." + rec.name
: std::string(rec.name);
#else
const auto full_name = std::string(rec.name);
#endif
char *tp_doc = nullptr;
if (rec.doc && options::show_user_defined_docstrings()) {
/* Allocate memory for docstring (using PyObject_MALLOC, since
Python will free this later on) */
size_t size = strlen(rec.doc) + 1;
tp_doc = (char *) PyObject_MALLOC(size);
memcpy((void *) tp_doc, rec.doc, size);
}
auto &internals = get_internals();
auto bases = tuple(rec.bases);
auto base = (bases.size() == 0) ? internals.instance_base
: bases[0].ptr();
/* Danger zone: from now (and until PyType_Ready), make sure to
issue no Python C API calls which could potentially invoke the
garbage collector (the GC will call type_traverse(), which will in
turn find the newly constructed type in an invalid state) */
auto metaclass = rec.metaclass.ptr() ? (PyTypeObject *) rec.metaclass.ptr()
: internals.default_metaclass;
auto heap_type = (PyHeapTypeObject *) metaclass->tp_alloc(metaclass, 0);
if (!heap_type)
pybind11_fail(std::string(rec.name) + ": Unable to create type object!");
heap_type->ht_name = name.release().ptr();
#if PY_MAJOR_VERSION >= 3 && PY_MINOR_VERSION >= 3
heap_type->ht_qualname = ht_qualname.release().ptr();
#endif
auto type = &heap_type->ht_type;
type->tp_name = strdup(full_name.c_str());
type->tp_doc = tp_doc;
type->tp_base = type_incref((PyTypeObject *)base);
type->tp_basicsize = static_cast<ssize_t>(sizeof(instance));
if (bases.size() > 0)
type->tp_bases = bases.release().ptr();
/* Don't inherit base __init__ */
type->tp_init = pybind11_object_init;
/* Supported protocols */
type->tp_as_number = &heap_type->as_number;
type->tp_as_sequence = &heap_type->as_sequence;
type->tp_as_mapping = &heap_type->as_mapping;
/* Flags */
type->tp_flags |= Py_TPFLAGS_DEFAULT | Py_TPFLAGS_BASETYPE | Py_TPFLAGS_HEAPTYPE;
#if PY_MAJOR_VERSION < 3
type->tp_flags |= Py_TPFLAGS_CHECKTYPES;
#endif
if (rec.dynamic_attr)
enable_dynamic_attributes(heap_type);
if (rec.buffer_protocol)
enable_buffer_protocol(heap_type);
if (PyType_Ready(type) < 0)
pybind11_fail(std::string(rec.name) + ": PyType_Ready failed (" + error_string() + ")!");
assert(rec.dynamic_attr ? PyType_HasFeature(type, Py_TPFLAGS_HAVE_GC)
: !PyType_HasFeature(type, Py_TPFLAGS_HAVE_GC));
/* Register type with the parent scope */
if (rec.scope)
setattr(rec.scope, rec.name, (PyObject *) type);
if (module) // Needed by pydoc
setattr((PyObject *) type, "__module__", module);
return (PyObject *) type;
}
NAMESPACE_END(detail)
NAMESPACE_END(pybind11)

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mmocr/models/textdet/postprocess/include/pybind11/common.h
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@ -1,2 +0,0 @@
#include "detail/common.h"
#warning "Including 'common.h' is deprecated. It will be removed in v3.0. Use 'pybind11.h'."

65
mmocr/models/textdet/postprocess/include/pybind11/complex.h
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@ -1,65 +0,0 @@
/*
pybind11/complex.h: Complex number support
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>
/// glibc defines I as a macro which breaks things, e.g., boost template names
#ifdef I
# undef I
#endif
NAMESPACE_BEGIN(PYBIND11_NAMESPACE)
template <typename T> struct format_descriptor<std::complex<T>, detail::enable_if_t<std::is_floating_point<T>::value>> {
static constexpr const char c = format_descriptor<T>::c;
static constexpr const char value[3] = { 'Z', c, '\0' };
static std::string format() { return std::string(value); }
};
#ifndef PYBIND11_CPP17
template <typename T> constexpr const char format_descriptor<
std::complex<T>, detail::enable_if_t<std::is_floating_point<T>::value>>::value[3];
#endif
NAMESPACE_BEGIN(detail)
template <typename T> struct is_fmt_numeric<std::complex<T>, detail::enable_if_t<std::is_floating_point<T>::value>> {
static constexpr bool value = true;
static constexpr int index = is_fmt_numeric<T>::index + 3;
};
template <typename T> class type_caster<std::complex<T>> {
public:
bool load(handle src, bool convert) {
if (!src)
return false;
if (!convert && !PyComplex_Check(src.ptr()))
return false;
Py_complex result = PyComplex_AsCComplex(src.ptr());
if (result.real == -1.0 && PyErr_Occurred()) {
PyErr_Clear();
return false;
}
value = std::complex<T>((T) result.real, (T) result.imag);
return true;
}
static handle cast(const std::complex<T> &src, return_value_policy /* policy */, handle /* parent */) {
return PyComplex_FromDoubles((double) src.real(), (double) src.imag());
}
PYBIND11_TYPE_CASTER(std::complex<T>, _("complex"));
};
NAMESPACE_END(detail)
NAMESPACE_END(PYBIND11_NAMESPACE)

185
mmocr/models/textdet/postprocess/include/pybind11/descr.h
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@ -1,185 +0,0 @@
/*
pybind11/descr.h: Helper type for concatenating type signatures
either at runtime (C++11) or compile time (C++14)
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 "common.h"
NAMESPACE_BEGIN(pybind11)
NAMESPACE_BEGIN(detail)
/* Concatenate type signatures at compile time using C++14 */
#if defined(PYBIND11_CPP14) && !defined(_MSC_VER)
#define PYBIND11_CONSTEXPR_DESCR
template <size_t Size1, size_t Size2> class descr {
template <size_t Size1_, size_t Size2_> friend class descr;
public:
constexpr descr(char const (&text) [Size1+1], const std::type_info * const (&types)[Size2+1])
: descr(text, types,
make_index_sequence<Size1>(),
make_index_sequence<Size2>()) { }
constexpr const char *text() const { return m_text; }
constexpr const std::type_info * const * types() const { return m_types; }
template <size_t OtherSize1, size_t OtherSize2>
constexpr descr<Size1 + OtherSize1, Size2 + OtherSize2> operator+(const descr<OtherSize1, OtherSize2> &other) const {
return concat(other,
make_index_sequence<Size1>(),
make_index_sequence<Size2>(),
make_index_sequence<OtherSize1>(),
make_index_sequence<OtherSize2>());
}
protected:
template <size_t... Indices1, size_t... Indices2>
constexpr descr(
char const (&text) [Size1+1],
const std::type_info * const (&types) [Size2+1],
index_sequence<Indices1...>, index_sequence<Indices2...>)
: m_text{text[Indices1]..., '\0'},
m_types{types[Indices2]..., nullptr } {}
template <size_t OtherSize1, size_t OtherSize2, size_t... Indices1,
size_t... Indices2, size_t... OtherIndices1, size_t... OtherIndices2>
constexpr descr<Size1 + OtherSize1, Size2 + OtherSize2>
concat(const descr<OtherSize1, OtherSize2> &other,
index_sequence<Indices1...>, index_sequence<Indices2...>,
index_sequence<OtherIndices1...>, index_sequence<OtherIndices2...>) const {
return descr<Size1 + OtherSize1, Size2 + OtherSize2>(
{ m_text[Indices1]..., other.m_text[OtherIndices1]..., '\0' },
{ m_types[Indices2]..., other.m_types[OtherIndices2]..., nullptr }
);
}
protected:
char m_text[Size1 + 1];
const std::type_info * m_types[Size2 + 1];
};
template <size_t Size> constexpr descr<Size - 1, 0> _(char const(&text)[Size]) {
return descr<Size - 1, 0>(text, { nullptr });
}
template <size_t Rem, size_t... Digits> struct int_to_str : int_to_str<Rem/10, Rem%10, Digits...> { };
template <size_t...Digits> struct int_to_str<0, Digits...> {
static constexpr auto digits = descr<sizeof...(Digits), 0>({ ('0' + Digits)..., '\0' }, { nullptr });
};
// Ternary description (like std::conditional)
template <bool B, size_t Size1, size_t Size2>
constexpr enable_if_t<B, descr<Size1 - 1, 0>> _(char const(&text1)[Size1], char const(&)[Size2]) {
return _(text1);
}
template <bool B, size_t Size1, size_t Size2>
constexpr enable_if_t<!B, descr<Size2 - 1, 0>> _(char const(&)[Size1], char const(&text2)[Size2]) {
return _(text2);
}
template <bool B, size_t SizeA1, size_t SizeA2, size_t SizeB1, size_t SizeB2>
constexpr enable_if_t<B, descr<SizeA1, SizeA2>> _(descr<SizeA1, SizeA2> d, descr<SizeB1, SizeB2>) { return d; }
template <bool B, size_t SizeA1, size_t SizeA2, size_t SizeB1, size_t SizeB2>
constexpr enable_if_t<!B, descr<SizeB1, SizeB2>> _(descr<SizeA1, SizeA2>, descr<SizeB1, SizeB2> d) { return d; }
template <size_t Size> auto constexpr _() -> decltype(int_to_str<Size / 10, Size % 10>::digits) {
return int_to_str<Size / 10, Size % 10>::digits;
}
template <typename Type> constexpr descr<1, 1> _() {
return descr<1, 1>({ '%', '\0' }, { &typeid(Type), nullptr });
}
inline constexpr descr<0, 0> concat() { return _(""); }
template <size_t Size1, size_t Size2, typename... Args> auto constexpr concat(descr<Size1, Size2> descr) { return descr; }
template <size_t Size1, size_t Size2, typename... Args> auto constexpr concat(descr<Size1, Size2> descr, Args&&... args) { return descr + _(", ") + concat(args...); }
template <size_t Size1, size_t Size2> auto constexpr type_descr(descr<Size1, Size2> descr) { return _("{") + descr + _("}"); }
#define PYBIND11_DESCR constexpr auto
#else /* Simpler C++11 implementation based on run-time memory allocation and copying */
class descr {
public:
PYBIND11_NOINLINE descr(const char *text, const std::type_info * const * types) {
size_t nChars = len(text), nTypes = len(types);
m_text = new char[nChars];
m_types = new const std::type_info *[nTypes];
memcpy(m_text, text, nChars * sizeof(char));
memcpy(m_types, types, nTypes * sizeof(const std::type_info *));
}
PYBIND11_NOINLINE descr operator+(descr &&d2) && {
descr r;
size_t nChars1 = len(m_text), nTypes1 = len(m_types);
size_t nChars2 = len(d2.m_text), nTypes2 = len(d2.m_types);
r.m_text = new char[nChars1 + nChars2 - 1];
r.m_types = new const std::type_info *[nTypes1 + nTypes2 - 1];
memcpy(r.m_text, m_text, (nChars1-1) * sizeof(char));
memcpy(r.m_text + nChars1 - 1, d2.m_text, nChars2 * sizeof(char));
memcpy(r.m_types, m_types, (nTypes1-1) * sizeof(std::type_info *));
memcpy(r.m_types + nTypes1 - 1, d2.m_types, nTypes2 * sizeof(std::type_info *));
delete[] m_text; delete[] m_types;
delete[] d2.m_text; delete[] d2.m_types;
return r;
}
char *text() { return m_text; }
const std::type_info * * types() { return m_types; }
protected:
PYBIND11_NOINLINE descr() { }
template <typename T> static size_t len(const T *ptr) { // return length including null termination
const T *it = ptr;
while (*it++ != (T) 0)
;
return static_cast<size_t>(it - ptr);
}
const std::type_info **m_types = nullptr;
char *m_text = nullptr;
};
/* The 'PYBIND11_NOINLINE inline' combinations below are intentional to get the desired linkage while producing as little object code as possible */
PYBIND11_NOINLINE inline descr _(const char *text) {
const std::type_info *types[1] = { nullptr };
return descr(text, types);
}
template <bool B> PYBIND11_NOINLINE enable_if_t<B, descr> _(const char *text1, const char *) { return _(text1); }
template <bool B> PYBIND11_NOINLINE enable_if_t<!B, descr> _(char const *, const char *text2) { return _(text2); }
template <bool B> PYBIND11_NOINLINE enable_if_t<B, descr> _(descr d, descr) { return d; }
template <bool B> PYBIND11_NOINLINE enable_if_t<!B, descr> _(descr, descr d) { return d; }
template <typename Type> PYBIND11_NOINLINE descr _() {
const std::type_info *types[2] = { &typeid(Type), nullptr };
return descr("%", types);
}
template <size_t Size> PYBIND11_NOINLINE descr _() {
const std::type_info *types[1] = { nullptr };
return descr(std::to_string(Size).c_str(), types);
}
PYBIND11_NOINLINE inline descr concat() { return _(""); }
PYBIND11_NOINLINE inline descr concat(descr &&d) { return d; }
template <typename... Args> PYBIND11_NOINLINE descr concat(descr &&d, Args&&... args) { return std::move(d) + _(", ") + concat(std::forward<Args>(args)...); }
PYBIND11_NOINLINE inline descr type_descr(descr&& d) { return _("{") + std::move(d) + _("}"); }
#define PYBIND11_DESCR ::pybind11::detail::descr
#endif
NAMESPACE_END(detail)
NAMESPACE_END(pybind11)

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mmocr/models/textdet/postprocess/include/pybind11/detail/class.h
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@ -1,622 +0,0 @@
/*
pybind11/detail/class.h: Python C API implementation details for py::class_
Copyright (c) 2017 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 "../attr.h"
NAMESPACE_BEGIN(PYBIND11_NAMESPACE)
NAMESPACE_BEGIN(detail)
#if PY_VERSION_HEX >= 0x03030000
# define PYBIND11_BUILTIN_QUALNAME
# define PYBIND11_SET_OLDPY_QUALNAME(obj, nameobj)
#else
// In pre-3.3 Python, we still set __qualname__ so that we can produce reliable function type
// signatures; in 3.3+ this macro expands to nothing:
# define PYBIND11_SET_OLDPY_QUALNAME(obj, nameobj) setattr((PyObject *) obj, "__qualname__", nameobj)
#endif
inline PyTypeObject *type_incref(PyTypeObject *type) {
Py_INCREF(type);
return type;
}
#if !defined(PYPY_VERSION)
/// `pybind11_static_property.__get__()`: Always pass the class instead of the instance.
extern "C" inline PyObject *pybind11_static_get(PyObject *self, PyObject * /*ob*/, PyObject *cls) {
return PyProperty_Type.tp_descr_get(self, cls, cls);
}
/// `pybind11_static_property.__set__()`: Just like the above `__get__()`.
extern "C" inline int pybind11_static_set(PyObject *self, PyObject *obj, PyObject *value) {
PyObject *cls = PyType_Check(obj) ? obj : (PyObject *) Py_TYPE(obj);
return PyProperty_Type.tp_descr_set(self, cls, value);
}
/** A `static_property` is the same as a `property` but the `__get__()` and `__set__()`
methods are modified to always use the object type instead of a concrete instance.
Return value: New reference. */
inline PyTypeObject *make_static_property_type() {
constexpr auto *name = "pybind11_static_property";
auto name_obj = reinterpret_steal<object>(PYBIND11_FROM_STRING(name));
/* Danger zone: from now (and until PyType_Ready), make sure to
issue no Python C API calls which could potentially invoke the
garbage collector (the GC will call type_traverse(), which will in
turn find the newly constructed type in an invalid state) */
auto heap_type = (PyHeapTypeObject *) PyType_Type.tp_alloc(&PyType_Type, 0);
if (!heap_type)
pybind11_fail("make_static_property_type(): error allocating type!");
heap_type->ht_name = name_obj.inc_ref().ptr();
#ifdef PYBIND11_BUILTIN_QUALNAME
heap_type->ht_qualname = name_obj.inc_ref().ptr();
#endif
auto type = &heap_type->ht_type;
type->tp_name = name;
type->tp_base = type_incref(&PyProperty_Type);
type->tp_flags = Py_TPFLAGS_DEFAULT | Py_TPFLAGS_BASETYPE | Py_TPFLAGS_HEAPTYPE;
type->tp_descr_get = pybind11_static_get;
type->tp_descr_set = pybind11_static_set;
if (PyType_Ready(type) < 0)
pybind11_fail("make_static_property_type(): failure in PyType_Ready()!");
setattr((PyObject *) type, "__module__", str("pybind11_builtins"));
PYBIND11_SET_OLDPY_QUALNAME(type, name_obj);
return type;
}
#else // PYPY
/** PyPy has some issues with the above C API, so we evaluate Python code instead.
This function will only be called once so performance isn't really a concern.
Return value: New reference. */
inline PyTypeObject *make_static_property_type() {
auto d = dict();
PyObject *result = PyRun_String(R"(\
class pybind11_static_property(property):
def __get__(self, obj, cls):
return property.__get__(self, cls, cls)
def __set__(self, obj, value):
cls = obj if isinstance(obj, type) else type(obj)
property.__set__(self, cls, value)
)", Py_file_input, d.ptr(), d.ptr()
);
if (result == nullptr)
throw error_already_set();
Py_DECREF(result);
return (PyTypeObject *) d["pybind11_static_property"].cast<object>().release().ptr();
}
#endif // PYPY
/** Types with static properties need to handle `Type.static_prop = x` in a specific way.
By default, Python replaces the `static_property` itself, but for wrapped C++ types
we need to call `static_property.__set__()` in order to propagate the new value to
the underlying C++ data structure. */
extern "C" inline int pybind11_meta_setattro(PyObject* obj, PyObject* name, PyObject* value) {
// Use `_PyType_Lookup()` instead of `PyObject_GetAttr()` in order to get the raw
// descriptor (`property`) instead of calling `tp_descr_get` (`property.__get__()`).
PyObject *descr = _PyType_Lookup((PyTypeObject *) obj, name);
// The following assignment combinations are possible:
// 1. `Type.static_prop = value` --> descr_set: `Type.static_prop.__set__(value)`
// 2. `Type.static_prop = other_static_prop` --> setattro: replace existing `static_prop`
// 3. `Type.regular_attribute = value` --> setattro: regular attribute assignment
const auto static_prop = (PyObject *) get_internals().static_property_type;
const auto call_descr_set = descr && PyObject_IsInstance(descr, static_prop)
&& !PyObject_IsInstance(value, static_prop);
if (call_descr_set) {
// Call `static_property.__set__()` instead of replacing the `static_property`.
#if !defined(PYPY_VERSION)
return Py_TYPE(descr)->tp_descr_set(descr, obj, value);
#else
if (PyObject *result = PyObject_CallMethod(descr, "__set__", "OO", obj, value)) {
Py_DECREF(result);
return 0;
} else {
return -1;
}
#endif
} else {
// Replace existing attribute.
return PyType_Type.tp_setattro(obj, name, value);
}
}
#if PY_MAJOR_VERSION >= 3
/**
* Python 3's PyInstanceMethod_Type hides itself via its tp_descr_get, which prevents aliasing
* methods via cls.attr("m2") = cls.attr("m1"): instead the tp_descr_get returns a plain function,
* when called on a class, or a PyMethod, when called on an instance. Override that behaviour here
* to do a special case bypass for PyInstanceMethod_Types.
*/
extern "C" inline PyObject *pybind11_meta_getattro(PyObject *obj, PyObject *name) {
PyObject *descr = _PyType_Lookup((PyTypeObject *) obj, name);
if (descr && PyInstanceMethod_Check(descr)) {
Py_INCREF(descr);
return descr;
}
else {
return PyType_Type.tp_getattro(obj, name);
}
}
#endif
/** This metaclass is assigned by default to all pybind11 types and is required in order
for static properties to function correctly. Users may override this using `py::metaclass`.
Return value: New reference. */
inline PyTypeObject* make_default_metaclass() {
constexpr auto *name = "pybind11_type";
auto name_obj = reinterpret_steal<object>(PYBIND11_FROM_STRING(name));
/* Danger zone: from now (and until PyType_Ready), make sure to
issue no Python C API calls which could potentially invoke the
garbage collector (the GC will call type_traverse(), which will in
turn find the newly constructed type in an invalid state) */
auto heap_type = (PyHeapTypeObject *) PyType_Type.tp_alloc(&PyType_Type, 0);
if (!heap_type)
pybind11_fail("make_default_metaclass(): error allocating metaclass!");
heap_type->ht_name = name_obj.inc_ref().ptr();
#ifdef PYBIND11_BUILTIN_QUALNAME
heap_type->ht_qualname = name_obj.inc_ref().ptr();
#endif
auto type = &heap_type->ht_type;
type->tp_name = name;
type->tp_base = type_incref(&PyType_Type);
type->tp_flags = Py_TPFLAGS_DEFAULT | Py_TPFLAGS_BASETYPE | Py_TPFLAGS_HEAPTYPE;
type->tp_setattro = pybind11_meta_setattro;
#if PY_MAJOR_VERSION >= 3
type->tp_getattro = pybind11_meta_getattro;
#endif
if (PyType_Ready(type) < 0)
pybind11_fail("make_default_metaclass(): failure in PyType_Ready()!");
setattr((PyObject *) type, "__module__", str("pybind11_builtins"));
PYBIND11_SET_OLDPY_QUALNAME(type, name_obj);
return type;
}
/// For multiple inheritance types we need to recursively register/deregister base pointers for any
/// base classes with pointers that are difference from the instance value pointer so that we can
/// correctly recognize an offset base class pointer. This calls a function with any offset base ptrs.
inline void traverse_offset_bases(void *valueptr, const detail::type_info *tinfo, instance *self,
bool (*f)(void * /*parentptr*/, instance * /*self*/)) {
for (handle h : reinterpret_borrow<tuple>(tinfo->type->tp_bases)) {
if (auto parent_tinfo = get_type_info((PyTypeObject *) h.ptr())) {
for (auto &c : parent_tinfo->implicit_casts) {
if (c.first == tinfo->cpptype) {
auto *parentptr = c.second(valueptr);
if (parentptr != valueptr)
f(parentptr, self);
traverse_offset_bases(parentptr, parent_tinfo, self, f);
break;
}
}
}
}
}
inline bool register_instance_impl(void *ptr, instance *self) {
get_internals().registered_instances.emplace(ptr, self);
return true; // unused, but gives the same signature as the deregister func
}
inline bool deregister_instance_impl(void *ptr, instance *self) {
auto &registered_instances = get_internals().registered_instances;
auto range = registered_instances.equal_range(ptr);
for (auto it = range.first; it != range.second; ++it) {
if (Py_TYPE(self) == Py_TYPE(it->second)) {
registered_instances.erase(it);
return true;
}
}
return false;
}
inline void register_instance(instance *self, void *valptr, const type_info *tinfo) {
register_instance_impl(valptr, self);
if (!tinfo->simple_ancestors)
traverse_offset_bases(valptr, tinfo, self, register_instance_impl);
}
inline bool deregister_instance(instance *self, void *valptr, const type_info *tinfo) {
bool ret = deregister_instance_impl(valptr, self);
if (!tinfo->simple_ancestors)
traverse_offset_bases(valptr, tinfo, self, deregister_instance_impl);
return ret;
}
/// Instance creation function for all pybind11 types. It allocates the internal instance layout for
/// holding C++ objects and holders. Allocation is done lazily (the first time the instance is cast
/// to a reference or pointer), and initialization is done by an `__init__` function.
inline PyObject *make_new_instance(PyTypeObject *type) {
#if defined(PYPY_VERSION)
// PyPy gets tp_basicsize wrong (issue 2482) under multiple inheritance when the first inherited
// object is a a plain Python type (i.e. not derived from an extension type). Fix it.
ssize_t instance_size = static_cast<ssize_t>(sizeof(instance));
if (type->tp_basicsize < instance_size) {
type->tp_basicsize = instance_size;
}
#endif
PyObject *self = type->tp_alloc(type, 0);
auto inst = reinterpret_cast<instance *>(self);
// Allocate the value/holder internals:
inst->allocate_layout();
inst->owned = true;
return self;
}
/// Instance creation function for all pybind11 types. It only allocates space for the
/// C++ object, but doesn't call the constructor -- an `__init__` function must do that.
extern "C" inline PyObject *pybind11_object_new(PyTypeObject *type, PyObject *, PyObject *) {
return make_new_instance(type);
}
/// An `__init__` function constructs the C++ object. Users should provide at least one
/// of these using `py::init` or directly with `.def(__init__, ...)`. Otherwise, the
/// following default function will be used which simply throws an exception.
extern "C" inline int pybind11_object_init(PyObject *self, PyObject *, PyObject *) {
PyTypeObject *type = Py_TYPE(self);
std::string msg;
#if defined(PYPY_VERSION)
msg += handle((PyObject *) type).attr("__module__").cast<std::string>() + ".";
#endif
msg += type->tp_name;
msg += ": No constructor defined!";
PyErr_SetString(PyExc_TypeError, msg.c_str());
return -1;
}
inline void add_patient(PyObject *nurse, PyObject *patient) {
auto &internals = get_internals();
auto instance = reinterpret_cast<detail::instance *>(nurse);
instance->has_patients = true;
Py_INCREF(patient);
internals.patients[nurse].push_back(patient);
}
inline void clear_patients(PyObject *self) {
auto instance = reinterpret_cast<detail::instance *>(self);
auto &internals = get_internals();
auto pos = internals.patients.find(self);
assert(pos != internals.patients.end());
// Clearing the patients can cause more Python code to run, which
// can invalidate the iterator. Extract the vector of patients
// from the unordered_map first.
auto patients = std::move(pos->second);
internals.patients.erase(pos);
instance->has_patients = false;
for (PyObject *&patient : patients)
Py_CLEAR(patient);
}
/// Clears all internal data from the instance and removes it from registered instances in
/// preparation for deallocation.
inline void clear_instance(PyObject *self) {
auto instance = reinterpret_cast<detail::instance *>(self);
// Deallocate any values/holders, if present:
for (auto &v_h : values_and_holders(instance)) {
if (v_h) {
// We have to deregister before we call dealloc because, for virtual MI types, we still
// need to be able to get the parent pointers.
if (v_h.instance_registered() && !deregister_instance(instance, v_h.value_ptr(), v_h.type))
pybind11_fail("pybind11_object_dealloc(): Tried to deallocate unregistered instance!");
if (instance->owned || v_h.holder_constructed())
v_h.type->dealloc(v_h);
}
}
// Deallocate the value/holder layout internals:
instance->deallocate_layout();
if (instance->weakrefs)
PyObject_ClearWeakRefs(self);
PyObject **dict_ptr = _PyObject_GetDictPtr(self);
if (dict_ptr)
Py_CLEAR(*dict_ptr);
if (instance->has_patients)
clear_patients(self);
}
/// Instance destructor function for all pybind11 types. It calls `type_info.dealloc`
/// to destroy the C++ object itself, while the rest is Python bookkeeping.
extern "C" inline void pybind11_object_dealloc(PyObject *self) {
clear_instance(self);
auto type = Py_TYPE(self);
type->tp_free(self);
// `type->tp_dealloc != pybind11_object_dealloc` means that we're being called
// as part of a derived type's dealloc, in which case we're not allowed to decref
// the type here. For cross-module compatibility, we shouldn't compare directly
// with `pybind11_object_dealloc`, but with the common one stashed in internals.
auto pybind11_object_type = (PyTypeObject *) get_internals().instance_base;
if (type->tp_dealloc == pybind11_object_type->tp_dealloc)
Py_DECREF(type);
}
/** Create the type which can be used as a common base for all classes. This is
needed in order to satisfy Python's requirements for multiple inheritance.
Return value: New reference. */
inline PyObject *make_object_base_type(PyTypeObject *metaclass) {
constexpr auto *name = "pybind11_object";
auto name_obj = reinterpret_steal<object>(PYBIND11_FROM_STRING(name));
/* Danger zone: from now (and until PyType_Ready), make sure to
issue no Python C API calls which could potentially invoke the
garbage collector (the GC will call type_traverse(), which will in
turn find the newly constructed type in an invalid state) */
auto heap_type = (PyHeapTypeObject *) metaclass->tp_alloc(metaclass, 0);
if (!heap_type)
pybind11_fail("make_object_base_type(): error allocating type!");
heap_type->ht_name = name_obj.inc_ref().ptr();
#ifdef PYBIND11_BUILTIN_QUALNAME
heap_type->ht_qualname = name_obj.inc_ref().ptr();
#endif
auto type = &heap_type->ht_type;
type->tp_name = name;
type->tp_base = type_incref(&PyBaseObject_Type);
type->tp_basicsize = static_cast<ssize_t>(sizeof(instance));
type->tp_flags = Py_TPFLAGS_DEFAULT | Py_TPFLAGS_BASETYPE | Py_TPFLAGS_HEAPTYPE;
type->tp_new = pybind11_object_new;
type->tp_init = pybind11_object_init;
type->tp_dealloc = pybind11_object_dealloc;
/* Support weak references (needed for the keep_alive feature) */
type->tp_weaklistoffset = offsetof(instance, weakrefs);
if (PyType_Ready(type) < 0)
pybind11_fail("PyType_Ready failed in make_object_base_type():" + error_string());
setattr((PyObject *) type, "__module__", str("pybind11_builtins"));
PYBIND11_SET_OLDPY_QUALNAME(type, name_obj);
assert(!PyType_HasFeature(type, Py_TPFLAGS_HAVE_GC));
return (PyObject *) heap_type;
}
/// dynamic_attr: Support for `d = instance.__dict__`.
extern "C" inline PyObject *pybind11_get_dict(PyObject *self, void *) {
PyObject *&dict = *_PyObject_GetDictPtr(self);
if (!dict)
dict = PyDict_New();
Py_XINCREF(dict);
return dict;
}
/// dynamic_attr: Support for `instance.__dict__ = dict()`.
extern "C" inline int pybind11_set_dict(PyObject *self, PyObject *new_dict, void *) {
if (!PyDict_Check(new_dict)) {
PyErr_Format(PyExc_TypeError, "__dict__ must be set to a dictionary, not a '%.200s'",
Py_TYPE(new_dict)->tp_name);
return -1;
}
PyObject *&dict = *_PyObject_GetDictPtr(self);
Py_INCREF(new_dict);
Py_CLEAR(dict);
dict = new_dict;
return 0;
}
/// dynamic_attr: Allow the garbage collector to traverse the internal instance `__dict__`.
extern "C" inline int pybind11_traverse(PyObject *self, visitproc visit, void *arg) {
PyObject *&dict = *_PyObject_GetDictPtr(self);
Py_VISIT(dict);
return 0;
}
/// dynamic_attr: Allow the GC to clear the dictionary.
extern "C" inline int pybind11_clear(PyObject *self) {
PyObject *&dict = *_PyObject_GetDictPtr(self);
Py_CLEAR(dict);
return 0;
}
/// Give instances of this type a `__dict__` and opt into garbage collection.
inline void enable_dynamic_attributes(PyHeapTypeObject *heap_type) {
auto type = &heap_type->ht_type;
#if defined(PYPY_VERSION)
pybind11_fail(std::string(type->tp_name) + ": dynamic attributes are "
"currently not supported in "
"conjunction with PyPy!");
#endif
type->tp_flags |= Py_TPFLAGS_HAVE_GC;
type->tp_dictoffset = type->tp_basicsize; // place dict at the end
type->tp_basicsize += (ssize_t)sizeof(PyObject *); // and allocate enough space for it
type->tp_traverse = pybind11_traverse;
type->tp_clear = pybind11_clear;
static PyGetSetDef getset[] = {
{const_cast<char*>("__dict__"), pybind11_get_dict, pybind11_set_dict, nullptr, nullptr},
{nullptr, nullptr, nullptr, nullptr, nullptr}
};
type->tp_getset = getset;
}
/// buffer_protocol: Fill in the view as specified by flags.
extern "C" inline int pybind11_getbuffer(PyObject *obj, Py_buffer *view, int flags) {
// Look for a `get_buffer` implementation in this type's info or any bases (following MRO).
type_info *tinfo = nullptr;
for (auto type : reinterpret_borrow<tuple>(Py_TYPE(obj)->tp_mro)) {
tinfo = get_type_info((PyTypeObject *) type.ptr());
if (tinfo && tinfo->get_buffer)
break;
}
if (view == nullptr || obj == nullptr || !tinfo || !tinfo->get_buffer) {
if (view)
view->obj = nullptr;
PyErr_SetString(PyExc_BufferError, "pybind11_getbuffer(): Internal error");
return -1;
}
std::memset(view, 0, sizeof(Py_buffer));
buffer_info *info = tinfo->get_buffer(obj, tinfo->get_buffer_data);
view->obj = obj;
view->ndim = 1;
view->internal = info;
view->buf = info->ptr;
view->itemsize = info->itemsize;
view->len = view->itemsize;
for (auto s : info->shape)
view->len *= s;
if ((flags & PyBUF_FORMAT) == PyBUF_FORMAT)
view->format = const_cast<char *>(info->format.c_str());
if ((flags & PyBUF_STRIDES) == PyBUF_STRIDES) {
view->ndim = (int) info->ndim;
view->strides = &info->strides[0];
view->shape = &info->shape[0];
}
Py_INCREF(view->obj);
return 0;
}
/// buffer_protocol: Release the resources of the buffer.
extern "C" inline void pybind11_releasebuffer(PyObject *, Py_buffer *view) {
delete (buffer_info *) view->internal;
}
/// Give this type a buffer interface.
inline void enable_buffer_protocol(PyHeapTypeObject *heap_type) {
heap_type->ht_type.tp_as_buffer = &heap_type->as_buffer;
#if PY_MAJOR_VERSION < 3
heap_type->ht_type.tp_flags |= Py_TPFLAGS_HAVE_NEWBUFFER;
#endif
heap_type->as_buffer.bf_getbuffer = pybind11_getbuffer;
heap_type->as_buffer.bf_releasebuffer = pybind11_releasebuffer;
}
/** Create a brand new Python type according to the `type_record` specification.
Return value: New reference. */
inline PyObject* make_new_python_type(const type_record &rec) {
auto name = reinterpret_steal<object>(PYBIND11_FROM_STRING(rec.name));
auto qualname = name;
if (rec.scope && !PyModule_Check(rec.scope.ptr()) && hasattr(rec.scope, "__qualname__")) {
#if PY_MAJOR_VERSION >= 3
qualname = reinterpret_steal<object>(
PyUnicode_FromFormat("%U.%U", rec.scope.attr("__qualname__").ptr(), name.ptr()));
#else
qualname = str(rec.scope.attr("__qualname__").cast<std::string>() + "." + rec.name);
#endif
}
object module;
if (rec.scope) {
if (hasattr(rec.scope, "__module__"))
module = rec.scope.attr("__module__");
else if (hasattr(rec.scope, "__name__"))
module = rec.scope.attr("__name__");
}
auto full_name = c_str(
#if !defined(PYPY_VERSION)
module ? str(module).cast<std::string>() + "." + rec.name :
#endif
rec.name);
char *tp_doc = nullptr;
if (rec.doc && options::show_user_defined_docstrings()) {
/* Allocate memory for docstring (using PyObject_MALLOC, since
Python will free this later on) */
size_t size = strlen(rec.doc) + 1;
tp_doc = (char *) PyObject_MALLOC(size);
memcpy((void *) tp_doc, rec.doc, size);
}
auto &internals = get_internals();
auto bases = tuple(rec.bases);
auto base = (bases.size() == 0) ? internals.instance_base
: bases[0].ptr();
/* Danger zone: from now (and until PyType_Ready), make sure to
issue no Python C API calls which could potentially invoke the
garbage collector (the GC will call type_traverse(), which will in
turn find the newly constructed type in an invalid state) */
auto metaclass = rec.metaclass.ptr() ? (PyTypeObject *) rec.metaclass.ptr()
: internals.default_metaclass;
auto heap_type = (PyHeapTypeObject *) metaclass->tp_alloc(metaclass, 0);
if (!heap_type)
pybind11_fail(std::string(rec.name) + ": Unable to create type object!");
heap_type->ht_name = name.release().ptr();
#ifdef PYBIND11_BUILTIN_QUALNAME
heap_type->ht_qualname = qualname.inc_ref().ptr();
#endif
auto type = &heap_type->ht_type;
type->tp_name = full_name;
type->tp_doc = tp_doc;
type->tp_base = type_incref((PyTypeObject *)base);
type->tp_basicsize = static_cast<ssize_t>(sizeof(instance));
if (bases.size() > 0)
type->tp_bases = bases.release().ptr();
/* Don't inherit base __init__ */
type->tp_init = pybind11_object_init;
/* Supported protocols */
type->tp_as_number = &heap_type->as_number;
type->tp_as_sequence = &heap_type->as_sequence;
type->tp_as_mapping = &heap_type->as_mapping;
/* Flags */
type->tp_flags |= Py_TPFLAGS_DEFAULT | Py_TPFLAGS_BASETYPE | Py_TPFLAGS_HEAPTYPE;
#if PY_MAJOR_VERSION < 3
type->tp_flags |= Py_TPFLAGS_CHECKTYPES;
#endif
if (rec.dynamic_attr)
enable_dynamic_attributes(heap_type);
if (rec.buffer_protocol)
enable_buffer_protocol(heap_type);
if (PyType_Ready(type) < 0)
pybind11_fail(std::string(rec.name) + ": PyType_Ready failed (" + error_string() + ")!");
assert(rec.dynamic_attr ? PyType_HasFeature(type, Py_TPFLAGS_HAVE_GC)
: !PyType_HasFeature(type, Py_TPFLAGS_HAVE_GC));
/* Register type with the parent scope */
if (rec.scope)
setattr(rec.scope, rec.name, (PyObject *) type);
else
Py_INCREF(type); // Keep it alive forever (reference leak)
if (module) // Needed by pydoc
setattr((PyObject *) type, "__module__", module);
PYBIND11_SET_OLDPY_QUALNAME(type, qualname);
return (PyObject *) type;
}
NAMESPACE_END(detail)
NAMESPACE_END(PYBIND11_NAMESPACE)

