Files
linguist/samples/C/sgd_fast.c
2013-01-12 23:48:04 -05:00

15670 lines
652 KiB
C

/* Generated by Cython 0.17.4 on Mon Jan 7 18:29:40 2013 */
#define PY_SSIZE_T_CLEAN
#include "Python.h"
#ifndef Py_PYTHON_H
#error Python headers needed to compile C extensions, please install development version of Python.
#elif PY_VERSION_HEX < 0x02040000
#error Cython requires Python 2.4+.
#else
#include <stddef.h> /* For offsetof */
#ifndef offsetof
#define offsetof(type, member) ( (size_t) & ((type*)0) -> member )
#endif
#if !defined(WIN32) && !defined(MS_WINDOWS)
#ifndef __stdcall
#define __stdcall
#endif
#ifndef __cdecl
#define __cdecl
#endif
#ifndef __fastcall
#define __fastcall
#endif
#endif
#ifndef DL_IMPORT
#define DL_IMPORT(t) t
#endif
#ifndef DL_EXPORT
#define DL_EXPORT(t) t
#endif
#ifndef PY_LONG_LONG
#define PY_LONG_LONG LONG_LONG
#endif
#ifndef Py_HUGE_VAL
#define Py_HUGE_VAL HUGE_VAL
#endif
#ifdef PYPY_VERSION
#define CYTHON_COMPILING_IN_PYPY 1
#define CYTHON_COMPILING_IN_CPYTHON 0
#else
#define CYTHON_COMPILING_IN_PYPY 0
#define CYTHON_COMPILING_IN_CPYTHON 1
#endif
#if PY_VERSION_HEX < 0x02050000
typedef int Py_ssize_t;
#define PY_SSIZE_T_MAX INT_MAX
#define PY_SSIZE_T_MIN INT_MIN
#define PY_FORMAT_SIZE_T ""
#define CYTHON_FORMAT_SSIZE_T ""
#define PyInt_FromSsize_t(z) PyInt_FromLong(z)
#define PyInt_AsSsize_t(o) __Pyx_PyInt_AsInt(o)
#define PyNumber_Index(o) ((PyNumber_Check(o) && !PyFloat_Check(o)) ? PyNumber_Int(o) : \
(PyErr_Format(PyExc_TypeError, \
"expected index value, got %.200s", Py_TYPE(o)->tp_name), \
(PyObject*)0))
#define __Pyx_PyIndex_Check(o) (PyNumber_Check(o) && !PyFloat_Check(o) && \
!PyComplex_Check(o))
#define PyIndex_Check __Pyx_PyIndex_Check
#define PyErr_WarnEx(category, message, stacklevel) PyErr_Warn(category, message)
#define __PYX_BUILD_PY_SSIZE_T "i"
#else
#define __PYX_BUILD_PY_SSIZE_T "n"
#define CYTHON_FORMAT_SSIZE_T "z"
#define __Pyx_PyIndex_Check PyIndex_Check
#endif
#if PY_VERSION_HEX < 0x02060000
#define Py_REFCNT(ob) (((PyObject*)(ob))->ob_refcnt)
#define Py_TYPE(ob) (((PyObject*)(ob))->ob_type)
#define Py_SIZE(ob) (((PyVarObject*)(ob))->ob_size)
#define PyVarObject_HEAD_INIT(type, size) \
PyObject_HEAD_INIT(type) size,
#define PyType_Modified(t)
typedef struct {
void *buf;
PyObject *obj;
Py_ssize_t len;
Py_ssize_t itemsize;
int readonly;
int ndim;
char *format;
Py_ssize_t *shape;
Py_ssize_t *strides;
Py_ssize_t *suboffsets;
void *internal;
} Py_buffer;
#define PyBUF_SIMPLE 0
#define PyBUF_WRITABLE 0x0001
#define PyBUF_FORMAT 0x0004
#define PyBUF_ND 0x0008
#define PyBUF_STRIDES (0x0010 | PyBUF_ND)
#define PyBUF_C_CONTIGUOUS (0x0020 | PyBUF_STRIDES)
#define PyBUF_F_CONTIGUOUS (0x0040 | PyBUF_STRIDES)
#define PyBUF_ANY_CONTIGUOUS (0x0080 | PyBUF_STRIDES)
#define PyBUF_INDIRECT (0x0100 | PyBUF_STRIDES)
#define PyBUF_RECORDS (PyBUF_STRIDES | PyBUF_FORMAT | PyBUF_WRITABLE)
#define PyBUF_FULL (PyBUF_INDIRECT | PyBUF_FORMAT | PyBUF_WRITABLE)
typedef int (*getbufferproc)(PyObject *, Py_buffer *, int);
typedef void (*releasebufferproc)(PyObject *, Py_buffer *);
#endif
#if PY_MAJOR_VERSION < 3
#define __Pyx_BUILTIN_MODULE_NAME "__builtin__"
#define __Pyx_PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos) \
PyCode_New(a, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos)
#else
#define __Pyx_BUILTIN_MODULE_NAME "builtins"
#define __Pyx_PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos) \
PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos)
#endif
#if PY_MAJOR_VERSION < 3 && PY_MINOR_VERSION < 6
#define PyUnicode_FromString(s) PyUnicode_Decode(s, strlen(s), "UTF-8", "strict")
#endif
#if PY_MAJOR_VERSION >= 3
#define Py_TPFLAGS_CHECKTYPES 0
#define Py_TPFLAGS_HAVE_INDEX 0
#endif
#if (PY_VERSION_HEX < 0x02060000) || (PY_MAJOR_VERSION >= 3)
#define Py_TPFLAGS_HAVE_NEWBUFFER 0
#endif
#if PY_VERSION_HEX > 0x03030000 && defined(PyUnicode_KIND)
#define CYTHON_PEP393_ENABLED 1
#define __Pyx_PyUnicode_READY(op) (likely(PyUnicode_IS_READY(op)) ? \
0 : _PyUnicode_Ready((PyObject *)(op)))
#define __Pyx_PyUnicode_GET_LENGTH(u) PyUnicode_GET_LENGTH(u)
#define __Pyx_PyUnicode_READ_CHAR(u, i) PyUnicode_READ_CHAR(u, i)
#define __Pyx_PyUnicode_READ(k, d, i) PyUnicode_READ(k, d, i)
#else
#define CYTHON_PEP393_ENABLED 0
#define __Pyx_PyUnicode_READY(op) (0)
#define __Pyx_PyUnicode_GET_LENGTH(u) PyUnicode_GET_SIZE(u)
#define __Pyx_PyUnicode_READ_CHAR(u, i) ((Py_UCS4)(PyUnicode_AS_UNICODE(u)[i]))
#define __Pyx_PyUnicode_READ(k, d, i) ((k=k), (Py_UCS4)(((Py_UNICODE*)d)[i]))
#endif
#if PY_MAJOR_VERSION >= 3
#define PyBaseString_Type PyUnicode_Type
#define PyStringObject PyUnicodeObject
#define PyString_Type PyUnicode_Type
#define PyString_Check PyUnicode_Check
#define PyString_CheckExact PyUnicode_CheckExact
#endif
#if PY_VERSION_HEX < 0x02060000
#define PyBytesObject PyStringObject
#define PyBytes_Type PyString_Type
#define PyBytes_Check PyString_Check
#define PyBytes_CheckExact PyString_CheckExact
#define PyBytes_FromString PyString_FromString
#define PyBytes_FromStringAndSize PyString_FromStringAndSize
#define PyBytes_FromFormat PyString_FromFormat
#define PyBytes_DecodeEscape PyString_DecodeEscape
#define PyBytes_AsString PyString_AsString
#define PyBytes_AsStringAndSize PyString_AsStringAndSize
#define PyBytes_Size PyString_Size
#define PyBytes_AS_STRING PyString_AS_STRING
#define PyBytes_GET_SIZE PyString_GET_SIZE
#define PyBytes_Repr PyString_Repr
#define PyBytes_Concat PyString_Concat
#define PyBytes_ConcatAndDel PyString_ConcatAndDel
#endif
#if PY_VERSION_HEX < 0x02060000
#define PySet_Check(obj) PyObject_TypeCheck(obj, &PySet_Type)
#define PyFrozenSet_Check(obj) PyObject_TypeCheck(obj, &PyFrozenSet_Type)
#endif
#ifndef PySet_CheckExact
#define PySet_CheckExact(obj) (Py_TYPE(obj) == &PySet_Type)
#endif
#define __Pyx_TypeCheck(obj, type) PyObject_TypeCheck(obj, (PyTypeObject *)type)
#if PY_MAJOR_VERSION >= 3
#define PyIntObject PyLongObject
#define PyInt_Type PyLong_Type
#define PyInt_Check(op) PyLong_Check(op)
#define PyInt_CheckExact(op) PyLong_CheckExact(op)
#define PyInt_FromString PyLong_FromString
#define PyInt_FromUnicode PyLong_FromUnicode
#define PyInt_FromLong PyLong_FromLong
#define PyInt_FromSize_t PyLong_FromSize_t
#define PyInt_FromSsize_t PyLong_FromSsize_t
#define PyInt_AsLong PyLong_AsLong
#define PyInt_AS_LONG PyLong_AS_LONG
#define PyInt_AsSsize_t PyLong_AsSsize_t
#define PyInt_AsUnsignedLongMask PyLong_AsUnsignedLongMask
#define PyInt_AsUnsignedLongLongMask PyLong_AsUnsignedLongLongMask
#endif
#if PY_MAJOR_VERSION >= 3
#define PyBoolObject PyLongObject
#endif
#if PY_VERSION_HEX < 0x03020000
typedef long Py_hash_t;
#define __Pyx_PyInt_FromHash_t PyInt_FromLong
#define __Pyx_PyInt_AsHash_t PyInt_AsLong
#else
#define __Pyx_PyInt_FromHash_t PyInt_FromSsize_t
#define __Pyx_PyInt_AsHash_t PyInt_AsSsize_t
#endif
#if (PY_MAJOR_VERSION < 3) || (PY_VERSION_HEX >= 0x03010300)
#define __Pyx_PySequence_GetSlice(obj, a, b) PySequence_GetSlice(obj, a, b)
#define __Pyx_PySequence_SetSlice(obj, a, b, value) PySequence_SetSlice(obj, a, b, value)
#define __Pyx_PySequence_DelSlice(obj, a, b) PySequence_DelSlice(obj, a, b)
#else
#define __Pyx_PySequence_GetSlice(obj, a, b) (unlikely(!(obj)) ? \
(PyErr_SetString(PyExc_SystemError, "null argument to internal routine"), (PyObject*)0) : \
(likely((obj)->ob_type->tp_as_mapping) ? (PySequence_GetSlice(obj, a, b)) : \
(PyErr_Format(PyExc_TypeError, "'%.200s' object is unsliceable", (obj)->ob_type->tp_name), (PyObject*)0)))
#define __Pyx_PySequence_SetSlice(obj, a, b, value) (unlikely(!(obj)) ? \
(PyErr_SetString(PyExc_SystemError, "null argument to internal routine"), -1) : \
(likely((obj)->ob_type->tp_as_mapping) ? (PySequence_SetSlice(obj, a, b, value)) : \
(PyErr_Format(PyExc_TypeError, "'%.200s' object doesn't support slice assignment", (obj)->ob_type->tp_name), -1)))
#define __Pyx_PySequence_DelSlice(obj, a, b) (unlikely(!(obj)) ? \
(PyErr_SetString(PyExc_SystemError, "null argument to internal routine"), -1) : \
(likely((obj)->ob_type->tp_as_mapping) ? (PySequence_DelSlice(obj, a, b)) : \
(PyErr_Format(PyExc_TypeError, "'%.200s' object doesn't support slice deletion", (obj)->ob_type->tp_name), -1)))
#endif
#if PY_MAJOR_VERSION >= 3
#define PyMethod_New(func, self, klass) ((self) ? PyMethod_New(func, self) : PyInstanceMethod_New(func))
#endif
#if PY_VERSION_HEX < 0x02050000
#define __Pyx_GetAttrString(o,n) PyObject_GetAttrString((o),((char *)(n)))
#define __Pyx_SetAttrString(o,n,a) PyObject_SetAttrString((o),((char *)(n)),(a))
#define __Pyx_DelAttrString(o,n) PyObject_DelAttrString((o),((char *)(n)))
#else
#define __Pyx_GetAttrString(o,n) PyObject_GetAttrString((o),(n))
#define __Pyx_SetAttrString(o,n,a) PyObject_SetAttrString((o),(n),(a))
#define __Pyx_DelAttrString(o,n) PyObject_DelAttrString((o),(n))
#endif
#if PY_VERSION_HEX < 0x02050000
#define __Pyx_NAMESTR(n) ((char *)(n))
#define __Pyx_DOCSTR(n) ((char *)(n))
#else
#define __Pyx_NAMESTR(n) (n)
#define __Pyx_DOCSTR(n) (n)
#endif
#if PY_MAJOR_VERSION >= 3
#define __Pyx_PyNumber_Divide(x,y) PyNumber_TrueDivide(x,y)
#define __Pyx_PyNumber_InPlaceDivide(x,y) PyNumber_InPlaceTrueDivide(x,y)
#else
#define __Pyx_PyNumber_Divide(x,y) PyNumber_Divide(x,y)
#define __Pyx_PyNumber_InPlaceDivide(x,y) PyNumber_InPlaceDivide(x,y)
#endif
#ifndef __PYX_EXTERN_C
#ifdef __cplusplus
#define __PYX_EXTERN_C extern "C"
#else
#define __PYX_EXTERN_C extern
#endif
#endif
#if defined(WIN32) || defined(MS_WINDOWS)
#define _USE_MATH_DEFINES
#endif
#include <math.h>
#define __PYX_HAVE__sklearn__linear_model__sgd_fast
#define __PYX_HAVE_API__sklearn__linear_model__sgd_fast
#include "math.h"
#include "stdio.h"
#include "stdlib.h"
#include "numpy/arrayobject.h"
#include "numpy/ufuncobject.h"
#ifdef _OPENMP
#include <omp.h>
#endif /* _OPENMP */
#ifdef PYREX_WITHOUT_ASSERTIONS
#define CYTHON_WITHOUT_ASSERTIONS
#endif
/* inline attribute */
#ifndef CYTHON_INLINE
#if defined(__GNUC__)
#define CYTHON_INLINE __inline__
#elif defined(_MSC_VER)
#define CYTHON_INLINE __inline
#elif defined (__STDC_VERSION__) && __STDC_VERSION__ >= 199901L
#define CYTHON_INLINE inline
#else
#define CYTHON_INLINE
#endif
#endif
/* unused attribute */
#ifndef CYTHON_UNUSED
# if defined(__GNUC__)
# if !(defined(__cplusplus)) || (__GNUC__ > 3 || (__GNUC__ == 3 && __GNUC_MINOR__ >= 4))
# define CYTHON_UNUSED __attribute__ ((__unused__))
# else
# define CYTHON_UNUSED
# endif
# elif defined(__ICC) || (defined(__INTEL_COMPILER) && !defined(_MSC_VER))
# define CYTHON_UNUSED __attribute__ ((__unused__))
# else
# define CYTHON_UNUSED
# endif
#endif
typedef struct {PyObject **p; char *s; const long n; const char* encoding; const char is_unicode; const char is_str; const char intern; } __Pyx_StringTabEntry; /*proto*/
/* Type Conversion Predeclarations */
#define __Pyx_PyBytes_FromUString(s) PyBytes_FromString((char*)s)
#define __Pyx_PyBytes_AsUString(s) ((unsigned char*) PyBytes_AsString(s))
#define __Pyx_Owned_Py_None(b) (Py_INCREF(Py_None), Py_None)
#define __Pyx_PyBool_FromLong(b) ((b) ? (Py_INCREF(Py_True), Py_True) : (Py_INCREF(Py_False), Py_False))
static CYTHON_INLINE int __Pyx_PyObject_IsTrue(PyObject*);
static CYTHON_INLINE PyObject* __Pyx_PyNumber_Int(PyObject* x);
static CYTHON_INLINE Py_ssize_t __Pyx_PyIndex_AsSsize_t(PyObject*);
static CYTHON_INLINE PyObject * __Pyx_PyInt_FromSize_t(size_t);
static CYTHON_INLINE size_t __Pyx_PyInt_AsSize_t(PyObject*);
#if CYTHON_COMPILING_IN_CPYTHON
#define __pyx_PyFloat_AsDouble(x) (PyFloat_CheckExact(x) ? PyFloat_AS_DOUBLE(x) : PyFloat_AsDouble(x))
#else
#define __pyx_PyFloat_AsDouble(x) PyFloat_AsDouble(x)
#endif
#define __pyx_PyFloat_AsFloat(x) ((float) __pyx_PyFloat_AsDouble(x))
#ifdef __GNUC__
/* Test for GCC > 2.95 */
#if __GNUC__ > 2 || (__GNUC__ == 2 && (__GNUC_MINOR__ > 95))
#define likely(x) __builtin_expect(!!(x), 1)
#define unlikely(x) __builtin_expect(!!(x), 0)
#else /* __GNUC__ > 2 ... */
#define likely(x) (x)
#define unlikely(x) (x)
#endif /* __GNUC__ > 2 ... */
#else /* __GNUC__ */
#define likely(x) (x)
#define unlikely(x) (x)
#endif /* __GNUC__ */
static PyObject *__pyx_m;
static PyObject *__pyx_b;
static PyObject *__pyx_empty_tuple;
static PyObject *__pyx_empty_bytes;
static int __pyx_lineno;
static int __pyx_clineno = 0;
static const char * __pyx_cfilenm= __FILE__;
static const char *__pyx_filename;
#if !defined(CYTHON_CCOMPLEX)
#if defined(__cplusplus)
#define CYTHON_CCOMPLEX 1
#elif defined(_Complex_I)
#define CYTHON_CCOMPLEX 1
#else
#define CYTHON_CCOMPLEX 0
#endif
#endif
#if CYTHON_CCOMPLEX
#ifdef __cplusplus
#include <complex>
#else
#include <complex.h>
#endif
#endif
#if CYTHON_CCOMPLEX && !defined(__cplusplus) && defined(__sun__) && defined(__GNUC__)
#undef _Complex_I
#define _Complex_I 1.0fj
#endif
static const char *__pyx_f[] = {
"sgd_fast.pyx",
"numpy.pxd",
"type.pxd",
"weight_vector.pxd",
"seq_dataset.pxd",
};
#define IS_UNSIGNED(type) (((type) -1) > 0)
struct __Pyx_StructField_;
#define __PYX_BUF_FLAGS_PACKED_STRUCT (1 << 0)
typedef struct {
const char* name; /* for error messages only */
struct __Pyx_StructField_* fields;
size_t size; /* sizeof(type) */
size_t arraysize[8]; /* length of array in each dimension */
int ndim;
char typegroup; /* _R_eal, _C_omplex, Signed _I_nt, _U_nsigned int, _S_truct, _P_ointer, _O_bject, c_H_ar */
char is_unsigned;
int flags;
} __Pyx_TypeInfo;
typedef struct __Pyx_StructField_ {
__Pyx_TypeInfo* type;
const char* name;
size_t offset;
} __Pyx_StructField;
typedef struct {
__Pyx_StructField* field;
size_t parent_offset;
} __Pyx_BufFmt_StackElem;
typedef struct {
__Pyx_StructField root;
__Pyx_BufFmt_StackElem* head;
size_t fmt_offset;
size_t new_count, enc_count;
size_t struct_alignment;
int is_complex;
char enc_type;
char new_packmode;
char enc_packmode;
char is_valid_array;
} __Pyx_BufFmt_Context;
/* "numpy.pxd":723
* # in Cython to enable them only on the right systems.