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mmocr/models/textdet/postprocess/include/pybind11/detail/common.h
View File

@ -1,807 +0,0 @@
/*
pybind11/detail/common.h -- Basic macros
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
#if !defined(NAMESPACE_BEGIN)
# define NAMESPACE_BEGIN(name) namespace name {
#endif
#if !defined(NAMESPACE_END)
# define NAMESPACE_END(name) }
#endif
// Robust support for some features and loading modules compiled against different pybind versions
// requires forcing hidden visibility on pybind code, so we enforce this by setting the attribute on
// the main `pybind11` namespace.
#if !defined(PYBIND11_NAMESPACE)
# ifdef __GNUG__
# define PYBIND11_NAMESPACE pybind11 __attribute__((visibility("hidden")))
# else
# define PYBIND11_NAMESPACE pybind11
# endif
#endif
#if !(defined(_MSC_VER) && __cplusplus == 199711L) && !defined(__INTEL_COMPILER)
# if __cplusplus >= 201402L
# define PYBIND11_CPP14
# if __cplusplus >= 201703L
# define PYBIND11_CPP17
# endif
# endif
#elif defined(_MSC_VER) && __cplusplus == 199711L
// MSVC sets _MSVC_LANG rather than __cplusplus (supposedly until the standard is fully implemented)
// Unless you use the /Zc:__cplusplus flag on Visual Studio 2017 15.7 Preview 3 or newer
# if _MSVC_LANG >= 201402L
# define PYBIND11_CPP14
# if _MSVC_LANG > 201402L && _MSC_VER >= 1910
# define PYBIND11_CPP17
# endif
# endif
#endif
// Compiler version assertions
#if defined(__INTEL_COMPILER)
# if __INTEL_COMPILER < 1700
# error pybind11 requires Intel C++ compiler v17 or newer
# endif
#elif defined(__clang__) && !defined(__apple_build_version__)
# if __clang_major__ < 3 || (__clang_major__ == 3 && __clang_minor__ < 3)
# error pybind11 requires clang 3.3 or newer
# endif
#elif defined(__clang__)
// Apple changes clang version macros to its Xcode version; the first Xcode release based on
// (upstream) clang 3.3 was Xcode 5:
# if __clang_major__ < 5
# error pybind11 requires Xcode/clang 5.0 or newer
# endif
#elif defined(__GNUG__)
# if __GNUC__ < 4 || (__GNUC__ == 4 && __GNUC_MINOR__ < 8)
# error pybind11 requires gcc 4.8 or newer
# endif
#elif defined(_MSC_VER)
// Pybind hits various compiler bugs in 2015u2 and earlier, and also makes use of some stl features
// (e.g. std::negation) added in 2015u3:
# if _MSC_FULL_VER < 190024210
# error pybind11 requires MSVC 2015 update 3 or newer
# endif
#endif
#if !defined(PYBIND11_EXPORT)
# if defined(WIN32) || defined(_WIN32)
# define PYBIND11_EXPORT __declspec(dllexport)
# else
# define PYBIND11_EXPORT __attribute__ ((visibility("default")))
# endif
#endif
#if defined(_MSC_VER)
# define PYBIND11_NOINLINE __declspec(noinline)
#else
# define PYBIND11_NOINLINE __attribute__ ((noinline))
#endif
#if defined(PYBIND11_CPP14)
# define PYBIND11_DEPRECATED(reason) [[deprecated(reason)]]
#else
# define PYBIND11_DEPRECATED(reason) __attribute__((deprecated(reason)))
#endif
#define PYBIND11_VERSION_MAJOR 2
#define PYBIND11_VERSION_MINOR 3
#define PYBIND11_VERSION_PATCH dev0
/// Include Python header, disable linking to pythonX_d.lib on Windows in debug mode
#if defined(_MSC_VER)
# if (PY_MAJOR_VERSION == 3 && PY_MINOR_VERSION < 4)
# define HAVE_ROUND 1
# endif
# pragma warning(push)
# pragma warning(disable: 4510 4610 4512 4005)
# if defined(_DEBUG)
# define PYBIND11_DEBUG_MARKER
# undef _DEBUG
# endif
#endif
#include <Python.h>
#include <frameobject.h>
#include <pythread.h>
#if defined(_WIN32) && (defined(min) || defined(max))
# error Macro clash with min and max -- define NOMINMAX when compiling your program on Windows
#endif
#if defined(isalnum)
# undef isalnum
# undef isalpha
# undef islower
# undef isspace
# undef isupper
# undef tolower
# undef toupper
#endif
#if defined(_MSC_VER)
# if defined(PYBIND11_DEBUG_MARKER)
# define _DEBUG
# undef PYBIND11_DEBUG_MARKER
# endif
# pragma warning(pop)
#endif
#include <cstddef>
#include <cstring>
#include <forward_list>
#include <vector>
#include <string>
#include <stdexcept>
#include <unordered_set>
#include <unordered_map>
#include <memory>
#include <typeindex>
#include <type_traits>
#if PY_MAJOR_VERSION >= 3 /// Compatibility macros for various Python versions
#define PYBIND11_INSTANCE_METHOD_NEW(ptr, class_) PyInstanceMethod_New(ptr)
#define PYBIND11_INSTANCE_METHOD_CHECK PyInstanceMethod_Check
#define PYBIND11_INSTANCE_METHOD_GET_FUNCTION PyInstanceMethod_GET_FUNCTION
#define PYBIND11_BYTES_CHECK PyBytes_Check
#define PYBIND11_BYTES_FROM_STRING PyBytes_FromString
#define PYBIND11_BYTES_FROM_STRING_AND_SIZE PyBytes_FromStringAndSize
#define PYBIND11_BYTES_AS_STRING_AND_SIZE PyBytes_AsStringAndSize
#define PYBIND11_BYTES_AS_STRING PyBytes_AsString
#define PYBIND11_BYTES_SIZE PyBytes_Size
#define PYBIND11_LONG_CHECK(o) PyLong_Check(o)
#define PYBIND11_LONG_AS_LONGLONG(o) PyLong_AsLongLong(o)
#define PYBIND11_LONG_FROM_SIGNED(o) PyLong_FromSsize_t((ssize_t) o)
#define PYBIND11_LONG_FROM_UNSIGNED(o) PyLong_FromSize_t((size_t) o)
#define PYBIND11_BYTES_NAME "bytes"
#define PYBIND11_STRING_NAME "str"
#define PYBIND11_SLICE_OBJECT PyObject
#define PYBIND11_FROM_STRING PyUnicode_FromString
#define PYBIND11_STR_TYPE ::pybind11::str
#define PYBIND11_BOOL_ATTR "__bool__"
#define PYBIND11_NB_BOOL(ptr) ((ptr)->nb_bool)
#define PYBIND11_PLUGIN_IMPL(name) \
extern "C" PYBIND11_EXPORT PyObject *PyInit_##name()
#else
#define PYBIND11_INSTANCE_METHOD_NEW(ptr, class_) PyMethod_New(ptr, nullptr, class_)
#define PYBIND11_INSTANCE_METHOD_CHECK PyMethod_Check
#define PYBIND11_INSTANCE_METHOD_GET_FUNCTION PyMethod_GET_FUNCTION
#define PYBIND11_BYTES_CHECK PyString_Check
#define PYBIND11_BYTES_FROM_STRING PyString_FromString
#define PYBIND11_BYTES_FROM_STRING_AND_SIZE PyString_FromStringAndSize
#define PYBIND11_BYTES_AS_STRING_AND_SIZE PyString_AsStringAndSize
#define PYBIND11_BYTES_AS_STRING PyString_AsString
#define PYBIND11_BYTES_SIZE PyString_Size
#define PYBIND11_LONG_CHECK(o) (PyInt_Check(o) || PyLong_Check(o))
#define PYBIND11_LONG_AS_LONGLONG(o) (PyInt_Check(o) ? (long long) PyLong_AsLong(o) : PyLong_AsLongLong(o))
#define PYBIND11_LONG_FROM_SIGNED(o) PyInt_FromSsize_t((ssize_t) o) // Returns long if needed.
#define PYBIND11_LONG_FROM_UNSIGNED(o) PyInt_FromSize_t((size_t) o) // Returns long if needed.
#define PYBIND11_BYTES_NAME "str"
#define PYBIND11_STRING_NAME "unicode"
#define PYBIND11_SLICE_OBJECT PySliceObject
#define PYBIND11_FROM_STRING PyString_FromString
#define PYBIND11_STR_TYPE ::pybind11::bytes
#define PYBIND11_BOOL_ATTR "__nonzero__"
#define PYBIND11_NB_BOOL(ptr) ((ptr)->nb_nonzero)
#define PYBIND11_PLUGIN_IMPL(name) \
static PyObject *pybind11_init_wrapper(); \
extern "C" PYBIND11_EXPORT void init##name() { \
(void)pybind11_init_wrapper(); \
} \
PyObject *pybind11_init_wrapper()
#endif
#if PY_VERSION_HEX >= 0x03050000 && PY_VERSION_HEX < 0x03050200
extern "C" {
struct _Py_atomic_address { void *value; };
PyAPI_DATA(_Py_atomic_address) _PyThreadState_Current;
}
#endif
#define PYBIND11_TRY_NEXT_OVERLOAD ((PyObject *) 1) // special failure return code
#define PYBIND11_STRINGIFY(x) #x
#define PYBIND11_TOSTRING(x) PYBIND11_STRINGIFY(x)
#define PYBIND11_CONCAT(first, second) first##second
#define PYBIND11_CHECK_PYTHON_VERSION \
{ \
const char *compiled_ver = PYBIND11_TOSTRING(PY_MAJOR_VERSION) \
"." PYBIND11_TOSTRING(PY_MINOR_VERSION); \
const char *runtime_ver = Py_GetVersion(); \
size_t len = std::strlen(compiled_ver); \
if (std::strncmp(runtime_ver, compiled_ver, len) != 0 \
|| (runtime_ver[len] >= '0' && runtime_ver[len] <= '9')) { \
PyErr_Format(PyExc_ImportError, \
"Python version mismatch: module was compiled for Python %s, " \
"but the interpreter version is incompatible: %s.", \
compiled_ver, runtime_ver); \
return nullptr; \
} \
}
#define PYBIND11_CATCH_INIT_EXCEPTIONS \
catch (pybind11::error_already_set &e) { \
PyErr_SetString(PyExc_ImportError, e.what()); \
return nullptr; \
} catch (const std::exception &e) { \
PyErr_SetString(PyExc_ImportError, e.what()); \
return nullptr; \
} \
/** \rst
***Deprecated in favor of PYBIND11_MODULE***
This macro creates the entry point that will be invoked when the Python interpreter
imports a plugin library. Please create a `module` in the function body and return
the pointer to its underlying Python object at the end.
.. code-block:: cpp
PYBIND11_PLUGIN(example) {
pybind11::module m("example", "pybind11 example plugin");
/// Set up bindings here
return m.ptr();
}
\endrst */
#define PYBIND11_PLUGIN(name) \
PYBIND11_DEPRECATED("PYBIND11_PLUGIN is deprecated, use PYBIND11_MODULE") \
static PyObject *pybind11_init(); \
PYBIND11_PLUGIN_IMPL(name) { \
PYBIND11_CHECK_PYTHON_VERSION \
try { \
return pybind11_init(); \
} PYBIND11_CATCH_INIT_EXCEPTIONS \
} \
PyObject *pybind11_init()
/** \rst
This macro creates the entry point that will be invoked when the Python interpreter
imports an extension module. The module name is given as the fist argument and it
should not be in quotes. The second macro argument defines a variable of type
`py::module` which can be used to initialize the module.
.. code-block:: cpp
PYBIND11_MODULE(example, m) {
m.doc() = "pybind11 example module";
// Add bindings here
m.def("foo", []() {
return "Hello, World!";
});
}
\endrst */
#define PYBIND11_MODULE(name, variable) \
static void PYBIND11_CONCAT(pybind11_init_, name)(pybind11::module &); \
PYBIND11_PLUGIN_IMPL(name) { \
PYBIND11_CHECK_PYTHON_VERSION \
auto m = pybind11::module(PYBIND11_TOSTRING(name)); \
try { \
PYBIND11_CONCAT(pybind11_init_, name)(m); \
return m.ptr(); \
} PYBIND11_CATCH_INIT_EXCEPTIONS \
} \
void PYBIND11_CONCAT(pybind11_init_, name)(pybind11::module &variable)
NAMESPACE_BEGIN(PYBIND11_NAMESPACE)
using ssize_t = Py_ssize_t;
using size_t = std::size_t;
/// Approach used to cast a previously unknown C++ instance into a Python object
enum class return_value_policy : uint8_t {
/** This is the default return value policy, which falls back to the policy
return_value_policy::take_ownership when the return value is a pointer.
Otherwise, it uses return_value::move or return_value::copy for rvalue
and lvalue references, respectively. See below for a description of what
all of these different policies do. */
automatic = 0,
/** As above, but use policy return_value_policy::reference when the return
value is a pointer. This is the default conversion policy for function
arguments when calling Python functions manually from C++ code (i.e. via
handle::operator()). You probably won't need to use this. */
automatic_reference,
/** Reference an existing object (i.e. do not create a new copy) and take
ownership. Python will call the destructor and delete operator when the
object’s reference count reaches zero. Undefined behavior ensues when
the C++ side does the same.. */
take_ownership,
/** Create a new copy of the returned object, which will be owned by
Python. This policy is comparably safe because the lifetimes of the two
instances are decoupled. */
copy,
/** Use std::move to move the return value contents into a new instance
that will be owned by Python. This policy is comparably safe because the
lifetimes of the two instances (move source and destination) are
decoupled. */
move,
/** Reference an existing object, but do not take ownership. The C++ side
is responsible for managing the object’s lifetime and deallocating it
when it is no longer used. Warning: undefined behavior will ensue when
the C++ side deletes an object that is still referenced and used by
Python. */
reference,
/** This policy only applies to methods and properties. It references the
object without taking ownership similar to the above
return_value_policy::reference policy. In contrast to that policy, the
function or property’s implicit this argument (called the parent) is
considered to be the the owner of the return value (the child).
pybind11 then couples the lifetime of the parent to the child via a
reference relationship that ensures that the parent cannot be garbage
collected while Python is still using the child. More advanced
variations of this scheme are also possible using combinations of
return_value_policy::reference and the keep_alive call policy */
reference_internal
};
NAMESPACE_BEGIN(detail)
inline static constexpr int log2(size_t n, int k = 0) { return (n <= 1) ? k : log2(n >> 1, k + 1); }
// Returns the size as a multiple of sizeof(void *), rounded up.
inline static constexpr size_t size_in_ptrs(size_t s) { return 1 + ((s - 1) >> log2(sizeof(void *))); }
/**
* The space to allocate for simple layout instance holders (see below) in multiple of the size of
* a pointer (e.g. 2 means 16 bytes on 64-bit architectures). The default is the minimum required
* to holder either a std::unique_ptr or std::shared_ptr (which is almost always
* sizeof(std::shared_ptr<T>)).
*/
constexpr size_t instance_simple_holder_in_ptrs() {
static_assert(sizeof(std::shared_ptr<int>) >= sizeof(std::unique_ptr<int>),
"pybind assumes std::shared_ptrs are at least as big as std::unique_ptrs");
return size_in_ptrs(sizeof(std::shared_ptr<int>));
}
// Forward declarations
struct type_info;
struct value_and_holder;
struct nonsimple_values_and_holders {
void **values_and_holders;
uint8_t *status;
};
/// The 'instance' type which needs to be standard layout (need to be able to use 'offsetof')
struct instance {
PyObject_HEAD
/// Storage for pointers and holder; see simple_layout, below, for a description
union {
void *simple_value_holder[1 + instance_simple_holder_in_ptrs()];
nonsimple_values_and_holders nonsimple;
};
/// Weak references
PyObject *weakrefs;
/// If true, the pointer is owned which means we're free to manage it with a holder.
bool owned : 1;
/**
* An instance has two possible value/holder layouts.
*
* Simple layout (when this flag is true), means the `simple_value_holder` is set with a pointer
* and the holder object governing that pointer, i.e. [val1*][holder]. This layout is applied
* whenever there is no python-side multiple inheritance of bound C++ types *and* the type's
* holder will fit in the default space (which is large enough to hold either a std::unique_ptr
* or std::shared_ptr).
*
* Non-simple layout applies when using custom holders that require more space than `shared_ptr`
* (which is typically the size of two pointers), or when multiple inheritance is used on the
* python side. Non-simple layout allocates the required amount of memory to have multiple
* bound C++ classes as parents. Under this layout, `nonsimple.values_and_holders` is set to a
* pointer to allocated space of the required space to hold a sequence of value pointers and
* holders followed `status`, a set of bit flags (1 byte each), i.e.
* [val1*][holder1][val2*][holder2]...[bb...] where each [block] is rounded up to a multiple of
* `sizeof(void *)`. `nonsimple.status` is, for convenience, a pointer to the
* beginning of the [bb...] block (but not independently allocated).
*
* Status bits indicate whether the associated holder is constructed (&
* status_holder_constructed) and whether the value pointer is registered (&
* status_instance_registered) in `registered_instances`.
*/
bool simple_layout : 1;
/// For simple layout, tracks whether the holder has been constructed
bool simple_holder_constructed : 1;
/// For simple layout, tracks whether the instance is registered in `registered_instances`
bool simple_instance_registered : 1;
/// If true, get_internals().patients has an entry for this object
bool has_patients : 1;
/// Initializes all of the above type/values/holders data (but not the instance values themselves)
void allocate_layout();
/// Destroys/deallocates all of the above
void deallocate_layout();
/// Returns the value_and_holder wrapper for the given type (or the first, if `find_type`
/// omitted). Returns a default-constructed (with `.inst = nullptr`) object on failure if
/// `throw_if_missing` is false.
value_and_holder get_value_and_holder(const type_info *find_type = nullptr, bool throw_if_missing = true);
/// Bit values for the non-simple status flags
static constexpr uint8_t status_holder_constructed = 1;
static constexpr uint8_t status_instance_registered = 2;
};
static_assert(std::is_standard_layout<instance>::value, "Internal error: `pybind11::detail::instance` is not standard layout!");
/// from __cpp_future__ import (convenient aliases from C++14/17)
#if defined(PYBIND11_CPP14) && (!defined(_MSC_VER) || _MSC_VER >= 1910)
using std::enable_if_t;
using std::conditional_t;
using std::remove_cv_t;
using std::remove_reference_t;
#else
template <bool B, typename T = void> using enable_if_t = typename std::enable_if<B, T>::type;
template <bool B, typename T, typename F> using conditional_t = typename std::conditional<B, T, F>::type;
template <typename T> using remove_cv_t = typename std::remove_cv<T>::type;
template <typename T> using remove_reference_t = typename std::remove_reference<T>::type;
#endif
/// Index sequences
#if defined(PYBIND11_CPP14)
using std::index_sequence;
using std::make_index_sequence;
#else
template<size_t ...> struct index_sequence { };
template<size_t N, size_t ...S> struct make_index_sequence_impl : make_index_sequence_impl <N - 1, N - 1, S...> { };
template<size_t ...S> struct make_index_sequence_impl <0, S...> { typedef index_sequence<S...> type; };
template<size_t N> using make_index_sequence = typename make_index_sequence_impl<N>::type;
#endif
/// Make an index sequence of the indices of true arguments
template <typename ISeq, size_t, bool...> struct select_indices_impl { using type = ISeq; };
template <size_t... IPrev, size_t I, bool B, bool... Bs> struct select_indices_impl<index_sequence<IPrev...>, I, B, Bs...>
: select_indices_impl<conditional_t<B, index_sequence<IPrev..., I>, index_sequence<IPrev...>>, I + 1, Bs...> {};
template <bool... Bs> using select_indices = typename select_indices_impl<index_sequence<>, 0, Bs...>::type;
/// Backports of std::bool_constant and std::negation to accommodate older compilers
template <bool B> using bool_constant = std::integral_constant<bool, B>;
template <typename T> struct negation : bool_constant<!T::value> { };
template <typename...> struct void_t_impl { using type = void; };
template <typename... Ts> using void_t = typename void_t_impl<Ts...>::type;
/// Compile-time all/any/none of that check the boolean value of all template types
#if defined(__cpp_fold_expressions) && !(defined(_MSC_VER) && (_MSC_VER < 1916))
template <class... Ts> using all_of = bool_constant<(Ts::value && ...)>;
template <class... Ts> using any_of = bool_constant<(Ts::value || ...)>;
#elif !defined(_MSC_VER)
template <bool...> struct bools {};
template <class... Ts> using all_of = std::is_same<
bools<Ts::value..., true>,
bools<true, Ts::value...>>;
template <class... Ts> using any_of = negation<all_of<negation<Ts>...>>;
#else
// MSVC has trouble with the above, but supports std::conjunction, which we can use instead (albeit
// at a slight loss of compilation efficiency).
template <class... Ts> using all_of = std::conjunction<Ts...>;
template <class... Ts> using any_of = std::disjunction<Ts...>;
#endif
template <class... Ts> using none_of = negation<any_of<Ts...>>;
template <class T, template<class> class... Predicates> using satisfies_all_of = all_of<Predicates<T>...>;
template <class T, template<class> class... Predicates> using satisfies_any_of = any_of<Predicates<T>...>;
template <class T, template<class> class... Predicates> using satisfies_none_of = none_of<Predicates<T>...>;
/// Strip the class from a method type
template <typename T> struct remove_class { };
template <typename C, typename R, typename... A> struct remove_class<R (C::*)(A...)> { typedef R type(A...); };
template <typename C, typename R, typename... A> struct remove_class<R (C::*)(A...) const> { typedef R type(A...); };
/// Helper template to strip away type modifiers
template <typename T> struct intrinsic_type { typedef T type; };
template <typename T> struct intrinsic_type<const T> { typedef typename intrinsic_type<T>::type type; };
template <typename T> struct intrinsic_type<T*> { typedef typename intrinsic_type<T>::type type; };
template <typename T> struct intrinsic_type<T&> { typedef typename intrinsic_type<T>::type type; };
template <typename T> struct intrinsic_type<T&&> { typedef typename intrinsic_type<T>::type type; };
template <typename T, size_t N> struct intrinsic_type<const T[N]> { typedef typename intrinsic_type<T>::type type; };
template <typename T, size_t N> struct intrinsic_type<T[N]> { typedef typename intrinsic_type<T>::type type; };
template <typename T> using intrinsic_t = typename intrinsic_type<T>::type;
/// Helper type to replace 'void' in some expressions
struct void_type { };
/// Helper template which holds a list of types
template <typename...> struct type_list { };
/// Compile-time integer sum
#ifdef __cpp_fold_expressions
template <typename... Ts> constexpr size_t constexpr_sum(Ts... ns) { return (0 + ... + size_t{ns}); }
#else
constexpr size_t constexpr_sum() { return 0; }
template <typename T, typename... Ts>
constexpr size_t constexpr_sum(T n, Ts... ns) { return size_t{n} + constexpr_sum(ns...); }
#endif
NAMESPACE_BEGIN(constexpr_impl)
/// Implementation details for constexpr functions
constexpr int first(int i) { return i; }
template <typename T, typename... Ts>
constexpr int first(int i, T v, Ts... vs) { return v ? i : first(i + 1, vs...); }
constexpr int last(int /*i*/, int result) { return result; }
template <typename T, typename... Ts>
constexpr int last(int i, int result, T v, Ts... vs) { return last(i + 1, v ? i : result, vs...); }
NAMESPACE_END(constexpr_impl)
/// Return the index of the first type in Ts which satisfies Predicate<T>. Returns sizeof...(Ts) if
/// none match.
template <template<typename> class Predicate, typename... Ts>
constexpr int constexpr_first() { return constexpr_impl::first(0, Predicate<Ts>::value...); }
/// Return the index of the last type in Ts which satisfies Predicate<T>, or -1 if none match.
template <template<typename> class Predicate, typename... Ts>
constexpr int constexpr_last() { return constexpr_impl::last(0, -1, Predicate<Ts>::value...); }
/// Return the Nth element from the parameter pack
template <size_t N, typename T, typename... Ts>
struct pack_element { using type = typename pack_element<N - 1, Ts...>::type; };
template <typename T, typename... Ts>
struct pack_element<0, T, Ts...> { using type = T; };
/// Return the one and only type which matches the predicate, or Default if none match.
/// If more than one type matches the predicate, fail at compile-time.
template <template<typename> class Predicate, typename Default, typename... Ts>
struct exactly_one {
static constexpr auto found = constexpr_sum(Predicate<Ts>::value...);
static_assert(found <= 1, "Found more than one type matching the predicate");
static constexpr auto index = found ? constexpr_first<Predicate, Ts...>() : 0;
using type = conditional_t<found, typename pack_element<index, Ts...>::type, Default>;
};
template <template<typename> class P, typename Default>
struct exactly_one<P, Default> { using type = Default; };
template <template<typename> class Predicate, typename Default, typename... Ts>
using exactly_one_t = typename exactly_one<Predicate, Default, Ts...>::type;
/// Defer the evaluation of type T until types Us are instantiated
template <typename T, typename... /*Us*/> struct deferred_type { using type = T; };
template <typename T, typename... Us> using deferred_t = typename deferred_type<T, Us...>::type;
/// Like is_base_of, but requires a strict base (i.e. `is_strict_base_of<T, T>::value == false`,
/// unlike `std::is_base_of`)
template <typename Base, typename Derived> using is_strict_base_of = bool_constant<
std::is_base_of<Base, Derived>::value && !std::is_same<Base, Derived>::value>;
/// Like is_base_of, but also requires that the base type is accessible (i.e. that a Derived pointer
/// can be converted to a Base pointer)
template <typename Base, typename Derived> using is_accessible_base_of = bool_constant<
std::is_base_of<Base, Derived>::value && std::is_convertible<Derived *, Base *>::value>;
template <template<typename...> class Base>
struct is_template_base_of_impl {
template <typename... Us> static std::true_type check(Base<Us...> *);
static std::false_type check(...);
};
/// Check if a template is the base of a type. For example:
/// `is_template_base_of<Base, T>` is true if `struct T : Base<U> {}` where U can be anything
template <template<typename...> class Base, typename T>
#if !defined(_MSC_VER)
using is_template_base_of = decltype(is_template_base_of_impl<Base>::check((intrinsic_t<T>*)nullptr));
#else // MSVC2015 has trouble with decltype in template aliases
struct is_template_base_of : decltype(is_template_base_of_impl<Base>::check((intrinsic_t<T>*)nullptr)) { };
#endif
/// Check if T is an instantiation of the template `Class`. For example:
/// `is_instantiation<shared_ptr, T>` is true if `T == shared_ptr<U>` where U can be anything.
template <template<typename...> class Class, typename T>
struct is_instantiation : std::false_type { };
template <template<typename...> class Class, typename... Us>
struct is_instantiation<Class, Class<Us...>> : std::true_type { };
/// Check if T is std::shared_ptr<U> where U can be anything
template <typename T> using is_shared_ptr = is_instantiation<std::shared_ptr, T>;
/// Check if T looks like an input iterator
template <typename T, typename = void> struct is_input_iterator : std::false_type {};
template <typename T>
struct is_input_iterator<T, void_t<decltype(*std::declval<T &>()), decltype(++std::declval<T &>())>>
: std::true_type {};
template <typename T> using is_function_pointer = bool_constant<
std::is_pointer<T>::value && std::is_function<typename std::remove_pointer<T>::type>::value>;
template <typename F> struct strip_function_object {
using type = typename remove_class<decltype(&F::operator())>::type;
};
// Extracts the function signature from a function, function pointer or lambda.
template <typename Function, typename F = remove_reference_t<Function>>
using function_signature_t = conditional_t<
std::is_function<F>::value,
F,
typename conditional_t<
std::is_pointer<F>::value || std::is_member_pointer<F>::value,
std::remove_pointer<F>,
strip_function_object<F>
>::type
>;
/// Returns true if the type looks like a lambda: that is, isn't a function, pointer or member
/// pointer. Note that this can catch all sorts of other things, too; this is intended to be used
/// in a place where passing a lambda makes sense.
template <typename T> using is_lambda = satisfies_none_of<remove_reference_t<T>,
std::is_function, std::is_pointer, std::is_member_pointer>;
/// Ignore that a variable is unused in compiler warnings
inline void ignore_unused(const int *) { }
/// Apply a function over each element of a parameter pack
#ifdef __cpp_fold_expressions
#define PYBIND11_EXPAND_SIDE_EFFECTS(PATTERN) (((PATTERN), void()), ...)
#else
using expand_side_effects = bool[];
#define PYBIND11_EXPAND_SIDE_EFFECTS(PATTERN) pybind11::detail::expand_side_effects{ ((PATTERN), void(), false)..., false }
#endif
NAMESPACE_END(detail)
/// C++ bindings of builtin Python exceptions
class builtin_exception : public std::runtime_error {
public:
using std::runtime_error::runtime_error;
/// Set the error using the Python C API
virtual void set_error() const = 0;
};
#define PYBIND11_RUNTIME_EXCEPTION(name, type) \
class name : public builtin_exception { public: \
using builtin_exception::builtin_exception; \
name() : name("") { } \
void set_error() const override { PyErr_SetString(type, what()); } \
};
PYBIND11_RUNTIME_EXCEPTION(stop_iteration, PyExc_StopIteration)
PYBIND11_RUNTIME_EXCEPTION(index_error, PyExc_IndexError)
PYBIND11_RUNTIME_EXCEPTION(key_error, PyExc_KeyError)
PYBIND11_RUNTIME_EXCEPTION(value_error, PyExc_ValueError)
PYBIND11_RUNTIME_EXCEPTION(type_error, PyExc_TypeError)
PYBIND11_RUNTIME_EXCEPTION(cast_error, PyExc_RuntimeError) /// Thrown when pybind11::cast or handle::call fail due to a type casting error
PYBIND11_RUNTIME_EXCEPTION(reference_cast_error, PyExc_RuntimeError) /// Used internally
[[noreturn]] PYBIND11_NOINLINE inline void pybind11_fail(const char *reason) { throw std::runtime_error(reason); }
[[noreturn]] PYBIND11_NOINLINE inline void pybind11_fail(const std::string &reason) { throw std::runtime_error(reason); }
template <typename T, typename SFINAE = void> struct format_descriptor { };
NAMESPACE_BEGIN(detail)
// Returns the index of the given type in the type char array below, and in the list in numpy.h
// The order here is: bool; 8 ints ((signed,unsigned)x(8,16,32,64)bits); float,double,long double;
// complex float,double,long double. Note that the long double types only participate when long
// double is actually longer than double (it isn't under MSVC).
// NB: not only the string below but also complex.h and numpy.h rely on this order.
template <typename T, typename SFINAE = void> struct is_fmt_numeric { static constexpr bool value = false; };
template <typename T> struct is_fmt_numeric<T, enable_if_t<std::is_arithmetic<T>::value>> {
static constexpr bool value = true;
static constexpr int index = std::is_same<T, bool>::value ? 0 : 1 + (
std::is_integral<T>::value ? detail::log2(sizeof(T))*2 + std::is_unsigned<T>::value : 8 + (
std::is_same<T, double>::value ? 1 : std::is_same<T, long double>::value ? 2 : 0));
};
NAMESPACE_END(detail)
template <typename T> struct format_descriptor<T, detail::enable_if_t<std::is_arithmetic<T>::value>> {
static constexpr const char c = "?bBhHiIqQfdg"[detail::is_fmt_numeric<T>::index];
static constexpr const char value[2] = { c, '\0' };
static std::string format() { return std::string(1, c); }
};
#if !defined(PYBIND11_CPP17)
template <typename T> constexpr const char format_descriptor<
T, detail::enable_if_t<std::is_arithmetic<T>::value>>::value[2];
#endif
/// RAII wrapper that temporarily clears any Python error state
struct error_scope {
PyObject *type, *value, *trace;
error_scope() { PyErr_Fetch(&type, &value, &trace); }
~error_scope() { PyErr_Restore(type, value, trace); }
};
/// Dummy destructor wrapper that can be used to expose classes with a private destructor
struct nodelete { template <typename T> void operator()(T*) { } };
// overload_cast requires variable templates: C++14
#if defined(PYBIND11_CPP14)
#define PYBIND11_OVERLOAD_CAST 1
NAMESPACE_BEGIN(detail)
template <typename... Args>
struct overload_cast_impl {
constexpr overload_cast_impl() {} // MSVC 2015 needs this
template <typename Return>
constexpr auto operator()(Return (*pf)(Args...)) const noexcept
-> decltype(pf) { return pf; }
template <typename Return, typename Class>
constexpr auto operator()(Return (Class::*pmf)(Args...), std::false_type = {}) const noexcept
-> decltype(pmf) { return pmf; }
template <typename Return, typename Class>
constexpr auto operator()(Return (Class::*pmf)(Args...) const, std::true_type) const noexcept
-> decltype(pmf) { return pmf; }
};
NAMESPACE_END(detail)
/// Syntax sugar for resolving overloaded function pointers:
/// - regular: static_cast<Return (Class::*)(Arg0, Arg1, Arg2)>(&Class::func)
/// - sweet: overload_cast<Arg0, Arg1, Arg2>(&Class::func)
template <typename... Args>
static constexpr detail::overload_cast_impl<Args...> overload_cast = {};
// MSVC 2015 only accepts this particular initialization syntax for this variable template.
/// Const member function selector for overload_cast
/// - regular: static_cast<Return (Class::*)(Arg) const>(&Class::func)
/// - sweet: overload_cast<Arg>(&Class::func, const_)
static constexpr auto const_ = std::true_type{};
#else // no overload_cast: providing something that static_assert-fails:
template <typename... Args> struct overload_cast {
static_assert(detail::deferred_t<std::false_type, Args...>::value,
"pybind11::overload_cast<...> requires compiling in C++14 mode");
};
#endif // overload_cast
NAMESPACE_BEGIN(detail)
// Adaptor for converting arbitrary container arguments into a vector; implicitly convertible from
// any standard container (or C-style array) supporting std::begin/std::end, any singleton
// arithmetic type (if T is arithmetic), or explicitly constructible from an iterator pair.
template <typename T>
class any_container {
std::vector<T> v;
public:
any_container() = default;
// Can construct from a pair of iterators
template <typename It, typename = enable_if_t<is_input_iterator<It>::value>>
any_container(It first, It last) : v(first, last) { }
// Implicit conversion constructor from any arbitrary container type with values convertible to T
template <typename Container, typename = enable_if_t<std::is_convertible<decltype(*std::begin(std::declval<const Container &>())), T>::value>>
any_container(const Container &c) : any_container(std::begin(c), std::end(c)) { }
// initializer_list's aren't deducible, so don't get matched by the above template; we need this
// to explicitly allow implicit conversion from one:
template <typename TIn, typename = enable_if_t<std::is_convertible<TIn, T>::value>>
any_container(const std::initializer_list<TIn> &c) : any_container(c.begin(), c.end()) { }
// Avoid copying if given an rvalue vector of the correct type.
any_container(std::vector<T> &&v) : v(std::move(v)) { }
// Moves the vector out of an rvalue any_container
operator std::vector<T> &&() && { return std::move(v); }
// Dereferencing obtains a reference to the underlying vector
std::vector<T> &operator*() { return v; }
const std::vector<T> &operator*() const { return v; }
// -> lets you call methods on the underlying vector
std::vector<T> *operator->() { return &v; }
const std::vector<T> *operator->() const { return &v; }
};
NAMESPACE_END(detail)
NAMESPACE_END(PYBIND11_NAMESPACE)

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/*
pybind11/detail/descr.h: Helper type for concatenating type signatures at compile time
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 "common.h"
NAMESPACE_BEGIN(PYBIND11_NAMESPACE)
NAMESPACE_BEGIN(detail)
#if !defined(_MSC_VER)
# define PYBIND11_DESCR_CONSTEXPR static constexpr
#else
# define PYBIND11_DESCR_CONSTEXPR const
#endif
/* Concatenate type signatures at compile time */
template <size_t N, typename... Ts>
struct descr {
char text[N + 1];
constexpr descr() : text{'\0'} { }
constexpr descr(char const (&s)[N+1]) : descr(s, make_index_sequence<N>()) { }
template <size_t... Is>
constexpr descr(char const (&s)[N+1], index_sequence<Is...>) : text{s[Is]..., '\0'} { }
template <typename... Chars>
constexpr descr(char c, Chars... cs) : text{c, static_cast<char>(cs)..., '\0'} { }
static constexpr std::array<const std::type_info *, sizeof...(Ts) + 1> types() {
return {{&typeid(Ts)..., nullptr}};
}
};
template <size_t N1, size_t N2, typename... Ts1, typename... Ts2, size_t... Is1, size_t... Is2>
constexpr descr<N1 + N2, Ts1..., Ts2...> plus_impl(const descr<N1, Ts1...> &a, const descr<N2, Ts2...> &b,
index_sequence<Is1...>, index_sequence<Is2...>) {
return {a.text[Is1]..., b.text[Is2]...};
}
template <size_t N1, size_t N2, typename... Ts1, typename... Ts2>
constexpr descr<N1 + N2, Ts1..., Ts2...> operator+(const descr<N1, Ts1...> &a, const descr<N2, Ts2...> &b) {
return plus_impl(a, b, make_index_sequence<N1>(), make_index_sequence<N2>());
}
template <size_t N>
constexpr descr<N - 1> _(char const(&text)[N]) { return descr<N - 1>(text); }
constexpr descr<0> _(char const(&)[1]) { return {}; }
template <size_t Rem, size_t... Digits> struct int_to_str : int_to_str<Rem/10, Rem%10, Digits...> { };
template <size_t...Digits> struct int_to_str<0, Digits...> {
static constexpr auto digits = descr<sizeof...(Digits)>(('0' + Digits)...);
};
// Ternary description (like std::conditional)
template <bool B, size_t N1, size_t N2>
constexpr enable_if_t<B, descr<N1 - 1>> _(char const(&text1)[N1], char const(&)[N2]) {
return _(text1);
}
template <bool B, size_t N1, size_t N2>
constexpr enable_if_t<!B, descr<N2 - 1>> _(char const(&)[N1], char const(&text2)[N2]) {
return _(text2);
}
template <bool B, typename T1, typename T2>
constexpr enable_if_t<B, T1> _(const T1 &d, const T2 &) { return d; }
template <bool B, typename T1, typename T2>
constexpr enable_if_t<!B, T2> _(const T1 &, const T2 &d) { return d; }
template <size_t Size> auto constexpr _() -> decltype(int_to_str<Size / 10, Size % 10>::digits) {
return int_to_str<Size / 10, Size % 10>::digits;
}
template <typename Type> constexpr descr<1, Type> _() { return {'%'}; }
constexpr descr<0> concat() { return {}; }
template <size_t N, typename... Ts>
constexpr descr<N, Ts...> concat(const descr<N, Ts...> &descr) { return descr; }
template <size_t N, typename... Ts, typename... Args>
constexpr auto concat(const descr<N, Ts...> &d, const Args &...args)
-> decltype(std::declval<descr<N + 2, Ts...>>() + concat(args...)) {
return d + _(", ") + concat(args...);
}
template <size_t N, typename... Ts>
constexpr descr<N + 2, Ts...> type_descr(const descr<N, Ts...> &descr) {
return _("{") + descr + _("}");
}
NAMESPACE_END(detail)
NAMESPACE_END(PYBIND11_NAMESPACE)

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/*
pybind11/detail/init.h: init factory function implementation and support code.
Copyright (c) 2017 Jason Rhinelander <jason@imaginary.ca>
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 "class.h"
NAMESPACE_BEGIN(PYBIND11_NAMESPACE)
NAMESPACE_BEGIN(detail)
template <>
class type_caster<value_and_holder> {
public:
bool load(handle h, bool) {
value = reinterpret_cast<value_and_holder *>(h.ptr());
return true;
}
template <typename> using cast_op_type = value_and_holder &;
operator value_and_holder &() { return *value; }
static constexpr auto name = _<value_and_holder>();
private:
value_and_holder *value = nullptr;
};
NAMESPACE_BEGIN(initimpl)
inline void no_nullptr(void *ptr) {
if (!ptr) throw type_error("pybind11::init(): factory function returned nullptr");
}
// Implementing functions for all forms of py::init<...> and py::init(...)
template <typename Class> using Cpp = typename Class::type;
template <typename Class> using Alias = typename Class::type_alias;
template <typename Class> using Holder = typename Class::holder_type;
template <typename Class> using is_alias_constructible = std::is_constructible<Alias<Class>, Cpp<Class> &&>;
// Takes a Cpp pointer and returns true if it actually is a polymorphic Alias instance.
template <typename Class, enable_if_t<Class::has_alias, int> = 0>
bool is_alias(Cpp<Class> *ptr) {
return dynamic_cast<Alias<Class> *>(ptr) != nullptr;
}
// Failing fallback version of the above for a no-alias class (always returns false)
template <typename /*Class*/>
constexpr bool is_alias(void *) { return false; }
// Constructs and returns a new object; if the given arguments don't map to a constructor, we fall
// back to brace aggregate initiailization so that for aggregate initialization can be used with
// py::init, e.g. `py::init<int, int>` to initialize a `struct T { int a; int b; }`. For
// non-aggregate types, we need to use an ordinary T(...) constructor (invoking as `T{...}` usually
// works, but will not do the expected thing when `T` has an `initializer_list<T>` constructor).
template <typename Class, typename... Args, detail::enable_if_t<std::is_constructible<Class, Args...>::value, int> = 0>
inline Class *construct_or_initialize(Args &&...args) { return new Class(std::forward<Args>(args)...); }
template <typename Class, typename... Args, detail::enable_if_t<!std::is_constructible<Class, Args...>::value, int> = 0>
inline Class *construct_or_initialize(Args &&...args) { return new Class{std::forward<Args>(args)...}; }
// Attempts to constructs an alias using a `Alias(Cpp &&)` constructor. This allows types with
// an alias to provide only a single Cpp factory function as long as the Alias can be
// constructed from an rvalue reference of the base Cpp type. This means that Alias classes
// can, when appropriate, simply define a `Alias(Cpp &&)` constructor rather than needing to
// inherit all the base class constructors.
template <typename Class>
void construct_alias_from_cpp(std::true_type /*is_alias_constructible*/,
value_and_holder &v_h, Cpp<Class> &&base) {
v_h.value_ptr() = new Alias<Class>(std::move(base));
}
template <typename Class>
[[noreturn]] void construct_alias_from_cpp(std::false_type /*!is_alias_constructible*/,
value_and_holder &, Cpp<Class> &&) {
throw type_error("pybind11::init(): unable to convert returned instance to required "
"alias class: no `Alias<Class>(Class &&)` constructor available");
}
// Error-generating fallback for factories that don't match one of the below construction
// mechanisms.
template <typename Class>
void construct(...) {
static_assert(!std::is_same<Class, Class>::value /* always false */,
"pybind11::init(): init function must return a compatible pointer, "
"holder, or value");
}
// Pointer return v1: the factory function returns a class pointer for a registered class.
// If we don't need an alias (because this class doesn't have one, or because the final type is
// inherited on the Python side) we can simply take over ownership. Otherwise we need to try to
// construct an Alias from the returned base instance.
template <typename Class>
void construct(value_and_holder &v_h, Cpp<Class> *ptr, bool need_alias) {
no_nullptr(ptr);
if (Class::has_alias && need_alias && !is_alias<Class>(ptr)) {
// We're going to try to construct an alias by moving the cpp type. Whether or not
// that succeeds, we still need to destroy the original cpp pointer (either the
// moved away leftover, if the alias construction works, or the value itself if we
// throw an error), but we can't just call `delete ptr`: it might have a special
// deleter, or might be shared_from_this. So we construct a holder around it as if
// it was a normal instance, then steal the holder away into a local variable; thus
// the holder and destruction happens when we leave the C++ scope, and the holder
// class gets to handle the destruction however it likes.
v_h.value_ptr() = ptr;
v_h.set_instance_registered(true); // To prevent init_instance from registering it
v_h.type->init_instance(v_h.inst, nullptr); // Set up the holder
Holder<Class> temp_holder(std::move(v_h.holder<Holder<Class>>())); // Steal the holder
v_h.type->dealloc(v_h); // Destroys the moved-out holder remains, resets value ptr to null
v_h.set_instance_registered(false);
construct_alias_from_cpp<Class>(is_alias_constructible<Class>{}, v_h, std::move(*ptr));
} else {
// Otherwise the type isn't inherited, so we don't need an Alias
v_h.value_ptr() = ptr;
}
}
// Pointer return v2: a factory that always returns an alias instance ptr. We simply take over
// ownership of the pointer.
template <typename Class, enable_if_t<Class::has_alias, int> = 0>
void construct(value_and_holder &v_h, Alias<Class> *alias_ptr, bool) {
no_nullptr(alias_ptr);
v_h.value_ptr() = static_cast<Cpp<Class> *>(alias_ptr);
}
// Holder return: copy its pointer, and move or copy the returned holder into the new instance's
// holder. This also handles types like std::shared_ptr<T> and std::unique_ptr<T> where T is a
// derived type (through those holder's implicit conversion from derived class holder constructors).
template <typename Class>
void construct(value_and_holder &v_h, Holder<Class> holder, bool need_alias) {
auto *ptr = holder_helper<Holder<Class>>::get(holder);
// If we need an alias, check that the held pointer is actually an alias instance
if (Class::has_alias && need_alias && !is_alias<Class>(ptr))
throw type_error("pybind11::init(): construction failed: returned holder-wrapped instance "
"is not an alias instance");
v_h.value_ptr() = ptr;
v_h.type->init_instance(v_h.inst, &holder);
}
// return-by-value version 1: returning a cpp class by value. If the class has an alias and an
// alias is required the alias must have an `Alias(Cpp &&)` constructor so that we can construct
// the alias from the base when needed (i.e. because of Python-side inheritance). When we don't
// need it, we simply move-construct the cpp value into a new instance.
template <typename Class>
void construct(value_and_holder &v_h, Cpp<Class> &&result, bool need_alias) {
static_assert(std::is_move_constructible<Cpp<Class>>::value,
"pybind11::init() return-by-value factory function requires a movable class");
if (Class::has_alias && need_alias)
construct_alias_from_cpp<Class>(is_alias_constructible<Class>{}, v_h, std::move(result));
else
v_h.value_ptr() = new Cpp<Class>(std::move(result));
}
// return-by-value version 2: returning a value of the alias type itself. We move-construct an
// Alias instance (even if no the python-side inheritance is involved). The is intended for
// cases where Alias initialization is always desired.
template <typename Class>
void construct(value_and_holder &v_h, Alias<Class> &&result, bool) {
static_assert(std::is_move_constructible<Alias<Class>>::value,
"pybind11::init() return-by-alias-value factory function requires a movable alias class");
v_h.value_ptr() = new Alias<Class>(std::move(result));
}
// Implementing class for py::init<...>()
template <typename... Args>
struct constructor {
template <typename Class, typename... Extra, enable_if_t<!Class::has_alias, int> = 0>
static void execute(Class &cl, const Extra&... extra) {
cl.def("__init__", [](value_and_holder &v_h, Args... args) {
v_h.value_ptr() = construct_or_initialize<Cpp<Class>>(std::forward<Args>(args)...);
}, is_new_style_constructor(), extra...);
}
template <typename Class, typename... Extra,
enable_if_t<Class::has_alias &&
std::is_constructible<Cpp<Class>, Args...>::value, int> = 0>
static void execute(Class &cl, const Extra&... extra) {
cl.def("__init__", [](value_and_holder &v_h, Args... args) {
if (Py_TYPE(v_h.inst) == v_h.type->type)
v_h.value_ptr() = construct_or_initialize<Cpp<Class>>(std::forward<Args>(args)...);
else
v_h.value_ptr() = construct_or_initialize<Alias<Class>>(std::forward<Args>(args)...);
}, is_new_style_constructor(), extra...);
}
template <typename Class, typename... Extra,
enable_if_t<Class::has_alias &&
!std::is_constructible<Cpp<Class>, Args...>::value, int> = 0>
static void execute(Class &cl, const Extra&... extra) {
cl.def("__init__", [](value_and_holder &v_h, Args... args) {
v_h.value_ptr() = construct_or_initialize<Alias<Class>>(std::forward<Args>(args)...);
}, is_new_style_constructor(), extra...);
}
};
// Implementing class for py::init_alias<...>()
template <typename... Args> struct alias_constructor {
template <typename Class, typename... Extra,
enable_if_t<Class::has_alias && std::is_constructible<Alias<Class>, Args...>::value, int> = 0>
static void execute(Class &cl, const Extra&... extra) {
cl.def("__init__", [](value_and_holder &v_h, Args... args) {
v_h.value_ptr() = construct_or_initialize<Alias<Class>>(std::forward<Args>(args)...);
}, is_new_style_constructor(), extra...);
}
};
// Implementation class for py::init(Func) and py::init(Func, AliasFunc)
template <typename CFunc, typename AFunc = void_type (*)(),
typename = function_signature_t<CFunc>, typename = function_signature_t<AFunc>>
struct factory;
// Specialization for py::init(Func)
template <typename Func, typename Return, typename... Args>
struct factory<Func, void_type (*)(), Return(Args...)> {
remove_reference_t<Func> class_factory;
factory(Func &&f) : class_factory(std::forward<Func>(f)) { }
// The given class either has no alias or has no separate alias factory;
// this always constructs the class itself. If the class is registered with an alias
// type and an alias instance is needed (i.e. because the final type is a Python class
// inheriting from the C++ type) the returned value needs to either already be an alias
// instance, or the alias needs to be constructible from a `Class &&` argument.
template <typename Class, typename... Extra>
void execute(Class &cl, const Extra &...extra) && {
#if defined(PYBIND11_CPP14)
cl.def("__init__", [func = std::move(class_factory)]
#else
auto &func = class_factory;
cl.def("__init__", [func]
#endif
(value_and_holder &v_h, Args... args) {
construct<Class>(v_h, func(std::forward<Args>(args)...),
Py_TYPE(v_h.inst) != v_h.type->type);
}, is_new_style_constructor(), extra...);
}
};
// Specialization for py::init(Func, AliasFunc)
template <typename CFunc, typename AFunc,
typename CReturn, typename... CArgs, typename AReturn, typename... AArgs>
struct factory<CFunc, AFunc, CReturn(CArgs...), AReturn(AArgs...)> {
static_assert(sizeof...(CArgs) == sizeof...(AArgs),
"pybind11::init(class_factory, alias_factory): class and alias factories "
"must have identical argument signatures");
static_assert(all_of<std::is_same<CArgs, AArgs>...>::value,
"pybind11::init(class_factory, alias_factory): class and alias factories "
"must have identical argument signatures");
remove_reference_t<CFunc> class_factory;
remove_reference_t<AFunc> alias_factory;
factory(CFunc &&c, AFunc &&a)
: class_factory(std::forward<CFunc>(c)), alias_factory(std::forward<AFunc>(a)) { }
// The class factory is called when the `self` type passed to `__init__` is the direct
// class (i.e. not inherited), the alias factory when `self` is a Python-side subtype.
template <typename Class, typename... Extra>
void execute(Class &cl, const Extra&... extra) && {
static_assert(Class::has_alias, "The two-argument version of `py::init()` can "
"only be used if the class has an alias");
#if defined(PYBIND11_CPP14)
cl.def("__init__", [class_func = std::move(class_factory), alias_func = std::move(alias_factory)]
#else
auto &class_func = class_factory;
auto &alias_func = alias_factory;
cl.def("__init__", [class_func, alias_func]
#endif
(value_and_holder &v_h, CArgs... args) {
if (Py_TYPE(v_h.inst) == v_h.type->type)
// If the instance type equals the registered type we don't have inheritance, so
// don't need the alias and can construct using the class function:
construct<Class>(v_h, class_func(std::forward<CArgs>(args)...), false);
else
construct<Class>(v_h, alias_func(std::forward<CArgs>(args)...), true);
}, is_new_style_constructor(), extra...);
}
};
/// Set just the C++ state. Same as `__init__`.
template <typename Class, typename T>
void setstate(value_and_holder &v_h, T &&result, bool need_alias) {
construct<Class>(v_h, std::forward<T>(result), need_alias);
}
/// Set both the C++ and Python states
template <typename Class, typename T, typename O,
enable_if_t<std::is_convertible<O, handle>::value, int> = 0>
void setstate(value_and_holder &v_h, std::pair<T, O> &&result, bool need_alias) {
construct<Class>(v_h, std::move(result.first), need_alias);
setattr((PyObject *) v_h.inst, "__dict__", result.second);
}
/// Implementation for py::pickle(GetState, SetState)
template <typename Get, typename Set,
typename = function_signature_t<Get>, typename = function_signature_t<Set>>
struct pickle_factory;
template <typename Get, typename Set,
typename RetState, typename Self, typename NewInstance, typename ArgState>
struct pickle_factory<Get, Set, RetState(Self), NewInstance(ArgState)> {
static_assert(std::is_same<intrinsic_t<RetState>, intrinsic_t<ArgState>>::value,
"The type returned by `__getstate__` must be the same "
"as the argument accepted by `__setstate__`");
remove_reference_t<Get> get;
remove_reference_t<Set> set;
pickle_factory(Get get, Set set)
: get(std::forward<Get>(get)), set(std::forward<Set>(set)) { }
template <typename Class, typename... Extra>
void execute(Class &cl, const Extra &...extra) && {
cl.def("__getstate__", std::move(get));
#if defined(PYBIND11_CPP14)
cl.def("__setstate__", [func = std::move(set)]
#else
auto &func = set;
cl.def("__setstate__", [func]
#endif
(value_and_holder &v_h, ArgState state) {
setstate<Class>(v_h, func(std::forward<ArgState>(state)),
Py_TYPE(v_h.inst) != v_h.type->type);
}, is_new_style_constructor(), extra...);
}
};
NAMESPACE_END(initimpl)
NAMESPACE_END(detail)
NAMESPACE_END(pybind11)