*
* ctypedef npy_int8 int8_t # <<<<<<<<<<<<<<
* ctypedef npy_int16 int16_t
* ctypedef npy_int32 int32_t
*/
typedef npy_int8 __pyx_t_5numpy_int8_t;
/* "numpy.pxd":724
*
* ctypedef npy_int8 int8_t
* ctypedef npy_int16 int16_t # <<<<<<<<<<<<<<
* ctypedef npy_int32 int32_t
* ctypedef npy_int64 int64_t
*/
typedef npy_int16 __pyx_t_5numpy_int16_t;
/* "numpy.pxd":725
* ctypedef npy_int8 int8_t
* ctypedef npy_int16 int16_t
* ctypedef npy_int32 int32_t # <<<<<<<<<<<<<<
* ctypedef npy_int64 int64_t
* #ctypedef npy_int96 int96_t
*/
typedef npy_int32 __pyx_t_5numpy_int32_t;
/* "numpy.pxd":726
* ctypedef npy_int16 int16_t
* ctypedef npy_int32 int32_t
* ctypedef npy_int64 int64_t # <<<<<<<<<<<<<<
* #ctypedef npy_int96 int96_t
* #ctypedef npy_int128 int128_t
*/
typedef npy_int64 __pyx_t_5numpy_int64_t;
/* "numpy.pxd":730
* #ctypedef npy_int128 int128_t
*
* ctypedef npy_uint8 uint8_t # <<<<<<<<<<<<<<
* ctypedef npy_uint16 uint16_t
* ctypedef npy_uint32 uint32_t
*/
typedef npy_uint8 __pyx_t_5numpy_uint8_t;
/* "numpy.pxd":731
*
* ctypedef npy_uint8 uint8_t
* ctypedef npy_uint16 uint16_t # <<<<<<<<<<<<<<
* ctypedef npy_uint32 uint32_t
* ctypedef npy_uint64 uint64_t
*/
typedef npy_uint16 __pyx_t_5numpy_uint16_t;
/* "numpy.pxd":732
* ctypedef npy_uint8 uint8_t
* ctypedef npy_uint16 uint16_t
* ctypedef npy_uint32 uint32_t # <<<<<<<<<<<<<<
* ctypedef npy_uint64 uint64_t
* #ctypedef npy_uint96 uint96_t
*/
typedef npy_uint32 __pyx_t_5numpy_uint32_t;
/* "numpy.pxd":733
* ctypedef npy_uint16 uint16_t
* ctypedef npy_uint32 uint32_t
* ctypedef npy_uint64 uint64_t # <<<<<<<<<<<<<<
* #ctypedef npy_uint96 uint96_t
* #ctypedef npy_uint128 uint128_t
*/
typedef npy_uint64 __pyx_t_5numpy_uint64_t;
/* "numpy.pxd":737
* #ctypedef npy_uint128 uint128_t
*
* ctypedef npy_float32 float32_t # <<<<<<<<<<<<<<
* ctypedef npy_float64 float64_t
* #ctypedef npy_float80 float80_t
*/
typedef npy_float32 __pyx_t_5numpy_float32_t;
/* "numpy.pxd":738
*
* ctypedef npy_float32 float32_t
* ctypedef npy_float64 float64_t # <<<<<<<<<<<<<<
* #ctypedef npy_float80 float80_t
* #ctypedef npy_float128 float128_t
*/
typedef npy_float64 __pyx_t_5numpy_float64_t;
/* "numpy.pxd":747
* # The int types are mapped a bit surprising --
* # numpy.int corresponds to 'l' and numpy.long to 'q'
* ctypedef npy_long int_t # <<<<<<<<<<<<<<
* ctypedef npy_longlong long_t
* ctypedef npy_longlong longlong_t
*/
typedef npy_long __pyx_t_5numpy_int_t;
/* "numpy.pxd":748
* # numpy.int corresponds to 'l' and numpy.long to 'q'
* ctypedef npy_long int_t
* ctypedef npy_longlong long_t # <<<<<<<<<<<<<<
* ctypedef npy_longlong longlong_t
*
*/
typedef npy_longlong __pyx_t_5numpy_long_t;
/* "numpy.pxd":749
* ctypedef npy_long int_t
* ctypedef npy_longlong long_t
* ctypedef npy_longlong longlong_t # <<<<<<<<<<<<<<
*
* ctypedef npy_ulong uint_t
*/
typedef npy_longlong __pyx_t_5numpy_longlong_t;
/* "numpy.pxd":751
* ctypedef npy_longlong longlong_t
*
* ctypedef npy_ulong uint_t # <<<<<<<<<<<<<<
* ctypedef npy_ulonglong ulong_t
* ctypedef npy_ulonglong ulonglong_t
*/
typedef npy_ulong __pyx_t_5numpy_uint_t;
/* "numpy.pxd":752
*
* ctypedef npy_ulong uint_t
* ctypedef npy_ulonglong ulong_t # <<<<<<<<<<<<<<
* ctypedef npy_ulonglong ulonglong_t
*
*/
typedef npy_ulonglong __pyx_t_5numpy_ulong_t;
/* "numpy.pxd":753
* ctypedef npy_ulong uint_t
* ctypedef npy_ulonglong ulong_t
* ctypedef npy_ulonglong ulonglong_t # <<<<<<<<<<<<<<
*
* ctypedef npy_intp intp_t
*/
typedef npy_ulonglong __pyx_t_5numpy_ulonglong_t;
/* "numpy.pxd":755
* ctypedef npy_ulonglong ulonglong_t
*
* ctypedef npy_intp intp_t # <<<<<<<<<<<<<<
* ctypedef npy_uintp uintp_t
*
*/
typedef npy_intp __pyx_t_5numpy_intp_t;
/* "numpy.pxd":756
*
* ctypedef npy_intp intp_t
* ctypedef npy_uintp uintp_t # <<<<<<<<<<<<<<
*
* ctypedef npy_double float_t
*/
typedef npy_uintp __pyx_t_5numpy_uintp_t;
/* "numpy.pxd":758
* ctypedef npy_uintp uintp_t
*
* ctypedef npy_double float_t # <<<<<<<<<<<<<<
* ctypedef npy_double double_t
* ctypedef npy_longdouble longdouble_t
*/
typedef npy_double __pyx_t_5numpy_float_t;
/* "numpy.pxd":759
*
* ctypedef npy_double float_t
* ctypedef npy_double double_t # <<<<<<<<<<<<<<
* ctypedef npy_longdouble longdouble_t
*
*/
typedef npy_double __pyx_t_5numpy_double_t;
/* "numpy.pxd":760
* ctypedef npy_double float_t
* ctypedef npy_double double_t
* ctypedef npy_longdouble longdouble_t # <<<<<<<<<<<<<<
*
* ctypedef npy_cfloat cfloat_t
*/
typedef npy_longdouble __pyx_t_5numpy_longdouble_t;
/* "sklearn/utils/weight_vector.pxd":10
*
*
* ctypedef np.float64_t DOUBLE # <<<<<<<<<<<<<<
* ctypedef np.int32_t INTEGER
*
*/
typedef __pyx_t_5numpy_float64_t __pyx_t_7sklearn_5utils_13weight_vector_DOUBLE;
/* "sklearn/utils/weight_vector.pxd":11
*
* ctypedef np.float64_t DOUBLE
* ctypedef np.int32_t INTEGER # <<<<<<<<<<<<<<
*
*
*/
typedef __pyx_t_5numpy_int32_t __pyx_t_7sklearn_5utils_13weight_vector_INTEGER;
/* "sklearn/utils/seq_dataset.pxd":5
* cimport numpy as np
*
* ctypedef np.float64_t DOUBLE # <<<<<<<<<<<<<<
* ctypedef np.int32_t INTEGER
*
*/
typedef __pyx_t_5numpy_float64_t __pyx_t_7sklearn_5utils_11seq_dataset_DOUBLE;
/* "sklearn/utils/seq_dataset.pxd":6
*
* ctypedef np.float64_t DOUBLE
* ctypedef np.int32_t INTEGER # <<<<<<<<<<<<<<
*
*
*/
typedef __pyx_t_5numpy_int32_t __pyx_t_7sklearn_5utils_11seq_dataset_INTEGER;
/* "sklearn/linear_model/sgd_fast.pyx":25
*
*
* ctypedef np.float64_t DOUBLE # <<<<<<<<<<<<<<
* ctypedef np.int32_t INTEGER
*
*/
typedef __pyx_t_5numpy_float64_t __pyx_t_7sklearn_12linear_model_8sgd_fast_DOUBLE;
/* "sklearn/linear_model/sgd_fast.pyx":26
*
* ctypedef np.float64_t DOUBLE
* ctypedef np.int32_t INTEGER # <<<<<<<<<<<<<<
*
*
*/
typedef __pyx_t_5numpy_int32_t __pyx_t_7sklearn_12linear_model_8sgd_fast_INTEGER;
#if CYTHON_CCOMPLEX
#ifdef __cplusplus
typedef ::std::complex< float > __pyx_t_float_complex;
#else
typedef float _Complex __pyx_t_float_complex;
#endif
#else
typedef struct { float real, imag; } __pyx_t_float_complex;
#endif
#if CYTHON_CCOMPLEX
#ifdef __cplusplus
typedef ::std::complex< double > __pyx_t_double_complex;
#else
typedef double _Complex __pyx_t_double_complex;
#endif
#else
typedef struct { double real, imag; } __pyx_t_double_complex;
#endif
/*--- Type declarations ---*/
struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_LossFunction;
struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_Regression;
struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_Huber;
struct __pyx_obj_7sklearn_5utils_11seq_dataset_SequentialDataset;
struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_EpsilonInsensitive;
struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_Classification;
struct __pyx_obj_7sklearn_5utils_11seq_dataset_CSRDataset;
struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_Log;
struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_Hinge;
struct __pyx_obj_7sklearn_5utils_11seq_dataset_ArrayDataset;
struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_SquaredHinge;
struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_ModifiedHuber;
struct __pyx_obj_7sklearn_5utils_13weight_vector_WeightVector;
struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_SquaredLoss;
struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_SquaredEpsilonInsensitive;
/* "numpy.pxd":762
* ctypedef npy_longdouble longdouble_t
*
* ctypedef npy_cfloat cfloat_t # <<<<<<<<<<<<<<
* ctypedef npy_cdouble cdouble_t
* ctypedef npy_clongdouble clongdouble_t
*/
typedef npy_cfloat __pyx_t_5numpy_cfloat_t;
/* "numpy.pxd":763
*
* ctypedef npy_cfloat cfloat_t
* ctypedef npy_cdouble cdouble_t # <<<<<<<<<<<<<<
* ctypedef npy_clongdouble clongdouble_t
*
*/
typedef npy_cdouble __pyx_t_5numpy_cdouble_t;
/* "numpy.pxd":764
* ctypedef npy_cfloat cfloat_t
* ctypedef npy_cdouble cdouble_t
* ctypedef npy_clongdouble clongdouble_t # <<<<<<<<<<<<<<
*
* ctypedef npy_cdouble complex_t
*/
typedef npy_clongdouble __pyx_t_5numpy_clongdouble_t;
/* "numpy.pxd":766
* ctypedef npy_clongdouble clongdouble_t
*
* ctypedef npy_cdouble complex_t # <<<<<<<<<<<<<<
*
* cdef inline object PyArray_MultiIterNew1(a):
*/
typedef npy_cdouble __pyx_t_5numpy_complex_t;
/* "sklearn/linear_model/sgd_fast.pyx":46
* # ----------------------------------------
*
* cdef class LossFunction: # <<<<<<<<<<<<<<
* """Base class for convex loss functions"""
*
*/
struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_LossFunction {
PyObject_HEAD
struct __pyx_vtabstruct_7sklearn_12linear_model_8sgd_fast_LossFunction *__pyx_vtab;
};
/* "sklearn/linear_model/sgd_fast.pyx":84
*
*
* cdef class Regression(LossFunction): # <<<<<<<<<<<<<<
* """Base class for loss functions for regression"""
*
*/
struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_Regression {
struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_LossFunction __pyx_base;
};
/* "sklearn/linear_model/sgd_fast.pyx":235
*
*
* cdef class Huber(Regression): # <<<<<<<<<<<<<<
* """Huber regression loss
*
*/
struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_Huber {
struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_Regression __pyx_base;
double c;
};
/* "sklearn/utils/seq_dataset.pxd":9
*
*
* cdef class SequentialDataset: # <<<<<<<<<<<<<<
* cdef Py_ssize_t n_samples
*
*/
struct __pyx_obj_7sklearn_5utils_11seq_dataset_SequentialDataset {
PyObject_HEAD
struct __pyx_vtabstruct_7sklearn_5utils_11seq_dataset_SequentialDataset *__pyx_vtab;
Py_ssize_t n_samples;
};
/* "sklearn/linear_model/sgd_fast.pyx":271
*
*
* cdef class EpsilonInsensitive(Regression): # <<<<<<<<<<<<<<
* """Epsilon-Insensitive loss (used by SVR).
*
*/
struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_EpsilonInsensitive {
struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_Regression __pyx_base;
double epsilon;
};
/* "sklearn/linear_model/sgd_fast.pyx":94
*
*
* cdef class Classification(LossFunction): # <<<<<<<<<<<<<<
* """Base class for loss functions for classification"""
*
*/
struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_Classification {
struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_LossFunction __pyx_base;
};
/* "sklearn/utils/seq_dataset.pxd":34
*
*
* cdef class CSRDataset(SequentialDataset): # <<<<<<<<<<<<<<
* cdef int current_index
* cdef int stride
*/
struct __pyx_obj_7sklearn_5utils_11seq_dataset_CSRDataset {
struct __pyx_obj_7sklearn_5utils_11seq_dataset_SequentialDataset __pyx_base;
int current_index;
int stride;
__pyx_t_7sklearn_5utils_11seq_dataset_DOUBLE *X_data_ptr;
__pyx_t_7sklearn_5utils_11seq_dataset_INTEGER *X_indptr_ptr;
__pyx_t_7sklearn_5utils_11seq_dataset_INTEGER *X_indices_ptr;
__pyx_t_7sklearn_5utils_11seq_dataset_DOUBLE *Y_data_ptr;
PyArrayObject *feature_indices;
__pyx_t_7sklearn_5utils_11seq_dataset_INTEGER *feature_indices_ptr;
PyArrayObject *index;
__pyx_t_7sklearn_5utils_11seq_dataset_INTEGER *index_data_ptr;
__pyx_t_7sklearn_5utils_11seq_dataset_DOUBLE *sample_weight_data;
};
/* "sklearn/linear_model/sgd_fast.pyx":198
*
*
* cdef class Log(Classification): # <<<<<<<<<<<<<<
* """Logistic regression loss for binary classification with y in {-1, 1}"""
*
*/
struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_Log {
struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_Classification __pyx_base;
};
/* "sklearn/linear_model/sgd_fast.pyx":134
*
*
* cdef class Hinge(Classification): # <<<<<<<<<<<<<<
* """Hinge loss for binary classification tasks with y in {-1,1}
*
*/
struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_Hinge {
struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_Classification __pyx_base;
double threshold;
};
/* "sklearn/utils/seq_dataset.pxd":17
*
*
* cdef class ArrayDataset(SequentialDataset): # <<<<<<<<<<<<<<
* cdef Py_ssize_t n_features
* cdef int current_index
*/
struct __pyx_obj_7sklearn_5utils_11seq_dataset_ArrayDataset {
struct __pyx_obj_7sklearn_5utils_11seq_dataset_SequentialDataset __pyx_base;
Py_ssize_t n_features;
int current_index;
int stride;
__pyx_t_7sklearn_5utils_11seq_dataset_DOUBLE *X_data_ptr;
__pyx_t_7sklearn_5utils_11seq_dataset_DOUBLE *Y_data_ptr;
PyArrayObject *feature_indices;
__pyx_t_7sklearn_5utils_11seq_dataset_INTEGER *feature_indices_ptr;
PyArrayObject *index;
__pyx_t_7sklearn_5utils_11seq_dataset_INTEGER *index_data_ptr;
__pyx_t_7sklearn_5utils_11seq_dataset_DOUBLE *sample_weight_data;
};
/* "sklearn/linear_model/sgd_fast.pyx":166
*
*
* cdef class SquaredHinge(LossFunction): # <<<<<<<<<<<<<<
* """Squared Hinge loss for binary classification tasks with y in {-1,1}
*
*/
struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_SquaredHinge {
struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_LossFunction __pyx_base;
double threshold;
};
/* "sklearn/linear_model/sgd_fast.pyx":104
*
*
* cdef class ModifiedHuber(Classification): # <<<<<<<<<<<<<<
* """Modified Huber loss for binary classification with y in {-1, 1}
*
*/
struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_ModifiedHuber {
struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_Classification __pyx_base;
};
/* "sklearn/utils/weight_vector.pxd":14
*
*
* cdef class WeightVector(object): # <<<<<<<<<<<<<<
* cdef np.ndarray w
* cdef DOUBLE *w_data_ptr
*/
struct __pyx_obj_7sklearn_5utils_13weight_vector_WeightVector {
PyObject_HEAD
struct __pyx_vtabstruct_7sklearn_5utils_13weight_vector_WeightVector *__pyx_vtab;
PyArrayObject *w;
__pyx_t_7sklearn_5utils_13weight_vector_DOUBLE *w_data_ptr;
double wscale;
Py_ssize_t n_features;
double sq_norm;
};
/* "sklearn/linear_model/sgd_fast.pyx":223
*
*
* cdef class SquaredLoss(Regression): # <<<<<<<<<<<<<<
* """Squared loss traditional used in linear regression."""
* cpdef double loss(self, double p, double y):
*/
struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_SquaredLoss {
struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_Regression __pyx_base;
};
/* "sklearn/linear_model/sgd_fast.pyx":298
*
*
* cdef class SquaredEpsilonInsensitive(Regression): # <<<<<<<<<<<<<<
* """Epsilon-Insensitive loss.
*
*/
struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_SquaredEpsilonInsensitive {
struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_Regression __pyx_base;
double epsilon;
};
/* "sklearn/linear_model/sgd_fast.pyx":46
* # ----------------------------------------
*
* cdef class LossFunction: # <<<<<<<<<<<<<<
* """Base class for convex loss functions"""
*
*/
struct __pyx_vtabstruct_7sklearn_12linear_model_8sgd_fast_LossFunction {
double (*loss)(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_LossFunction *, double, double, int __pyx_skip_dispatch);
double (*dloss)(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_LossFunction *, double, double, int __pyx_skip_dispatch);
};
static struct __pyx_vtabstruct_7sklearn_12linear_model_8sgd_fast_LossFunction *__pyx_vtabptr_7sklearn_12linear_model_8sgd_fast_LossFunction;
/* "sklearn/linear_model/sgd_fast.pyx":84
*
*
* cdef class Regression(LossFunction): # <<<<<<<<<<<<<<
* """Base class for loss functions for regression"""
*
*/
struct __pyx_vtabstruct_7sklearn_12linear_model_8sgd_fast_Regression {
struct __pyx_vtabstruct_7sklearn_12linear_model_8sgd_fast_LossFunction __pyx_base;
};
static struct __pyx_vtabstruct_7sklearn_12linear_model_8sgd_fast_Regression *__pyx_vtabptr_7sklearn_12linear_model_8sgd_fast_Regression;
/* "sklearn/linear_model/sgd_fast.pyx":223
*
*
* cdef class SquaredLoss(Regression): # <<<<<<<<<<<<<<
* """Squared loss traditional used in linear regression."""
* cpdef double loss(self, double p, double y):
*/
struct __pyx_vtabstruct_7sklearn_12linear_model_8sgd_fast_SquaredLoss {
struct __pyx_vtabstruct_7sklearn_12linear_model_8sgd_fast_Regression __pyx_base;
};
static struct __pyx_vtabstruct_7sklearn_12linear_model_8sgd_fast_SquaredLoss *__pyx_vtabptr_7sklearn_12linear_model_8sgd_fast_SquaredLoss;
/* "sklearn/linear_model/sgd_fast.pyx":94
*
*
* cdef class Classification(LossFunction): # <<<<<<<<<<<<<<
* """Base class for loss functions for classification"""
*
*/
struct __pyx_vtabstruct_7sklearn_12linear_model_8sgd_fast_Classification {
struct __pyx_vtabstruct_7sklearn_12linear_model_8sgd_fast_LossFunction __pyx_base;
};
static struct __pyx_vtabstruct_7sklearn_12linear_model_8sgd_fast_Classification *__pyx_vtabptr_7sklearn_12linear_model_8sgd_fast_Classification;
/* "sklearn/linear_model/sgd_fast.pyx":104
*
*
* cdef class ModifiedHuber(Classification): # <<<<<<<<<<<<<<
* """Modified Huber loss for binary classification with y in {-1, 1}
*
*/
struct __pyx_vtabstruct_7sklearn_12linear_model_8sgd_fast_ModifiedHuber {
struct __pyx_vtabstruct_7sklearn_12linear_model_8sgd_fast_Classification __pyx_base;
};
static struct __pyx_vtabstruct_7sklearn_12linear_model_8sgd_fast_ModifiedHuber *__pyx_vtabptr_7sklearn_12linear_model_8sgd_fast_ModifiedHuber;
/* "sklearn/linear_model/sgd_fast.pyx":198
*
*
* cdef class Log(Classification): # <<<<<<<<<<<<<<
* """Logistic regression loss for binary classification with y in {-1, 1}"""
*
*/
struct __pyx_vtabstruct_7sklearn_12linear_model_8sgd_fast_Log {
struct __pyx_vtabstruct_7sklearn_12linear_model_8sgd_fast_Classification __pyx_base;
};
static struct __pyx_vtabstruct_7sklearn_12linear_model_8sgd_fast_Log *__pyx_vtabptr_7sklearn_12linear_model_8sgd_fast_Log;
/* "sklearn/linear_model/sgd_fast.pyx":298
*
*
* cdef class SquaredEpsilonInsensitive(Regression): # <<<<<<<<<<<<<<
* """Epsilon-Insensitive loss.
*
*/
struct __pyx_vtabstruct_7sklearn_12linear_model_8sgd_fast_SquaredEpsilonInsensitive {
struct __pyx_vtabstruct_7sklearn_12linear_model_8sgd_fast_Regression __pyx_base;
};
static struct __pyx_vtabstruct_7sklearn_12linear_model_8sgd_fast_SquaredEpsilonInsensitive *__pyx_vtabptr_7sklearn_12linear_model_8sgd_fast_SquaredEpsilonInsensitive;
/* "sklearn/utils/seq_dataset.pxd":9
*
*
* cdef class SequentialDataset: # <<<<<<<<<<<<<<
* cdef Py_ssize_t n_samples
*
*/
struct __pyx_vtabstruct_7sklearn_5utils_11seq_dataset_SequentialDataset {
void (*next)(struct __pyx_obj_7sklearn_5utils_11seq_dataset_SequentialDataset *, __pyx_t_7sklearn_5utils_11seq_dataset_DOUBLE **, __pyx_t_7sklearn_5utils_11seq_dataset_INTEGER **, int *, __pyx_t_7sklearn_5utils_11seq_dataset_DOUBLE *, __pyx_t_7sklearn_5utils_11seq_dataset_DOUBLE *);
void (*shuffle)(struct __pyx_obj_7sklearn_5utils_11seq_dataset_SequentialDataset *, PyObject *);
};
static struct __pyx_vtabstruct_7sklearn_5utils_11seq_dataset_SequentialDataset *__pyx_vtabptr_7sklearn_5utils_11seq_dataset_SequentialDataset;
/* "sklearn/utils/seq_dataset.pxd":17
*
*
* cdef class ArrayDataset(SequentialDataset): # <<<<<<<<<<<<<<
* cdef Py_ssize_t n_features
* cdef int current_index
*/
struct __pyx_vtabstruct_7sklearn_5utils_11seq_dataset_ArrayDataset {
struct __pyx_vtabstruct_7sklearn_5utils_11seq_dataset_SequentialDataset __pyx_base;
};
static struct __pyx_vtabstruct_7sklearn_5utils_11seq_dataset_ArrayDataset *__pyx_vtabptr_7sklearn_5utils_11seq_dataset_ArrayDataset;
/* "sklearn/utils/seq_dataset.pxd":34
*
*
* cdef class CSRDataset(SequentialDataset): # <<<<<<<<<<<<<<
* cdef int current_index
* cdef int stride
*/
struct __pyx_vtabstruct_7sklearn_5utils_11seq_dataset_CSRDataset {
struct __pyx_vtabstruct_7sklearn_5utils_11seq_dataset_SequentialDataset __pyx_base;
};
static struct __pyx_vtabstruct_7sklearn_5utils_11seq_dataset_CSRDataset *__pyx_vtabptr_7sklearn_5utils_11seq_dataset_CSRDataset;
/* "sklearn/linear_model/sgd_fast.pyx":271
*
*
* cdef class EpsilonInsensitive(Regression): # <<<<<<<<<<<<<<
* """Epsilon-Insensitive loss (used by SVR).