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/*
pybind11/detail/internals.h: Internal data structure and related functions
Copyright (c) 2017 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 "../pytypes.h"
NAMESPACE_BEGIN(PYBIND11_NAMESPACE)
NAMESPACE_BEGIN(detail)
// Forward declarations
inline PyTypeObject *make_static_property_type();
inline PyTypeObject *make_default_metaclass();
inline PyObject *make_object_base_type(PyTypeObject *metaclass);
// The old Python Thread Local Storage (TLS) API is deprecated in Python 3.7 in favor of the new
// Thread Specific Storage (TSS) API.
#if PY_VERSION_HEX >= 0x03070000
# define PYBIND11_TLS_KEY_INIT(var) Py_tss_t *var = nullptr
# define PYBIND11_TLS_GET_VALUE(key) PyThread_tss_get((key))
# define PYBIND11_TLS_REPLACE_VALUE(key, value) PyThread_tss_set((key), (tstate))
# define PYBIND11_TLS_DELETE_VALUE(key) PyThread_tss_set((key), nullptr)
#else
// Usually an int but a long on Cygwin64 with Python 3.x
# define PYBIND11_TLS_KEY_INIT(var) decltype(PyThread_create_key()) var = 0
# define PYBIND11_TLS_GET_VALUE(key) PyThread_get_key_value((key))
# if PY_MAJOR_VERSION < 3
# define PYBIND11_TLS_DELETE_VALUE(key) \
PyThread_delete_key_value(key)
# define PYBIND11_TLS_REPLACE_VALUE(key, value) \
do { \
PyThread_delete_key_value((key)); \
PyThread_set_key_value((key), (value)); \
} while (false)
# else
# define PYBIND11_TLS_DELETE_VALUE(key) \
PyThread_set_key_value((key), nullptr)
# define PYBIND11_TLS_REPLACE_VALUE(key, value) \
PyThread_set_key_value((key), (value))
# endif
#endif
// Python loads modules by default with dlopen with the RTLD_LOCAL flag; under libc++ and possibly
// other STLs, this means `typeid(A)` from one module won't equal `typeid(A)` from another module
// even when `A` is the same, non-hidden-visibility type (e.g. from a common include). Under
// libstdc++, this doesn't happen: equality and the type_index hash are based on the type name,
// which works. If not under a known-good stl, provide our own name-based hash and equality
// functions that use the type name.
#if defined(__GLIBCXX__)
inline bool same_type(const std::type_info &lhs, const std::type_info &rhs) { return lhs == rhs; }
using type_hash = std::hash<std::type_index>;
using type_equal_to = std::equal_to<std::type_index>;
#else
inline bool same_type(const std::type_info &lhs, const std::type_info &rhs) {
return lhs.name() == rhs.name() || std::strcmp(lhs.name(), rhs.name()) == 0;
}
struct type_hash {
size_t operator()(const std::type_index &t) const {
size_t hash = 5381;
const char *ptr = t.name();
while (auto c = static_cast<unsigned char>(*ptr++))
hash = (hash * 33) ^ c;
return hash;
}
};
struct type_equal_to {
bool operator()(const std::type_index &lhs, const std::type_index &rhs) const {
return lhs.name() == rhs.name() || std::strcmp(lhs.name(), rhs.name()) == 0;
}
};
#endif
template <typename value_type>
using type_map = std::unordered_map<std::type_index, value_type, type_hash, type_equal_to>;
struct overload_hash {
inline size_t operator()(const std::pair<const PyObject *, const char *>& v) const {
size_t value = std::hash<const void *>()(v.first);
value ^= std::hash<const void *>()(v.second) + 0x9e3779b9 + (value<<6) + (value>>2);
return value;
}
};
/// Internal data structure used to track registered instances and types.
/// Whenever binary incompatible changes are made to this structure,
/// `PYBIND11_INTERNALS_VERSION` must be incremented.
struct internals {
type_map<type_info *> registered_types_cpp; // std::type_index -> pybind11's type information
std::unordered_map<PyTypeObject *, std::vector<type_info *>> registered_types_py; // PyTypeObject* -> base type_info(s)
std::unordered_multimap<const void *, instance*> registered_instances; // void * -> instance*
std::unordered_set<std::pair<const PyObject *, const char *>, overload_hash> inactive_overload_cache;
type_map<std::vector<bool (*)(PyObject *, void *&)>> direct_conversions;
std::unordered_map<const PyObject *, std::vector<PyObject *>> patients;
std::forward_list<void (*) (std::exception_ptr)> registered_exception_translators;
std::unordered_map<std::string, void *> shared_data; // Custom data to be shared across extensions
std::vector<PyObject *> loader_patient_stack; // Used by `loader_life_support`
std::forward_list<std::string> static_strings; // Stores the std::strings backing detail::c_str()
PyTypeObject *static_property_type;
PyTypeObject *default_metaclass;
PyObject *instance_base;
#if defined(WITH_THREAD)
PYBIND11_TLS_KEY_INIT(tstate);
PyInterpreterState *istate = nullptr;
#endif
};
/// Additional type information which does not fit into the PyTypeObject.
/// Changes to this struct also require bumping `PYBIND11_INTERNALS_VERSION`.
struct type_info {
PyTypeObject *type;
const std::type_info *cpptype;
size_t type_size, type_align, holder_size_in_ptrs;
void *(*operator_new)(size_t);
void (*init_instance)(instance *, const void *);
void (*dealloc)(value_and_holder &v_h);
std::vector<PyObject *(*)(PyObject *, PyTypeObject *)> implicit_conversions;
std::vector<std::pair<const std::type_info *, void *(*)(void *)>> implicit_casts;
std::vector<bool (*)(PyObject *, void *&)> *direct_conversions;
buffer_info *(*get_buffer)(PyObject *, void *) = nullptr;
void *get_buffer_data = nullptr;
void *(*module_local_load)(PyObject *, const type_info *) = nullptr;
/* A simple type never occurs as a (direct or indirect) parent
* of a class that makes use of multiple inheritance */
bool simple_type : 1;
/* True if there is no multiple inheritance in this type's inheritance tree */
bool simple_ancestors : 1;
/* for base vs derived holder_type checks */
bool default_holder : 1;
/* true if this is a type registered with py::module_local */
bool module_local : 1;
};
/// Tracks the `internals` and `type_info` ABI version independent of the main library version
#define PYBIND11_INTERNALS_VERSION 3
#if defined(_DEBUG)
# define PYBIND11_BUILD_TYPE "_debug"
#else
# define PYBIND11_BUILD_TYPE ""
#endif
#if defined(WITH_THREAD)
# define PYBIND11_INTERNALS_KIND ""
#else
# define PYBIND11_INTERNALS_KIND "_without_thread"
#endif
#define PYBIND11_INTERNALS_ID "__pybind11_internals_v" \
PYBIND11_TOSTRING(PYBIND11_INTERNALS_VERSION) PYBIND11_INTERNALS_KIND PYBIND11_BUILD_TYPE "__"
#define PYBIND11_MODULE_LOCAL_ID "__pybind11_module_local_v" \
PYBIND11_TOSTRING(PYBIND11_INTERNALS_VERSION) PYBIND11_INTERNALS_KIND PYBIND11_BUILD_TYPE "__"
/// Each module locally stores a pointer to the `internals` data. The data
/// itself is shared among modules with the same `PYBIND11_INTERNALS_ID`.
inline internals **&get_internals_pp() {
static internals **internals_pp = nullptr;
return internals_pp;
}
/// Return a reference to the current `internals` data
PYBIND11_NOINLINE inline internals &get_internals() {
auto **&internals_pp = get_internals_pp();
if (internals_pp && *internals_pp)
return **internals_pp;
constexpr auto *id = PYBIND11_INTERNALS_ID;
auto builtins = handle(PyEval_GetBuiltins());
if (builtins.contains(id) && isinstance<capsule>(builtins[id])) {
internals_pp = static_cast<internals **>(capsule(builtins[id]));
// We loaded builtins through python's builtins, which means that our `error_already_set`
// and `builtin_exception` may be different local classes than the ones set up in the
// initial exception translator, below, so add another for our local exception classes.
//
// libstdc++ doesn't require this (types there are identified only by name)
#if !defined(__GLIBCXX__)
(*internals_pp)->registered_exception_translators.push_front(
[](std::exception_ptr p) -> void {
try {
if (p) std::rethrow_exception(p);
} catch (error_already_set &e) { e.restore(); return;
} catch (const builtin_exception &e) { e.set_error(); return;
}
}
);
#endif
} else {
if (!internals_pp) internals_pp = new internals*();
auto *&internals_ptr = *internals_pp;
internals_ptr = new internals();
#if defined(WITH_THREAD)
PyEval_InitThreads();
PyThreadState *tstate = PyThreadState_Get();
#if PY_VERSION_HEX >= 0x03070000
internals_ptr->tstate = PyThread_tss_alloc();
if (!internals_ptr->tstate || PyThread_tss_create(internals_ptr->tstate))
pybind11_fail("get_internals: could not successfully initialize the TSS key!");
PyThread_tss_set(internals_ptr->tstate, tstate);
#else
internals_ptr->tstate = PyThread_create_key();
if (internals_ptr->tstate == -1)
pybind11_fail("get_internals: could not successfully initialize the TLS key!");
PyThread_set_key_value(internals_ptr->tstate, tstate);
#endif
internals_ptr->istate = tstate->interp;
#endif
builtins[id] = capsule(internals_pp);
internals_ptr->registered_exception_translators.push_front(
[](std::exception_ptr p) -> void {
try {
if (p) std::rethrow_exception(p);
} catch (error_already_set &e) { e.restore(); return;
} catch (const builtin_exception &e) { e.set_error(); return;
} catch (const std::bad_alloc &e) { PyErr_SetString(PyExc_MemoryError, e.what()); return;
} catch (const std::domain_error &e) { PyErr_SetString(PyExc_ValueError, e.what()); return;
} catch (const std::invalid_argument &e) { PyErr_SetString(PyExc_ValueError, e.what()); return;
} catch (const std::length_error &e) { PyErr_SetString(PyExc_ValueError, e.what()); return;
} catch (const std::out_of_range &e) { PyErr_SetString(PyExc_IndexError, e.what()); return;
} catch (const std::range_error &e) { PyErr_SetString(PyExc_ValueError, e.what()); return;
} catch (const std::exception &e) { PyErr_SetString(PyExc_RuntimeError, e.what()); return;
} catch (...) {
PyErr_SetString(PyExc_RuntimeError, "Caught an unknown exception!");
return;
}
}
);
internals_ptr->static_property_type = make_static_property_type();
internals_ptr->default_metaclass = make_default_metaclass();
internals_ptr->instance_base = make_object_base_type(internals_ptr->default_metaclass);
}
return **internals_pp;
}
/// Works like `internals.registered_types_cpp`, but for module-local registered types:
inline type_map<type_info *> &registered_local_types_cpp() {
static type_map<type_info *> locals{};
return locals;
}
/// Constructs a std::string with the given arguments, stores it in `internals`, and returns its
/// `c_str()`. Such strings objects have a long storage duration -- the internal strings are only
/// cleared when the program exits or after interpreter shutdown (when embedding), and so are
/// suitable for c-style strings needed by Python internals (such as PyTypeObject's tp_name).
template <typename... Args>
const char *c_str(Args &&...args) {
auto &strings = get_internals().static_strings;
strings.emplace_front(std::forward<Args>(args)...);
return strings.front().c_str();
}
NAMESPACE_END(detail)
/// Returns a named pointer that is shared among all extension modules (using the same
/// pybind11 version) running in the current interpreter. Names starting with underscores
/// are reserved for internal usage. Returns `nullptr` if no matching entry was found.
inline PYBIND11_NOINLINE void *get_shared_data(const std::string &name) {
auto &internals = detail::get_internals();
auto it = internals.shared_data.find(name);
return it != internals.shared_data.end() ? it->second : nullptr;
}
/// Set the shared data that can be later recovered by `get_shared_data()`.
inline PYBIND11_NOINLINE void *set_shared_data(const std::string &name, void *data) {
detail::get_internals().shared_data[name] = data;
return data;
}
/// Returns a typed reference to a shared data entry (by using `get_shared_data()`) if
/// such entry exists. Otherwise, a new object of default-constructible type `T` is
/// added to the shared data under the given name and a reference to it is returned.
template<typename T>
T &get_or_create_shared_data(const std::string &name) {
auto &internals = detail::get_internals();
auto it = internals.shared_data.find(name);
T *ptr = (T *) (it != internals.shared_data.end() ? it->second : nullptr);
if (!ptr) {
ptr = new T();
internals.shared_data[name] = ptr;
}
return *ptr;
}
NAMESPACE_END(PYBIND11_NAMESPACE)

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/*
pybind11/detail/typeid.h: Compiler-independent access to type identifiers
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 <cstdio>
#include <cstdlib>
#if defined(__GNUG__)
#include <cxxabi.h>
#endif
NAMESPACE_BEGIN(PYBIND11_NAMESPACE)
NAMESPACE_BEGIN(detail)
/// Erase all occurrences of a substring
inline void erase_all(std::string &string, const std::string &search) {
for (size_t pos = 0;;) {
pos = string.find(search, pos);
if (pos == std::string::npos) break;
string.erase(pos, search.length());
}
}
PYBIND11_NOINLINE inline void clean_type_id(std::string &name) {
#if defined(__GNUG__)
int status = 0;
std::unique_ptr<char, void (*)(void *)> res {
abi::__cxa_demangle(name.c_str(), nullptr, nullptr, &status), std::free };
if (status == 0)
name = res.get();
#else
detail::erase_all(name, "class ");
detail::erase_all(name, "struct ");
detail::erase_all(name, "enum ");
#endif
detail::erase_all(name, "pybind11::");
}
NAMESPACE_END(detail)
/// Return a string representation of a C++ type
template <typename T> static std::string type_id() {
std::string name(typeid(T).name());
detail::clean_type_id(name);
return name;
}
NAMESPACE_END(PYBIND11_NAMESPACE)

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/*
pybind11/eigen.h: Transparent conversion for dense and sparse Eigen matrices
Copyright (c) 2016 Wenzel Jakob <wenzel.jakob@epfl.ch>
All rights reserved. Use of this source code is governed by a
BSD-style license that can be found in the LICENSE file.
*/
#pragma once
#include "numpy.h"
#if defined(__INTEL_COMPILER)
# pragma warning(disable: 1682) // implicit conversion of a 64-bit integral type to a smaller integral type (potential portability problem)
#elif defined(__GNUG__) || defined(__clang__)
# pragma GCC diagnostic push
# pragma GCC diagnostic ignored "-Wconversion"
# pragma GCC diagnostic ignored "-Wdeprecated-declarations"
# ifdef __clang__
// Eigen generates a bunch of implicit-copy-constructor-is-deprecated warnings with -Wdeprecated
// under Clang, so disable that warning here:
# pragma GCC diagnostic ignored "-Wdeprecated"
# endif
# if __GNUC__ >= 7
# pragma GCC diagnostic ignored "-Wint-in-bool-context"
# endif
#endif
#if defined(_MSC_VER)
# pragma warning(push)
# pragma warning(disable: 4127) // warning C4127: Conditional expression is constant
# pragma warning(disable: 4996) // warning C4996: std::unary_negate is deprecated in C++17
#endif
#include <Eigen/Core>
#include <Eigen/SparseCore>
// Eigen prior to 3.2.7 doesn't have proper move constructors--but worse, some classes get implicit
// move constructors that break things. We could detect this an explicitly copy, but an extra copy
// of matrices seems highly undesirable.
static_assert(EIGEN_VERSION_AT_LEAST(3,2,7), "Eigen support in pybind11 requires Eigen >= 3.2.7");
NAMESPACE_BEGIN(PYBIND11_NAMESPACE)
// Provide a convenience alias for easier pass-by-ref usage with fully dynamic strides:
using EigenDStride = Eigen::Stride<Eigen::Dynamic, Eigen::Dynamic>;
template <typename MatrixType> using EigenDRef = Eigen::Ref<MatrixType, 0, EigenDStride>;
template <typename MatrixType> using EigenDMap = Eigen::Map<MatrixType, 0, EigenDStride>;
NAMESPACE_BEGIN(detail)
#if EIGEN_VERSION_AT_LEAST(3,3,0)
using EigenIndex = Eigen::Index;
#else
using EigenIndex = EIGEN_DEFAULT_DENSE_INDEX_TYPE;
#endif
// Matches Eigen::Map, Eigen::Ref, blocks, etc:
template <typename T> using is_eigen_dense_map = all_of<is_template_base_of<Eigen::DenseBase, T>, std::is_base_of<Eigen::MapBase<T, Eigen::ReadOnlyAccessors>, T>>;
template <typename T> using is_eigen_mutable_map = std::is_base_of<Eigen::MapBase<T, Eigen::WriteAccessors>, T>;
template <typename T> using is_eigen_dense_plain = all_of<negation<is_eigen_dense_map<T>>, is_template_base_of<Eigen::PlainObjectBase, T>>;
template <typename T> using is_eigen_sparse = is_template_base_of<Eigen::SparseMatrixBase, T>;
// Test for objects inheriting from EigenBase<Derived> that aren't captured by the above. This
// basically covers anything that can be assigned to a dense matrix but that don't have a typical
// matrix data layout that can be copied from their .data(). For example, DiagonalMatrix and
// SelfAdjointView fall into this category.
template <typename T> using is_eigen_other = all_of<
is_template_base_of<Eigen::EigenBase, T>,
negation<any_of<is_eigen_dense_map<T>, is_eigen_dense_plain<T>, is_eigen_sparse<T>>>
>;
// Captures numpy/eigen conformability status (returned by EigenProps::conformable()):
template <bool EigenRowMajor> struct EigenConformable {
bool conformable = false;
EigenIndex rows = 0, cols = 0;
EigenDStride stride{0, 0}; // Only valid if negativestrides is false!
bool negativestrides = false; // If true, do not use stride!
EigenConformable(bool fits = false) : conformable{fits} {}
// Matrix type:
EigenConformable(EigenIndex r, EigenIndex c,
EigenIndex rstride, EigenIndex cstride) :
conformable{true}, rows{r}, cols{c} {
// TODO: when Eigen bug #747 is fixed, remove the tests for non-negativity. http://eigen.tuxfamily.org/bz/show_bug.cgi?id=747
if (rstride < 0 || cstride < 0) {
negativestrides = true;
} else {
stride = {EigenRowMajor ? rstride : cstride /* outer stride */,
EigenRowMajor ? cstride : rstride /* inner stride */ };
}
}
// Vector type:
EigenConformable(EigenIndex r, EigenIndex c, EigenIndex stride)
: EigenConformable(r, c, r == 1 ? c*stride : stride, c == 1 ? r : r*stride) {}
template <typename props> bool stride_compatible() const {
// To have compatible strides, we need (on both dimensions) one of fully dynamic strides,
// matching strides, or a dimension size of 1 (in which case the stride value is irrelevant)
return
!negativestrides &&
(props::inner_stride == Eigen::Dynamic || props::inner_stride == stride.inner() ||
(EigenRowMajor ? cols : rows) == 1) &&
(props::outer_stride == Eigen::Dynamic || props::outer_stride == stride.outer() ||
(EigenRowMajor ? rows : cols) == 1);
}
operator bool() const { return conformable; }
};
template <typename Type> struct eigen_extract_stride { using type = Type; };
template <typename PlainObjectType, int MapOptions, typename StrideType>
struct eigen_extract_stride<Eigen::Map<PlainObjectType, MapOptions, StrideType>> { using type = StrideType; };
template <typename PlainObjectType, int Options, typename StrideType>
struct eigen_extract_stride<Eigen::Ref<PlainObjectType, Options, StrideType>> { using type = StrideType; };
// Helper struct for extracting information from an Eigen type
template <typename Type_> struct EigenProps {
using Type = Type_;
using Scalar = typename Type::Scalar;
using StrideType = typename eigen_extract_stride<Type>::type;
static constexpr EigenIndex
rows = Type::RowsAtCompileTime,
cols = Type::ColsAtCompileTime,
size = Type::SizeAtCompileTime;
static constexpr bool
row_major = Type::IsRowMajor,
vector = Type::IsVectorAtCompileTime, // At least one dimension has fixed size 1
fixed_rows = rows != Eigen::Dynamic,
fixed_cols = cols != Eigen::Dynamic,
fixed = size != Eigen::Dynamic, // Fully-fixed size
dynamic = !fixed_rows && !fixed_cols; // Fully-dynamic size
template <EigenIndex i, EigenIndex ifzero> using if_zero = std::integral_constant<EigenIndex, i == 0 ? ifzero : i>;
static constexpr EigenIndex inner_stride = if_zero<StrideType::InnerStrideAtCompileTime, 1>::value,
outer_stride = if_zero<StrideType::OuterStrideAtCompileTime,
vector ? size : row_major ? cols : rows>::value;
static constexpr bool dynamic_stride = inner_stride == Eigen::Dynamic && outer_stride == Eigen::Dynamic;
static constexpr bool requires_row_major = !dynamic_stride && !vector && (row_major ? inner_stride : outer_stride) == 1;
static constexpr bool requires_col_major = !dynamic_stride && !vector && (row_major ? outer_stride : inner_stride) == 1;
// Takes an input array and determines whether we can make it fit into the Eigen type. If
// the array is a vector, we attempt to fit it into either an Eigen 1xN or Nx1 vector
// (preferring the latter if it will fit in either, i.e. for a fully dynamic matrix type).
static EigenConformable<row_major> conformable(const array &a) {
const auto dims = a.ndim();
if (dims < 1 || dims > 2)
return false;
if (dims == 2) { // Matrix type: require exact match (or dynamic)
EigenIndex
np_rows = a.shape(0),
np_cols = a.shape(1),
np_rstride = a.strides(0) / static_cast<ssize_t>(sizeof(Scalar)),
np_cstride = a.strides(1) / static_cast<ssize_t>(sizeof(Scalar));
if ((fixed_rows && np_rows != rows) || (fixed_cols && np_cols != cols))
return false;
return {np_rows, np_cols, np_rstride, np_cstride};
}
// Otherwise we're storing an n-vector. Only one of the strides will be used, but whichever
// is used, we want the (single) numpy stride value.
const EigenIndex n = a.shape(0),
stride = a.strides(0) / static_cast<ssize_t>(sizeof(Scalar));
if (vector) { // Eigen type is a compile-time vector
if (fixed && size != n)
return false; // Vector size mismatch
return {rows == 1 ? 1 : n, cols == 1 ? 1 : n, stride};
}
else if (fixed) {
// The type has a fixed size, but is not a vector: abort
return false;
}
else if (fixed_cols) {
// Since this isn't a vector, cols must be != 1. We allow this only if it exactly
// equals the number of elements (rows is Dynamic, and so 1 row is allowed).
if (cols != n) return false;
return {1, n, stride};
}
else {
// Otherwise it's either fully dynamic, or column dynamic; both become a column vector
if (fixed_rows && rows != n) return false;
return {n, 1, stride};
}
}
static constexpr bool show_writeable = is_eigen_dense_map<Type>::value && is_eigen_mutable_map<Type>::value;
static constexpr bool show_order = is_eigen_dense_map<Type>::value;
static constexpr bool show_c_contiguous = show_order && requires_row_major;
static constexpr bool show_f_contiguous = !show_c_contiguous && show_order && requires_col_major;
static constexpr auto descriptor =
_("numpy.ndarray[") + npy_format_descriptor<Scalar>::name +
_("[") + _<fixed_rows>(_<(size_t) rows>(), _("m")) +
_(", ") + _<fixed_cols>(_<(size_t) cols>(), _("n")) +
_("]") +
// For a reference type (e.g. Ref<MatrixXd>) we have other constraints that might need to be
// satisfied: writeable=True (for a mutable reference), and, depending on the map's stride
// options, possibly f_contiguous or c_contiguous. We include them in the descriptor output
// to provide some hint as to why a TypeError is occurring (otherwise it can be confusing to
// see that a function accepts a 'numpy.ndarray[float64[3,2]]' and an error message that you
// *gave* a numpy.ndarray of the right type and dimensions.
_<show_writeable>(", flags.writeable", "") +
_<show_c_contiguous>(", flags.c_contiguous", "") +
_<show_f_contiguous>(", flags.f_contiguous", "") +
_("]");
};
// Casts an Eigen type to numpy array. If given a base, the numpy array references the src data,
// otherwise it'll make a copy. writeable lets you turn off the writeable flag for the array.
template <typename props> handle eigen_array_cast(typename props::Type const &src, handle base = handle(), bool writeable = true) {
constexpr ssize_t elem_size = sizeof(typename props::Scalar);
array a;
if (props::vector)
a = array({ src.size() }, { elem_size * src.innerStride() }, src.data(), base);
else
a = array({ src.rows(), src.cols() }, { elem_size * src.rowStride(), elem_size * src.colStride() },
src.data(), base);
if (!writeable)
array_proxy(a.ptr())->flags &= ~detail::npy_api::NPY_ARRAY_WRITEABLE_;
return a.release();
}
// Takes an lvalue ref to some Eigen type and a (python) base object, creating a numpy array that
// reference the Eigen object's data with `base` as the python-registered base class (if omitted,
// the base will be set to None, and lifetime management is up to the caller). The numpy array is
// non-writeable if the given type is const.
template <typename props, typename Type>
handle eigen_ref_array(Type &src, handle parent = none()) {
// none here is to get past array's should-we-copy detection, which currently always
// copies when there is no base. Setting the base to None should be harmless.
return eigen_array_cast<props>(src, parent, !std::is_const<Type>::value);
}
// Takes a pointer to some dense, plain Eigen type, builds a capsule around it, then returns a numpy
// array that references the encapsulated data with a python-side reference to the capsule to tie
// its destruction to that of any dependent python objects. Const-ness is determined by whether or
// not the Type of the pointer given is const.
template <typename props, typename Type, typename = enable_if_t<is_eigen_dense_plain<Type>::value>>
handle eigen_encapsulate(Type *src) {
capsule base(src, [](void *o) { delete static_cast<Type *>(o); });
return eigen_ref_array<props>(*src, base);
}
// Type caster for regular, dense matrix types (e.g. MatrixXd), but not maps/refs/etc. of dense
// types.
template<typename Type>
struct type_caster<Type, enable_if_t<is_eigen_dense_plain<Type>::value>> {
using Scalar = typename Type::Scalar;
using props = EigenProps<Type>;
bool load(handle src, bool convert) {
// If we're in no-convert mode, only load if given an array of the correct type
if (!convert && !isinstance<array_t<Scalar>>(src))
return false;
// Coerce into an array, but don't do type conversion yet; the copy below handles it.
auto buf = array::ensure(src);
if (!buf)
return false;
auto dims = buf.ndim();
if (dims < 1 || dims > 2)
return false;
auto fits = props::conformable(buf);
if (!fits)
return false;
// Allocate the new type, then build a numpy reference into it
value = Type(fits.rows, fits.cols);
auto ref = reinterpret_steal<array>(eigen_ref_array<props>(value));
if (dims == 1) ref = ref.squeeze();
else if (ref.ndim() == 1) buf = buf.squeeze();
int result = detail::npy_api::get().PyArray_CopyInto_(ref.ptr(), buf.ptr());
if (result < 0) { // Copy failed!
PyErr_Clear();
return false;
}
return true;
}
private:
// Cast implementation
template <typename CType>
static handle cast_impl(CType *src, return_value_policy policy, handle parent) {
switch (policy) {
case return_value_policy::take_ownership:
case return_value_policy::automatic:
return eigen_encapsulate<props>(src);
case return_value_policy::move:
return eigen_encapsulate<props>(new CType(std::move(*src)));
case return_value_policy::copy:
return eigen_array_cast<props>(*src);
case return_value_policy::reference:
case return_value_policy::automatic_reference:
return eigen_ref_array<props>(*src);
case return_value_policy::reference_internal:
return eigen_ref_array<props>(*src, parent);
default:
throw cast_error("unhandled return_value_policy: should not happen!");
};
}
public:
// Normal returned non-reference, non-const value:
static handle cast(Type &&src, return_value_policy /* policy */, handle parent) {
return cast_impl(&src, return_value_policy::move, parent);
}
// If you return a non-reference const, we mark the numpy array readonly:
static handle cast(const Type &&src, return_value_policy /* policy */, handle parent) {
return cast_impl(&src, return_value_policy::move, parent);
}
// lvalue reference return; default (automatic) becomes copy
static handle cast(Type &src, return_value_policy policy, handle parent) {
if (policy == return_value_policy::automatic || policy == return_value_policy::automatic_reference)
policy = return_value_policy::copy;
return cast_impl(&src, policy, parent);
}
// const lvalue reference return; default (automatic) becomes copy
static handle cast(const Type &src, return_value_policy policy, handle parent) {
if (policy == return_value_policy::automatic || policy == return_value_policy::automatic_reference)
policy = return_value_policy::copy;
return cast(&src, policy, parent);
}
// non-const pointer return
static handle cast(Type *src, return_value_policy policy, handle parent) {
return cast_impl(src, policy, parent);
}
// const pointer return
static handle cast(const Type *src, return_value_policy policy, handle parent) {
return cast_impl(src, policy, parent);
}
static constexpr auto name = props::descriptor;
operator Type*() { return &value; }
operator Type&() { return value; }
operator Type&&() && { return std::move(value); }
template <typename T> using cast_op_type = movable_cast_op_type<T>;
private:
Type value;
};
// Base class for casting reference/map/block/etc. objects back to python.
template <typename MapType> struct eigen_map_caster {
private:
using props = EigenProps<MapType>;
public:
// Directly referencing a ref/map's data is a bit dangerous (whatever the map/ref points to has
// to stay around), but we'll allow it under the assumption that you know what you're doing (and
// have an appropriate keep_alive in place). We return a numpy array pointing directly at the
// ref's data (The numpy array ends up read-only if the ref was to a const matrix type.) Note
// that this means you need to ensure you don't destroy the object in some other way (e.g. with
// an appropriate keep_alive, or with a reference to a statically allocated matrix).
static handle cast(const MapType &src, return_value_policy policy, handle parent) {
switch (policy) {
case return_value_policy::copy:
return eigen_array_cast<props>(src);
case return_value_policy::reference_internal:
return eigen_array_cast<props>(src, parent, is_eigen_mutable_map<MapType>::value);
case return_value_policy::reference:
case return_value_policy::automatic:
case return_value_policy::automatic_reference:
return eigen_array_cast<props>(src, none(), is_eigen_mutable_map<MapType>::value);
default:
// move, take_ownership don't make any sense for a ref/map:
pybind11_fail("Invalid return_value_policy for Eigen Map/Ref/Block type");
}
}
static constexpr auto name = props::descriptor;
// Explicitly delete these: support python -> C++ conversion on these (i.e. these can be return
// types but not bound arguments). We still provide them (with an explicitly delete) so that
// you end up here if you try anyway.
bool load(handle, bool) = delete;
operator MapType() = delete;
template <typename> using cast_op_type = MapType;
};
// We can return any map-like object (but can only load Refs, specialized next):
template <typename Type> struct type_caster<Type, enable_if_t<is_eigen_dense_map<Type>::value>>
: eigen_map_caster<Type> {};
// Loader for Ref<...> arguments. See the documentation for info on how to make this work without
// copying (it requires some extra effort in many cases).
template <typename PlainObjectType, typename StrideType>
struct type_caster<
Eigen::Ref<PlainObjectType, 0, StrideType>,
enable_if_t<is_eigen_dense_map<Eigen::Ref<PlainObjectType, 0, StrideType>>::value>
> : public eigen_map_caster<Eigen::Ref<PlainObjectType, 0, StrideType>> {
private:
using Type = Eigen::Ref<PlainObjectType, 0, StrideType>;
using props = EigenProps<Type>;
using Scalar = typename props::Scalar;
using MapType = Eigen::Map<PlainObjectType, 0, StrideType>;
using Array = array_t<Scalar, array::forcecast |
((props::row_major ? props::inner_stride : props::outer_stride) == 1 ? array::c_style :
(props::row_major ? props::outer_stride : props::inner_stride) == 1 ? array::f_style : 0)>;
static constexpr bool need_writeable = is_eigen_mutable_map<Type>::value;
// Delay construction (these have no default constructor)
std::unique_ptr<MapType> map;
std::unique_ptr<Type> ref;
// Our array. When possible, this is just a numpy array pointing to the source data, but
// sometimes we can't avoid copying (e.g. input is not a numpy array at all, has an incompatible
// layout, or is an array of a type that needs to be converted). Using a numpy temporary
// (rather than an Eigen temporary) saves an extra copy when we need both type conversion and
// storage order conversion. (Note that we refuse to use this temporary copy when loading an
// argument for a Ref<M> with M non-const, i.e. a read-write reference).
Array copy_or_ref;
public:
bool load(handle src, bool convert) {
// First check whether what we have is already an array of the right type. If not, we can't
// avoid a copy (because the copy is also going to do type conversion).
bool need_copy = !isinstance<Array>(src);
EigenConformable<props::row_major> fits;
if (!need_copy) {
// We don't need a converting copy, but we also need to check whether the strides are
// compatible with the Ref's stride requirements
Array aref = reinterpret_borrow<Array>(src);
if (aref && (!need_writeable || aref.writeable())) {
fits = props::conformable(aref);
if (!fits) return false; // Incompatible dimensions
if (!fits.template stride_compatible<props>())
need_copy = true;
else
copy_or_ref = std::move(aref);
}
else {
need_copy = true;
}
}
if (need_copy) {
// We need to copy: If we need a mutable reference, or we're not supposed to convert
// (either because we're in the no-convert overload pass, or because we're explicitly
// instructed not to copy (via `py::arg().noconvert()`) we have to fail loading.
if (!convert || need_writeable) return false;
Array copy = Array::ensure(src);
if (!copy) return false;
fits = props::conformable(copy);
if (!fits || !fits.template stride_compatible<props>())
return false;
copy_or_ref = std::move(copy);
loader_life_support::add_patient(copy_or_ref);
}
ref.reset();
map.reset(new MapType(data(copy_or_ref), fits.rows, fits.cols, make_stride(fits.stride.outer(), fits.stride.inner())));
ref.reset(new Type(*map));
return true;
}
operator Type*() { return ref.get(); }
operator Type&() { return *ref; }
template <typename _T> using cast_op_type = pybind11::detail::cast_op_type<_T>;
private:
template <typename T = Type, enable_if_t<is_eigen_mutable_map<T>::value, int> = 0>
Scalar *data(Array &a) { return a.mutable_data(); }
template <typename T = Type, enable_if_t<!is_eigen_mutable_map<T>::value, int> = 0>
const Scalar *data(Array &a) { return a.data(); }
// Attempt to figure out a constructor of `Stride` that will work.
// If both strides are fixed, use a default constructor:
template <typename S> using stride_ctor_default = bool_constant<
S::InnerStrideAtCompileTime != Eigen::Dynamic && S::OuterStrideAtCompileTime != Eigen::Dynamic &&
std::is_default_constructible<S>::value>;
// Otherwise, if there is a two-index constructor, assume it is (outer,inner) like
// Eigen::Stride, and use it:
template <typename S> using stride_ctor_dual = bool_constant<
!stride_ctor_default<S>::value && std::is_constructible<S, EigenIndex, EigenIndex>::value>;
// Otherwise, if there is a one-index constructor, and just one of the strides is dynamic, use
// it (passing whichever stride is dynamic).
template <typename S> using stride_ctor_outer = bool_constant<
!any_of<stride_ctor_default<S>, stride_ctor_dual<S>>::value &&
S::OuterStrideAtCompileTime == Eigen::Dynamic && S::InnerStrideAtCompileTime != Eigen::Dynamic &&
std::is_constructible<S, EigenIndex>::value>;
template <typename S> using stride_ctor_inner = bool_constant<
!any_of<stride_ctor_default<S>, stride_ctor_dual<S>>::value &&
S::InnerStrideAtCompileTime == Eigen::Dynamic && S::OuterStrideAtCompileTime != Eigen::Dynamic &&
std::is_constructible<S, EigenIndex>::value>;
template <typename S = StrideType, enable_if_t<stride_ctor_default<S>::value, int> = 0>
static S make_stride(EigenIndex, EigenIndex) { return S(); }
template <typename S = StrideType, enable_if_t<stride_ctor_dual<S>::value, int> = 0>
static S make_stride(EigenIndex outer, EigenIndex inner) { return S(outer, inner); }
template <typename S = StrideType, enable_if_t<stride_ctor_outer<S>::value, int> = 0>
static S make_stride(EigenIndex outer, EigenIndex) { return S(outer); }
template <typename S = StrideType, enable_if_t<stride_ctor_inner<S>::value, int> = 0>
static S make_stride(EigenIndex, EigenIndex inner) { return S(inner); }
};
// type_caster for special matrix types (e.g. DiagonalMatrix), which are EigenBase, but not
// EigenDense (i.e. they don't have a data(), at least not with the usual matrix layout).
// load() is not supported, but we can cast them into the python domain by first copying to a
// regular Eigen::Matrix, then casting that.
template <typename Type>
struct type_caster<Type, enable_if_t<is_eigen_other<Type>::value>> {
protected:
using Matrix = Eigen::Matrix<typename Type::Scalar, Type::RowsAtCompileTime, Type::ColsAtCompileTime>;
using props = EigenProps<Matrix>;
public:
static handle cast(const Type &src, return_value_policy /* policy */, handle /* parent */) {
handle h = eigen_encapsulate<props>(new Matrix(src));
return h;
}
static handle cast(const Type *src, return_value_policy policy, handle parent) { return cast(*src, policy, parent); }
static constexpr auto name = props::descriptor;
// Explicitly delete these: support python -> C++ conversion on these (i.e. these can be return
// types but not bound arguments). We still provide them (with an explicitly delete) so that
// you end up here if you try anyway.
bool load(handle, bool) = delete;
operator Type() = delete;
template <typename> using cast_op_type = Type;
};
template<typename Type>
struct type_caster<Type, enable_if_t<is_eigen_sparse<Type>::value>> {
typedef typename Type::Scalar Scalar;
typedef remove_reference_t<decltype(*std::declval<Type>().outerIndexPtr())> StorageIndex;
typedef typename Type::Index Index;
static constexpr bool rowMajor = Type::IsRowMajor;
bool load(handle src, bool) {
if (!src)
return false;
auto obj = reinterpret_borrow<object>(src);
object sparse_module = module::import("scipy.sparse");
object matrix_type = sparse_module.attr(
rowMajor ? "csr_matrix" : "csc_matrix");
if (!obj.get_type().is(matrix_type)) {
try {
obj = matrix_type(obj);
} catch (const error_already_set &) {
return false;
}
}
auto values = array_t<Scalar>((object) obj.attr("data"));
auto innerIndices = array_t<StorageIndex>((object) obj.attr("indices"));
auto outerIndices = array_t<StorageIndex>((object) obj.attr("indptr"));
auto shape = pybind11::tuple((pybind11::object) obj.attr("shape"));
auto nnz = obj.attr("nnz").cast<Index>();
if (!values || !innerIndices || !outerIndices)
return false;
value = Eigen::MappedSparseMatrix<Scalar, Type::Flags, StorageIndex>(
shape[0].cast<Index>(), shape[1].cast<Index>(), nnz,
outerIndices.mutable_data(), innerIndices.mutable_data(), values.mutable_data());
return true;
}
static handle cast(const Type &src, return_value_policy /* policy */, handle /* parent */) {
const_cast<Type&>(src).makeCompressed();
object matrix_type = module::import("scipy.sparse").attr(
rowMajor ? "csr_matrix" : "csc_matrix");
array data(src.nonZeros(), src.valuePtr());
array outerIndices((rowMajor ? src.rows() : src.cols()) + 1, src.outerIndexPtr());
array innerIndices(src.nonZeros(), src.innerIndexPtr());
return matrix_type(
std::make_tuple(data, innerIndices, outerIndices),
std::make_pair(src.rows(), src.cols())
).release();
}
PYBIND11_TYPE_CASTER(Type, _<(Type::IsRowMajor) != 0>("scipy.sparse.csr_matrix[", "scipy.sparse.csc_matrix[")
+ npy_format_descriptor<Scalar>::name + _("]"));
};
NAMESPACE_END(detail)
NAMESPACE_END(PYBIND11_NAMESPACE)
#if defined(__GNUG__) || defined(__clang__)
# pragma GCC diagnostic pop
#elif defined(_MSC_VER)
# pragma warning(pop)
#endif