*
*/
struct __pyx_vtabstruct_7sklearn_12linear_model_8sgd_fast_EpsilonInsensitive {
struct __pyx_vtabstruct_7sklearn_12linear_model_8sgd_fast_Regression __pyx_base;
};
static struct __pyx_vtabstruct_7sklearn_12linear_model_8sgd_fast_EpsilonInsensitive *__pyx_vtabptr_7sklearn_12linear_model_8sgd_fast_EpsilonInsensitive;
/* "sklearn/linear_model/sgd_fast.pyx":166
*
*
* cdef class SquaredHinge(LossFunction): # <<<<<<<<<<<<<<
* """Squared Hinge loss for binary classification tasks with y in {-1,1}
*
*/
struct __pyx_vtabstruct_7sklearn_12linear_model_8sgd_fast_SquaredHinge {
struct __pyx_vtabstruct_7sklearn_12linear_model_8sgd_fast_LossFunction __pyx_base;
};
static struct __pyx_vtabstruct_7sklearn_12linear_model_8sgd_fast_SquaredHinge *__pyx_vtabptr_7sklearn_12linear_model_8sgd_fast_SquaredHinge;
/* "sklearn/linear_model/sgd_fast.pyx":235
*
*
* cdef class Huber(Regression): # <<<<<<<<<<<<<<
* """Huber regression loss
*
*/
struct __pyx_vtabstruct_7sklearn_12linear_model_8sgd_fast_Huber {
struct __pyx_vtabstruct_7sklearn_12linear_model_8sgd_fast_Regression __pyx_base;
};
static struct __pyx_vtabstruct_7sklearn_12linear_model_8sgd_fast_Huber *__pyx_vtabptr_7sklearn_12linear_model_8sgd_fast_Huber;
/* "sklearn/linear_model/sgd_fast.pyx":134
*
*
* cdef class Hinge(Classification): # <<<<<<<<<<<<<<
* """Hinge loss for binary classification tasks with y in {-1,1}
*
*/
struct __pyx_vtabstruct_7sklearn_12linear_model_8sgd_fast_Hinge {
struct __pyx_vtabstruct_7sklearn_12linear_model_8sgd_fast_Classification __pyx_base;
};
static struct __pyx_vtabstruct_7sklearn_12linear_model_8sgd_fast_Hinge *__pyx_vtabptr_7sklearn_12linear_model_8sgd_fast_Hinge;
/* "sklearn/utils/weight_vector.pxd":14
*
*
* cdef class WeightVector(object): # <<<<<<<<<<<<<<
* cdef np.ndarray w
* cdef DOUBLE *w_data_ptr
*/
struct __pyx_vtabstruct_7sklearn_5utils_13weight_vector_WeightVector {
void (*add)(struct __pyx_obj_7sklearn_5utils_13weight_vector_WeightVector *, __pyx_t_7sklearn_5utils_13weight_vector_DOUBLE *, __pyx_t_7sklearn_5utils_13weight_vector_INTEGER *, int, double);
double (*dot)(struct __pyx_obj_7sklearn_5utils_13weight_vector_WeightVector *, __pyx_t_7sklearn_5utils_13weight_vector_DOUBLE *, __pyx_t_7sklearn_5utils_13weight_vector_INTEGER *, int);
void (*scale)(struct __pyx_obj_7sklearn_5utils_13weight_vector_WeightVector *, double);
void (*reset_wscale)(struct __pyx_obj_7sklearn_5utils_13weight_vector_WeightVector *);
double (*norm)(struct __pyx_obj_7sklearn_5utils_13weight_vector_WeightVector *);
};
static struct __pyx_vtabstruct_7sklearn_5utils_13weight_vector_WeightVector *__pyx_vtabptr_7sklearn_5utils_13weight_vector_WeightVector;
#ifndef CYTHON_REFNANNY
#define CYTHON_REFNANNY 0
#endif
#if CYTHON_REFNANNY
typedef struct {
void (*INCREF)(void*, PyObject*, int);
void (*DECREF)(void*, PyObject*, int);
void (*GOTREF)(void*, PyObject*, int);
void (*GIVEREF)(void*, PyObject*, int);
void* (*SetupContext)(const char*, int, const char*);
void (*FinishContext)(void**);
} __Pyx_RefNannyAPIStruct;
static __Pyx_RefNannyAPIStruct *__Pyx_RefNanny = NULL;
static __Pyx_RefNannyAPIStruct *__Pyx_RefNannyImportAPI(const char *modname); /*proto*/
#define __Pyx_RefNannyDeclarations void *__pyx_refnanny = NULL;
#ifdef WITH_THREAD
#define __Pyx_RefNannySetupContext(name, acquire_gil) \
if (acquire_gil) { \
PyGILState_STATE __pyx_gilstate_save = PyGILState_Ensure(); \
__pyx_refnanny = __Pyx_RefNanny->SetupContext((name), __LINE__, __FILE__); \
PyGILState_Release(__pyx_gilstate_save); \
} else { \
__pyx_refnanny = __Pyx_RefNanny->SetupContext((name), __LINE__, __FILE__); \
}
#else
#define __Pyx_RefNannySetupContext(name, acquire_gil) \
__pyx_refnanny = __Pyx_RefNanny->SetupContext((name), __LINE__, __FILE__)
#endif
#define __Pyx_RefNannyFinishContext() \
__Pyx_RefNanny->FinishContext(&__pyx_refnanny)
#define __Pyx_INCREF(r) __Pyx_RefNanny->INCREF(__pyx_refnanny, (PyObject *)(r), __LINE__)
#define __Pyx_DECREF(r) __Pyx_RefNanny->DECREF(__pyx_refnanny, (PyObject *)(r), __LINE__)
#define __Pyx_GOTREF(r) __Pyx_RefNanny->GOTREF(__pyx_refnanny, (PyObject *)(r), __LINE__)
#define __Pyx_GIVEREF(r) __Pyx_RefNanny->GIVEREF(__pyx_refnanny, (PyObject *)(r), __LINE__)
#define __Pyx_XINCREF(r) do { if((r) != NULL) {__Pyx_INCREF(r); }} while(0)
#define __Pyx_XDECREF(r) do { if((r) != NULL) {__Pyx_DECREF(r); }} while(0)
#define __Pyx_XGOTREF(r) do { if((r) != NULL) {__Pyx_GOTREF(r); }} while(0)
#define __Pyx_XGIVEREF(r) do { if((r) != NULL) {__Pyx_GIVEREF(r);}} while(0)
#else
#define __Pyx_RefNannyDeclarations
#define __Pyx_RefNannySetupContext(name, acquire_gil)
#define __Pyx_RefNannyFinishContext()
#define __Pyx_INCREF(r) Py_INCREF(r)
#define __Pyx_DECREF(r) Py_DECREF(r)
#define __Pyx_GOTREF(r)
#define __Pyx_GIVEREF(r)
#define __Pyx_XINCREF(r) Py_XINCREF(r)
#define __Pyx_XDECREF(r) Py_XDECREF(r)
#define __Pyx_XGOTREF(r)
#define __Pyx_XGIVEREF(r)
#endif /* CYTHON_REFNANNY */
#define __Pyx_CLEAR(r) do { PyObject* tmp = ((PyObject*)(r)); r = NULL; __Pyx_DECREF(tmp);} while(0)
#define __Pyx_XCLEAR(r) do { if((r) != NULL) {PyObject* tmp = ((PyObject*)(r)); r = NULL; __Pyx_DECREF(tmp);}} while(0)
static PyObject *__Pyx_GetName(PyObject *dict, PyObject *name); /*proto*/
static CYTHON_INLINE void __Pyx_ErrRestore(PyObject *type, PyObject *value, PyObject *tb); /*proto*/
static CYTHON_INLINE void __Pyx_ErrFetch(PyObject **type, PyObject **value, PyObject **tb); /*proto*/
static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, PyObject *cause); /*proto*/
static void __Pyx_RaiseArgtupleInvalid(const char* func_name, int exact,
Py_ssize_t num_min, Py_ssize_t num_max, Py_ssize_t num_found); /*proto*/
static void __Pyx_RaiseDoubleKeywordsError(const char* func_name, PyObject* kw_name); /*proto*/
static int __Pyx_ParseOptionalKeywords(PyObject *kwds, PyObject **argnames[], \
PyObject *kwds2, PyObject *values[], Py_ssize_t num_pos_args, \
const char* function_name); /*proto*/
static int __Pyx_ArgTypeTest(PyObject *obj, PyTypeObject *type, int none_allowed,
const char *name, int exact); /*proto*/
static CYTHON_INLINE int __Pyx_GetBufferAndValidate(Py_buffer* buf, PyObject* obj,
__Pyx_TypeInfo* dtype, int flags, int nd, int cast, __Pyx_BufFmt_StackElem* stack);
static CYTHON_INLINE void __Pyx_SafeReleaseBuffer(Py_buffer* info);
static CYTHON_INLINE int __Pyx_TypeTest(PyObject *obj, PyTypeObject *type); /*proto*/
static void __Pyx_RaiseBufferFallbackError(void); /*proto*/
static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Generic(PyObject *o, PyObject* j) {
PyObject *r;
if (!j) return NULL;
r = PyObject_GetItem(o, j);
Py_DECREF(j);
return r;
}
#define __Pyx_GetItemInt_List(o, i, size, to_py_func) (((size) <= sizeof(Py_ssize_t)) ? \
__Pyx_GetItemInt_List_Fast(o, i) : \
__Pyx_GetItemInt_Generic(o, to_py_func(i)))
static CYTHON_INLINE PyObject *__Pyx_GetItemInt_List_Fast(PyObject *o, Py_ssize_t i) {
#if CYTHON_COMPILING_IN_CPYTHON
if (likely((0 <= i) & (i < PyList_GET_SIZE(o)))) {
PyObject *r = PyList_GET_ITEM(o, i);
Py_INCREF(r);
return r;
}
else if ((-PyList_GET_SIZE(o) <= i) & (i < 0)) {
PyObject *r = PyList_GET_ITEM(o, PyList_GET_SIZE(o) + i);
Py_INCREF(r);
return r;
}
return __Pyx_GetItemInt_Generic(o, PyInt_FromSsize_t(i));
#else
return PySequence_GetItem(o, i);
#endif
}
#define __Pyx_GetItemInt_Tuple(o, i, size, to_py_func) (((size) <= sizeof(Py_ssize_t)) ? \
__Pyx_GetItemInt_Tuple_Fast(o, i) : \
__Pyx_GetItemInt_Generic(o, to_py_func(i)))
static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Tuple_Fast(PyObject *o, Py_ssize_t i) {
#if CYTHON_COMPILING_IN_CPYTHON
if (likely((0 <= i) & (i < PyTuple_GET_SIZE(o)))) {
PyObject *r = PyTuple_GET_ITEM(o, i);
Py_INCREF(r);
return r;
}
else if ((-PyTuple_GET_SIZE(o) <= i) & (i < 0)) {
PyObject *r = PyTuple_GET_ITEM(o, PyTuple_GET_SIZE(o) + i);
Py_INCREF(r);
return r;
}
return __Pyx_GetItemInt_Generic(o, PyInt_FromSsize_t(i));
#else
return PySequence_GetItem(o, i);
#endif
}
#define __Pyx_GetItemInt(o, i, size, to_py_func) (((size) <= sizeof(Py_ssize_t)) ? \
__Pyx_GetItemInt_Fast(o, i) : \
__Pyx_GetItemInt_Generic(o, to_py_func(i)))
static CYTHON_INLINE PyObject *__Pyx_GetItemInt_Fast(PyObject *o, Py_ssize_t i) {
#if CYTHON_COMPILING_IN_CPYTHON
if (PyList_CheckExact(o)) {
Py_ssize_t n = (likely(i >= 0)) ? i : i + PyList_GET_SIZE(o);
if (likely((n >= 0) & (n < PyList_GET_SIZE(o)))) {
PyObject *r = PyList_GET_ITEM(o, n);
Py_INCREF(r);
return r;
}
}
else if (PyTuple_CheckExact(o)) {
Py_ssize_t n = (likely(i >= 0)) ? i : i + PyTuple_GET_SIZE(o);
if (likely((n >= 0) & (n < PyTuple_GET_SIZE(o)))) {
PyObject *r = PyTuple_GET_ITEM(o, n);
Py_INCREF(r);
return r;
}
} else { /* inlined PySequence_GetItem() */
PySequenceMethods *m = Py_TYPE(o)->tp_as_sequence;
if (likely(m && m->sq_item)) {
if (unlikely(i < 0) && likely(m->sq_length)) {
Py_ssize_t l = m->sq_length(o);
if (unlikely(l < 0)) return NULL;
i += l;
}
return m->sq_item(o, i);
}
}
#else
if (PySequence_Check(o)) {
return PySequence_GetItem(o, i);
}
#endif
return __Pyx_GetItemInt_Generic(o, PyInt_FromSsize_t(i));
}
static CYTHON_INLINE void __Pyx_RaiseTooManyValuesError(Py_ssize_t expected);
static CYTHON_INLINE void __Pyx_RaiseNeedMoreValuesError(Py_ssize_t index);
static CYTHON_INLINE void __Pyx_RaiseNoneNotIterableError(void);
static CYTHON_INLINE int __Pyx_IterFinish(void); /*proto*/
static int __Pyx_IternextUnpackEndCheck(PyObject *retval, Py_ssize_t expected); /*proto*/
typedef struct {
Py_ssize_t shape, strides, suboffsets;
} __Pyx_Buf_DimInfo;
typedef struct {
size_t refcount;
Py_buffer pybuffer;
} __Pyx_Buffer;
typedef struct {
__Pyx_Buffer *rcbuffer;
char *data;
__Pyx_Buf_DimInfo diminfo[8];
} __Pyx_LocalBuf_ND;
#if PY_MAJOR_VERSION < 3
static int __Pyx_GetBuffer(PyObject *obj, Py_buffer *view, int flags);
static void __Pyx_ReleaseBuffer(Py_buffer *view);
#else
#define __Pyx_GetBuffer PyObject_GetBuffer
#define __Pyx_ReleaseBuffer PyBuffer_Release
#endif
static Py_ssize_t __Pyx_zeros[] = {0, 0, 0, 0, 0, 0, 0, 0};
static Py_ssize_t __Pyx_minusones[] = {-1, -1, -1, -1, -1, -1, -1, -1};
static PyObject *__Pyx_Import(PyObject *name, PyObject *from_list, long level); /*proto*/
static CYTHON_INLINE void __Pyx_RaiseImportError(PyObject *name);
static int __Pyx_Print(PyObject*, PyObject *, int); /*proto*/
#if CYTHON_COMPILING_IN_PYPY || PY_MAJOR_VERSION >= 3
static PyObject* __pyx_print = 0;
static PyObject* __pyx_print_kwargs = 0;
#endif
static int __Pyx_PrintOne(PyObject* stream, PyObject *o); /*proto*/
#if CYTHON_CCOMPLEX
#ifdef __cplusplus
#define __Pyx_CREAL(z) ((z).real())
#define __Pyx_CIMAG(z) ((z).imag())
#else
#define __Pyx_CREAL(z) (__real__(z))
#define __Pyx_CIMAG(z) (__imag__(z))
#endif
#else
#define __Pyx_CREAL(z) ((z).real)
#define __Pyx_CIMAG(z) ((z).imag)
#endif
#if defined(_WIN32) && defined(__cplusplus) && CYTHON_CCOMPLEX
#define __Pyx_SET_CREAL(z,x) ((z).real(x))
#define __Pyx_SET_CIMAG(z,y) ((z).imag(y))
#else
#define __Pyx_SET_CREAL(z,x) __Pyx_CREAL(z) = (x)
#define __Pyx_SET_CIMAG(z,y) __Pyx_CIMAG(z) = (y)
#endif
static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float, float);
#if CYTHON_CCOMPLEX
#define __Pyx_c_eqf(a, b) ((a)==(b))
#define __Pyx_c_sumf(a, b) ((a)+(b))
#define __Pyx_c_difff(a, b) ((a)-(b))
#define __Pyx_c_prodf(a, b) ((a)*(b))
#define __Pyx_c_quotf(a, b) ((a)/(b))
#define __Pyx_c_negf(a) (-(a))
#ifdef __cplusplus
#define __Pyx_c_is_zerof(z) ((z)==(float)0)
#define __Pyx_c_conjf(z) (::std::conj(z))
#if 1
#define __Pyx_c_absf(z) (::std::abs(z))
#define __Pyx_c_powf(a, b) (::std::pow(a, b))
#endif
#else
#define __Pyx_c_is_zerof(z) ((z)==0)
#define __Pyx_c_conjf(z) (conjf(z))
#if 1
#define __Pyx_c_absf(z) (cabsf(z))
#define __Pyx_c_powf(a, b) (cpowf(a, b))
#endif
#endif
#else
static CYTHON_INLINE int __Pyx_c_eqf(__pyx_t_float_complex, __pyx_t_float_complex);
static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_sumf(__pyx_t_float_complex, __pyx_t_float_complex);
static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_difff(__pyx_t_float_complex, __pyx_t_float_complex);
static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_prodf(__pyx_t_float_complex, __pyx_t_float_complex);
static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_quotf(__pyx_t_float_complex, __pyx_t_float_complex);
static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_negf(__pyx_t_float_complex);
static CYTHON_INLINE int __Pyx_c_is_zerof(__pyx_t_float_complex);
static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_conjf(__pyx_t_float_complex);
#if 1
static CYTHON_INLINE float __Pyx_c_absf(__pyx_t_float_complex);
static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_powf(__pyx_t_float_complex, __pyx_t_float_complex);
#endif
#endif
static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double, double);
#if CYTHON_CCOMPLEX
#define __Pyx_c_eq(a, b) ((a)==(b))
#define __Pyx_c_sum(a, b) ((a)+(b))
#define __Pyx_c_diff(a, b) ((a)-(b))
#define __Pyx_c_prod(a, b) ((a)*(b))
#define __Pyx_c_quot(a, b) ((a)/(b))
#define __Pyx_c_neg(a) (-(a))
#ifdef __cplusplus
#define __Pyx_c_is_zero(z) ((z)==(double)0)
#define __Pyx_c_conj(z) (::std::conj(z))
#if 1
#define __Pyx_c_abs(z) (::std::abs(z))
#define __Pyx_c_pow(a, b) (::std::pow(a, b))
#endif
#else
#define __Pyx_c_is_zero(z) ((z)==0)
#define __Pyx_c_conj(z) (conj(z))
#if 1
#define __Pyx_c_abs(z) (cabs(z))
#define __Pyx_c_pow(a, b) (cpow(a, b))
#endif
#endif
#else
static CYTHON_INLINE int __Pyx_c_eq(__pyx_t_double_complex, __pyx_t_double_complex);
static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_sum(__pyx_t_double_complex, __pyx_t_double_complex);
static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_diff(__pyx_t_double_complex, __pyx_t_double_complex);
static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_prod(__pyx_t_double_complex, __pyx_t_double_complex);
static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_quot(__pyx_t_double_complex, __pyx_t_double_complex);
static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_neg(__pyx_t_double_complex);
static CYTHON_INLINE int __Pyx_c_is_zero(__pyx_t_double_complex);
static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_conj(__pyx_t_double_complex);
#if 1
static CYTHON_INLINE double __Pyx_c_abs(__pyx_t_double_complex);
static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_pow(__pyx_t_double_complex, __pyx_t_double_complex);
#endif
#endif
static CYTHON_INLINE unsigned char __Pyx_PyInt_AsUnsignedChar(PyObject *);
static CYTHON_INLINE unsigned short __Pyx_PyInt_AsUnsignedShort(PyObject *);
static CYTHON_INLINE unsigned int __Pyx_PyInt_AsUnsignedInt(PyObject *);
static CYTHON_INLINE char __Pyx_PyInt_AsChar(PyObject *);
static CYTHON_INLINE short __Pyx_PyInt_AsShort(PyObject *);
static CYTHON_INLINE int __Pyx_PyInt_AsInt(PyObject *);
static CYTHON_INLINE signed char __Pyx_PyInt_AsSignedChar(PyObject *);
static CYTHON_INLINE signed short __Pyx_PyInt_AsSignedShort(PyObject *);
static CYTHON_INLINE signed int __Pyx_PyInt_AsSignedInt(PyObject *);
static CYTHON_INLINE int __Pyx_PyInt_AsLongDouble(PyObject *);
static CYTHON_INLINE unsigned long __Pyx_PyInt_AsUnsignedLong(PyObject *);
static CYTHON_INLINE unsigned PY_LONG_LONG __Pyx_PyInt_AsUnsignedLongLong(PyObject *);
static CYTHON_INLINE long __Pyx_PyInt_AsLong(PyObject *);
static CYTHON_INLINE PY_LONG_LONG __Pyx_PyInt_AsLongLong(PyObject *);
static CYTHON_INLINE signed long __Pyx_PyInt_AsSignedLong(PyObject *);
static CYTHON_INLINE signed PY_LONG_LONG __Pyx_PyInt_AsSignedLongLong(PyObject *);
static void __Pyx_WriteUnraisable(const char *name, int clineno,
int lineno, const char *filename); /*proto*/
static int __Pyx_check_binary_version(void);
static int __Pyx_SetVtable(PyObject *dict, void *vtable); /*proto*/
#if !defined(__Pyx_PyIdentifier_FromString)
#if PY_MAJOR_VERSION < 3
#define __Pyx_PyIdentifier_FromString(s) PyString_FromString(s)
#else
#define __Pyx_PyIdentifier_FromString(s) PyUnicode_FromString(s)
#endif
#endif
static PyObject *__Pyx_ImportModule(const char *name); /*proto*/
static PyTypeObject *__Pyx_ImportType(const char *module_name, const char *class_name, size_t size, int strict); /*proto*/
static void* __Pyx_GetVtable(PyObject *dict); /*proto*/
typedef struct {
int code_line;
PyCodeObject* code_object;
} __Pyx_CodeObjectCacheEntry;
struct __Pyx_CodeObjectCache {
int count;
int max_count;
__Pyx_CodeObjectCacheEntry* entries;
};
static struct __Pyx_CodeObjectCache __pyx_code_cache = {0,0,NULL};
static int __pyx_bisect_code_objects(__Pyx_CodeObjectCacheEntry* entries, int count, int code_line);
static PyCodeObject *__pyx_find_code_object(int code_line);
static void __pyx_insert_code_object(int code_line, PyCodeObject* code_object);
static void __Pyx_AddTraceback(const char *funcname, int c_line,
int py_line, const char *filename); /*proto*/
static int __Pyx_InitStrings(__Pyx_StringTabEntry *t); /*proto*/
/* Module declarations from 'libc.math' */
/* Module declarations from 'cpython.buffer' */
/* Module declarations from 'cpython.ref' */
/* Module declarations from 'libc.stdio' */
/* Module declarations from 'cpython.object' */
/* Module declarations from '__builtin__' */
/* Module declarations from 'cpython.type' */
static PyTypeObject *__pyx_ptype_7cpython_4type_type = 0;
/* Module declarations from 'libc.stdlib' */
/* Module declarations from 'numpy' */
/* Module declarations from 'numpy' */
static PyTypeObject *__pyx_ptype_5numpy_dtype = 0;
static PyTypeObject *__pyx_ptype_5numpy_flatiter = 0;
static PyTypeObject *__pyx_ptype_5numpy_broadcast = 0;
static PyTypeObject *__pyx_ptype_5numpy_ndarray = 0;
static PyTypeObject *__pyx_ptype_5numpy_ufunc = 0;
static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *, char *, char *, int *); /*proto*/
/* Module declarations from 'cython' */
/* Module declarations from 'sklearn.utils.weight_vector' */
static PyTypeObject *__pyx_ptype_7sklearn_5utils_13weight_vector_WeightVector = 0;
/* Module declarations from 'sklearn.utils.seq_dataset' */
static PyTypeObject *__pyx_ptype_7sklearn_5utils_11seq_dataset_SequentialDataset = 0;
static PyTypeObject *__pyx_ptype_7sklearn_5utils_11seq_dataset_ArrayDataset = 0;
static PyTypeObject *__pyx_ptype_7sklearn_5utils_11seq_dataset_CSRDataset = 0;
/* Module declarations from 'sklearn.linear_model.sgd_fast' */
static PyTypeObject *__pyx_ptype_7sklearn_12linear_model_8sgd_fast_LossFunction = 0;
static PyTypeObject *__pyx_ptype_7sklearn_12linear_model_8sgd_fast_Regression = 0;
static PyTypeObject *__pyx_ptype_7sklearn_12linear_model_8sgd_fast_Classification = 0;
static PyTypeObject *__pyx_ptype_7sklearn_12linear_model_8sgd_fast_ModifiedHuber = 0;
static PyTypeObject *__pyx_ptype_7sklearn_12linear_model_8sgd_fast_Hinge = 0;
static PyTypeObject *__pyx_ptype_7sklearn_12linear_model_8sgd_fast_SquaredHinge = 0;
static PyTypeObject *__pyx_ptype_7sklearn_12linear_model_8sgd_fast_Log = 0;
static PyTypeObject *__pyx_ptype_7sklearn_12linear_model_8sgd_fast_SquaredLoss = 0;
static PyTypeObject *__pyx_ptype_7sklearn_12linear_model_8sgd_fast_Huber = 0;
static PyTypeObject *__pyx_ptype_7sklearn_12linear_model_8sgd_fast_EpsilonInsensitive = 0;
static PyTypeObject *__pyx_ptype_7sklearn_12linear_model_8sgd_fast_SquaredEpsilonInsensitive = 0;
static CYTHON_INLINE double __pyx_f_7sklearn_12linear_model_8sgd_fast_max(double, double); /*proto*/
static CYTHON_INLINE double __pyx_f_7sklearn_12linear_model_8sgd_fast_min(double, double); /*proto*/
static double __pyx_f_7sklearn_12linear_model_8sgd_fast_sqnorm(__pyx_t_7sklearn_12linear_model_8sgd_fast_DOUBLE *, __pyx_t_7sklearn_12linear_model_8sgd_fast_INTEGER *, int); /*proto*/
static void __pyx_f_7sklearn_12linear_model_8sgd_fast_l1penalty(struct __pyx_obj_7sklearn_5utils_13weight_vector_WeightVector *, __pyx_t_7sklearn_12linear_model_8sgd_fast_DOUBLE *, __pyx_t_7sklearn_12linear_model_8sgd_fast_INTEGER *, int, double); /*proto*/
static __Pyx_TypeInfo __Pyx_TypeInfo_nn___pyx_t_7sklearn_12linear_model_8sgd_fast_DOUBLE = { "DOUBLE", NULL, sizeof(__pyx_t_7sklearn_12linear_model_8sgd_fast_DOUBLE), { 0 }, 0, 'R', 0, 0 };
#define __Pyx_MODULE_NAME "sklearn.linear_model.sgd_fast"
int __pyx_module_is_main_sklearn__linear_model__sgd_fast = 0;
/* Implementation of 'sklearn.linear_model.sgd_fast' */
static PyObject *__pyx_builtin_NotImplementedError;
static PyObject *__pyx_builtin_range;
static PyObject *__pyx_builtin_ValueError;
static PyObject *__pyx_builtin_RuntimeError;
static PyObject *__pyx_pf_7sklearn_12linear_model_8sgd_fast_12LossFunction_loss(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_LossFunction *__pyx_v_self, double __pyx_v_p, double __pyx_v_y); /* proto */
static PyObject *__pyx_pf_7sklearn_12linear_model_8sgd_fast_12LossFunction_2dloss(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_LossFunction *__pyx_v_self, double __pyx_v_p, double __pyx_v_y); /* proto */
static PyObject *__pyx_pf_7sklearn_12linear_model_8sgd_fast_10Regression_loss(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_Regression *__pyx_v_self, double __pyx_v_p, double __pyx_v_y); /* proto */
static PyObject *__pyx_pf_7sklearn_12linear_model_8sgd_fast_10Regression_2dloss(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_Regression *__pyx_v_self, double __pyx_v_p, double __pyx_v_y); /* proto */
static PyObject *__pyx_pf_7sklearn_12linear_model_8sgd_fast_14Classification_loss(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_Classification *__pyx_v_self, double __pyx_v_p, double __pyx_v_y); /* proto */
static PyObject *__pyx_pf_7sklearn_12linear_model_8sgd_fast_14Classification_2dloss(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_Classification *__pyx_v_self, double __pyx_v_p, double __pyx_v_y); /* proto */
static PyObject *__pyx_pf_7sklearn_12linear_model_8sgd_fast_13ModifiedHuber_loss(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_ModifiedHuber *__pyx_v_self, double __pyx_v_p, double __pyx_v_y); /* proto */
static PyObject *__pyx_pf_7sklearn_12linear_model_8sgd_fast_13ModifiedHuber_2dloss(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_ModifiedHuber *__pyx_v_self, double __pyx_v_p, double __pyx_v_y); /* proto */
static PyObject *__pyx_pf_7sklearn_12linear_model_8sgd_fast_13ModifiedHuber_4__reduce__(CYTHON_UNUSED struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_ModifiedHuber *__pyx_v_self); /* proto */
static int __pyx_pf_7sklearn_12linear_model_8sgd_fast_5Hinge___init__(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_Hinge *__pyx_v_self, double __pyx_v_threshold); /* proto */
static PyObject *__pyx_pf_7sklearn_12linear_model_8sgd_fast_5Hinge_2loss(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_Hinge *__pyx_v_self, double __pyx_v_p, double __pyx_v_y); /* proto */
static PyObject *__pyx_pf_7sklearn_12linear_model_8sgd_fast_5Hinge_4dloss(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_Hinge *__pyx_v_self, double __pyx_v_p, double __pyx_v_y); /* proto */
static PyObject *__pyx_pf_7sklearn_12linear_model_8sgd_fast_5Hinge_6__reduce__(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_Hinge *__pyx_v_self); /* proto */
static int __pyx_pf_7sklearn_12linear_model_8sgd_fast_12SquaredHinge___init__(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_SquaredHinge *__pyx_v_self, double __pyx_v_threshold); /* proto */
static PyObject *__pyx_pf_7sklearn_12linear_model_8sgd_fast_12SquaredHinge_2loss(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_SquaredHinge *__pyx_v_self, double __pyx_v_p, double __pyx_v_y); /* proto */
static PyObject *__pyx_pf_7sklearn_12linear_model_8sgd_fast_12SquaredHinge_4dloss(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_SquaredHinge *__pyx_v_self, double __pyx_v_p, double __pyx_v_y); /* proto */
static PyObject *__pyx_pf_7sklearn_12linear_model_8sgd_fast_12SquaredHinge_6__reduce__(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_SquaredHinge *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_7sklearn_12linear_model_8sgd_fast_3Log_loss(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_Log *__pyx_v_self, double __pyx_v_p, double __pyx_v_y); /* proto */
static PyObject *__pyx_pf_7sklearn_12linear_model_8sgd_fast_3Log_2dloss(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_Log *__pyx_v_self, double __pyx_v_p, double __pyx_v_y); /* proto */
static PyObject *__pyx_pf_7sklearn_12linear_model_8sgd_fast_3Log_4__reduce__(CYTHON_UNUSED struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_Log *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_7sklearn_12linear_model_8sgd_fast_11SquaredLoss_loss(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_SquaredLoss *__pyx_v_self, double __pyx_v_p, double __pyx_v_y); /* proto */
static PyObject *__pyx_pf_7sklearn_12linear_model_8sgd_fast_11SquaredLoss_2dloss(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_SquaredLoss *__pyx_v_self, double __pyx_v_p, double __pyx_v_y); /* proto */
static PyObject *__pyx_pf_7sklearn_12linear_model_8sgd_fast_11SquaredLoss_4__reduce__(CYTHON_UNUSED struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_SquaredLoss *__pyx_v_self); /* proto */
static int __pyx_pf_7sklearn_12linear_model_8sgd_fast_5Huber___init__(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_Huber *__pyx_v_self, double __pyx_v_c); /* proto */
static PyObject *__pyx_pf_7sklearn_12linear_model_8sgd_fast_5Huber_2loss(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_Huber *__pyx_v_self, double __pyx_v_p, double __pyx_v_y); /* proto */
static PyObject *__pyx_pf_7sklearn_12linear_model_8sgd_fast_5Huber_4dloss(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_Huber *__pyx_v_self, double __pyx_v_p, double __pyx_v_y); /* proto */
static PyObject *__pyx_pf_7sklearn_12linear_model_8sgd_fast_5Huber_6__reduce__(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_Huber *__pyx_v_self); /* proto */
static int __pyx_pf_7sklearn_12linear_model_8sgd_fast_18EpsilonInsensitive___init__(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_EpsilonInsensitive *__pyx_v_self, double __pyx_v_epsilon); /* proto */
static PyObject *__pyx_pf_7sklearn_12linear_model_8sgd_fast_18EpsilonInsensitive_2loss(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_EpsilonInsensitive *__pyx_v_self, double __pyx_v_p, double __pyx_v_y); /* proto */
static PyObject *__pyx_pf_7sklearn_12linear_model_8sgd_fast_18EpsilonInsensitive_4dloss(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_EpsilonInsensitive *__pyx_v_self, double __pyx_v_p, double __pyx_v_y); /* proto */
static PyObject *__pyx_pf_7sklearn_12linear_model_8sgd_fast_18EpsilonInsensitive_6__reduce__(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_EpsilonInsensitive *__pyx_v_self); /* proto */
static int __pyx_pf_7sklearn_12linear_model_8sgd_fast_25SquaredEpsilonInsensitive___init__(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_SquaredEpsilonInsensitive *__pyx_v_self, double __pyx_v_epsilon); /* proto */
static PyObject *__pyx_pf_7sklearn_12linear_model_8sgd_fast_25SquaredEpsilonInsensitive_2loss(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_SquaredEpsilonInsensitive *__pyx_v_self, double __pyx_v_p, double __pyx_v_y); /* proto */
static PyObject *__pyx_pf_7sklearn_12linear_model_8sgd_fast_25SquaredEpsilonInsensitive_4dloss(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_SquaredEpsilonInsensitive *__pyx_v_self, double __pyx_v_p, double __pyx_v_y); /* proto */
static PyObject *__pyx_pf_7sklearn_12linear_model_8sgd_fast_25SquaredEpsilonInsensitive_6__reduce__(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_SquaredEpsilonInsensitive *__pyx_v_self); /* proto */
static PyObject *__pyx_pf_7sklearn_12linear_model_8sgd_fast_plain_sgd(CYTHON_UNUSED PyObject *__pyx_self, PyArrayObject *__pyx_v_weights, double __pyx_v_intercept, struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_LossFunction *__pyx_v_loss, int __pyx_v_penalty_type, double __pyx_v_alpha, double __pyx_v_C, double __pyx_v_rho, struct __pyx_obj_7sklearn_5utils_11seq_dataset_SequentialDataset *__pyx_v_dataset, int __pyx_v_n_iter, int __pyx_v_fit_intercept, int __pyx_v_verbose, int __pyx_v_shuffle, PyObject *__pyx_v_seed, double __pyx_v_weight_pos, double __pyx_v_weight_neg, int __pyx_v_learning_rate, double __pyx_v_eta0, double __pyx_v_power_t, double __pyx_v_t, double __pyx_v_intercept_decay); /* proto */
static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /* proto */