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@ -1,200 +0,0 @@
/*
pybind11/embed.h: Support for embedding the interpreter
Copyright (c) 2017 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 "eval.h"
#if defined(PYPY_VERSION)
# error Embedding the interpreter is not supported with PyPy
#endif
#if PY_MAJOR_VERSION >= 3
# define PYBIND11_EMBEDDED_MODULE_IMPL(name) \
extern "C" PyObject *pybind11_init_impl_##name() { \
return pybind11_init_wrapper_##name(); \
}
#else
# define PYBIND11_EMBEDDED_MODULE_IMPL(name) \
extern "C" void pybind11_init_impl_##name() { \
pybind11_init_wrapper_##name(); \
}
#endif
/** \rst
Add a new module to the table of builtins for the interpreter. Must be
defined in global scope. The first macro parameter is the name of the
module (without quotes). The second parameter is the variable which will
be used as the interface to add functions and classes to the module.
.. code-block:: cpp
PYBIND11_EMBEDDED_MODULE(example, m) {
// ... initialize functions and classes here
m.def("foo", []() {
return "Hello, World!";
});
}
\endrst */
#define PYBIND11_EMBEDDED_MODULE(name, variable) \
static void PYBIND11_CONCAT(pybind11_init_, name)(pybind11::module &); \
static PyObject PYBIND11_CONCAT(*pybind11_init_wrapper_, name)() { \
auto m = pybind11::module(PYBIND11_TOSTRING(name)); \
try { \
PYBIND11_CONCAT(pybind11_init_, name)(m); \
return m.ptr(); \
} catch (pybind11::error_already_set &e) { \
PyErr_SetString(PyExc_ImportError, e.what()); \
return nullptr; \
} catch (const std::exception &e) { \
PyErr_SetString(PyExc_ImportError, e.what()); \
return nullptr; \
} \
} \
PYBIND11_EMBEDDED_MODULE_IMPL(name) \
pybind11::detail::embedded_module name(PYBIND11_TOSTRING(name), \
PYBIND11_CONCAT(pybind11_init_impl_, name)); \
void PYBIND11_CONCAT(pybind11_init_, name)(pybind11::module &variable)
NAMESPACE_BEGIN(PYBIND11_NAMESPACE)
NAMESPACE_BEGIN(detail)
/// Python 2.7/3.x compatible version of `PyImport_AppendInittab` and error checks.
struct embedded_module {
#if PY_MAJOR_VERSION >= 3
using init_t = PyObject *(*)();
#else
using init_t = void (*)();
#endif
embedded_module(const char *name, init_t init) {
if (Py_IsInitialized())
pybind11_fail("Can't add new modules after the interpreter has been initialized");
auto result = PyImport_AppendInittab(name, init);
if (result == -1)
pybind11_fail("Insufficient memory to add a new module");
}
};
NAMESPACE_END(detail)
/** \rst
Initialize the Python interpreter. No other pybind11 or CPython API functions can be
called before this is done; with the exception of `PYBIND11_EMBEDDED_MODULE`. The
optional parameter can be used to skip the registration of signal handlers (see the
`Python documentation`_ for details). Calling this function again after the interpreter
has already been initialized is a fatal error.
If initializing the Python interpreter fails, then the program is terminated. (This
is controlled by the CPython runtime and is an exception to pybind11's normal behavior
of throwing exceptions on errors.)
.. _Python documentation: https://docs.python.org/3/c-api/init.html#c.Py_InitializeEx
\endrst */
inline void initialize_interpreter(bool init_signal_handlers = true) {
if (Py_IsInitialized())
pybind11_fail("The interpreter is already running");
Py_InitializeEx(init_signal_handlers ? 1 : 0);
// Make .py files in the working directory available by default
module::import("sys").attr("path").cast<list>().append(".");
}
/** \rst
Shut down the Python interpreter. No pybind11 or CPython API functions can be called
after this. In addition, pybind11 objects must not outlive the interpreter:
.. code-block:: cpp
{ // BAD
py::initialize_interpreter();
auto hello = py::str("Hello, World!");
py::finalize_interpreter();
} // <-- BOOM, hello's destructor is called after interpreter shutdown
{ // GOOD
py::initialize_interpreter();
{ // scoped
auto hello = py::str("Hello, World!");
} // <-- OK, hello is cleaned up properly
py::finalize_interpreter();
}
{ // BETTER
py::scoped_interpreter guard{};
auto hello = py::str("Hello, World!");
}
.. warning::
The interpreter can be restarted by calling `initialize_interpreter` again.
Modules created using pybind11 can be safely re-initialized. However, Python
itself cannot completely unload binary extension modules and there are several
caveats with regard to interpreter restarting. All the details can be found
in the CPython documentation. In short, not all interpreter memory may be
freed, either due to reference cycles or user-created global data.
\endrst */
inline void finalize_interpreter() {
handle builtins(PyEval_GetBuiltins());
const char *id = PYBIND11_INTERNALS_ID;
// Get the internals pointer (without creating it if it doesn't exist). It's possible for the
// internals to be created during Py_Finalize() (e.g. if a py::capsule calls `get_internals()`
// during destruction), so we get the pointer-pointer here and check it after Py_Finalize().
detail::internals **internals_ptr_ptr = detail::get_internals_pp();
// It could also be stashed in builtins, so look there too:
if (builtins.contains(id) && isinstance<capsule>(builtins[id]))
internals_ptr_ptr = capsule(builtins[id]);
Py_Finalize();
if (internals_ptr_ptr) {
delete *internals_ptr_ptr;
*internals_ptr_ptr = nullptr;
}
}
/** \rst
Scope guard version of `initialize_interpreter` and `finalize_interpreter`.
This a move-only guard and only a single instance can exist.
.. code-block:: cpp
#include <pybind11/embed.h>
int main() {
py::scoped_interpreter guard{};
py::print(Hello, World!);
} // <-- interpreter shutdown
\endrst */
class scoped_interpreter {
public:
scoped_interpreter(bool init_signal_handlers = true) {
initialize_interpreter(init_signal_handlers);
}
scoped_interpreter(const scoped_interpreter &) = delete;
scoped_interpreter(scoped_interpreter &&other) noexcept { other.is_valid = false; }
scoped_interpreter &operator=(const scoped_interpreter &) = delete;
scoped_interpreter &operator=(scoped_interpreter &&) = delete;
~scoped_interpreter() {
if (is_valid)
finalize_interpreter();
}
private:
bool is_valid = true;
};
NAMESPACE_END(PYBIND11_NAMESPACE)

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/*
pybind11/exec.h: Support for evaluating Python expressions and statements
from strings and files
Copyright (c) 2016 Klemens Morgenstern <klemens.morgenstern@ed-chemnitz.de> and
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"
NAMESPACE_BEGIN(PYBIND11_NAMESPACE)
enum eval_mode {
/// Evaluate a string containing an isolated expression
eval_expr,
/// Evaluate a string containing a single statement. Returns \c none
eval_single_statement,
/// Evaluate a string containing a sequence of statement. Returns \c none
eval_statements
};
template <eval_mode mode = eval_expr>
object eval(str expr, object global = globals(), object local = object()) {
if (!local)
local = global;
/* PyRun_String does not accept a PyObject / encoding specifier,
this seems to be the only alternative */
std::string buffer = "# -*- coding: utf-8 -*-\n" + (std::string) expr;
int start;
switch (mode) {
case eval_expr: start = Py_eval_input; break;
case eval_single_statement: start = Py_single_input; break;
case eval_statements: start = Py_file_input; break;
default: pybind11_fail("invalid evaluation mode");
}
PyObject *result = PyRun_String(buffer.c_str(), start, global.ptr(), local.ptr());
if (!result)
throw error_already_set();
return reinterpret_steal<object>(result);
}
template <eval_mode mode = eval_expr, size_t N>
object eval(const char (&s)[N], object global = globals(), object local = object()) {
/* Support raw string literals by removing common leading whitespace */
auto expr = (s[0] == '\n') ? str(module::import("textwrap").attr("dedent")(s))
: str(s);
return eval<mode>(expr, global, local);
}
inline void exec(str expr, object global = globals(), object local = object()) {
eval<eval_statements>(expr, global, local);
}
template <size_t N>
void exec(const char (&s)[N], object global = globals(), object local = object()) {
eval<eval_statements>(s, global, local);
}
template <eval_mode mode = eval_statements>
object eval_file(str fname, object global = globals(), object local = object()) {
if (!local)
local = global;
int start;
switch (mode) {
case eval_expr: start = Py_eval_input; break;
case eval_single_statement: start = Py_single_input; break;
case eval_statements: start = Py_file_input; break;
default: pybind11_fail("invalid evaluation mode");
}
int closeFile = 1;
std::string fname_str = (std::string) fname;
#if PY_VERSION_HEX >= 0x03040000
FILE *f = _Py_fopen_obj(fname.ptr(), "r");
#elif PY_VERSION_HEX >= 0x03000000
FILE *f = _Py_fopen(fname.ptr(), "r");
#else
/* No unicode support in open() :( */
auto fobj = reinterpret_steal<object>(PyFile_FromString(
const_cast<char *>(fname_str.c_str()),
const_cast<char*>("r")));
FILE *f = nullptr;
if (fobj)
f = PyFile_AsFile(fobj.ptr());
closeFile = 0;
#endif
if (!f) {
PyErr_Clear();
pybind11_fail("File \"" + fname_str + "\" could not be opened!");
}
#if PY_VERSION_HEX < 0x03000000 && defined(PYPY_VERSION)
PyObject *result = PyRun_File(f, fname_str.c_str(), start, global.ptr(),
local.ptr());
(void) closeFile;
#else
PyObject *result = PyRun_FileEx(f, fname_str.c_str(), start, global.ptr(),
local.ptr(), closeFile);
#endif
if (!result)
throw error_already_set();
return reinterpret_steal<object>(result);
}
NAMESPACE_END(PYBIND11_NAMESPACE)

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/*
pybind11/functional.h: std::function<> support
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 <functional>
NAMESPACE_BEGIN(PYBIND11_NAMESPACE)
NAMESPACE_BEGIN(detail)
template <typename Return, typename... Args>
struct type_caster<std::function<Return(Args...)>> {
using type = std::function<Return(Args...)>;
using retval_type = conditional_t<std::is_same<Return, void>::value, void_type, Return>;
using function_type = Return (*) (Args...);
public:
bool load(handle src, bool convert) {
if (src.is_none()) {
// Defer accepting None to other overloads (if we aren't in convert mode):
if (!convert) return false;
return true;
}
if (!isinstance<function>(src))
return false;
auto func = reinterpret_borrow<function>(src);
/*
When passing a C++ function as an argument to another C++
function via Python, every function call would normally involve
a full C++ -> Python -> C++ roundtrip, which can be prohibitive.
Here, we try to at least detect the case where the function is
stateless (i.e. function pointer or lambda function without
captured variables), in which case the roundtrip can be avoided.
*/
if (auto cfunc = func.cpp_function()) {
auto c = reinterpret_borrow<capsule>(PyCFunction_GET_SELF(cfunc.ptr()));
auto rec = (function_record *) c;
if (rec && rec->is_stateless &&
same_type(typeid(function_type), *reinterpret_cast<const std::type_info *>(rec->data[1]))) {
struct capture { function_type f; };
value = ((capture *) &rec->data)->f;
return true;
}
}
value = [func](Args... args) -> Return {
gil_scoped_acquire acq;
object retval(func(std::forward<Args>(args)...));
/* Visual studio 2015 parser issue: need parentheses around this expression */
return (retval.template cast<Return>());
};
return true;
}
template <typename Func>
static handle cast(Func &&f_, return_value_policy policy, handle /* parent */) {
if (!f_)
return none().inc_ref();
auto result = f_.template target<function_type>();
if (result)
return cpp_function(*result, policy).release();
else
return cpp_function(std::forward<Func>(f_), policy).release();
}
PYBIND11_TYPE_CASTER(type, _("Callable[[") + concat(make_caster<Args>::name...) + _("], ")
+ make_caster<retval_type>::name + _("]"));
};
NAMESPACE_END(detail)
NAMESPACE_END(PYBIND11_NAMESPACE)

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/*
pybind11/iostream.h -- Tools to assist with redirecting cout and cerr to Python
Copyright (c) 2017 Henry F. Schreiner
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 <streambuf>
#include <ostream>
#include <string>
#include <memory>
#include <iostream>
NAMESPACE_BEGIN(PYBIND11_NAMESPACE)
NAMESPACE_BEGIN(detail)
// Buffer that writes to Python instead of C++
class pythonbuf : public std::streambuf {
private:
using traits_type = std::streambuf::traits_type;
char d_buffer[1024];
object pywrite;
object pyflush;
int overflow(int c) {
if (!traits_type::eq_int_type(c, traits_type::eof())) {
*pptr() = traits_type::to_char_type(c);
pbump(1);
}
return sync() == 0 ? traits_type::not_eof(c) : traits_type::eof();
}
int sync() {
if (pbase() != pptr()) {
// This subtraction cannot be negative, so dropping the sign
str line(pbase(), static_cast<size_t>(pptr() - pbase()));
pywrite(line);
pyflush();
setp(pbase(), epptr());
}
return 0;
}
public:
pythonbuf(object pyostream)
: pywrite(pyostream.attr("write")),
pyflush(pyostream.attr("flush")) {
setp(d_buffer, d_buffer + sizeof(d_buffer) - 1);
}
/// Sync before destroy
~pythonbuf() {
sync();
}
};
NAMESPACE_END(detail)
/** \rst
This a move-only guard that redirects output.
.. code-block:: cpp
#include <pybind11/iostream.h>
...
{
py::scoped_ostream_redirect output;
std::cout << "Hello, World!"; // Python stdout
} // <-- return std::cout to normal
You can explicitly pass the c++ stream and the python object,
for example to guard stderr instead.
.. code-block:: cpp
{
py::scoped_ostream_redirect output{std::cerr, py::module::import("sys").attr("stderr")};
std::cerr << "Hello, World!";
}
\endrst */
class scoped_ostream_redirect {
protected:
std::streambuf *old;
std::ostream &costream;
detail::pythonbuf buffer;
public:
scoped_ostream_redirect(
std::ostream &costream = std::cout,
object pyostream = module::import("sys").attr("stdout"))
: costream(costream), buffer(pyostream) {
old = costream.rdbuf(&buffer);
}
~scoped_ostream_redirect() {
costream.rdbuf(old);
}
scoped_ostream_redirect(const scoped_ostream_redirect &) = delete;
scoped_ostream_redirect(scoped_ostream_redirect &&other) = default;
scoped_ostream_redirect &operator=(const scoped_ostream_redirect &) = delete;
scoped_ostream_redirect &operator=(scoped_ostream_redirect &&) = delete;
};
/** \rst
Like `scoped_ostream_redirect`, but redirects cerr by default. This class
is provided primary to make ``py::call_guard`` easier to make.
.. code-block:: cpp
m.def("noisy_func", &noisy_func,
py::call_guard<scoped_ostream_redirect,
scoped_estream_redirect>());
\endrst */
class scoped_estream_redirect : public scoped_ostream_redirect {
public:
scoped_estream_redirect(
std::ostream &costream = std::cerr,
object pyostream = module::import("sys").attr("stderr"))
: scoped_ostream_redirect(costream,pyostream) {}
};
NAMESPACE_BEGIN(detail)
// Class to redirect output as a context manager. C++ backend.
class OstreamRedirect {
bool do_stdout_;
bool do_stderr_;
std::unique_ptr<scoped_ostream_redirect> redirect_stdout;
std::unique_ptr<scoped_estream_redirect> redirect_stderr;
public:
OstreamRedirect(bool do_stdout = true, bool do_stderr = true)
: do_stdout_(do_stdout), do_stderr_(do_stderr) {}
void enter() {
if (do_stdout_)
redirect_stdout.reset(new scoped_ostream_redirect());
if (do_stderr_)
redirect_stderr.reset(new scoped_estream_redirect());
}
void exit() {
redirect_stdout.reset();
redirect_stderr.reset();
}
};
NAMESPACE_END(detail)
/** \rst
This is a helper function to add a C++ redirect context manager to Python
instead of using a C++ guard. To use it, add the following to your binding code:
.. code-block:: cpp
#include <pybind11/iostream.h>
...
py::add_ostream_redirect(m, "ostream_redirect");
You now have a Python context manager that redirects your output:
.. code-block:: python
with m.ostream_redirect():
m.print_to_cout_function()
This manager can optionally be told which streams to operate on:
.. code-block:: python
with m.ostream_redirect(stdout=true, stderr=true):
m.noisy_function_with_error_printing()
\endrst */
inline class_<detail::OstreamRedirect> add_ostream_redirect(module m, std::string name = "ostream_redirect") {
return class_<detail::OstreamRedirect>(m, name.c_str(), module_local())
.def(init<bool,bool>(), arg("stdout")=true, arg("stderr")=true)
.def("__enter__", &detail::OstreamRedirect::enter)
.def("__exit__", [](detail::OstreamRedirect &self_, args) { self_.exit(); });
}
NAMESPACE_END(PYBIND11_NAMESPACE)

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/*
pybind11/operator.h: Metatemplates for operator overloading
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"
#if defined(__clang__) && !defined(__INTEL_COMPILER)
# pragma clang diagnostic ignored "-Wunsequenced" // multiple unsequenced modifications to 'self' (when using def(py::self OP Type()))
#elif defined(_MSC_VER)
# pragma warning(push)
# pragma warning(disable: 4127) // warning C4127: Conditional expression is constant
#endif
NAMESPACE_BEGIN(PYBIND11_NAMESPACE)
NAMESPACE_BEGIN(detail)
/// Enumeration with all supported operator types
enum op_id : int {
op_add, op_sub, op_mul, op_div, op_mod, op_divmod, op_pow, op_lshift,
op_rshift, op_and, op_xor, op_or, op_neg, op_pos, op_abs, op_invert,
op_int, op_long, op_float, op_str, op_cmp, op_gt, op_ge, op_lt, op_le,
op_eq, op_ne, op_iadd, op_isub, op_imul, op_idiv, op_imod, op_ilshift,
op_irshift, op_iand, op_ixor, op_ior, op_complex, op_bool, op_nonzero,
op_repr, op_truediv, op_itruediv, op_hash
};
enum op_type : int {
op_l, /* base type on left */
op_r, /* base type on right */
op_u /* unary operator */
};
struct self_t { };
static const self_t self = self_t();
/// Type for an unused type slot
struct undefined_t { };
/// Don't warn about an unused variable
inline self_t __self() { return self; }
/// base template of operator implementations
template <op_id, op_type, typename B, typename L, typename R> struct op_impl { };
/// Operator implementation generator
template <op_id id, op_type ot, typename L, typename R> struct op_ {
template <typename Class, typename... Extra> void execute(Class &cl, const Extra&... extra) const {
using Base = typename Class::type;
using L_type = conditional_t<std::is_same<L, self_t>::value, Base, L>;
using R_type = conditional_t<std::is_same<R, self_t>::value, Base, R>;
using op = op_impl<id, ot, Base, L_type, R_type>;
cl.def(op::name(), &op::execute, is_operator(), extra...);
#if PY_MAJOR_VERSION < 3
if (id == op_truediv || id == op_itruediv)
cl.def(id == op_itruediv ? "__idiv__" : ot == op_l ? "__div__" : "__rdiv__",
&op::execute, is_operator(), extra...);
#endif
}
template <typename Class, typename... Extra> void execute_cast(Class &cl, const Extra&... extra) const {
using Base = typename Class::type;
using L_type = conditional_t<std::is_same<L, self_t>::value, Base, L>;
using R_type = conditional_t<std::is_same<R, self_t>::value, Base, R>;
using op = op_impl<id, ot, Base, L_type, R_type>;
cl.def(op::name(), &op::execute_cast, is_operator(), extra...);
#if PY_MAJOR_VERSION < 3
if (id == op_truediv || id == op_itruediv)
cl.def(id == op_itruediv ? "__idiv__" : ot == op_l ? "__div__" : "__rdiv__",
&op::execute, is_operator(), extra...);
#endif
}
};
#define PYBIND11_BINARY_OPERATOR(id, rid, op, expr) \
template <typename B, typename L, typename R> struct op_impl<op_##id, op_l, B, L, R> { \
static char const* name() { return "__" #id "__"; } \
static auto execute(const L &l, const R &r) -> decltype(expr) { return (expr); } \
static B execute_cast(const L &l, const R &r) { return B(expr); } \
}; \
template <typename B, typename L, typename R> struct op_impl<op_##id, op_r, B, L, R> { \
static char const* name() { return "__" #rid "__"; } \
static auto execute(const R &r, const L &l) -> decltype(expr) { return (expr); } \
static B execute_cast(const R &r, const L &l) { return B(expr); } \
}; \
inline op_<op_##id, op_l, self_t, self_t> op(const self_t &, const self_t &) { \
return op_<op_##id, op_l, self_t, self_t>(); \
} \
template <typename T> op_<op_##id, op_l, self_t, T> op(const self_t &, const T &) { \
return op_<op_##id, op_l, self_t, T>(); \
} \
template <typename T> op_<op_##id, op_r, T, self_t> op(const T &, const self_t &) { \
return op_<op_##id, op_r, T, self_t>(); \
}
#define PYBIND11_INPLACE_OPERATOR(id, op, expr) \
template <typename B, typename L, typename R> struct op_impl<op_##id, op_l, B, L, R> { \
static char const* name() { return "__" #id "__"; } \
static auto execute(L &l, const R &r) -> decltype(expr) { return expr; } \
static B execute_cast(L &l, const R &r) { return B(expr); } \
}; \
template <typename T> op_<op_##id, op_l, self_t, T> op(const self_t &, const T &) { \
return op_<op_##id, op_l, self_t, T>(); \
}
#define PYBIND11_UNARY_OPERATOR(id, op, expr) \
template <typename B, typename L> struct op_impl<op_##id, op_u, B, L, undefined_t> { \
static char const* name() { return "__" #id "__"; } \
static auto execute(const L &l) -> decltype(expr) { return expr; } \
static B execute_cast(const L &l) { return B(expr); } \
}; \
inline op_<op_##id, op_u, self_t, undefined_t> op(const self_t &) { \
return op_<op_##id, op_u, self_t, undefined_t>(); \
}
PYBIND11_BINARY_OPERATOR(sub, rsub, operator-, l - r)
PYBIND11_BINARY_OPERATOR(add, radd, operator+, l + r)
PYBIND11_BINARY_OPERATOR(mul, rmul, operator*, l * r)
PYBIND11_BINARY_OPERATOR(truediv, rtruediv, operator/, l / r)
PYBIND11_BINARY_OPERATOR(mod, rmod, operator%, l % r)
PYBIND11_BINARY_OPERATOR(lshift, rlshift, operator<<, l << r)
PYBIND11_BINARY_OPERATOR(rshift, rrshift, operator>>, l >> r)
PYBIND11_BINARY_OPERATOR(and, rand, operator&, l & r)
PYBIND11_BINARY_OPERATOR(xor, rxor, operator^, l ^ r)
PYBIND11_BINARY_OPERATOR(eq, eq, operator==, l == r)
PYBIND11_BINARY_OPERATOR(ne, ne, operator!=, l != r)
PYBIND11_BINARY_OPERATOR(or, ror, operator|, l | r)
PYBIND11_BINARY_OPERATOR(gt, lt, operator>, l > r)
PYBIND11_BINARY_OPERATOR(ge, le, operator>=, l >= r)
PYBIND11_BINARY_OPERATOR(lt, gt, operator<, l < r)
PYBIND11_BINARY_OPERATOR(le, ge, operator<=, l <= r)
//PYBIND11_BINARY_OPERATOR(pow, rpow, pow, std::pow(l, r))
PYBIND11_INPLACE_OPERATOR(iadd, operator+=, l += r)
PYBIND11_INPLACE_OPERATOR(isub, operator-=, l -= r)
PYBIND11_INPLACE_OPERATOR(imul, operator*=, l *= r)
PYBIND11_INPLACE_OPERATOR(itruediv, operator/=, l /= r)
PYBIND11_INPLACE_OPERATOR(imod, operator%=, l %= r)
PYBIND11_INPLACE_OPERATOR(ilshift, operator<<=, l <<= r)
PYBIND11_INPLACE_OPERATOR(irshift, operator>>=, l >>= r)
PYBIND11_INPLACE_OPERATOR(iand, operator&=, l &= r)
PYBIND11_INPLACE_OPERATOR(ixor, operator^=, l ^= r)
PYBIND11_INPLACE_OPERATOR(ior, operator|=, l |= r)
PYBIND11_UNARY_OPERATOR(neg, operator-, -l)
PYBIND11_UNARY_OPERATOR(pos, operator+, +l)
PYBIND11_UNARY_OPERATOR(abs, abs, std::abs(l))
PYBIND11_UNARY_OPERATOR(hash, hash, std::hash<L>()(l))
PYBIND11_UNARY_OPERATOR(invert, operator~, (~l))
PYBIND11_UNARY_OPERATOR(bool, operator!, !!l)
PYBIND11_UNARY_OPERATOR(int, int_, (int) l)
PYBIND11_UNARY_OPERATOR(float, float_, (double) l)
#undef PYBIND11_BINARY_OPERATOR
#undef PYBIND11_INPLACE_OPERATOR
#undef PYBIND11_UNARY_OPERATOR
NAMESPACE_END(detail)
using detail::self;
NAMESPACE_END(PYBIND11_NAMESPACE)
#if defined(_MSC_VER)
# pragma warning(pop)
#endif

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/*
pybind11/options.h: global settings that are configurable at runtime.
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 "detail/common.h"
NAMESPACE_BEGIN(PYBIND11_NAMESPACE)
class options {
public:
// Default RAII constructor, which leaves settings as they currently are.
options() : previous_state(global_state()) {}
// Class is non-copyable.
options(const options&) = delete;
options& operator=(const options&) = delete;
// Destructor, which restores settings that were in effect before.
~options() {
global_state() = previous_state;
}
// Setter methods (affect the global state):
options& disable_user_defined_docstrings() & { global_state().show_user_defined_docstrings = false; return *this; }
options& enable_user_defined_docstrings() & { global_state().show_user_defined_docstrings = true; return *this; }
options& disable_function_signatures() & { global_state().show_function_signatures = false; return *this; }
options& enable_function_signatures() & { global_state().show_function_signatures = true; return *this; }
// Getter methods (return the global state):
static bool show_user_defined_docstrings() { return global_state().show_user_defined_docstrings; }
static bool show_function_signatures() { return global_state().show_function_signatures; }
// This type is not meant to be allocated on the heap.
void* operator new(size_t) = delete;
private:
struct state {
bool show_user_defined_docstrings = true; //< Include user-supplied texts in docstrings.
bool show_function_signatures = true; //< Include auto-generated function signatures in docstrings.
};
static state &global_state() {
static state instance;
return instance;
}
state previous_state;
};
NAMESPACE_END(PYBIND11_NAMESPACE)

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/*
pybind11/stl.h: Transparent conversion for STL data types
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 <set>
#include <unordered_set>
#include <map>
#include <unordered_map>
#include <iostream>
#include <list>
#include <deque>
#include <valarray>
#if defined(_MSC_VER)
#pragma warning(push)
#pragma warning(disable: 4127) // warning C4127: Conditional expression is constant
#endif
#ifdef __has_include
// std::optional (but including it in c++14 mode isn't allowed)
# if defined(PYBIND11_CPP17) && __has_include(<optional>)
# include <optional>
# define PYBIND11_HAS_OPTIONAL 1
# endif
// std::experimental::optional (but not allowed in c++11 mode)
# if defined(PYBIND11_CPP14) && (__has_include(<experimental/optional>) && \
!__has_include(<optional>))
# include <experimental/optional>
# define PYBIND11_HAS_EXP_OPTIONAL 1
# endif
// std::variant
# if defined(PYBIND11_CPP17) && __has_include(<variant>)
# include <variant>
# define PYBIND11_HAS_VARIANT 1
# endif
#elif defined(_MSC_VER) && defined(PYBIND11_CPP17)
# include <optional>
# include <variant>
# define PYBIND11_HAS_OPTIONAL 1
# define PYBIND11_HAS_VARIANT 1
#endif
NAMESPACE_BEGIN(PYBIND11_NAMESPACE)
NAMESPACE_BEGIN(detail)
/// Extracts an const lvalue reference or rvalue reference for U based on the type of T (e.g. for
/// forwarding a container element). Typically used indirect via forwarded_type(), below.
template <typename T, typename U>
using forwarded_type = conditional_t<
std::is_lvalue_reference<T>::value, remove_reference_t<U> &, remove_reference_t<U> &&>;
/// Forwards a value U as rvalue or lvalue according to whether T is rvalue or lvalue; typically
/// used for forwarding a container's elements.
template <typename T, typename U>
forwarded_type<T, U> forward_like(U &&u) {
return std::forward<detail::forwarded_type<T, U>>(std::forward<U>(u));
}
template <typename Type, typename Key> struct set_caster {
using type = Type;
using key_conv = make_caster<Key>;
bool load(handle src, bool convert) {
if (!isinstance<pybind11::set>(src))
return false;
auto s = reinterpret_borrow<pybind11::set>(src);
value.clear();
for (auto entry : s) {
key_conv conv;
if (!conv.load(entry, convert))
return false;
value.insert(cast_op<Key &&>(std::move(conv)));
}
return true;
}
template <typename T>
static handle cast(T &&src, return_value_policy policy, handle parent) {
if (!std::is_lvalue_reference<T>::value)
policy = return_value_policy_override<Key>::policy(policy);
pybind11::set s;
for (auto &&value : src) {
auto value_ = reinterpret_steal<object>(key_conv::cast(forward_like<T>(value), policy, parent));
if (!value_ || !s.add(value_))
return handle();
}
return s.release();
}
PYBIND11_TYPE_CASTER(type, _("Set[") + key_conv::name + _("]"));
};
template <typename Type, typename Key, typename Value> struct map_caster {
using key_conv = make_caster<Key>;
using value_conv = make_caster<Value>;
bool load(handle src, bool convert) {
if (!isinstance<dict>(src))
return false;
auto d = reinterpret_borrow<dict>(src);
value.clear();
for (auto it : d) {
key_conv kconv;
value_conv vconv;
if (!kconv.load(it.first.ptr(), convert) ||
!vconv.load(it.second.ptr(), convert))
return false;
value.emplace(cast_op<Key &&>(std::move(kconv)), cast_op<Value &&>(std::move(vconv)));
}
return true;
}
template <typename T>
static handle cast(T &&src, return_value_policy policy, handle parent) {
dict d;
return_value_policy policy_key = policy;
return_value_policy policy_value = policy;
if (!std::is_lvalue_reference<T>::value) {
policy_key = return_value_policy_override<Key>::policy(policy_key);
policy_value = return_value_policy_override<Value>::policy(policy_value);
}
for (auto &&kv : src) {
auto key = reinterpret_steal<object>(key_conv::cast(forward_like<T>(kv.first), policy_key, parent));
auto value = reinterpret_steal<object>(value_conv::cast(forward_like<T>(kv.second), policy_value, parent));
if (!key || !value)
return handle();
d[key] = value;
}
return d.release();
}
PYBIND11_TYPE_CASTER(Type, _("Dict[") + key_conv::name + _(", ") + value_conv::name + _("]"));
};
template <typename Type, typename Value> struct list_caster {
using value_conv = make_caster<Value>;
bool load(handle src, bool convert) {
if (!isinstance<sequence>(src) || isinstance<str>(src))
return false;
auto s = reinterpret_borrow<sequence>(src);
value.clear();
reserve_maybe(s, &value);
for (auto it : s) {
value_conv conv;
if (!conv.load(it, convert))
return false;
value.push_back(cast_op<Value &&>(std::move(conv)));
}
return true;
}
private:
template <typename T = Type,
enable_if_t<std::is_same<decltype(std::declval<T>().reserve(0)), void>::value, int> = 0>
void reserve_maybe(sequence s, Type *) { value.reserve(s.size()); }
void reserve_maybe(sequence, void *) { }
public:
template <typename T>
static handle cast(T &&src, return_value_policy policy, handle parent) {
if (!std::is_lvalue_reference<T>::value)
policy = return_value_policy_override<Value>::policy(policy);
list l(src.size());
size_t index = 0;
for (auto &&value : src) {
auto value_ = reinterpret_steal<object>(value_conv::cast(forward_like<T>(value), policy, parent));
if (!value_)
return handle();
PyList_SET_ITEM(l.ptr(), (ssize_t) index++, value_.release().ptr()); // steals a reference
}
return l.release();
}
PYBIND11_TYPE_CASTER(Type, _("List[") + value_conv::name + _("]"));
};
template <typename Type, typename Alloc> struct type_caster<std::vector<Type, Alloc>>
: list_caster<std::vector<Type, Alloc>, Type> { };
template <typename Type, typename Alloc> struct type_caster<std::deque<Type, Alloc>>
: list_caster<std::deque<Type, Alloc>, Type> { };
template <typename Type, typename Alloc> struct type_caster<std::list<Type, Alloc>>
: list_caster<std::list<Type, Alloc>, Type> { };
template <typename ArrayType, typename Value, bool Resizable, size_t Size = 0> struct array_caster {
using value_conv = make_caster<Value>;
private:
template <bool R = Resizable>
bool require_size(enable_if_t<R, size_t> size) {
if (value.size() != size)
value.resize(size);
return true;
}
template <bool R = Resizable>
bool require_size(enable_if_t<!R, size_t> size) {
return size == Size;
}
public:
bool load(handle src, bool convert) {
if (!isinstance<sequence>(src))
return false;
auto l = reinterpret_borrow<sequence>(src);
if (!require_size(l.size()))
return false;
size_t ctr = 0;
for (auto it : l) {
value_conv conv;
if (!conv.load(it, convert))
return false;
value[ctr++] = cast_op<Value &&>(std::move(conv));
}
return true;
}
template <typename T>
static handle cast(T &&src, return_value_policy policy, handle parent) {
list l(src.size());
size_t index = 0;
for (auto &&value : src) {
auto value_ = reinterpret_steal<object>(value_conv::cast(forward_like<T>(value), policy, parent));
if (!value_)
return handle();
PyList_SET_ITEM(l.ptr(), (ssize_t) index++, value_.release().ptr()); // steals a reference
}
return l.release();
}
PYBIND11_TYPE_CASTER(ArrayType, _("List[") + value_conv::name + _<Resizable>(_(""), _("[") + _<Size>() + _("]")) + _("]"));
};
template <typename Type, size_t Size> struct type_caster<std::array<Type, Size>>
: array_caster<std::array<Type, Size>, Type, false, Size> { };
template <typename Type> struct type_caster<std::valarray<Type>>
: array_caster<std::valarray<Type>, Type, true> { };
template <typename Key, typename Compare, typename Alloc> struct type_caster<std::set<Key, Compare, Alloc>>
: set_caster<std::set<Key, Compare, Alloc>, Key> { };
template <typename Key, typename Hash, typename Equal, typename Alloc> struct type_caster<std::unordered_set<Key, Hash, Equal, Alloc>>
: set_caster<std::unordered_set<Key, Hash, Equal, Alloc>, Key> { };
template <typename Key, typename Value, typename Compare, typename Alloc> struct type_caster<std::map<Key, Value, Compare, Alloc>>
: map_caster<std::map<Key, Value, Compare, Alloc>, Key, Value> { };
template <typename Key, typename Value, typename Hash, typename Equal, typename Alloc> struct type_caster<std::unordered_map<Key, Value, Hash, Equal, Alloc>>
: map_caster<std::unordered_map<Key, Value, Hash, Equal, Alloc>, Key, Value> { };
// This type caster is intended to be used for std::optional and std::experimental::optional
template<typename T> struct optional_caster {
using value_conv = make_caster<typename T::value_type>;
template <typename T_>
static handle cast(T_ &&src, return_value_policy policy, handle parent) {
if (!src)
return none().inc_ref();
policy = return_value_policy_override<typename T::value_type>::policy(policy);
return value_conv::cast(*std::forward<T_>(src), policy, parent);
}
bool load(handle src, bool convert) {
if (!src) {
return false;
} else if (src.is_none()) {
return true; // default-constructed value is already empty
}
value_conv inner_caster;
if (!inner_caster.load(src, convert))
return false;
value.emplace(cast_op<typename T::value_type &&>(std::move(inner_caster)));
return true;
}
PYBIND11_TYPE_CASTER(T, _("Optional[") + value_conv::name + _("]"));
};
#if PYBIND11_HAS_OPTIONAL
template<typename T> struct type_caster<std::optional<T>>
: public optional_caster<std::optional<T>> {};
template<> struct type_caster<std::nullopt_t>
: public void_caster<std::nullopt_t> {};
#endif
#if PYBIND11_HAS_EXP_OPTIONAL
template<typename T> struct type_caster<std::experimental::optional<T>>
: public optional_caster<std::experimental::optional<T>> {};
template<> struct type_caster<std::experimental::nullopt_t>
: public void_caster<std::experimental::nullopt_t> {};
#endif
/// Visit a variant and cast any found type to Python
struct variant_caster_visitor {
return_value_policy policy;
handle parent;
using result_type = handle; // required by boost::variant in C++11
template <typename T>
result_type operator()(T &&src) const {
return make_caster<T>::cast(std::forward<T>(src), policy, parent);
}
};
/// Helper class which abstracts away variant's `visit` function. `std::variant` and similar
/// `namespace::variant` types which provide a `namespace::visit()` function are handled here
/// automatically using argument-dependent lookup. Users can provide specializations for other
/// variant-like classes, e.g. `boost::variant` and `boost::apply_visitor`.
template <template<typename...> class Variant>
struct visit_helper {
template <typename... Args>
static auto call(Args &&...args) -> decltype(visit(std::forward<Args>(args)...)) {
return visit(std::forward<Args>(args)...);
}
};
/// Generic variant caster
template <typename Variant> struct variant_caster;
template <template<typename...> class V, typename... Ts>
struct variant_caster<V<Ts...>> {
static_assert(sizeof...(Ts) > 0, "Variant must consist of at least one alternative.");
template <typename U, typename... Us>
bool load_alternative(handle src, bool convert, type_list<U, Us...>) {
auto caster = make_caster<U>();
if (caster.load(src, convert)) {
value = cast_op<U>(caster);
return true;
}
return load_alternative(src, convert, type_list<Us...>{});
}
bool load_alternative(handle, bool, type_list<>) { return false; }
bool load(handle src, bool convert) {
// Do a first pass without conversions to improve constructor resolution.
// E.g. `py::int_(1).cast<variant<double, int>>()` needs to fill the `int`
// slot of the variant. Without two-pass loading `double` would be filled
// because it appears first and a conversion is possible.
if (convert && load_alternative(src, false, type_list<Ts...>{}))
return true;
return load_alternative(src, convert, type_list<Ts...>{});
}
template <typename Variant>
static handle cast(Variant &&src, return_value_policy policy, handle parent) {
return visit_helper<V>::call(variant_caster_visitor{policy, parent},
std::forward<Variant>(src));
}
using Type = V<Ts...>;
PYBIND11_TYPE_CASTER(Type, _("Union[") + detail::concat(make_caster<Ts>::name...) + _("]"));
};
#if PYBIND11_HAS_VARIANT
template <typename... Ts>
struct type_caster<std::variant<Ts...>> : variant_caster<std::variant<Ts...>> { };
#endif
NAMESPACE_END(detail)
inline std::ostream &operator<<(std::ostream &os, const handle &obj) {
os << (std::string) str(obj);
return os;
}
NAMESPACE_END(PYBIND11_NAMESPACE)
#if defined(_MSC_VER)
#pragma warning(pop)
#endif

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/*
pybind11/std_bind.h: Binding generators for STL data types
Copyright (c) 2016 Sergey Lyskov and Wenzel Jakob
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 "detail/common.h"
#include "operators.h"
#include <algorithm>
#include <sstream>
NAMESPACE_BEGIN(PYBIND11_NAMESPACE)
NAMESPACE_BEGIN(detail)
/* SFINAE helper class used by 'is_comparable */
template <typename T> struct container_traits {
template <typename T2> static std::true_type test_comparable(decltype(std::declval<const T2 &>() == std::declval<const T2 &>())*);
template <typename T2> static std::false_type test_comparable(...);
template <typename T2> static std::true_type test_value(typename T2::value_type *);
template <typename T2> static std::false_type test_value(...);
template <typename T2> static std::true_type test_pair(typename T2::first_type *, typename T2::second_type *);
template <typename T2> static std::false_type test_pair(...);
static constexpr const bool is_comparable = std::is_same<std::true_type, decltype(test_comparable<T>(nullptr))>::value;
static constexpr const bool is_pair = std::is_same<std::true_type, decltype(test_pair<T>(nullptr, nullptr))>::value;
static constexpr const bool is_vector = std::is_same<std::true_type, decltype(test_value<T>(nullptr))>::value;
static constexpr const bool is_element = !is_pair && !is_vector;
};
/* Default: is_comparable -> std::false_type */
template <typename T, typename SFINAE = void>
struct is_comparable : std::false_type { };
/* For non-map data structures, check whether operator== can be instantiated */
template <typename T>
struct is_comparable<
T, enable_if_t<container_traits<T>::is_element &&
container_traits<T>::is_comparable>>
: std::true_type { };
/* For a vector/map data structure, recursively check the value type (which is std::pair for maps) */
template <typename T>
struct is_comparable<T, enable_if_t<container_traits<T>::is_vector>> {
static constexpr const bool value =
is_comparable<typename T::value_type>::value;
};
/* For pairs, recursively check the two data types */
template <typename T>
struct is_comparable<T, enable_if_t<container_traits<T>::is_pair>> {
static constexpr const bool value =
is_comparable<typename T::first_type>::value &&
is_comparable<typename T::second_type>::value;
};
/* Fallback functions */
template <typename, typename, typename... Args> void vector_if_copy_constructible(const Args &...) { }
template <typename, typename, typename... Args> void vector_if_equal_operator(const Args &...) { }
template <typename, typename, typename... Args> void vector_if_insertion_operator(const Args &...) { }
template <typename, typename, typename... Args> void vector_modifiers(const Args &...) { }
template<typename Vector, typename Class_>
void vector_if_copy_constructible(enable_if_t<is_copy_constructible<Vector>::value, Class_> &cl) {
cl.def(init<const Vector &>(), "Copy constructor");
}
template<typename Vector, typename Class_>
void vector_if_equal_operator(enable_if_t<is_comparable<Vector>::value, Class_> &cl) {
using T = typename Vector::value_type;
cl.def(self == self);
cl.def(self != self);
cl.def("count",
[](const Vector &v, const T &x) {
return std::count(v.begin(), v.end(), x);
},
arg("x"),
"Return the number of times ``x`` appears in the list"
);
cl.def("remove", [](Vector &v, const T &x) {
auto p = std::find(v.begin(), v.end(), x);
if (p != v.end())
v.erase(p);
else
throw value_error();
},
arg("x"),
"Remove the first item from the list whose value is x. "
"It is an error if there is no such item."
);
cl.def("__contains__",
[](const Vector &v, const T &x) {
return std::find(v.begin(), v.end(), x) != v.end();
},
arg("x"),
"Return true the container contains ``x``"
);
}
// Vector modifiers -- requires a copyable vector_type:
// (Technically, some of these (pop and __delitem__) don't actually require copyability, but it seems
// silly to allow deletion but not insertion, so include them here too.)
template <typename Vector, typename Class_>
void vector_modifiers(enable_if_t<is_copy_constructible<typename Vector::value_type>::value, Class_> &cl) {
using T = typename Vector::value_type;
using SizeType = typename Vector::size_type;
using DiffType = typename Vector::difference_type;
cl.def("append",
[](Vector &v, const T &value) { v.push_back(value); },
arg("x"),
"Add an item to the end of the list");
cl.def(init([](iterable it) {
auto v = std::unique_ptr<Vector>(new Vector());
v->reserve(len(it));
for (handle h : it)
v->push_back(h.cast<T>());
return v.release();
}));
cl.def("extend",
[](Vector &v, const Vector &src) {
v.insert(v.end(), src.begin(), src.end());
},
arg("L"),
"Extend the list by appending all the items in the given list"
);
cl.def("insert",
[](Vector &v, SizeType i, const T &x) {
if (i > v.size())
throw index_error();
v.insert(v.begin() + (DiffType) i, x);
},
arg("i") , arg("x"),
"Insert an item at a given position."
);
cl.def("pop",
[](Vector &v) {
if (v.empty())
throw index_error();
T t = v.back();
v.pop_back();
return t;
},
"Remove and return the last item"
);
cl.def("pop",
[](Vector &v, SizeType i) {
if (i >= v.size())
throw index_error();
T t = v[i];
v.erase(v.begin() + (DiffType) i);
return t;
},
arg("i"),
"Remove and return the item at index ``i``"
);
cl.def("__setitem__",
[](Vector &v, SizeType i, const T &t) {
if (i >= v.size())
throw index_error();
v[i] = t;
}
);
/// Slicing protocol
cl.def("__getitem__",
[](const Vector &v, slice slice) -> Vector * {
size_t start, stop, step, slicelength;
if (!slice.compute(v.size(), &start, &stop, &step, &slicelength))
throw error_already_set();
Vector *seq = new Vector();
seq->reserve((size_t) slicelength);
for (size_t i=0; i<slicelength; ++i) {
seq->push_back(v[start]);
start += step;
}
return seq;
},
arg("s"),
"Retrieve list elements using a slice object"
);
cl.def("__setitem__",
[](Vector &v, slice slice, const Vector &value) {
size_t start, stop, step, slicelength;
if (!slice.compute(v.size(), &start, &stop, &step, &slicelength))
throw error_already_set();
if (slicelength != value.size())
throw std::runtime_error("Left and right hand size of slice assignment have different sizes!");
for (size_t i=0; i<slicelength; ++i) {
v[start] = value[i];
start += step;
}
},
"Assign list elements using a slice object"
);
cl.def("__delitem__",
[](Vector &v, SizeType i) {
if (i >= v.size())
throw index_error();
v.erase(v.begin() + DiffType(i));
},
"Delete the list elements at index ``i``"
);
cl.def("__delitem__",
[](Vector &v, slice slice) {
size_t start, stop, step, slicelength;
if (!slice.compute(v.size(), &start, &stop, &step, &slicelength))
throw error_already_set();
if (step == 1 && false) {
v.erase(v.begin() + (DiffType) start, v.begin() + DiffType(start + slicelength));
} else {
for (size_t i = 0; i < slicelength; ++i) {
v.erase(v.begin() + DiffType(start));
start += step - 1;
}
}
},
"Delete list elements using a slice object"
);
}
// If the type has an operator[] that doesn't return a reference (most notably std::vector<bool>),
// we have to access by copying; otherwise we return by reference.
template <typename Vector> using vector_needs_copy = negation<
std::is_same<decltype(std::declval<Vector>()[typename Vector::size_type()]), typename Vector::value_type &>>;
// The usual case: access and iterate by reference
template <typename Vector, typename Class_>
void vector_accessor(enable_if_t<!vector_needs_copy<Vector>::value, Class_> &cl) {
using T = typename Vector::value_type;
using SizeType = typename Vector::size_type;
using ItType = typename Vector::iterator;
cl.def("__getitem__",
[](Vector &v, SizeType i) -> T & {
if (i >= v.size())
throw index_error();
return v[i];
},
return_value_policy::reference_internal // ref + keepalive
);
cl.def("__iter__",
[](Vector &v) {
return make_iterator<
return_value_policy::reference_internal, ItType, ItType, T&>(
v.begin(), v.end());
},
keep_alive<0, 1>() /* Essential: keep list alive while iterator exists */
);
}
// The case for special objects, like std::vector<bool>, that have to be returned-by-copy:
template <typename Vector, typename Class_>
void vector_accessor(enable_if_t<vector_needs_copy<Vector>::value, Class_> &cl) {
using T = typename Vector::value_type;
using SizeType = typename Vector::size_type;
using ItType = typename Vector::iterator;
cl.def("__getitem__",
[](const Vector &v, SizeType i) -> T {
if (i >= v.size())
throw index_error();
return v[i];
}
);
cl.def("__iter__",
[](Vector &v) {
return make_iterator<
return_value_policy::copy, ItType, ItType, T>(
v.begin(), v.end());
},
keep_alive<0, 1>() /* Essential: keep list alive while iterator exists */
);
}
template <typename Vector, typename Class_> auto vector_if_insertion_operator(Class_ &cl, std::string const &name)
-> decltype(std::declval<std::ostream&>() << std::declval<typename Vector::value_type>(), void()) {
using size_type = typename Vector::size_type;
cl.def("__repr__",
[name](Vector &v) {
std::ostringstream s;
s << name << '[';
for (size_type i=0; i < v.size(); ++i) {
s << v[i];
if (i != v.size() - 1)
s << ", ";
}
s << ']';
return s.str();
},
"Return the canonical string representation of this list."
);
}
// Provide the buffer interface for vectors if we have data() and we have a format for it
// GCC seems to have "void std::vector<bool>::data()" - doing SFINAE on the existence of data() is insufficient, we need to check it returns an appropriate pointer
template <typename Vector, typename = void>
struct vector_has_data_and_format : std::false_type {};
template <typename Vector>
struct vector_has_data_and_format<Vector, enable_if_t<std::is_same<decltype(format_descriptor<typename Vector::value_type>::format(), std::declval<Vector>().data()), typename Vector::value_type*>::value>> : std::true_type {};
// Add the buffer interface to a vector
template <typename Vector, typename Class_, typename... Args>
enable_if_t<detail::any_of<std::is_same<Args, buffer_protocol>...>::value>
vector_buffer(Class_& cl) {
using T = typename Vector::value_type;
static_assert(vector_has_data_and_format<Vector>::value, "There is not an appropriate format descriptor for this vector");
// numpy.h declares this for arbitrary types, but it may raise an exception and crash hard at runtime if PYBIND11_NUMPY_DTYPE hasn't been called, so check here
format_descriptor<T>::format();
cl.def_buffer([](Vector& v) -> buffer_info {
return buffer_info(v.data(), static_cast<ssize_t>(sizeof(T)), format_descriptor<T>::format(), 1, {v.size()}, {sizeof(T)});
});
cl.def(init([](buffer buf) {
auto info = buf.request();
if (info.ndim != 1 || info.strides[0] % static_cast<ssize_t>(sizeof(T)))
throw type_error("Only valid 1D buffers can be copied to a vector");
if (!detail::compare_buffer_info<T>::compare(info) || (ssize_t) sizeof(T) != info.itemsize)
throw type_error("Format mismatch (Python: " + info.format + " C++: " + format_descriptor<T>::format() + ")");
auto vec = std::unique_ptr<Vector>(new Vector());
vec->reserve((size_t) info.shape[0]);
T *p = static_cast<T*>(info.ptr);
ssize_t step = info.strides[0] / static_cast<ssize_t>(sizeof(T));
T *end = p + info.shape[0] * step;
for (; p != end; p += step)
vec->push_back(*p);
return vec.release();
}));
return;
}
template <typename Vector, typename Class_, typename... Args>
enable_if_t<!detail::any_of<std::is_same<Args, buffer_protocol>...>::value> vector_buffer(Class_&) {}
NAMESPACE_END(detail)
//
// std::vector
//
template <typename Vector, typename holder_type = std::unique_ptr<Vector>, typename... Args>
class_<Vector, holder_type> bind_vector(handle scope, std::string const &name, Args&&... args) {
using Class_ = class_<Vector, holder_type>;
// If the value_type is unregistered (e.g. a converting type) or is itself registered
// module-local then make the vector binding module-local as well:
using vtype = typename Vector::value_type;
auto vtype_info = detail::get_type_info(typeid(vtype));
bool local = !vtype_info || vtype_info->module_local;
Class_ cl(scope, name.c_str(), pybind11::module_local(local), std::forward<Args>(args)...);
// Declare the buffer interface if a buffer_protocol() is passed in
detail::vector_buffer<Vector, Class_, Args...>(cl);
cl.def(init<>());
// Register copy constructor (if possible)
detail::vector_if_copy_constructible<Vector, Class_>(cl);
// Register comparison-related operators and functions (if possible)
detail::vector_if_equal_operator<Vector, Class_>(cl);
// Register stream insertion operator (if possible)
detail::vector_if_insertion_operator<Vector, Class_>(cl, name);
// Modifiers require copyable vector value type
detail::vector_modifiers<Vector, Class_>(cl);
// Accessor and iterator; return by value if copyable, otherwise we return by ref + keep-alive
detail::vector_accessor<Vector, Class_>(cl);
cl.def("__bool__",
[](const Vector &v) -> bool {
return !v.empty();
},
"Check whether the list is nonempty"
);
cl.def("__len__", &Vector::size);
#if 0
// C++ style functions deprecated, leaving it here as an example
cl.def(init<size_type>());
cl.def("resize",
(void (Vector::*) (size_type count)) & Vector::resize,
"changes the number of elements stored");
cl.def("erase",
[](Vector &v, SizeType i) {
if (i >= v.size())
throw index_error();
v.erase(v.begin() + i);
}, "erases element at index ``i``");
cl.def("empty", &Vector::empty, "checks whether the container is empty");
cl.def("size", &Vector::size, "returns the number of elements");
cl.def("push_back", (void (Vector::*)(const T&)) &Vector::push_back, "adds an element to the end");
cl.def("pop_back", &Vector::pop_back, "removes the last element");
cl.def("max_size", &Vector::max_size, "returns the maximum possible number of elements");
cl.def("reserve", &Vector::reserve, "reserves storage");
cl.def("capacity", &Vector::capacity, "returns the number of elements that can be held in currently allocated storage");
cl.def("shrink_to_fit", &Vector::shrink_to_fit, "reduces memory usage by freeing unused memory");
cl.def("clear", &Vector::clear, "clears the contents");
cl.def("swap", &Vector::swap, "swaps the contents");
cl.def("front", [](Vector &v) {
if (v.size()) return v.front();
else throw index_error();
}, "access the first element");
cl.def("back", [](Vector &v) {
if (v.size()) return v.back();
else throw index_error();
}, "access the last element ");
#endif
return cl;
}
//
// std::map, std::unordered_map
//
NAMESPACE_BEGIN(detail)
/* Fallback functions */
template <typename, typename, typename... Args> void map_if_insertion_operator(const Args &...) { }
template <typename, typename, typename... Args> void map_assignment(const Args &...) { }
// Map assignment when copy-assignable: just copy the value
template <typename Map, typename Class_>
void map_assignment(enable_if_t<std::is_copy_assignable<typename Map::mapped_type>::value, Class_> &cl) {
using KeyType = typename Map::key_type;
using MappedType = typename Map::mapped_type;
cl.def("__setitem__",
[](Map &m, const KeyType &k, const MappedType &v) {
auto it = m.find(k);
if (it != m.end()) it->second = v;
else m.emplace(k, v);
}
);
}
// Not copy-assignable, but still copy-constructible: we can update the value by erasing and reinserting
template<typename Map, typename Class_>
void map_assignment(enable_if_t<
!std::is_copy_assignable<typename Map::mapped_type>::value &&
is_copy_constructible<typename Map::mapped_type>::value,
Class_> &cl) {
using KeyType = typename Map::key_type;
using MappedType = typename Map::mapped_type;
cl.def("__setitem__",
[](Map &m, const KeyType &k, const MappedType &v) {
// We can't use m[k] = v; because value type might not be default constructable
auto r = m.emplace(k, v);
if (!r.second) {
// value type is not copy assignable so the only way to insert it is to erase it first...
m.erase(r.first);
m.emplace(k, v);
}
}
);
}
template <typename Map, typename Class_> auto map_if_insertion_operator(Class_ &cl, std::string const &name)
-> decltype(std::declval<std::ostream&>() << std::declval<typename Map::key_type>() << std::declval<typename Map::mapped_type>(), void()) {
cl.def("__repr__",
[name](Map &m) {
std::ostringstream s;
s << name << '{';
bool f = false;
for (auto const &kv : m) {
if (f)
s << ", ";
s << kv.first << ": " << kv.second;
f = true;
}
s << '}';
return s.str();
},
"Return the canonical string representation of this map."
);
}
NAMESPACE_END(detail)
template <typename Map, typename holder_type = std::unique_ptr<Map>, typename... Args>
class_<Map, holder_type> bind_map(handle scope, const std::string &name, Args&&... args) {
using KeyType = typename Map::key_type;
using MappedType = typename Map::mapped_type;
using Class_ = class_<Map, holder_type>;
// If either type is a non-module-local bound type then make the map binding non-local as well;
// otherwise (e.g. both types are either module-local or converting) the map will be
// module-local.
auto tinfo = detail::get_type_info(typeid(MappedType));
bool local = !tinfo || tinfo->module_local;
if (local) {
tinfo = detail::get_type_info(typeid(KeyType));
local = !tinfo || tinfo->module_local;
}
Class_ cl(scope, name.c_str(), pybind11::module_local(local), std::forward<Args>(args)...);
cl.def(init<>());
// Register stream insertion operator (if possible)
detail::map_if_insertion_operator<Map, Class_>(cl, name);
cl.def("__bool__",
[](const Map &m) -> bool { return !m.empty(); },
"Check whether the map is nonempty"
);
cl.def("__iter__",
[](Map &m) { return make_key_iterator(m.begin(), m.end()); },
keep_alive<0, 1>() /* Essential: keep list alive while iterator exists */
);
cl.def("items",
[](Map &m) { return make_iterator(m.begin(), m.end()); },
keep_alive<0, 1>() /* Essential: keep list alive while iterator exists */
);
cl.def("__getitem__",
[](Map &m, const KeyType &k) -> MappedType & {
auto it = m.find(k);
if (it == m.end())
throw key_error();
return it->second;
},
return_value_policy::reference_internal // ref + keepalive
);
// Assignment provided only if the type is copyable
detail::map_assignment<Map, Class_>(cl);
cl.def("__delitem__",
[](Map &m, const KeyType &k) {
auto it = m.find(k);
if (it == m.end())
throw key_error();
m.erase(it);
}
);
cl.def("__len__", &Map::size);
return cl;
}
NAMESPACE_END(PYBIND11_NAMESPACE)

53
mmocr/models/textdet/postprocess/include/pybind11/typeid.h
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@ -1,53 +0,0 @@
/*
pybind11/typeid.h: Compiler-independent access to type identifiers
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 <cstdio>
#include <cstdlib>
#if defined(__GNUG__)
#include <cxxabi.h>
#endif
NAMESPACE_BEGIN(pybind11)
NAMESPACE_BEGIN(detail)
/// Erase all occurrences of a substring
inline void erase_all(std::string &string, const std::string &search) {
for (size_t pos = 0;;) {
pos = string.find(search, pos);
if (pos == std::string::npos) break;
string.erase(pos, search.length());
}
}
PYBIND11_NOINLINE inline void clean_type_id(std::string &name) {
#if defined(__GNUG__)
int status = 0;
std::unique_ptr<char, void (*)(void *)> res {
abi::__cxa_demangle(name.c_str(), nullptr, nullptr, &status), std::free };
if (status == 0)
name = res.get();
#else
detail::erase_all(name, "class ");
detail::erase_all(name, "struct ");
detail::erase_all(name, "enum ");
#endif
detail::erase_all(name, "pybind11::");
}
NAMESPACE_END(detail)
/// Return a string representation of a C++ type
template <typename T> static std::string type_id() {
std::string name(typeid(T).name());
detail::clean_type_id(name);
return name;
}
NAMESPACE_END(pybind11)