static void __pyx_pf_5numpy_7ndarray_2__releasebuffer__(PyArrayObject *__pyx_v_self, Py_buffer *__pyx_v_info); /* proto */
static char __pyx_k_1[] = "-- Epoch %d";
static char __pyx_k_2[] = "Norm: %.2f, NNZs: %d, Bias: %.6f, T: %d, Avg. loss: %.6f";
static char __pyx_k_3[] = "Total training time: %.2f seconds.";
static char __pyx_k_4[] = "floating-point under-/overflow occured.";
static char __pyx_k_6[] = "ndarray is not C contiguous";
static char __pyx_k_8[] = "ndarray is not Fortran contiguous";
static char __pyx_k_10[] = "Non-native byte order not supported";
static char __pyx_k_12[] = "unknown dtype code in numpy.pxd (%d)";
static char __pyx_k_13[] = "Format string allocated too short, see comment in numpy.pxd";
static char __pyx_k_16[] = "Format string allocated too short.";
static char __pyx_k_20[] = "/scratch/apps/src/scikit-learn/sklearn/linear_model/sgd_fast.pyx";
static char __pyx_k_21[] = "sklearn.linear_model.sgd_fast";
static char __pyx_k__B[] = "B";
static char __pyx_k__C[] = "C";
static char __pyx_k__H[] = "H";
static char __pyx_k__I[] = "I";
static char __pyx_k__L[] = "L";
static char __pyx_k__O[] = "O";
static char __pyx_k__Q[] = "Q";
static char __pyx_k__b[] = "b";
static char __pyx_k__c[] = "c";
static char __pyx_k__d[] = "d";
static char __pyx_k__f[] = "f";
static char __pyx_k__g[] = "g";
static char __pyx_k__h[] = "h";
static char __pyx_k__i[] = "i";
static char __pyx_k__l[] = "l";
static char __pyx_k__p[] = "p";
static char __pyx_k__q[] = "q";
static char __pyx_k__t[] = "t";
static char __pyx_k__u[] = "u";
static char __pyx_k__w[] = "w";
static char __pyx_k__y[] = "y";
static char __pyx_k__Zd[] = "Zd";
static char __pyx_k__Zf[] = "Zf";
static char __pyx_k__Zg[] = "Zg";
static char __pyx_k__np[] = "np";
static char __pyx_k__any[] = "any";
static char __pyx_k__eta[] = "eta";
static char __pyx_k__rho[] = "rho";
static char __pyx_k__sys[] = "sys";
static char __pyx_k__eta0[] = "eta0";
static char __pyx_k__loss[] = "loss";
static char __pyx_k__seed[] = "seed";
static char __pyx_k__time[] = "time";
static char __pyx_k__xnnz[] = "xnnz";
static char __pyx_k__alpha[] = "alpha";
static char __pyx_k__count[] = "count";
static char __pyx_k__dloss[] = "dloss";
static char __pyx_k__dtype[] = "dtype";
static char __pyx_k__epoch[] = "epoch";
static char __pyx_k__isinf[] = "isinf";
static char __pyx_k__isnan[] = "isnan";
static char __pyx_k__numpy[] = "numpy";
static char __pyx_k__order[] = "order";
static char __pyx_k__range[] = "range";
static char __pyx_k__shape[] = "shape";
static char __pyx_k__zeros[] = "zeros";
static char __pyx_k__n_iter[] = "n_iter";
static char __pyx_k__update[] = "update";
static char __pyx_k__dataset[] = "dataset";
static char __pyx_k__epsilon[] = "epsilon";
static char __pyx_k__float64[] = "float64";
static char __pyx_k__nonzero[] = "nonzero";
static char __pyx_k__power_t[] = "power_t";
static char __pyx_k__shuffle[] = "shuffle";
static char __pyx_k__sumloss[] = "sumloss";
static char __pyx_k__t_start[] = "t_start";
static char __pyx_k__verbose[] = "verbose";
static char __pyx_k__weights[] = "weights";
static char __pyx_k____main__[] = "__main__";
static char __pyx_k____test__[] = "__test__";
static char __pyx_k__is_hinge[] = "is_hinge";
static char __pyx_k__intercept[] = "intercept";
static char __pyx_k__n_samples[] = "n_samples";
static char __pyx_k__plain_sgd[] = "plain_sgd";
static char __pyx_k__threshold[] = "threshold";
static char __pyx_k__x_ind_ptr[] = "x_ind_ptr";
static char __pyx_k__ValueError[] = "ValueError";
static char __pyx_k__n_features[] = "n_features";
static char __pyx_k__q_data_ptr[] = "q_data_ptr";
static char __pyx_k__weight_neg[] = "weight_neg";
static char __pyx_k__weight_pos[] = "weight_pos";
static char __pyx_k__x_data_ptr[] = "x_data_ptr";
static char __pyx_k__RuntimeError[] = "RuntimeError";
static char __pyx_k__class_weight[] = "class_weight";
static char __pyx_k__penalty_type[] = "penalty_type";
static char __pyx_k__fit_intercept[] = "fit_intercept";
static char __pyx_k__learning_rate[] = "learning_rate";
static char __pyx_k__sample_weight[] = "sample_weight";
static char __pyx_k__intercept_decay[] = "intercept_decay";
static char __pyx_k__NotImplementedError[] = "NotImplementedError";
static PyObject *__pyx_kp_s_1;
static PyObject *__pyx_kp_u_10;
static PyObject *__pyx_kp_u_12;
static PyObject *__pyx_kp_u_13;
static PyObject *__pyx_kp_u_16;
static PyObject *__pyx_kp_s_2;
static PyObject *__pyx_kp_s_20;
static PyObject *__pyx_n_s_21;
static PyObject *__pyx_kp_s_3;
static PyObject *__pyx_kp_s_4;
static PyObject *__pyx_kp_u_6;
static PyObject *__pyx_kp_u_8;
static PyObject *__pyx_n_s__C;
static PyObject *__pyx_n_s__NotImplementedError;
static PyObject *__pyx_n_s__RuntimeError;
static PyObject *__pyx_n_s__ValueError;
static PyObject *__pyx_n_s____main__;
static PyObject *__pyx_n_s____test__;
static PyObject *__pyx_n_s__alpha;
static PyObject *__pyx_n_s__any;
static PyObject *__pyx_n_s__c;
static PyObject *__pyx_n_s__class_weight;
static PyObject *__pyx_n_s__count;
static PyObject *__pyx_n_s__dataset;
static PyObject *__pyx_n_s__dloss;
static PyObject *__pyx_n_s__dtype;
static PyObject *__pyx_n_s__epoch;
static PyObject *__pyx_n_s__epsilon;
static PyObject *__pyx_n_s__eta;
static PyObject *__pyx_n_s__eta0;
static PyObject *__pyx_n_s__fit_intercept;
static PyObject *__pyx_n_s__float64;
static PyObject *__pyx_n_s__i;
static PyObject *__pyx_n_s__intercept;
static PyObject *__pyx_n_s__intercept_decay;
static PyObject *__pyx_n_s__is_hinge;
static PyObject *__pyx_n_s__isinf;
static PyObject *__pyx_n_s__isnan;
static PyObject *__pyx_n_s__learning_rate;
static PyObject *__pyx_n_s__loss;
static PyObject *__pyx_n_s__n_features;
static PyObject *__pyx_n_s__n_iter;
static PyObject *__pyx_n_s__n_samples;
static PyObject *__pyx_n_s__nonzero;
static PyObject *__pyx_n_s__np;
static PyObject *__pyx_n_s__numpy;
static PyObject *__pyx_n_s__order;
static PyObject *__pyx_n_s__p;
static PyObject *__pyx_n_s__penalty_type;
static PyObject *__pyx_n_s__plain_sgd;
static PyObject *__pyx_n_s__power_t;
static PyObject *__pyx_n_s__q;
static PyObject *__pyx_n_s__q_data_ptr;
static PyObject *__pyx_n_s__range;
static PyObject *__pyx_n_s__rho;
static PyObject *__pyx_n_s__sample_weight;
static PyObject *__pyx_n_s__seed;
static PyObject *__pyx_n_s__shape;
static PyObject *__pyx_n_s__shuffle;
static PyObject *__pyx_n_s__sumloss;
static PyObject *__pyx_n_s__sys;
static PyObject *__pyx_n_s__t;
static PyObject *__pyx_n_s__t_start;
static PyObject *__pyx_n_s__threshold;
static PyObject *__pyx_n_s__time;
static PyObject *__pyx_n_s__u;
static PyObject *__pyx_n_s__update;
static PyObject *__pyx_n_s__verbose;
static PyObject *__pyx_n_s__w;
static PyObject *__pyx_n_s__weight_neg;
static PyObject *__pyx_n_s__weight_pos;
static PyObject *__pyx_n_s__weights;
static PyObject *__pyx_n_s__x_data_ptr;
static PyObject *__pyx_n_s__x_ind_ptr;
static PyObject *__pyx_n_s__xnnz;
static PyObject *__pyx_n_s__y;
static PyObject *__pyx_n_s__zeros;
static PyObject *__pyx_int_15;
static PyObject *__pyx_k_tuple_5;
static PyObject *__pyx_k_tuple_7;
static PyObject *__pyx_k_tuple_9;
static PyObject *__pyx_k_tuple_11;
static PyObject *__pyx_k_tuple_14;
static PyObject *__pyx_k_tuple_15;
static PyObject *__pyx_k_tuple_17;
static PyObject *__pyx_k_tuple_18;
static PyObject *__pyx_k_codeobj_19;
/* "sklearn/linear_model/sgd_fast.pyx":49
* """Base class for convex loss functions"""
*
* cpdef double loss(self, double p, double y): # <<<<<<<<<<<<<<
* """Evaluate the loss function.
*
*/
static PyObject *__pyx_pw_7sklearn_12linear_model_8sgd_fast_12LossFunction_1loss(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/
static double __pyx_f_7sklearn_12linear_model_8sgd_fast_12LossFunction_loss(CYTHON_UNUSED struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_LossFunction *__pyx_v_self, CYTHON_UNUSED double __pyx_v_p, CYTHON_UNUSED double __pyx_v_y, int __pyx_skip_dispatch) {
double __pyx_r;
__Pyx_RefNannyDeclarations
PyObject *__pyx_t_1 = NULL;
PyObject *__pyx_t_2 = NULL;
PyObject *__pyx_t_3 = NULL;
PyObject *__pyx_t_4 = NULL;
double __pyx_t_5;
int __pyx_lineno = 0;
const char *__pyx_filename = NULL;
int __pyx_clineno = 0;
__Pyx_RefNannySetupContext("loss", 0);
/* Check if called by wrapper */
if (unlikely(__pyx_skip_dispatch)) ;
/* Check if overriden in Python */
else if (unlikely(Py_TYPE(((PyObject *)__pyx_v_self))->tp_dictoffset != 0)) {
__pyx_t_1 = PyObject_GetAttr(((PyObject *)__pyx_v_self), __pyx_n_s__loss); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 49; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_1);
if (!PyCFunction_Check(__pyx_t_1) || (PyCFunction_GET_FUNCTION(__pyx_t_1) != (PyCFunction)__pyx_pw_7sklearn_12linear_model_8sgd_fast_12LossFunction_1loss)) {
__pyx_t_2 = PyFloat_FromDouble(__pyx_v_p); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 49; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_2);
__pyx_t_3 = PyFloat_FromDouble(__pyx_v_y); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 49; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_3);
__pyx_t_4 = PyTuple_New(2); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 49; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_4);
PyTuple_SET_ITEM(__pyx_t_4, 0, __pyx_t_2);
__Pyx_GIVEREF(__pyx_t_2);
PyTuple_SET_ITEM(__pyx_t_4, 1, __pyx_t_3);
__Pyx_GIVEREF(__pyx_t_3);
__pyx_t_2 = 0;
__pyx_t_3 = 0;
__pyx_t_3 = PyObject_Call(__pyx_t_1, ((PyObject *)__pyx_t_4), NULL); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 49; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_3);
__Pyx_DECREF(((PyObject *)__pyx_t_4)); __pyx_t_4 = 0;
__pyx_t_5 = __pyx_PyFloat_AsDouble(__pyx_t_3); if (unlikely((__pyx_t_5 == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 49; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0;
__pyx_r = __pyx_t_5;
__Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0;
goto __pyx_L0;
}
__Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0;
}
/* "sklearn/linear_model/sgd_fast.pyx":64
* The loss evaluated at `p` and `y`.
* """
* raise NotImplementedError() # <<<<<<<<<<<<<<
*
* cpdef double dloss(self, double p, double y):
*/
__pyx_t_1 = PyObject_Call(__pyx_builtin_NotImplementedError, ((PyObject *)__pyx_empty_tuple), NULL); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 64; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_1);
__Pyx_Raise(__pyx_t_1, 0, 0, 0);
__Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0;
{__pyx_filename = __pyx_f[0]; __pyx_lineno = 64; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__pyx_r = 0;
goto __pyx_L0;
__pyx_L1_error:;
__Pyx_XDECREF(__pyx_t_1);
__Pyx_XDECREF(__pyx_t_2);
__Pyx_XDECREF(__pyx_t_3);
__Pyx_XDECREF(__pyx_t_4);
__Pyx_WriteUnraisable("sklearn.linear_model.sgd_fast.LossFunction.loss", __pyx_clineno, __pyx_lineno, __pyx_filename);
__pyx_r = 0;
__pyx_L0:;
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* Python wrapper */
static PyObject *__pyx_pw_7sklearn_12linear_model_8sgd_fast_12LossFunction_1loss(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/
static char __pyx_doc_7sklearn_12linear_model_8sgd_fast_12LossFunction_loss[] = "Evaluate the loss function.\n\n Parameters\n ----------\n p : double\n The prediction, p = w^T x\n y : double\n The true value (aka target)\n\n Returns\n -------\n double\n The loss evaluated at `p` and `y`.\n ";
static PyObject *__pyx_pw_7sklearn_12linear_model_8sgd_fast_12LossFunction_1loss(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds) {
double __pyx_v_p;
double __pyx_v_y;
PyObject *__pyx_r = 0;
__Pyx_RefNannyDeclarations
__Pyx_RefNannySetupContext("loss (wrapper)", 0);
{
static PyObject **__pyx_pyargnames[] = {&__pyx_n_s__p,&__pyx_n_s__y,0};
PyObject* values[2] = {0,0};
if (unlikely(__pyx_kwds)) {
Py_ssize_t kw_args;
const Py_ssize_t pos_args = PyTuple_GET_SIZE(__pyx_args);
switch (pos_args) {
case 2: values[1] = PyTuple_GET_ITEM(__pyx_args, 1);
case 1: values[0] = PyTuple_GET_ITEM(__pyx_args, 0);
case 0: break;
default: goto __pyx_L5_argtuple_error;
}
kw_args = PyDict_Size(__pyx_kwds);
switch (pos_args) {
case 0:
if (likely((values[0] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__p)) != 0)) kw_args--;
else goto __pyx_L5_argtuple_error;
case 1:
if (likely((values[1] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__y)) != 0)) kw_args--;
else {
__Pyx_RaiseArgtupleInvalid("loss", 1, 2, 2, 1); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 49; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
}
if (unlikely(kw_args > 0)) {
if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, pos_args, "loss") < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 49; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
} else if (PyTuple_GET_SIZE(__pyx_args) != 2) {
goto __pyx_L5_argtuple_error;
} else {
values[0] = PyTuple_GET_ITEM(__pyx_args, 0);
values[1] = PyTuple_GET_ITEM(__pyx_args, 1);
}
__pyx_v_p = __pyx_PyFloat_AsDouble(values[0]); if (unlikely((__pyx_v_p == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 49; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
__pyx_v_y = __pyx_PyFloat_AsDouble(values[1]); if (unlikely((__pyx_v_y == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 49; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
goto __pyx_L4_argument_unpacking_done;
__pyx_L5_argtuple_error:;
__Pyx_RaiseArgtupleInvalid("loss", 1, 2, 2, PyTuple_GET_SIZE(__pyx_args)); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 49; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
__pyx_L3_error:;
__Pyx_AddTraceback("sklearn.linear_model.sgd_fast.LossFunction.loss", __pyx_clineno, __pyx_lineno, __pyx_filename);
__Pyx_RefNannyFinishContext();
return NULL;
__pyx_L4_argument_unpacking_done:;
__pyx_r = __pyx_pf_7sklearn_12linear_model_8sgd_fast_12LossFunction_loss(((struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_LossFunction *)__pyx_v_self), __pyx_v_p, __pyx_v_y);
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* "sklearn/linear_model/sgd_fast.pyx":49
* """Base class for convex loss functions"""
*
* cpdef double loss(self, double p, double y): # <<<<<<<<<<<<<<
* """Evaluate the loss function.