195
mmocr/models/textdet/postprocess/pan.cpp
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@ -1,195 +0,0 @@
// This implementation is from https://github.com/WenmuZhou/PAN.pytorch/blob/master/post_processing/pse.cpp
#include <queue>
#include <math.h>
#include <map>
#include <algorithm>
#include <vector>
#include <array>
#include "include/pybind11/pybind11.h"
#include "include/pybind11/numpy.h"
#include "include/pybind11/stl.h"
#include "include/pybind11/stl_bind.h"
namespace py = pybind11;
namespace panet{
py::array_t<uint8_t> assign_pixels(
py::array_t<uint8_t, py::array::c_style> text,
py::array_t<float, py::array::c_style> similarity_vectors,
py::array_t<int32_t, py::array::c_style> label_map,
int label_num,
float dis_threshold = 0.8)
{
auto pbuf_text = text.request();
auto pbuf_similarity_vectors = similarity_vectors.request();
auto pbuf_label_map = label_map.request();
if (pbuf_label_map.ndim != 2 || pbuf_label_map.shape[0]==0 || pbuf_label_map.shape[1]==0)
throw std::runtime_error("label map must have a shape of (h>0, w>0)");
int h = pbuf_label_map.shape[0];
int w = pbuf_label_map.shape[1];
if (pbuf_similarity_vectors.ndim != 3 || pbuf_similarity_vectors.shape[0]!=h || pbuf_similarity_vectors.shape[1]!=w || pbuf_similarity_vectors.shape[2]!=4 ||
pbuf_text.shape[0]!=h || pbuf_text.shape[1]!=w)
throw std::runtime_error("similarity_vectors must have a shape of (h,w,4) and text must have a shape of (h,w,4)");
//初始化结果
auto res = py::array_t<uint8_t>(pbuf_text.size);
auto pbuf_res = res.request();
// 获取 text similarity_vectors 和 label_map的指针
auto ptr_label_map = static_cast<int32_t *>(pbuf_label_map.ptr);
auto ptr_text = static_cast<uint8_t *>(pbuf_text.ptr);
auto ptr_similarity_vectors = static_cast<float *>(pbuf_similarity_vectors.ptr);
auto ptr_res = static_cast<uint8_t *>(pbuf_res.ptr);
std::queue<std::tuple<int, int, int32_t>> q;
// 计算各个kernel的similarity_vectors
std::vector<std::array<float, 5>> kernel_vector(label_num);
// 文本像素入队列
for (int i = 0; i<h; i++)
{
auto p_label_map = ptr_label_map + i*w;
auto p_res = ptr_res + i*w;
auto p_similarity_vectors = ptr_similarity_vectors + i*w*4;
for(int j = 0, k = 0; j<w && k < w * 4; j++,k+=4)
{
int32_t label = p_label_map[j];
if (label>0)
{
kernel_vector[label][0] += p_similarity_vectors[k];
kernel_vector[label][1] += p_similarity_vectors[k+1];
kernel_vector[label][2] += p_similarity_vectors[k+2];
kernel_vector[label][3] += p_similarity_vectors[k+3];
kernel_vector[label][4] += 1;
q.push(std::make_tuple(i, j, label));
}
p_res[j] = label;
}
}
for(int i=0;i<label_num;i++)
{
for (int j=0;j<4;j++)
{
kernel_vector[i][j] /= kernel_vector[i][4];
}
}
int dx[4] = {-1, 1, 0, 0};
int dy[4] = {0, 0, -1, 1};
while(!q.empty()){
//get each queue menber in q
auto q_n = q.front();
q.pop();
int y = std::get<0>(q_n);
int x = std::get<1>(q_n);
int32_t l = std::get<2>(q_n);
//store the edge pixel after one expansion
auto kernel_cv = kernel_vector[l];
for (int idx=0; idx<4; idx++)
{
int tmpy = y + dy[idx];
int tmpx = x + dx[idx];
auto p_res = ptr_res + tmpy*w;
if (tmpy<0 || tmpy>=h || tmpx<0 || tmpx>=w)
continue;
if (!ptr_text[tmpy*w+tmpx] || p_res[tmpx]>0)
continue;
// 计算距离
float dis = 0;
auto p_similarity_vectors = ptr_similarity_vectors + tmpy * w*4;
for(size_t i=0;i<4;i++)
{
dis += pow(kernel_cv[i] - p_similarity_vectors[tmpx*4 + i],2);
}
dis = sqrt(dis);
if(dis >= dis_threshold)
continue;
q.push(std::make_tuple(tmpy, tmpx, l));
p_res[tmpx]=l;
}
}
return res;
}
std::map<int,std::vector<float>> estimate_text_confidence(
py::array_t<int32_t, py::array::c_style> label_map,
py::array_t<float, py::array::c_style> score_map,
int label_num)
{
auto pbuf_label_map = label_map.request();
auto pbuf_score_map = score_map.request();
auto ptr_label_map = static_cast<int32_t *>(pbuf_label_map.ptr);
auto ptr_score_map = static_cast<float *>(pbuf_score_map.ptr);
int h = pbuf_label_map.shape[0];
int w = pbuf_label_map.shape[1];
std::map<int,std::vector<float>> point_dict;
std::vector<std::vector<float>> point_vector;
for(int i=0;i<label_num;i++)
{
std::vector<float> point;
point.push_back(0);
point.push_back(0);
point_vector.push_back(point);
}
for (int i = 0; i<h; i++)
{
auto p_label_map = ptr_label_map + i*w;
auto p_score_map = ptr_score_map + i*w;
for(int j = 0; j<w; j++)
{
int32_t label = p_label_map[j];
if(label==0)
{
continue;
}
float score = p_score_map[j];
point_vector[label][0] += score;
point_vector[label][1] += 1;
point_vector[label].push_back(j);
point_vector[label].push_back(i);
}
}
for(int i=0;i<label_num;i++)
{
if(point_vector[i].size() > 2)
{
point_vector[i][0] /= point_vector[i][1];
point_dict[i] = point_vector[i];
}
}
return point_dict;
}
std::vector<int> get_pixel_num(
py::array_t<int32_t, py::array::c_style> label_map,
int label_num)
{
auto pbuf_label_map = label_map.request();
auto ptr_label_map = static_cast<int32_t *>(pbuf_label_map.ptr);
int h = pbuf_label_map.shape[0];
int w = pbuf_label_map.shape[1];
std::vector<int> point_vector;
for(int i=0;i<label_num;i++){
point_vector.push_back(0);
}
for (int i = 0; i<h; i++){
auto p_label_map = ptr_label_map + i*w;
for(int j = 0; j<w; j++){
int32_t label = p_label_map[j];
if(label==0){
continue;
}
point_vector[label] += 1;
}
}
return point_vector;
}
}
PYBIND11_MODULE(pan, m){
m.def("assign_pixels", &panet::assign_pixels, " assign pixels to text kernels", py::arg("text"), py::arg("similarity_vectors"), py::arg("label_map"), py::arg("label_num"), py::arg("dis_threshold")=0.8);
m.def("estimate_text_confidence", &panet::estimate_text_confidence, " estimate average confidence for text instances", py::arg("label_map"), py::arg("score_map"), py::arg("label_num"));
m.def("get_pixel_num", &panet::get_pixel_num, " get each text instance pixel number", py::arg("label_map"), py::arg("label_num"));
}

128
mmocr/models/textdet/postprocess/pse.cpp
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// This implementation is from https://github.com/whai362/PSENet/blob/master/pse/adaptor.cpp
#include "pybind11/pybind11.h"
#include "pybind11/numpy.h"
#include "pybind11/stl.h"
#include "pybind11/stl_bind.h"
#include <iostream>
#include <queue>
using namespace std;
namespace py = pybind11;
namespace pse_adaptor {
class Point2d {
public:
int x;
int y;
Point2d() : x(0), y(0)
{}
Point2d(int _x, int _y) : x(_x), y(_y)
{}
};
void growing_text_line(const int *data,
vector<pybind11::ssize_t> &data_shape,
const int *label_map,
vector<pybind11::ssize_t> &label_shape,
int &label_num,
float &min_area,
vector<vector<int>> &text_line) {
std::vector<int> area(label_num + 1);
for (int x = 0; x < label_shape[0]; ++x) {
for (int y = 0; y < label_shape[1]; ++y) {
int label = label_map[x * label_shape[1] + y];
if (label == 0) continue;
area[label] += 1;
}
}
queue<Point2d> queue, next_queue;
for (int x = 0; x < label_shape[0]; ++x) {
vector<int> row(label_shape[1]);
for (int y = 0; y < label_shape[1]; ++y) {
int label = label_map[x * label_shape[1] + y];
if (label == 0) continue;
if (area[label] < min_area) continue;
Point2d point(x, y);
queue.push(point);
row[y] = label;
}
text_line.emplace_back(row);
}
int dx[] = {-1, 1, 0, 0};
int dy[] = {0, 0, -1, 1};
for (int kernel_id = data_shape[0] - 2; kernel_id >= 0; --kernel_id) {
while (!queue.empty()) {
Point2d point = queue.front();
queue.pop();
int x = point.x;
int y = point.y;
int label = text_line[x][y];
bool is_edge = true;
for (int d = 0; d < 4; ++d) {
int tmp_x = x + dx[d];
int tmp_y = y + dy[d];
if (tmp_x < 0 || tmp_x >= (int)text_line.size()) continue;
if (tmp_y < 0 || tmp_y >= (int)text_line[1].size()) continue;
int kernel_value = data[kernel_id * data_shape[1] * data_shape[2] + tmp_x * data_shape[2] + tmp_y];
if (kernel_value == 0) continue;
if (text_line[tmp_x][tmp_y] > 0) continue;
Point2d point(tmp_x, tmp_y);
queue.push(point);
text_line[tmp_x][tmp_y] = label;
is_edge = false;
}
if (is_edge) {
next_queue.push(point);
}
}
swap(queue, next_queue);
}
}
vector<vector<int>> pse(py::array_t<int, py::array::c_style | py::array::forcecast> quad_n9,
float min_area,
py::array_t<int32_t, py::array::c_style> label_map,
int label_num) {
auto buf = quad_n9.request();
auto data = static_cast<int *>(buf.ptr);
vector<pybind11::ssize_t> data_shape = buf.shape;
auto buf_label_map = label_map.request();
auto data_label_map = static_cast<int32_t *>(buf_label_map.ptr);
vector<pybind11::ssize_t> label_map_shape = buf_label_map.shape;
vector<vector<int>> text_line;
growing_text_line(data,
data_shape,
data_label_map,
label_map_shape,
label_num,
min_area,
text_line);
return text_line;
}
}
PYBIND11_PLUGIN(pse) {
py::module m("pse", "pse");
m.def("pse", &pse_adaptor::pse, "pse");
return m.ptr();
}

39
mmocr/models/textdet/postprocess/wrapper.py
View File

@ -2,6 +2,7 @@ import cv2
import numpy as np
import pyclipper
import torch
from mmcv.ops import contour_expand, pixel_group
from numpy.linalg import norm
from shapely.geometry import Polygon
from skimage.morphology import skeletonize
@ -36,7 +37,6 @@ def pan_decode(preds,
min_text_confidence=0.5,
min_kernel_confidence=0.5,
min_text_avg_confidence=0.85,
min_kernel_area=0,
min_text_area=16):
"""Convert scores to quadrangles via post processing in PANet. This is
partially adapted from https://github.com/WenmuZhou/PAN.pytorch.
@ -47,13 +47,11 @@ def pan_decode(preds,
min_text_confidence (float): The minimal text confidence.
min_kernel_confidence (float): The minimal kernel confidence.
min_text_avg_confidence (float): The minimal text average confidence.
min_kernel_area (int): The minimal text kernel area.
min_text_area (int): The minimal text instance region area.
Returns:
boundaries: (list[list[float]]): The instance boundary and its
instance confidence list.
"""
from .pan import assign_pixels, estimate_text_confidence, get_pixel_num
preds[:2, :, :] = torch.sigmoid(preds[:2, :, :])
preds = preds.detach().cpu().numpy()
@ -64,28 +62,16 @@ def pan_decode(preds,
region_num, labels = cv2.connectedComponents(
kernel.astype(np.uint8), connectivity=4)
valid_kernel_inx = []
region_pixel_num = get_pixel_num(labels, region_num)
# from inx 1. 0: meaningless.
for region_idx in range(1, region_num):
if region_pixel_num[region_idx] < min_kernel_area:
continue
valid_kernel_inx.append(region_idx)
# assign pixels to valid kernels
assignment = assign_pixels(
text.astype(np.uint8), embeddings, labels, region_num, 0.8)
assignment = assignment.reshape(text.shape)
contours, _ = cv2.findContours((kernel * 255).astype(np.uint8),
cv2.RETR_LIST, cv2.CHAIN_APPROX_NONE)
kernel_contours = np.zeros(text.shape, dtype='uint8')
cv2.drawContours(kernel_contours, contours, -1, 255)
text_points = pixel_group(text_score, text, embeddings, labels,
kernel_contours, region_num,
min_text_avg_confidence)
boundaries = []
# compute text avg confidence
text_points = estimate_text_confidence(assignment, text_score, region_num)
for text_inx, text_point in text_points.items():
if text_inx not in valid_kernel_inx:
continue
for text_inx, text_point in enumerate(text_points):
text_confidence = text_point[0]
text_point = text_point[2:]
text_point = np.array(text_point, dtype=int).reshape(-1, 2)
@ -133,17 +119,16 @@ def pse_decode(preds,
score = score.data.cpu().numpy().astype(np.float32) # to numpy
kernel_masks = kernel_masks.data.cpu().numpy().astype(np.uint8) # to numpy
from .pse import pse
region_num, labels = cv2.connectedComponents(
kernel_masks[-1], connectivity=4)
# labels = pse(kernel_masks, min_kernel_area)
labels = pse(kernel_masks, min_kernel_area, labels, region_num)
labels = contour_expand(kernel_masks, labels, min_kernel_area, region_num)
labels = np.array(labels)
label_num = np.max(labels) + 1
label_num = np.max(labels)
boundaries = []
for i in range(1, label_num):
for i in range(1, label_num + 1):
points = np.array(np.where(labels == i)).transpose((1, 0))[:, ::-1]
area = points.shape[0]
score_instance = np.mean(score[labels == i])

3
mmocr/models/utils/__init__.py
View File

@ -1,3 +0,0 @@
from .ops.rroi_align import RROIAlign
__all__ = ['RROIAlign']

3
mmocr/models/utils/ops/rroi_align/__init__.py
View File

@ -1,3 +0,0 @@
from .rroi_align import RROIAlign
__all__ = ['RROIAlign']

46
mmocr/models/utils/ops/rroi_align/csrc/csc/RROIAlign.h
View File

@ -1,46 +0,0 @@
// Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
#pragma once
#include "cpu/vision.h"
#ifdef WITH_CUDA
#include "cuda/vision.h"
#endif
// Interface for Python
std::tuple<at::Tensor, at::Tensor, at::Tensor> RROIAlign_forward(const at::Tensor& input,
const at::Tensor& rois,
const float spatial_scale,
const int pooled_height,
const int pooled_width) {
if (input.type().is_cuda()) {
#ifdef WITH_CUDA
return RROIAlign_forward_cuda(input, rois, spatial_scale, pooled_height, pooled_width);
#else
AT_ERROR("Not compiled with GPU support");
#endif
}
AT_ERROR("Not implemented on the CPU");
//return RROIAlign_forward_cpu(input, rois, spatial_scale, pooled_height, pooled_width, sampling_ratio);
}
at::Tensor RROIAlign_backward(const at::Tensor& grad,
const at::Tensor& rois,
const at::Tensor& con_idx_x,
const at::Tensor& con_idx_y,
const float spatial_scale,
const int pooled_height,
const int pooled_width,
const int batch_size,
const int channels,
const int height,
const int width) {
if (grad.type().is_cuda()) {
#ifdef WITH_CUDA
return RROIAlign_backward_cuda(grad, rois, con_idx_x, con_idx_y, spatial_scale, pooled_height, pooled_width, batch_size, channels, height, width);
#else
AT_ERROR("Not compiled with GPU support");
#endif
}
AT_ERROR("Not implemented on the CPU");
}

257
mmocr/models/utils/ops/rroi_align/csrc/csc/cpu/ROIAlign_cpu.cpp
View File

@ -1,257 +0,0 @@
// Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
#include "vision.h"
// implementation taken from Caffe2
template <typename T>
struct PreCalc {
int pos1;
int pos2;
int pos3;
int pos4;
T w1;
T w2;
T w3;
T w4;
};
template <typename T>
void pre_calc_for_bilinear_interpolate(
const int height,
const int width,
const int pooled_height,
const int pooled_width,
const int iy_upper,
const int ix_upper,
T roi_start_h,
T roi_start_w,
T bin_size_h,
T bin_size_w,
int roi_bin_grid_h,
int roi_bin_grid_w,
std::vector<PreCalc<T>>& pre_calc) {
int pre_calc_index = 0;
for (int ph = 0; ph < pooled_height; ph++) {
for (int pw = 0; pw < pooled_width; pw++) {
for (int iy = 0; iy < iy_upper; iy++) {
const T yy = roi_start_h + ph * bin_size_h +
static_cast<T>(iy + .5f) * bin_size_h /
static_cast<T>(roi_bin_grid_h); // e.g., 0.5, 1.5
for (int ix = 0; ix < ix_upper; ix++) {
const T xx = roi_start_w + pw * bin_size_w +
static_cast<T>(ix + .5f) * bin_size_w /
static_cast<T>(roi_bin_grid_w);
T x = xx;
T y = yy;
// deal with: inverse elements are out of feature map boundary
if (y < -1.0 || y > height || x < -1.0 || x > width) {
// empty
PreCalc<T> pc;
pc.pos1 = 0;
pc.pos2 = 0;
pc.pos3 = 0;
pc.pos4 = 0;
pc.w1 = 0;
pc.w2 = 0;
pc.w3 = 0;
pc.w4 = 0;
pre_calc[pre_calc_index] = pc;
pre_calc_index += 1;
continue;
}
if (y <= 0) {
y = 0;
}
if (x <= 0) {
x = 0;
}
int y_low = (int)y;
int x_low = (int)x;
int y_high;
int x_high;
if (y_low >= height - 1) {
y_high = y_low = height - 1;
y = (T)y_low;
} else {
y_high = y_low + 1;
}
if (x_low >= width - 1) {
x_high = x_low = width - 1;
x = (T)x_low;
} else {
x_high = x_low + 1;
}
T ly = y - y_low;
T lx = x - x_low;
T hy = 1. - ly, hx = 1. - lx;
T w1 = hy * hx, w2 = hy * lx, w3 = ly * hx, w4 = ly * lx;
// save weights and indeces
PreCalc<T> pc;
pc.pos1 = y_low * width + x_low;
pc.pos2 = y_low * width + x_high;
pc.pos3 = y_high * width + x_low;
pc.pos4 = y_high * width + x_high;
pc.w1 = w1;
pc.w2 = w2;
pc.w3 = w3;
pc.w4 = w4;
pre_calc[pre_calc_index] = pc;
pre_calc_index += 1;
}
}
}
}
}
template <typename T>
void ROIAlignForward_cpu_kernel(
const int nthreads,
const T* bottom_data,
const T& spatial_scale,
const int channels,
const int height,
const int width,
const int pooled_height,
const int pooled_width,
const int sampling_ratio,
const T* bottom_rois,
//int roi_cols,
T* top_data) {
//AT_ASSERT(roi_cols == 4 || roi_cols == 5);
int roi_cols = 5;
int n_rois = nthreads / channels / pooled_width / pooled_height;
// (n, c, ph, pw) is an element in the pooled output
// can be parallelized using omp
// #pragma omp parallel for num_threads(32)
for (int n = 0; n < n_rois; n++) {
int index_n = n * channels * pooled_width * pooled_height;
// roi could have 4 or 5 columns
const T* offset_bottom_rois = bottom_rois + n * roi_cols;
int roi_batch_ind = 0;
if (roi_cols == 5) {
roi_batch_ind = offset_bottom_rois[0];
offset_bottom_rois++;
}
// Do not using rounding; this implementation detail is critical
T roi_start_w = offset_bottom_rois[0] * spatial_scale;
T roi_start_h = offset_bottom_rois[1] * spatial_scale;
T roi_end_w = offset_bottom_rois[2] * spatial_scale;
T roi_end_h = offset_bottom_rois[3] * spatial_scale;
// T roi_start_w = round(offset_bottom_rois[0] * spatial_scale);
// T roi_start_h = round(offset_bottom_rois[1] * spatial_scale);
// T roi_end_w = round(offset_bottom_rois[2] * spatial_scale);
// T roi_end_h = round(offset_bottom_rois[3] * spatial_scale);
// Force malformed ROIs to be 1x1
T roi_width = std::max(roi_end_w - roi_start_w, (T)1.);
T roi_height = std::max(roi_end_h - roi_start_h, (T)1.);
T bin_size_h = static_cast<T>(roi_height) / static_cast<T>(pooled_height);
T bin_size_w = static_cast<T>(roi_width) / static_cast<T>(pooled_width);
// We use roi_bin_grid to sample the grid and mimic integral
int roi_bin_grid_h = (sampling_ratio > 0)
? sampling_ratio
: ceil(roi_height / pooled_height); // e.g., = 2
int roi_bin_grid_w =
(sampling_ratio > 0) ? sampling_ratio : ceil(roi_width / pooled_width);
// We do average (integral) pooling inside a bin
const T count = roi_bin_grid_h * roi_bin_grid_w; // e.g. = 4
// we want to precalculate indeces and weights shared by all chanels,
// this is the key point of optimiation
std::vector<PreCalc<T>> pre_calc(
roi_bin_grid_h * roi_bin_grid_w * pooled_width * pooled_height);
pre_calc_for_bilinear_interpolate(
height,
width,
pooled_height,
pooled_width,
roi_bin_grid_h,
roi_bin_grid_w,
roi_start_h,
roi_start_w,
bin_size_h,
bin_size_w,
roi_bin_grid_h,
roi_bin_grid_w,
pre_calc);
for (int c = 0; c < channels; c++) {
int index_n_c = index_n + c * pooled_width * pooled_height;
const T* offset_bottom_data =
bottom_data + (roi_batch_ind * channels + c) * height * width;
int pre_calc_index = 0;
for (int ph = 0; ph < pooled_height; ph++) {
for (int pw = 0; pw < pooled_width; pw++) {
int index = index_n_c + ph * pooled_width + pw;
T output_val = 0.;
for (int iy = 0; iy < roi_bin_grid_h; iy++) {
for (int ix = 0; ix < roi_bin_grid_w; ix++) {
PreCalc<T> pc = pre_calc[pre_calc_index];
output_val += pc.w1 * offset_bottom_data[pc.pos1] +
pc.w2 * offset_bottom_data[pc.pos2] +
pc.w3 * offset_bottom_data[pc.pos3] +
pc.w4 * offset_bottom_data[pc.pos4];
pre_calc_index += 1;
}
}
output_val /= count;
top_data[index] = output_val;
} // for pw
} // for ph
} // for c
} // for n
}
at::Tensor ROIAlign_forward_cpu(const at::Tensor& input,
const at::Tensor& rois,
const float spatial_scale,
const int pooled_height,
const int pooled_width,
const int sampling_ratio) {
AT_ASSERTM(!input.type().is_cuda(), "input must be a CPU tensor");
AT_ASSERTM(!rois.type().is_cuda(), "rois must be a CPU tensor");
auto num_rois = rois.size(0);
auto channels = input.size(1);
auto height = input.size(2);
auto width = input.size(3);
auto output = at::empty({num_rois, channels, pooled_height, pooled_width}, input.options());
auto output_size = num_rois * pooled_height * pooled_width * channels;
if (output.numel() == 0) {
return output;
}
AT_DISPATCH_FLOATING_TYPES(input.type(), "ROIAlign_forward", [&] {
ROIAlignForward_cpu_kernel<scalar_t>(
output_size,
input.data<scalar_t>(),
spatial_scale,
channels,
height,
width,
pooled_height,
pooled_width,
sampling_ratio,
rois.data<scalar_t>(),
output.data<scalar_t>());
});
return output;
}

11
mmocr/models/utils/ops/rroi_align/csrc/csc/cpu/vision.h
View File

@ -1,11 +0,0 @@
// Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
#pragma once
#include <torch/extension.h>
at::Tensor ROIAlign_forward_cpu(const at::Tensor& input,
const at::Tensor& rois,
const float spatial_scale,
const int pooled_height,
const int pooled_width,
const int sampling_ratio);

346
mmocr/models/utils/ops/rroi_align/csrc/csc/cuda/ROIAlign_cuda.cu
View File

@ -1,346 +0,0 @@
// Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
#include <ATen/ATen.h>
#include <ATen/cuda/CUDAContext.h>
#include <THC/THC.h>
#include <THC/THCAtomics.cuh>
#include <THC/THCDeviceUtils.cuh>
// TODO make it in a common file
#define CUDA_1D_KERNEL_LOOP(i, n) \
for (int i = blockIdx.x * blockDim.x + threadIdx.x; i < n; \
i += blockDim.x * gridDim.x)
template <typename T>
__device__ T bilinear_interpolate(const T* bottom_data,
const int height, const int width,
T y, T x,
const int index /* index for debug only*/) {
// deal with cases that inverse elements are out of feature map boundary
if (y < -1.0 || y > height || x < -1.0 || x > width) {
//empty
return 0;
}
if (y <= 0) y = 0;
if (x <= 0) x = 0;
int y_low = (int) y;
int x_low = (int) x;
int y_high;
int x_high;
if (y_low >= height - 1) {
y_high = y_low = height - 1;
y = (T) y_low;
} else {
y_high = y_low + 1;
}
if (x_low >= width - 1) {
x_high = x_low = width - 1;
x = (T) x_low;
} else {
x_high = x_low + 1;
}
T ly = y - y_low;
T lx = x - x_low;
T hy = 1. - ly, hx = 1. - lx;
// do bilinear interpolation
T v1 = bottom_data[y_low * width + x_low];
T v2 = bottom_data[y_low * width + x_high];
T v3 = bottom_data[y_high * width + x_low];
T v4 = bottom_data[y_high * width + x_high];
T w1 = hy * hx, w2 = hy * lx, w3 = ly * hx, w4 = ly * lx;
T val = (w1 * v1 + w2 * v2 + w3 * v3 + w4 * v4);
return val;
}
template <typename T>
__global__ void RoIAlignForward(const int nthreads, const T* bottom_data,
const T spatial_scale, const int channels,
const int height, const int width,
const int pooled_height, const int pooled_width,
const int sampling_ratio,
const T* bottom_rois, T* top_data) {
CUDA_1D_KERNEL_LOOP(index, nthreads) {
// (n, c, ph, pw) is an element in the pooled output
int pw = index % pooled_width;
int ph = (index / pooled_width) % pooled_height;
int c = (index / pooled_width / pooled_height) % channels;
int n = index / pooled_width / pooled_height / channels;
const T* offset_bottom_rois = bottom_rois + n * 5;
int roi_batch_ind = offset_bottom_rois[0];
// Do not using rounding; this implementation detail is critical
T roi_start_w = offset_bottom_rois[1] * spatial_scale;
T roi_start_h = offset_bottom_rois[2] * spatial_scale;
T roi_end_w = offset_bottom_rois[3] * spatial_scale;
T roi_end_h = offset_bottom_rois[4] * spatial_scale;
// T roi_start_w = round(offset_bottom_rois[1] * spatial_scale);
// T roi_start_h = round(offset_bottom_rois[2] * spatial_scale);
// T roi_end_w = round(offset_bottom_rois[3] * spatial_scale);
// T roi_end_h = round(offset_bottom_rois[4] * spatial_scale);
// Force malformed ROIs to be 1x1
T roi_width = max(roi_end_w - roi_start_w, (T)1.);
T roi_height = max(roi_end_h - roi_start_h, (T)1.);
T bin_size_h = static_cast<T>(roi_height) / static_cast<T>(pooled_height);
T bin_size_w = static_cast<T>(roi_width) / static_cast<T>(pooled_width);
const T* offset_bottom_data = bottom_data + (roi_batch_ind * channels + c) * height * width;
// We use roi_bin_grid to sample the grid and mimic integral
int roi_bin_grid_h = (sampling_ratio > 0) ? sampling_ratio : ceilf(roi_height / pooled_height); // e.g., = 2
int roi_bin_grid_w = (sampling_ratio > 0) ? sampling_ratio : ceilf(roi_width / pooled_width);
// We do average (integral) pooling inside a bin
const T count = roi_bin_grid_h * roi_bin_grid_w; // e.g. = 4
T output_val = 0.;
for (int iy = 0; iy < roi_bin_grid_h; iy ++) // e.g., iy = 0, 1
{
const T y = roi_start_h + ph * bin_size_h + static_cast<T>(iy + .5f) * bin_size_h / static_cast<T>(roi_bin_grid_h); // e.g., 0.5, 1.5
for (int ix = 0; ix < roi_bin_grid_w; ix ++)
{
const T x = roi_start_w + pw * bin_size_w + static_cast<T>(ix + .5f) * bin_size_w / static_cast<T>(roi_bin_grid_w);
T val = bilinear_interpolate(offset_bottom_data, height, width, y, x, index);
output_val += val;
}
}
output_val /= count;
top_data[index] = output_val;
}
}
template <typename T>
__device__ void bilinear_interpolate_gradient(
const int height, const int width,
T y, T x,
T & w1, T & w2, T & w3, T & w4,
int & x_low, int & x_high, int & y_low, int & y_high,
const int index /* index for debug only*/) {
// deal with cases that inverse elements are out of feature map boundary
if (y < -1.0 || y > height || x < -1.0 || x > width) {
//empty
w1 = w2 = w3 = w4 = 0.;
x_low = x_high = y_low = y_high = -1;
return;
}
if (y <= 0) y = 0;
if (x <= 0) x = 0;
y_low = (int) y;
x_low = (int) x;
if (y_low >= height - 1) {
y_high = y_low = height - 1;
y = (T) y_low;
} else {
y_high = y_low + 1;
}
if (x_low >= width - 1) {
x_high = x_low = width - 1;
x = (T) x_low;
} else {
x_high = x_low + 1;
}
T ly = y - y_low;
T lx = x - x_low;
T hy = 1. - ly, hx = 1. - lx;
// reference in forward
// T v1 = bottom_data[y_low * width + x_low];
// T v2 = bottom_data[y_low * width + x_high];
// T v3 = bottom_data[y_high * width + x_low];
// T v4 = bottom_data[y_high * width + x_high];
// T val = (w1 * v1 + w2 * v2 + w3 * v3 + w4 * v4);
w1 = hy * hx, w2 = hy * lx, w3 = ly * hx, w4 = ly * lx;
return;
}
template <typename T>
__global__ void RoIAlignBackwardFeature(const int nthreads, const T* top_diff,
const int num_rois, const T spatial_scale,
const int channels, const int height, const int width,
const int pooled_height, const int pooled_width,
const int sampling_ratio,
T* bottom_diff,
const T* bottom_rois) {
CUDA_1D_KERNEL_LOOP(index, nthreads) {
// (n, c, ph, pw) is an element in the pooled output
int pw = index % pooled_width;
int ph = (index / pooled_width) % pooled_height;
int c = (index / pooled_width / pooled_height) % channels;
int n = index / pooled_width / pooled_height / channels;
const T* offset_bottom_rois = bottom_rois + n * 5;
int roi_batch_ind = offset_bottom_rois[0];
// Do not using rounding; this implementation detail is critical
T roi_start_w = offset_bottom_rois[1] * spatial_scale;
T roi_start_h = offset_bottom_rois[2] * spatial_scale;
T roi_end_w = offset_bottom_rois[3] * spatial_scale;
T roi_end_h = offset_bottom_rois[4] * spatial_scale;
// T roi_start_w = round(offset_bottom_rois[1] * spatial_scale);
// T roi_start_h = round(offset_bottom_rois[2] * spatial_scale);
// T roi_end_w = round(offset_bottom_rois[3] * spatial_scale);
// T roi_end_h = round(offset_bottom_rois[4] * spatial_scale);
// Force malformed ROIs to be 1x1
T roi_width = max(roi_end_w - roi_start_w, (T)1.);
T roi_height = max(roi_end_h - roi_start_h, (T)1.);
T bin_size_h = static_cast<T>(roi_height) / static_cast<T>(pooled_height);
T bin_size_w = static_cast<T>(roi_width) / static_cast<T>(pooled_width);
T* offset_bottom_diff = bottom_diff + (roi_batch_ind * channels + c) * height * width;
int top_offset = (n * channels + c) * pooled_height * pooled_width;
const T* offset_top_diff = top_diff + top_offset;
const T top_diff_this_bin = offset_top_diff[ph * pooled_width + pw];
// We use roi_bin_grid to sample the grid and mimic integral
int roi_bin_grid_h = (sampling_ratio > 0) ? sampling_ratio : ceilf(roi_height / pooled_height); // e.g., = 2
int roi_bin_grid_w = (sampling_ratio > 0) ? sampling_ratio : ceilf(roi_width / pooled_width);
// We do average (integral) pooling inside a bin
const T count = roi_bin_grid_h * roi_bin_grid_w; // e.g. = 4
for (int iy = 0; iy < roi_bin_grid_h; iy ++) // e.g., iy = 0, 1
{
const T y = roi_start_h + ph * bin_size_h + static_cast<T>(iy + .5f) * bin_size_h / static_cast<T>(roi_bin_grid_h); // e.g., 0.5, 1.5
for (int ix = 0; ix < roi_bin_grid_w; ix ++)
{
const T x = roi_start_w + pw * bin_size_w + static_cast<T>(ix + .5f) * bin_size_w / static_cast<T>(roi_bin_grid_w);
T w1, w2, w3, w4;
int x_low, x_high, y_low, y_high;
bilinear_interpolate_gradient(height, width, y, x,
w1, w2, w3, w4,
x_low, x_high, y_low, y_high,
index);
T g1 = top_diff_this_bin * w1 / count;
T g2 = top_diff_this_bin * w2 / count;
T g3 = top_diff_this_bin * w3 / count;
T g4 = top_diff_this_bin * w4 / count;
if (x_low >= 0 && x_high >= 0 && y_low >= 0 && y_high >= 0)
{
atomicAdd(offset_bottom_diff + y_low * width + x_low, static_cast<T>(g1));
atomicAdd(offset_bottom_diff + y_low * width + x_high, static_cast<T>(g2));
atomicAdd(offset_bottom_diff + y_high * width + x_low, static_cast<T>(g3));
atomicAdd(offset_bottom_diff + y_high * width + x_high, static_cast<T>(g4));
} // if
} // ix
} // iy
} // CUDA_1D_KERNEL_LOOP
} // RoIAlignBackward
at::Tensor ROIAlign_forward_cuda(const at::Tensor& input,
const at::Tensor& rois,
const float spatial_scale,
const int pooled_height,
const int pooled_width,
const int sampling_ratio) {
AT_ASSERTM(input.type().is_cuda(), "input must be a CUDA tensor");
AT_ASSERTM(rois.type().is_cuda(), "rois must be a CUDA tensor");
auto num_rois = rois.size(0);
auto channels = input.size(1);
auto height = input.size(2);
auto width = input.size(3);
auto output = at::empty({num_rois, channels, pooled_height, pooled_width}, input.options());
auto output_size = num_rois * pooled_height * pooled_width * channels;
cudaStream_t stream = at::cuda::getCurrentCUDAStream();
dim3 grid(std::min(THCCeilDiv((long)output_size, 512L), 4096L));
dim3 block(512);
if (output.numel() == 0) {
THCudaCheck(cudaGetLastError());
return output;
}
AT_DISPATCH_FLOATING_TYPES(input.type(), "ROIAlign_forward", [&] {
RoIAlignForward<scalar_t><<<grid, block, 0, stream>>>(
output_size,
input.contiguous().data<scalar_t>(),
spatial_scale,
channels,
height,
width,
pooled_height,
pooled_width,
sampling_ratio,
rois.contiguous().data<scalar_t>(),
output.data<scalar_t>());
});
THCudaCheck(cudaGetLastError());
return output;
}
// TODO remove the dependency on input and use instead its sizes -> save memory
at::Tensor ROIAlign_backward_cuda(const at::Tensor& grad,
const at::Tensor& rois,
const float spatial_scale,
const int pooled_height,
const int pooled_width,
const int batch_size,
const int channels,
const int height,
const int width,
const int sampling_ratio) {
AT_ASSERTM(grad.type().is_cuda(), "grad must be a CUDA tensor");
AT_ASSERTM(rois.type().is_cuda(), "rois must be a CUDA tensor");
auto num_rois = rois.size(0);
auto grad_input = at::zeros({batch_size, channels, height, width}, grad.options());
cudaStream_t stream = at::cuda::getCurrentCUDAStream();
dim3 grid(std::min(THCCeilDiv((long)grad.numel(), 512L), 4096L));
dim3 block(512);
// handle possibly empty gradients
if (grad.numel() == 0) {
THCudaCheck(cudaGetLastError());
return grad_input;
}
AT_DISPATCH_FLOATING_TYPES(grad.type(), "ROIAlign_backward", [&] {
RoIAlignBackwardFeature<scalar_t><<<grid, block, 0, stream>>>(
grad.numel(),
grad.contiguous().data<scalar_t>(),
num_rois,
spatial_scale,
channels,
height,
width,
pooled_height,
pooled_width,
sampling_ratio,
grad_input.data<scalar_t>(),
rois.contiguous().data<scalar_t>());
});
THCudaCheck(cudaGetLastError());
return grad_input;
}