*
*/
static PyObject *__pyx_pf_7sklearn_12linear_model_8sgd_fast_12LossFunction_loss(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_LossFunction *__pyx_v_self, double __pyx_v_p, double __pyx_v_y) {
PyObject *__pyx_r = NULL;
__Pyx_RefNannyDeclarations
PyObject *__pyx_t_1 = NULL;
int __pyx_lineno = 0;
const char *__pyx_filename = NULL;
int __pyx_clineno = 0;
__Pyx_RefNannySetupContext("loss", 0);
__Pyx_XDECREF(__pyx_r);
__pyx_t_1 = PyFloat_FromDouble(((struct __pyx_vtabstruct_7sklearn_12linear_model_8sgd_fast_LossFunction *)__pyx_v_self->__pyx_vtab)->loss(__pyx_v_self, __pyx_v_p, __pyx_v_y, 1)); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 49; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_1);
__pyx_r = __pyx_t_1;
__pyx_t_1 = 0;
goto __pyx_L0;
__pyx_r = Py_None; __Pyx_INCREF(Py_None);
goto __pyx_L0;
__pyx_L1_error:;
__Pyx_XDECREF(__pyx_t_1);
__Pyx_AddTraceback("sklearn.linear_model.sgd_fast.LossFunction.loss", __pyx_clineno, __pyx_lineno, __pyx_filename);
__pyx_r = NULL;
__pyx_L0:;
__Pyx_XGIVEREF(__pyx_r);
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* "sklearn/linear_model/sgd_fast.pyx":66
* raise NotImplementedError()
*
* cpdef double dloss(self, double p, double y): # <<<<<<<<<<<<<<
* """Evaluate the derivative of the loss function with respect to
* the prediction `p`.
*/
static PyObject *__pyx_pw_7sklearn_12linear_model_8sgd_fast_12LossFunction_3dloss(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/
static double __pyx_f_7sklearn_12linear_model_8sgd_fast_12LossFunction_dloss(CYTHON_UNUSED struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_LossFunction *__pyx_v_self, CYTHON_UNUSED double __pyx_v_p, CYTHON_UNUSED double __pyx_v_y, int __pyx_skip_dispatch) {
double __pyx_r;
__Pyx_RefNannyDeclarations
PyObject *__pyx_t_1 = NULL;
PyObject *__pyx_t_2 = NULL;
PyObject *__pyx_t_3 = NULL;
PyObject *__pyx_t_4 = NULL;
double __pyx_t_5;
int __pyx_lineno = 0;
const char *__pyx_filename = NULL;
int __pyx_clineno = 0;
__Pyx_RefNannySetupContext("dloss", 0);
/* Check if called by wrapper */
if (unlikely(__pyx_skip_dispatch)) ;
/* Check if overriden in Python */
else if (unlikely(Py_TYPE(((PyObject *)__pyx_v_self))->tp_dictoffset != 0)) {
__pyx_t_1 = PyObject_GetAttr(((PyObject *)__pyx_v_self), __pyx_n_s__dloss); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 66; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_1);
if (!PyCFunction_Check(__pyx_t_1) || (PyCFunction_GET_FUNCTION(__pyx_t_1) != (PyCFunction)__pyx_pw_7sklearn_12linear_model_8sgd_fast_12LossFunction_3dloss)) {
__pyx_t_2 = PyFloat_FromDouble(__pyx_v_p); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 66; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_2);
__pyx_t_3 = PyFloat_FromDouble(__pyx_v_y); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 66; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_3);
__pyx_t_4 = PyTuple_New(2); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 66; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_4);
PyTuple_SET_ITEM(__pyx_t_4, 0, __pyx_t_2);
__Pyx_GIVEREF(__pyx_t_2);
PyTuple_SET_ITEM(__pyx_t_4, 1, __pyx_t_3);
__Pyx_GIVEREF(__pyx_t_3);
__pyx_t_2 = 0;
__pyx_t_3 = 0;
__pyx_t_3 = PyObject_Call(__pyx_t_1, ((PyObject *)__pyx_t_4), NULL); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 66; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_3);
__Pyx_DECREF(((PyObject *)__pyx_t_4)); __pyx_t_4 = 0;
__pyx_t_5 = __pyx_PyFloat_AsDouble(__pyx_t_3); if (unlikely((__pyx_t_5 == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 66; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0;
__pyx_r = __pyx_t_5;
__Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0;
goto __pyx_L0;
}
__Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0;
}
/* "sklearn/linear_model/sgd_fast.pyx":81
* The derivative of the loss function w.r.t. `p`.
* """
* raise NotImplementedError() # <<<<<<<<<<<<<<
*
*
*/
__pyx_t_1 = PyObject_Call(__pyx_builtin_NotImplementedError, ((PyObject *)__pyx_empty_tuple), NULL); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 81; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_1);
__Pyx_Raise(__pyx_t_1, 0, 0, 0);
__Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0;
{__pyx_filename = __pyx_f[0]; __pyx_lineno = 81; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__pyx_r = 0;
goto __pyx_L0;
__pyx_L1_error:;
__Pyx_XDECREF(__pyx_t_1);
__Pyx_XDECREF(__pyx_t_2);
__Pyx_XDECREF(__pyx_t_3);
__Pyx_XDECREF(__pyx_t_4);
__Pyx_WriteUnraisable("sklearn.linear_model.sgd_fast.LossFunction.dloss", __pyx_clineno, __pyx_lineno, __pyx_filename);
__pyx_r = 0;
__pyx_L0:;
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* Python wrapper */
static PyObject *__pyx_pw_7sklearn_12linear_model_8sgd_fast_12LossFunction_3dloss(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/
static char __pyx_doc_7sklearn_12linear_model_8sgd_fast_12LossFunction_2dloss[] = "Evaluate the derivative of the loss function with respect to\n the prediction `p`.\n\n Parameters\n ----------\n p : double\n The prediction, p = w^T x\n y : double\n The true value (aka target)\n Returns\n -------\n double\n The derivative of the loss function w.r.t. `p`.\n ";
static PyObject *__pyx_pw_7sklearn_12linear_model_8sgd_fast_12LossFunction_3dloss(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds) {
double __pyx_v_p;
double __pyx_v_y;
PyObject *__pyx_r = 0;
__Pyx_RefNannyDeclarations
__Pyx_RefNannySetupContext("dloss (wrapper)", 0);
{
static PyObject **__pyx_pyargnames[] = {&__pyx_n_s__p,&__pyx_n_s__y,0};
PyObject* values[2] = {0,0};
if (unlikely(__pyx_kwds)) {
Py_ssize_t kw_args;
const Py_ssize_t pos_args = PyTuple_GET_SIZE(__pyx_args);
switch (pos_args) {
case 2: values[1] = PyTuple_GET_ITEM(__pyx_args, 1);
case 1: values[0] = PyTuple_GET_ITEM(__pyx_args, 0);
case 0: break;
default: goto __pyx_L5_argtuple_error;
}
kw_args = PyDict_Size(__pyx_kwds);
switch (pos_args) {
case 0:
if (likely((values[0] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__p)) != 0)) kw_args--;
else goto __pyx_L5_argtuple_error;
case 1:
if (likely((values[1] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__y)) != 0)) kw_args--;
else {
__Pyx_RaiseArgtupleInvalid("dloss", 1, 2, 2, 1); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 66; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
}
if (unlikely(kw_args > 0)) {
if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, pos_args, "dloss") < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 66; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
} else if (PyTuple_GET_SIZE(__pyx_args) != 2) {
goto __pyx_L5_argtuple_error;
} else {
values[0] = PyTuple_GET_ITEM(__pyx_args, 0);
values[1] = PyTuple_GET_ITEM(__pyx_args, 1);
}
__pyx_v_p = __pyx_PyFloat_AsDouble(values[0]); if (unlikely((__pyx_v_p == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 66; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
__pyx_v_y = __pyx_PyFloat_AsDouble(values[1]); if (unlikely((__pyx_v_y == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 66; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
goto __pyx_L4_argument_unpacking_done;
__pyx_L5_argtuple_error:;
__Pyx_RaiseArgtupleInvalid("dloss", 1, 2, 2, PyTuple_GET_SIZE(__pyx_args)); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 66; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
__pyx_L3_error:;
__Pyx_AddTraceback("sklearn.linear_model.sgd_fast.LossFunction.dloss", __pyx_clineno, __pyx_lineno, __pyx_filename);
__Pyx_RefNannyFinishContext();
return NULL;
__pyx_L4_argument_unpacking_done:;
__pyx_r = __pyx_pf_7sklearn_12linear_model_8sgd_fast_12LossFunction_2dloss(((struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_LossFunction *)__pyx_v_self), __pyx_v_p, __pyx_v_y);
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* "sklearn/linear_model/sgd_fast.pyx":66
* raise NotImplementedError()
*
* cpdef double dloss(self, double p, double y): # <<<<<<<<<<<<<<
* """Evaluate the derivative of the loss function with respect to
* the prediction `p`.
*/
static PyObject *__pyx_pf_7sklearn_12linear_model_8sgd_fast_12LossFunction_2dloss(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_LossFunction *__pyx_v_self, double __pyx_v_p, double __pyx_v_y) {
PyObject *__pyx_r = NULL;
__Pyx_RefNannyDeclarations
PyObject *__pyx_t_1 = NULL;
int __pyx_lineno = 0;
const char *__pyx_filename = NULL;
int __pyx_clineno = 0;
__Pyx_RefNannySetupContext("dloss", 0);
__Pyx_XDECREF(__pyx_r);
__pyx_t_1 = PyFloat_FromDouble(((struct __pyx_vtabstruct_7sklearn_12linear_model_8sgd_fast_LossFunction *)__pyx_v_self->__pyx_vtab)->dloss(__pyx_v_self, __pyx_v_p, __pyx_v_y, 1)); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 66; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_1);
__pyx_r = __pyx_t_1;
__pyx_t_1 = 0;
goto __pyx_L0;
__pyx_r = Py_None; __Pyx_INCREF(Py_None);
goto __pyx_L0;
__pyx_L1_error:;
__Pyx_XDECREF(__pyx_t_1);
__Pyx_AddTraceback("sklearn.linear_model.sgd_fast.LossFunction.dloss", __pyx_clineno, __pyx_lineno, __pyx_filename);
__pyx_r = NULL;
__pyx_L0:;
__Pyx_XGIVEREF(__pyx_r);
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* "sklearn/linear_model/sgd_fast.pyx":87
* """Base class for loss functions for regression"""
*
* cpdef double loss(self, double p, double y): # <<<<<<<<<<<<<<
* raise NotImplementedError()
*
*/
static PyObject *__pyx_pw_7sklearn_12linear_model_8sgd_fast_10Regression_1loss(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/
static double __pyx_f_7sklearn_12linear_model_8sgd_fast_10Regression_loss(CYTHON_UNUSED struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_Regression *__pyx_v_self, CYTHON_UNUSED double __pyx_v_p, CYTHON_UNUSED double __pyx_v_y, int __pyx_skip_dispatch) {
double __pyx_r;
__Pyx_RefNannyDeclarations
PyObject *__pyx_t_1 = NULL;
PyObject *__pyx_t_2 = NULL;
PyObject *__pyx_t_3 = NULL;
PyObject *__pyx_t_4 = NULL;
double __pyx_t_5;
int __pyx_lineno = 0;
const char *__pyx_filename = NULL;
int __pyx_clineno = 0;
__Pyx_RefNannySetupContext("loss", 0);
/* Check if called by wrapper */
if (unlikely(__pyx_skip_dispatch)) ;
/* Check if overriden in Python */
else if (unlikely(Py_TYPE(((PyObject *)__pyx_v_self))->tp_dictoffset != 0)) {
__pyx_t_1 = PyObject_GetAttr(((PyObject *)__pyx_v_self), __pyx_n_s__loss); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 87; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_1);
if (!PyCFunction_Check(__pyx_t_1) || (PyCFunction_GET_FUNCTION(__pyx_t_1) != (PyCFunction)__pyx_pw_7sklearn_12linear_model_8sgd_fast_10Regression_1loss)) {
__pyx_t_2 = PyFloat_FromDouble(__pyx_v_p); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 87; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_2);
__pyx_t_3 = PyFloat_FromDouble(__pyx_v_y); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 87; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_3);
__pyx_t_4 = PyTuple_New(2); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 87; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_4);
PyTuple_SET_ITEM(__pyx_t_4, 0, __pyx_t_2);
__Pyx_GIVEREF(__pyx_t_2);
PyTuple_SET_ITEM(__pyx_t_4, 1, __pyx_t_3);
__Pyx_GIVEREF(__pyx_t_3);
__pyx_t_2 = 0;
__pyx_t_3 = 0;
__pyx_t_3 = PyObject_Call(__pyx_t_1, ((PyObject *)__pyx_t_4), NULL); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 87; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_3);
__Pyx_DECREF(((PyObject *)__pyx_t_4)); __pyx_t_4 = 0;
__pyx_t_5 = __pyx_PyFloat_AsDouble(__pyx_t_3); if (unlikely((__pyx_t_5 == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 87; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0;
__pyx_r = __pyx_t_5;
__Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0;
goto __pyx_L0;
}
__Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0;
}
/* "sklearn/linear_model/sgd_fast.pyx":88
*
* cpdef double loss(self, double p, double y):
* raise NotImplementedError() # <<<<<<<<<<<<<<
*
* cpdef double dloss(self, double p, double y):
*/
__pyx_t_1 = PyObject_Call(__pyx_builtin_NotImplementedError, ((PyObject *)__pyx_empty_tuple), NULL); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 88; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_1);
__Pyx_Raise(__pyx_t_1, 0, 0, 0);
__Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0;
{__pyx_filename = __pyx_f[0]; __pyx_lineno = 88; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__pyx_r = 0;
goto __pyx_L0;
__pyx_L1_error:;
__Pyx_XDECREF(__pyx_t_1);
__Pyx_XDECREF(__pyx_t_2);
__Pyx_XDECREF(__pyx_t_3);
__Pyx_XDECREF(__pyx_t_4);
__Pyx_WriteUnraisable("sklearn.linear_model.sgd_fast.Regression.loss", __pyx_clineno, __pyx_lineno, __pyx_filename);
__pyx_r = 0;
__pyx_L0:;
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* Python wrapper */
static PyObject *__pyx_pw_7sklearn_12linear_model_8sgd_fast_10Regression_1loss(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/
static PyObject *__pyx_pw_7sklearn_12linear_model_8sgd_fast_10Regression_1loss(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds) {
double __pyx_v_p;
double __pyx_v_y;
PyObject *__pyx_r = 0;
__Pyx_RefNannyDeclarations
__Pyx_RefNannySetupContext("loss (wrapper)", 0);
{
static PyObject **__pyx_pyargnames[] = {&__pyx_n_s__p,&__pyx_n_s__y,0};
PyObject* values[2] = {0,0};
if (unlikely(__pyx_kwds)) {
Py_ssize_t kw_args;
const Py_ssize_t pos_args = PyTuple_GET_SIZE(__pyx_args);
switch (pos_args) {