202
mmocr/models/utils/ops/rroi_align/csrc/csc/cuda/ROIPool_cuda.cu
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@ -1,202 +0,0 @@
// Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
#include <ATen/ATen.h>
#include <ATen/cuda/CUDAContext.h>
#include <THC/THC.h>
#include <THC/THCAtomics.cuh>
#include <THC/THCDeviceUtils.cuh>
// TODO make it in a common file
#define CUDA_1D_KERNEL_LOOP(i, n) \
for (int i = blockIdx.x * blockDim.x + threadIdx.x; i < n; \
i += blockDim.x * gridDim.x)
template <typename T>
__global__ void RoIPoolFForward(const int nthreads, const T* bottom_data,
const T spatial_scale, const int channels, const int height,
const int width, const int pooled_height, const int pooled_width,
const T* bottom_rois, T* top_data, int* argmax_data) {
CUDA_1D_KERNEL_LOOP(index, nthreads) {
// (n, c, ph, pw) is an element in the pooled output
int pw = index % pooled_width;
int ph = (index / pooled_width) % pooled_height;
int c = (index / pooled_width / pooled_height) % channels;
int n = index / pooled_width / pooled_height / channels;
const T* offset_bottom_rois = bottom_rois + n * 5;
int roi_batch_ind = offset_bottom_rois[0];
int roi_start_w = roundf(offset_bottom_rois[1] * spatial_scale);
int roi_start_h = roundf(offset_bottom_rois[2] * spatial_scale);
int roi_end_w = roundf(offset_bottom_rois[3] * spatial_scale);
int roi_end_h = roundf(offset_bottom_rois[4] * spatial_scale);
// Force malformed ROIs to be 1x1
int roi_width = max(roi_end_w - roi_start_w + 1, 1);
int roi_height = max(roi_end_h - roi_start_h + 1, 1);
T bin_size_h = static_cast<T>(roi_height)
/ static_cast<T>(pooled_height);
T bin_size_w = static_cast<T>(roi_width)
/ static_cast<T>(pooled_width);
int hstart = static_cast<int>(floorf(static_cast<T>(ph)
* bin_size_h));
int wstart = static_cast<int>(floorf(static_cast<T>(pw)
* bin_size_w));
int hend = static_cast<int>(ceilf(static_cast<T>(ph + 1)
* bin_size_h));
int wend = static_cast<int>(ceilf(static_cast<T>(pw + 1)
* bin_size_w));
// Add roi offsets and clip to input boundaries
hstart = min(max(hstart + roi_start_h, 0), height);
hend = min(max(hend + roi_start_h, 0), height);
wstart = min(max(wstart + roi_start_w, 0), width);
wend = min(max(wend + roi_start_w, 0), width);
bool is_empty = (hend <= hstart) || (wend <= wstart);
// Define an empty pooling region to be zero
T maxval = is_empty ? 0 : -FLT_MAX;
// If nothing is pooled, argmax = -1 causes nothing to be backprop'd
int maxidx = -1;
const T* offset_bottom_data =
bottom_data + (roi_batch_ind * channels + c) * height * width;
for (int h = hstart; h < hend; ++h) {
for (int w = wstart; w < wend; ++w) {
int bottom_index = h * width + w;
if (offset_bottom_data[bottom_index] > maxval) {
maxval = offset_bottom_data[bottom_index];
maxidx = bottom_index;
}
}
}
top_data[index] = maxval;
argmax_data[index] = maxidx;
}
}
template <typename T>
__global__ void RoIPoolFBackward(const int nthreads, const T* top_diff,
const int* argmax_data, const int num_rois, const T spatial_scale,
const int channels, const int height, const int width,
const int pooled_height, const int pooled_width, T* bottom_diff,
const T* bottom_rois) {
CUDA_1D_KERNEL_LOOP(index, nthreads) {
// (n, c, ph, pw) is an element in the pooled output
int pw = index % pooled_width;
int ph = (index / pooled_width) % pooled_height;
int c = (index / pooled_width / pooled_height) % channels;
int n = index / pooled_width / pooled_height / channels;
const T* offset_bottom_rois = bottom_rois + n * 5;
int roi_batch_ind = offset_bottom_rois[0];
int bottom_offset = (roi_batch_ind * channels + c) * height * width;
int top_offset = (n * channels + c) * pooled_height * pooled_width;
const T* offset_top_diff = top_diff + top_offset;
T* offset_bottom_diff = bottom_diff + bottom_offset;
const int* offset_argmax_data = argmax_data + top_offset;
int argmax = offset_argmax_data[ph * pooled_width + pw];
if (argmax != -1) {
atomicAdd(
offset_bottom_diff + argmax,
static_cast<T>(offset_top_diff[ph * pooled_width + pw]));
}
}
}
std::tuple<at::Tensor, at::Tensor> ROIPool_forward_cuda(const at::Tensor& input,
const at::Tensor& rois,
const float spatial_scale,
const int pooled_height,
const int pooled_width) {
AT_ASSERTM(input.type().is_cuda(), "input must be a CUDA tensor");
AT_ASSERTM(rois.type().is_cuda(), "rois must be a CUDA tensor");
auto num_rois = rois.size(0);
auto channels = input.size(1);
auto height = input.size(2);
auto width = input.size(3);
auto output = at::empty({num_rois, channels, pooled_height, pooled_width}, input.options());
auto output_size = num_rois * pooled_height * pooled_width * channels;
auto argmax = at::zeros({num_rois, channels, pooled_height, pooled_width}, input.options().dtype(at::kInt));
cudaStream_t stream = at::cuda::getCurrentCUDAStream();
dim3 grid(std::min(THCCeilDiv((long)output_size, 512L), 4096L));
dim3 block(512);
if (output.numel() == 0) {
THCudaCheck(cudaGetLastError());
return std::make_tuple(output, argmax);
}
AT_DISPATCH_FLOATING_TYPES(input.type(), "ROIPool_forward", [&] {
RoIPoolFForward<scalar_t><<<grid, block, 0, stream>>>(
output_size,
input.contiguous().data<scalar_t>(),
spatial_scale,
channels,
height,
width,
pooled_height,
pooled_width,
rois.contiguous().data<scalar_t>(),
output.data<scalar_t>(),
argmax.data<int>());
});
THCudaCheck(cudaGetLastError());
return std::make_tuple(output, argmax);
}
// TODO remove the dependency on input and use instead its sizes -> save memory
at::Tensor ROIPool_backward_cuda(const at::Tensor& grad,
const at::Tensor& input,
const at::Tensor& rois,
const at::Tensor& argmax,
const float spatial_scale,
const int pooled_height,
const int pooled_width,
const int batch_size,
const int channels,
const int height,
const int width) {
AT_ASSERTM(grad.type().is_cuda(), "grad must be a CUDA tensor");
AT_ASSERTM(rois.type().is_cuda(), "rois must be a CUDA tensor");
// TODO add more checks
auto num_rois = rois.size(0);
auto grad_input = at::zeros({batch_size, channels, height, width}, grad.options());
cudaStream_t stream = at::cuda::getCurrentCUDAStream();
dim3 grid(std::min(THCCeilDiv((long)grad.numel(), 512L), 4096L));
dim3 block(512);
// handle possibly empty gradients
if (grad.numel() == 0) {
THCudaCheck(cudaGetLastError());
return grad_input;
}
AT_DISPATCH_FLOATING_TYPES(grad.type(), "ROIPool_backward", [&] {
RoIPoolFBackward<scalar_t><<<grid, block, 0, stream>>>(
grad.numel(),
grad.contiguous().data<scalar_t>(),
argmax.data<int>(),
num_rois,
spatial_scale,
channels,
height,
width,
pooled_height,
pooled_width,
grad_input.data<scalar_t>(),
rois.contiguous().data<scalar_t>());
});
THCudaCheck(cudaGetLastError());
return grad_input;
}

375
mmocr/models/utils/ops/rroi_align/csrc/csc/cuda/RROIAlign_cuda.cu
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@ -1,375 +0,0 @@
// Copyright (c) Jianqi Ma. All Rights Reserved.
#include <ATen/ATen.h>
#include <ATen/cuda/CUDAContext.h>
#include <THC/THC.h>
#include <THC/THCAtomics.cuh>
#include <THC/THCDeviceUtils.cuh>
#include <stdio.h>
#include <math.h>
#include <float.h>
//#include "rroi_alignment_kernel.h"
#define CUDA_1D_KERNEL_LOOP(i, n) \
for (int i = blockIdx.x * blockDim.x + threadIdx.x; i < n; \
i += blockDim.x * gridDim.x)
template <typename T>
__global__ void RROIAlignForward(
const int nthreads,
const T* bottom_data,
const T spatial_scale,
int height,
int width,
int channels,
const int pooled_height,
const int pooled_width,
const T* bottom_rois,
T* top_data,
float* con_idx_x,
float* con_idx_y)
{
CUDA_1D_KERNEL_LOOP(index, nthreads)
{
// +0.5 shift removed
int imageWidth = width;
int imageHeight = height;
// (n, c, ph, pw) is an element in the pooled output
int n = index;
int pw = n % pooled_width;
n /= pooled_width;
int ph = n % pooled_height;
n /= pooled_height;
int c = n % channels;
n /= channels;
const T* offset_bottom_rois = bottom_rois + n * 7; //= 7 is rois dimension 0
int roi_batch_ind = offset_bottom_rois[0];
T cx = offset_bottom_rois[1];
T cy = offset_bottom_rois[2];
T h = offset_bottom_rois[3];
T w = offset_bottom_rois[4];
//T angle = offset_bottom_rois[5]/180.0*3.1415926535;
T Alpha = offset_bottom_rois[5];
T Beta = offset_bottom_rois[6];
//TransformPrepare
T dx = -pooled_width/2.0;
T dy = -pooled_height/2.0;
T Sx = w*spatial_scale/pooled_width;
T Sy = h*spatial_scale/pooled_height;
//T Alpha = cos(angle);
//T Beta = sin(angle);
T Dx = cx*spatial_scale;
T Dy = cy*spatial_scale;
T M[2][3];
M[0][0] = Alpha*Sx;
M[0][1] = Beta*Sy;
M[0][2] = Alpha*Sx*dx+Beta*Sy*dy+Dx;
M[1][0] = -Beta*Sx;
M[1][1] = Alpha*Sy;
M[1][2] = -Beta*Sx*dx+Alpha*Sy*dy+Dy;
T P[8];
P[0] = M[0][0]*pw+M[0][1]*ph+M[0][2];
P[1] = M[1][0]*pw+M[1][1]*ph+M[1][2];
P[2] = M[0][0]*pw+M[0][1]*(ph+1)+M[0][2];
P[3] = M[1][0]*pw+M[1][1]*(ph+1)+M[1][2];
P[4] = M[0][0]*(pw+1)+M[0][1]*ph+M[0][2];
P[5] = M[1][0]*(pw+1)+M[1][1]*ph+M[1][2];
P[6] = M[0][0]*(pw+1)+M[0][1]*(ph+1)+M[0][2];
P[7] = M[1][0]*(pw+1)+M[1][1]*(ph+1)+M[1][2];
T leftMost = (max(roundf(min(min(P[0],P[2]),min(P[4],P[6]))),0.0));
T rightMost= (min(roundf(max(max(P[0],P[2]),max(P[4],P[6]))),imageWidth-1.0));
T topMost= (max(roundf(min(min(P[1],P[3]),min(P[5],P[7]))),0.0));
T bottomMost= (min(roundf(max(max(P[1],P[3]),max(P[5],P[7]))),imageHeight-1.0));
//float maxval = 0;
//int maxidx = -1;
const T* offset_bottom_data = bottom_data + (roi_batch_ind * channels + c) * height * width;
//float AB[2];
//AB[0] = P[2] - P[0];
//AB[1] = P[3] - P[1];
//float ABAB = AB[0]*AB[0] +AB[1]*AB[1];
//float AC[2];
//AC[0] = P[4] - P[0];
//AC[1] = P[5] - P[1];
//float ACAC = AC[0]*AC[0] + AC[1]*AC[1];
float bin_cx = (leftMost + rightMost) / 2.0; // shift
float bin_cy = (topMost + bottomMost) / 2.0;
int bin_l = (int)floorf(bin_cx);
int bin_r = (int)ceilf(bin_cx);
int bin_t = (int)floorf(bin_cy);
int bin_b = (int)ceilf(bin_cy);
T lt_value = 0.0;
if (bin_t > 0 && bin_l > 0 && bin_t < height && bin_l < width)
lt_value = offset_bottom_data[bin_t * width + bin_l];
T rt_value = 0.0;
if (bin_t > 0 && bin_r > 0 && bin_t < height && bin_r < width)
rt_value = offset_bottom_data[bin_t * width + bin_r];
T lb_value = 0.0;
if (bin_b > 0 && bin_l > 0 && bin_b < height && bin_l < width)
lb_value = offset_bottom_data[bin_b * width + bin_l];
T rb_value = 0.0;
if (bin_b > 0 && bin_r > 0 && bin_b < height && bin_r < width)
rb_value = offset_bottom_data[bin_b * width + bin_r];
T rx = bin_cx - floorf(bin_cx);
T ry = bin_cy - floorf(bin_cy);
T wlt = (1.0 - rx) * (1.0 - ry);
T wrt = rx * (1.0 - ry);
T wrb = rx * ry;
T wlb = (1.0 - rx) * ry;
T inter_val = 0.0;
inter_val += lt_value * wlt;
inter_val += rt_value * wrt;
inter_val += rb_value * wrb;
inter_val += lb_value * wlb;
atomicAdd(top_data + index, static_cast<T>(inter_val));
atomicAdd(con_idx_x + index, static_cast<float>(bin_cx));
atomicAdd(con_idx_y + index, static_cast<float>(bin_cy));
//top_data[index] = static_cast<T>(inter_val);
//con_idx_x[index] = bin_cx;
//con_idx_y[index] = bin_cy;
}
}
/**
int RROIAlignForwardLaucher(
const float* bottom_data, const float spatial_scale, const int num_rois, const int height,
const int width, const int channels, const int pooled_height,
const int pooled_width, const float* bottom_rois,
float* top_data, float* con_idx_x, float* con_idx_y, const float* im_info, cudaStream_t stream)
{
const int kThreadsPerBlock = 1024;
const int output_size = num_rois * pooled_height * pooled_width * channels;
cudaError_t err;
RROIAlignForward<<<(output_size + kThreadsPerBlock - 1) / kThreadsPerBlock, kThreadsPerBlock, 0, stream>>>(
output_size, bottom_data, spatial_scale, height, width, channels, pooled_height,
pooled_width, bottom_rois, top_data, con_idx_x, con_idx_y, im_info);
err = cudaGetLastError();
if(cudaSuccess != err)
{
fprintf( stderr, "RRoI forward cudaCheckError() failed : %s\n", cudaGetErrorString( err ) );
exit( -1 );
}
return 1;
}
*/
//ROIAlign_forward_cuda
//std::tuple<at::Tensor, at::Tensor> ROIPool_forward_cuda(const at::Tensor& input,
// const at::Tensor& rois,
// const float spatial_scale,
// const int pooled_height,
// const int pooled_width)
std::tuple<at::Tensor, at::Tensor, at::Tensor> RROIAlign_forward_cuda(
const at::Tensor& input,
const at::Tensor& rois,
const float spatial_scale,
const int pooled_height,
const int pooled_width)
{
AT_ASSERTM(input.type().is_cuda(), "input must be a CUDA tensor");
AT_ASSERTM(rois.type().is_cuda(), "rois must be a CUDA tensor");
auto num_rois = rois.size(0);
auto channels = input.size(1);
auto height = input.size(2);
auto width = input.size(3);
auto output = at::zeros({num_rois, channels, pooled_height, pooled_width}, input.options());
auto output_size = num_rois * pooled_height * pooled_width * channels;
auto con_idx_x = at::zeros({num_rois, channels, pooled_height, pooled_width}, input.options().dtype(at::kFloat));
auto con_idx_y = at::zeros({num_rois, channels, pooled_height, pooled_width}, input.options().dtype(at::kFloat));
dim3 grid(std::min(THCCeilDiv((long)output_size, 512L), 4096L));
dim3 block(512);
//const int kThreadsPerBlock = 1024;
cudaStream_t stream = at::cuda::getCurrentCUDAStream();
if (output.numel() == 0) {
THCudaCheck(cudaGetLastError());
return std::make_tuple(output, con_idx_x, con_idx_y);//, con_idx_y; //std::make_tuple(
}
AT_DISPATCH_FLOATING_TYPES(input.type(), "RROIAlign_forward", [&] {
RROIAlignForward<scalar_t><<<grid, block, 0, stream>>>(
output_size,
input.contiguous().data<scalar_t>(),
spatial_scale,
height,
width,
channels,
pooled_height,
pooled_width,
rois.contiguous().data<scalar_t>(),
output.data<scalar_t>(),
con_idx_x.data<float>(),
con_idx_y.data<float>());
}
);
THCudaCheck(cudaGetLastError());
return std::make_tuple(output, con_idx_x, con_idx_y);
}
template <typename T>
__global__ void RROIAlignBackward(
const int nthreads,
const T* top_diff,
const float* con_idx_x,
const float* con_idx_y,
const int num_rois,
const float spatial_scale,
const int height,
const int width,
const int channels,
const int pooled_height,
const int pooled_width,
T* bottom_diff,
const T* bottom_rois) {
CUDA_1D_KERNEL_LOOP(index, nthreads)
{
// (n, c, ph, pw) is an element in the pooled output
int n = index;
//int w = n % width;
n /= pooled_width;
//int h = n % height;
n /= pooled_height;
int c = n % channels;
n /= channels;
const T* offset_bottom_rois = bottom_rois + n * 7;
int roi_batch_ind = offset_bottom_rois[0];
T* offset_bottom_diff = bottom_diff + (roi_batch_ind * channels + c) * height * width;
//int bottom_index = argmax_data[index];
float bw = con_idx_x[index];
float bh = con_idx_y[index];
//if (bh > 0.00001 && bw > 0.00001 && bw < height-1 && bw < width-1){
int bin_xs = int(floorf(bw));
int bin_ys = int(floorf(bh));
float rx = bw - float(bin_xs);
float ry = bh - float(bin_ys);
T wlt = (1.0 - rx) * (1.0 - ry);
T wrt = rx * (1.0 - ry);
T wrb = rx * ry;
T wlb = (1.0 - rx) * ry;
// if(bottom_index >= 0) // original != 0 maybe wrong
// bottom_diff[bottom_index]+=top_diff[index] ;
//int min_x = bin_xs, 0), width - 1);
//int min_y = min(max(bin_ys, 0), height - 1);
//int max_x = max(min(bin_xs + 1, width - 1), 0);
//int max_y = max(min(bin_ys + 1, height - 1), 0);
int min_x = (int)floorf(bw);
int max_x = (int)ceilf(bw);
int min_y = (int)floorf(bh);
int max_y = (int)ceilf(bh);
T top_diff_of_bin = top_diff[index];
T v1 = wlt * top_diff_of_bin;
T v2 = wrt * top_diff_of_bin;
T v3 = wrb * top_diff_of_bin;
T v4 = wlb * top_diff_of_bin;
// Atomic add
if (min_y > 0 && min_x > 0 && min_y < height - 1 && min_x < width - 1)
atomicAdd(offset_bottom_diff + min_y * width + min_x, static_cast<T>(v1));
if (min_y > 0 && max_x < width - 1 && min_y < height - 1 && max_x > 0)
atomicAdd(offset_bottom_diff + min_y * width + max_x, static_cast<T>(v2));
if (max_y < height - 1 && max_x < width - 1 && max_y > 0 && max_x > 0)
atomicAdd(offset_bottom_diff + max_y * width + max_x, static_cast<T>(v3));
if (max_y < height - 1 && min_x > 0 && max_y > 0 && min_x < width - 1)
atomicAdd(offset_bottom_diff + max_y * width + min_x, static_cast<T>(v4));
//}
}
}
// TODO remove the dependency on input and use instead its sizes -> save memory
at::Tensor RROIAlign_backward_cuda(const at::Tensor& grad,
const at::Tensor& rois,
const at::Tensor& con_idx_x,
const at::Tensor& con_idx_y,
const float spatial_scale,
const int pooled_height,
const int pooled_width,
const int batch_size,
const int channels,
const int height,
const int width) {
AT_ASSERTM(grad.type().is_cuda(), "grad must be a CUDA tensor");
AT_ASSERTM(rois.type().is_cuda(), "rois must be a CUDA tensor");
// TODO add more checks
auto num_rois = rois.size(0);
auto grad_input = at::zeros({batch_size, channels, height, width}, grad.options());
cudaStream_t stream = at::cuda::getCurrentCUDAStream();
dim3 grid(std::min(THCCeilDiv((long)grad.numel(), 512L), 4096L));
dim3 block(512);
// handle possibly empty gradients
if (grad.numel() == 0) {
THCudaCheck(cudaGetLastError());
return grad_input;
}
AT_DISPATCH_FLOATING_TYPES(grad.type(), "RROIAlign_backward", [&] {
RROIAlignBackward<scalar_t><<<grid, block, 0, stream>>>(
grad.numel(),
grad.contiguous().data<scalar_t>(),
con_idx_x.data<float>(),
con_idx_y.data<float>(),
num_rois,
spatial_scale,
height,
width,
channels,
pooled_height,
pooled_width,
grad_input.data<scalar_t>(),
rois.contiguous().data<scalar_t>());
});
THCudaCheck(cudaGetLastError());
return grad_input;
}

25
mmocr/models/utils/ops/rroi_align/csrc/csc/cuda/vision.h
View File

@ -1,25 +0,0 @@
// Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
#pragma once
#include <torch/extension.h>
std::tuple<at::Tensor, at::Tensor, at::Tensor> RROIAlign_forward_cuda(const at::Tensor& input,
const at::Tensor& rois,
const float spatial_scale,
const int pooled_height,
const int pooled_width);
at::Tensor RROIAlign_backward_cuda(const at::Tensor& grad,
const at::Tensor& rois,
const at::Tensor& con_idx_x,
const at::Tensor& con_idx_y,
const float spatial_scale,
const int pooled_height,
const int pooled_width,
const int batch_size,
const int channels,
const int height,
const int width);
at::Tensor compute_flow_cuda(const at::Tensor& boxes,
const int height,
const int width);

10
mmocr/models/utils/ops/rroi_align/csrc/csc/vision.cpp
View File

@ -1,10 +0,0 @@
// Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved.
#include "RROIAlign.h"
PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) {
m.def("rroi_align_forward", &RROIAlign_forward, "RROIAlign_forward");
m.def("rroi_align_backward", &RROIAlign_backward, "RROIAlign_backward");
}

57
mmocr/models/utils/ops/rroi_align/rroi_align.py
View File

@ -1,57 +0,0 @@
from torch import nn
from torch.autograd import Function
from torch.autograd.function import once_differentiable
from torch.nn.modules.utils import _pair
from .csrc import rroi_align_backward, rroi_align_forward
class _RROIAlign(Function):
@staticmethod
def forward(ctx, input, roi, output_size, spatial_scale):
ctx.output_size = _pair(output_size)
ctx.spatial_scale = spatial_scale
ctx.input_shape = input.size()
total_output = rroi_align_forward(input, roi, spatial_scale,
output_size[0], output_size[1])
output, con_idx_x, con_idx_y = total_output
ctx.save_for_backward(roi, con_idx_x, con_idx_y)
return output
@staticmethod
@once_differentiable
def backward(ctx, grad_output):
rois, con_idx_x, con_idx_y = ctx.saved_tensors
output_size = ctx.output_size
spatial_scale = ctx.spatial_scale
bs, ch, h, w = ctx.input_shape
grad_input = rroi_align_backward(grad_output, rois, con_idx_x,
con_idx_y, spatial_scale,
output_size[0], output_size[1], bs,
ch, h, w)
return grad_input, None, None, None
rroi_align = _RROIAlign.apply
class RROIAlign(nn.Module):
def __init__(self, output_size, spatial_scale):
super(RROIAlign, self).__init__()
self.output_size = output_size
self.spatial_scale = spatial_scale
def forward(self, input, rois):
return rroi_align(input, rois, self.output_size, self.spatial_scale)
def __repr__(self):
tmpstr = self.__class__.__name__ + '('
tmpstr += 'output_size=' + str(self.output_size)
tmpstr += ', spatial_scale=' + str(self.spatial_scale)
tmpstr += ')'
return tmpstr

2
requirements/mminstall.txt
View File

@ -1,2 +1,2 @@
mmcv-full>=1.3.1
mmcv-full>=1.3.4
mmdet>=2.11.0

54
setup.py
View File

@ -1,12 +1,7 @@
import glob
import os
import sys
from setuptools import find_packages, setup
import torch
from torch.utils.cpp_extension import (CUDA_HOME, BuildExtension, CppExtension,
CUDAExtension)
def readme():
with open('README.md', encoding='utf-8') as f:
@ -103,47 +98,11 @@ def parse_requirements(fname='requirements.txt', with_version=True):
return packages
def get_rroi_align_extensions():
extensions_dir = 'mmocr/models/utils/ops/rroi_align/csrc/csc'
main_file = glob.glob(os.path.join(extensions_dir, '*.cpp'))
source_cpu = glob.glob(os.path.join(extensions_dir, 'cpu', '*.cpp'))
source_cuda = glob.glob(os.path.join(extensions_dir, 'cuda', '*.cu'))
sources = main_file + source_cpu
extension = CppExtension
extra_compile_args = {'cxx': ['/utf-8']} if is_windows else {'cxx': []}
define_macros = []
if torch.cuda.is_available() and CUDA_HOME is not None:
extension = CUDAExtension
sources += source_cuda
define_macros += [('WITH_CUDA', None)]
extra_compile_args['nvcc'] = [
'-DCUDA_HAS_FP16=1',
'-D__CUDA_NO_HALF_OPERATORS__',
'-D__CUDA_NO_HALF_CONVERSIONS__',
'-D__CUDA_NO_HALF2_OPERATORS__',
]
print(sources)
include_dirs = [extensions_dir]
print('include_dirs', include_dirs, flush=True)
ext = extension(
name='mmocr.models.utils.ops.rroi_align.csrc',
sources=sources,
include_dirs=include_dirs,
define_macros=define_macros,
extra_compile_args=extra_compile_args,
)
return ext
if __name__ == '__main__':
library_dirs = [
lp for lp in os.environ.get('LD_LIBRARY_PATH', '').split(':')
if len(lp) > 1
]
cpp_root = 'mmocr/models/textdet/postprocess/'
setup(
name='mmocr',
version=get_version(),
@ -156,7 +115,6 @@ if __name__ == '__main__':
packages=find_packages(exclude=('configs', 'tools', 'demo')),
include_package_data=True,
url='https://github.com/open-mmlab/mmocr',
package_data={'mmocr.ops': ['*/*.so']},
classifiers=[
'Development Status :: 4 - Beta',
'License :: OSI Approved :: Apache Software License',
@ -176,16 +134,4 @@ if __name__ == '__main__':
'build': parse_requirements('requirements/build.txt'),
'optional': parse_requirements('requirements/optional.txt'),
},
ext_modules=[
CppExtension(
name='mmocr.models.textdet.postprocess.pan',
sources=[cpp_root + 'pan.cpp'],
extra_compile_args=(['/utf-8'] if is_windows else [])),
CppExtension(
name='mmocr.models.textdet.postprocess.pse',
sources=[cpp_root + 'pse.cpp'],
extra_compile_args=(['/utf-8'] if is_windows else [])),
get_rroi_align_extensions()
],
cmdclass={'build_ext': BuildExtension},
zip_safe=False)