case 2: values[1] = PyTuple_GET_ITEM(__pyx_args, 1);
case 1: values[0] = PyTuple_GET_ITEM(__pyx_args, 0);
case 0: break;
default: goto __pyx_L5_argtuple_error;
}
kw_args = PyDict_Size(__pyx_kwds);
switch (pos_args) {
case 0:
if (likely((values[0] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__p)) != 0)) kw_args--;
else goto __pyx_L5_argtuple_error;
case 1:
if (likely((values[1] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__y)) != 0)) kw_args--;
else {
__Pyx_RaiseArgtupleInvalid("loss", 1, 2, 2, 1); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 87; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
}
if (unlikely(kw_args > 0)) {
if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, pos_args, "loss") < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 87; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
} else if (PyTuple_GET_SIZE(__pyx_args) != 2) {
goto __pyx_L5_argtuple_error;
} else {
values[0] = PyTuple_GET_ITEM(__pyx_args, 0);
values[1] = PyTuple_GET_ITEM(__pyx_args, 1);
}
__pyx_v_p = __pyx_PyFloat_AsDouble(values[0]); if (unlikely((__pyx_v_p == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 87; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
__pyx_v_y = __pyx_PyFloat_AsDouble(values[1]); if (unlikely((__pyx_v_y == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 87; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
goto __pyx_L4_argument_unpacking_done;
__pyx_L5_argtuple_error:;
__Pyx_RaiseArgtupleInvalid("loss", 1, 2, 2, PyTuple_GET_SIZE(__pyx_args)); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 87; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
__pyx_L3_error:;
__Pyx_AddTraceback("sklearn.linear_model.sgd_fast.Regression.loss", __pyx_clineno, __pyx_lineno, __pyx_filename);
__Pyx_RefNannyFinishContext();
return NULL;
__pyx_L4_argument_unpacking_done:;
__pyx_r = __pyx_pf_7sklearn_12linear_model_8sgd_fast_10Regression_loss(((struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_Regression *)__pyx_v_self), __pyx_v_p, __pyx_v_y);
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* "sklearn/linear_model/sgd_fast.pyx":87
* """Base class for loss functions for regression"""
*
* cpdef double loss(self, double p, double y): # <<<<<<<<<<<<<<
* raise NotImplementedError()
*
*/
static PyObject *__pyx_pf_7sklearn_12linear_model_8sgd_fast_10Regression_loss(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_Regression *__pyx_v_self, double __pyx_v_p, double __pyx_v_y) {
PyObject *__pyx_r = NULL;
__Pyx_RefNannyDeclarations
PyObject *__pyx_t_1 = NULL;
int __pyx_lineno = 0;
const char *__pyx_filename = NULL;
int __pyx_clineno = 0;
__Pyx_RefNannySetupContext("loss", 0);
__Pyx_XDECREF(__pyx_r);
__pyx_t_1 = PyFloat_FromDouble(((struct __pyx_vtabstruct_7sklearn_12linear_model_8sgd_fast_Regression *)__pyx_v_self->__pyx_base.__pyx_vtab)->__pyx_base.loss(((struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_LossFunction *)__pyx_v_self), __pyx_v_p, __pyx_v_y, 1)); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 87; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_1);
__pyx_r = __pyx_t_1;
__pyx_t_1 = 0;
goto __pyx_L0;
__pyx_r = Py_None; __Pyx_INCREF(Py_None);
goto __pyx_L0;
__pyx_L1_error:;
__Pyx_XDECREF(__pyx_t_1);
__Pyx_AddTraceback("sklearn.linear_model.sgd_fast.Regression.loss", __pyx_clineno, __pyx_lineno, __pyx_filename);
__pyx_r = NULL;
__pyx_L0:;
__Pyx_XGIVEREF(__pyx_r);
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* "sklearn/linear_model/sgd_fast.pyx":90
* raise NotImplementedError()
*
* cpdef double dloss(self, double p, double y): # <<<<<<<<<<<<<<
* raise NotImplementedError()
*
*/
static PyObject *__pyx_pw_7sklearn_12linear_model_8sgd_fast_10Regression_3dloss(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/
static double __pyx_f_7sklearn_12linear_model_8sgd_fast_10Regression_dloss(CYTHON_UNUSED struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_Regression *__pyx_v_self, CYTHON_UNUSED double __pyx_v_p, CYTHON_UNUSED double __pyx_v_y, int __pyx_skip_dispatch) {
double __pyx_r;
__Pyx_RefNannyDeclarations
PyObject *__pyx_t_1 = NULL;
PyObject *__pyx_t_2 = NULL;
PyObject *__pyx_t_3 = NULL;
PyObject *__pyx_t_4 = NULL;
double __pyx_t_5;
int __pyx_lineno = 0;
const char *__pyx_filename = NULL;
int __pyx_clineno = 0;
__Pyx_RefNannySetupContext("dloss", 0);
/* Check if called by wrapper */
if (unlikely(__pyx_skip_dispatch)) ;
/* Check if overriden in Python */
else if (unlikely(Py_TYPE(((PyObject *)__pyx_v_self))->tp_dictoffset != 0)) {
__pyx_t_1 = PyObject_GetAttr(((PyObject *)__pyx_v_self), __pyx_n_s__dloss); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 90; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_1);
if (!PyCFunction_Check(__pyx_t_1) || (PyCFunction_GET_FUNCTION(__pyx_t_1) != (PyCFunction)__pyx_pw_7sklearn_12linear_model_8sgd_fast_10Regression_3dloss)) {
__pyx_t_2 = PyFloat_FromDouble(__pyx_v_p); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 90; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_2);
__pyx_t_3 = PyFloat_FromDouble(__pyx_v_y); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 90; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_3);
__pyx_t_4 = PyTuple_New(2); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 90; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_4);
PyTuple_SET_ITEM(__pyx_t_4, 0, __pyx_t_2);
__Pyx_GIVEREF(__pyx_t_2);
PyTuple_SET_ITEM(__pyx_t_4, 1, __pyx_t_3);
__Pyx_GIVEREF(__pyx_t_3);
__pyx_t_2 = 0;
__pyx_t_3 = 0;
__pyx_t_3 = PyObject_Call(__pyx_t_1, ((PyObject *)__pyx_t_4), NULL); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 90; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_3);
__Pyx_DECREF(((PyObject *)__pyx_t_4)); __pyx_t_4 = 0;
__pyx_t_5 = __pyx_PyFloat_AsDouble(__pyx_t_3); if (unlikely((__pyx_t_5 == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 90; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0;
__pyx_r = __pyx_t_5;
__Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0;
goto __pyx_L0;
}
__Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0;
}
/* "sklearn/linear_model/sgd_fast.pyx":91
*
* cpdef double dloss(self, double p, double y):
* raise NotImplementedError() # <<<<<<<<<<<<<<
*
*
*/
__pyx_t_1 = PyObject_Call(__pyx_builtin_NotImplementedError, ((PyObject *)__pyx_empty_tuple), NULL); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 91; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_1);
__Pyx_Raise(__pyx_t_1, 0, 0, 0);
__Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0;
{__pyx_filename = __pyx_f[0]; __pyx_lineno = 91; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__pyx_r = 0;
goto __pyx_L0;
__pyx_L1_error:;
__Pyx_XDECREF(__pyx_t_1);
__Pyx_XDECREF(__pyx_t_2);
__Pyx_XDECREF(__pyx_t_3);
__Pyx_XDECREF(__pyx_t_4);
__Pyx_WriteUnraisable("sklearn.linear_model.sgd_fast.Regression.dloss", __pyx_clineno, __pyx_lineno, __pyx_filename);
__pyx_r = 0;
__pyx_L0:;
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* Python wrapper */
static PyObject *__pyx_pw_7sklearn_12linear_model_8sgd_fast_10Regression_3dloss(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/
static PyObject *__pyx_pw_7sklearn_12linear_model_8sgd_fast_10Regression_3dloss(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds) {
double __pyx_v_p;
double __pyx_v_y;
PyObject *__pyx_r = 0;
__Pyx_RefNannyDeclarations
__Pyx_RefNannySetupContext("dloss (wrapper)", 0);
{
static PyObject **__pyx_pyargnames[] = {&__pyx_n_s__p,&__pyx_n_s__y,0};
PyObject* values[2] = {0,0};
if (unlikely(__pyx_kwds)) {
Py_ssize_t kw_args;
const Py_ssize_t pos_args = PyTuple_GET_SIZE(__pyx_args);
switch (pos_args) {
case 2: values[1] = PyTuple_GET_ITEM(__pyx_args, 1);
case 1: values[0] = PyTuple_GET_ITEM(__pyx_args, 0);
case 0: break;
default: goto __pyx_L5_argtuple_error;
}
kw_args = PyDict_Size(__pyx_kwds);
switch (pos_args) {
case 0:
if (likely((values[0] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__p)) != 0)) kw_args--;
else goto __pyx_L5_argtuple_error;
case 1:
if (likely((values[1] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__y)) != 0)) kw_args--;
else {
__Pyx_RaiseArgtupleInvalid("dloss", 1, 2, 2, 1); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 90; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
}
if (unlikely(kw_args > 0)) {
if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, pos_args, "dloss") < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 90; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
} else if (PyTuple_GET_SIZE(__pyx_args) != 2) {
goto __pyx_L5_argtuple_error;
} else {
values[0] = PyTuple_GET_ITEM(__pyx_args, 0);
values[1] = PyTuple_GET_ITEM(__pyx_args, 1);
}
__pyx_v_p = __pyx_PyFloat_AsDouble(values[0]); if (unlikely((__pyx_v_p == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 90; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
__pyx_v_y = __pyx_PyFloat_AsDouble(values[1]); if (unlikely((__pyx_v_y == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 90; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
goto __pyx_L4_argument_unpacking_done;
__pyx_L5_argtuple_error:;
__Pyx_RaiseArgtupleInvalid("dloss", 1, 2, 2, PyTuple_GET_SIZE(__pyx_args)); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 90; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
__pyx_L3_error:;
__Pyx_AddTraceback("sklearn.linear_model.sgd_fast.Regression.dloss", __pyx_clineno, __pyx_lineno, __pyx_filename);
__Pyx_RefNannyFinishContext();
return NULL;
__pyx_L4_argument_unpacking_done:;
__pyx_r = __pyx_pf_7sklearn_12linear_model_8sgd_fast_10Regression_2dloss(((struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_Regression *)__pyx_v_self), __pyx_v_p, __pyx_v_y);
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* "sklearn/linear_model/sgd_fast.pyx":90
* raise NotImplementedError()
*
* cpdef double dloss(self, double p, double y): # <<<<<<<<<<<<<<
* raise NotImplementedError()
*
*/
static PyObject *__pyx_pf_7sklearn_12linear_model_8sgd_fast_10Regression_2dloss(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_Regression *__pyx_v_self, double __pyx_v_p, double __pyx_v_y) {
PyObject *__pyx_r = NULL;
__Pyx_RefNannyDeclarations
PyObject *__pyx_t_1 = NULL;
int __pyx_lineno = 0;
const char *__pyx_filename = NULL;
int __pyx_clineno = 0;
__Pyx_RefNannySetupContext("dloss", 0);
__Pyx_XDECREF(__pyx_r);
__pyx_t_1 = PyFloat_FromDouble(((struct __pyx_vtabstruct_7sklearn_12linear_model_8sgd_fast_Regression *)__pyx_v_self->__pyx_base.__pyx_vtab)->__pyx_base.dloss(((struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_LossFunction *)__pyx_v_self), __pyx_v_p, __pyx_v_y, 1)); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 90; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_1);
__pyx_r = __pyx_t_1;
__pyx_t_1 = 0;
goto __pyx_L0;
__pyx_r = Py_None; __Pyx_INCREF(Py_None);
goto __pyx_L0;
__pyx_L1_error:;
__Pyx_XDECREF(__pyx_t_1);
__Pyx_AddTraceback("sklearn.linear_model.sgd_fast.Regression.dloss", __pyx_clineno, __pyx_lineno, __pyx_filename);
__pyx_r = NULL;
__pyx_L0:;
__Pyx_XGIVEREF(__pyx_r);
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* "sklearn/linear_model/sgd_fast.pyx":97
* """Base class for loss functions for classification"""
*
* cpdef double loss(self, double p, double y): # <<<<<<<<<<<<<<
* raise NotImplementedError()
*
*/
static PyObject *__pyx_pw_7sklearn_12linear_model_8sgd_fast_14Classification_1loss(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/
static double __pyx_f_7sklearn_12linear_model_8sgd_fast_14Classification_loss(CYTHON_UNUSED struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_Classification *__pyx_v_self, CYTHON_UNUSED double __pyx_v_p, CYTHON_UNUSED double __pyx_v_y, int __pyx_skip_dispatch) {
double __pyx_r;
__Pyx_RefNannyDeclarations
PyObject *__pyx_t_1 = NULL;
PyObject *__pyx_t_2 = NULL;
PyObject *__pyx_t_3 = NULL;
PyObject *__pyx_t_4 = NULL;
double __pyx_t_5;
int __pyx_lineno = 0;
const char *__pyx_filename = NULL;
int __pyx_clineno = 0;
__Pyx_RefNannySetupContext("loss", 0);
/* Check if called by wrapper */
if (unlikely(__pyx_skip_dispatch)) ;
/* Check if overriden in Python */
else if (unlikely(Py_TYPE(((PyObject *)__pyx_v_self))->tp_dictoffset != 0)) {
__pyx_t_1 = PyObject_GetAttr(((PyObject *)__pyx_v_self), __pyx_n_s__loss); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 97; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_1);
if (!PyCFunction_Check(__pyx_t_1) || (PyCFunction_GET_FUNCTION(__pyx_t_1) != (PyCFunction)__pyx_pw_7sklearn_12linear_model_8sgd_fast_14Classification_1loss)) {
__pyx_t_2 = PyFloat_FromDouble(__pyx_v_p); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 97; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_2);
__pyx_t_3 = PyFloat_FromDouble(__pyx_v_y); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 97; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_3);
__pyx_t_4 = PyTuple_New(2); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 97; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_4);
PyTuple_SET_ITEM(__pyx_t_4, 0, __pyx_t_2);
__Pyx_GIVEREF(__pyx_t_2);
PyTuple_SET_ITEM(__pyx_t_4, 1, __pyx_t_3);
__Pyx_GIVEREF(__pyx_t_3);
__pyx_t_2 = 0;
__pyx_t_3 = 0;
__pyx_t_3 = PyObject_Call(__pyx_t_1, ((PyObject *)__pyx_t_4), NULL); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 97; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_3);
__Pyx_DECREF(((PyObject *)__pyx_t_4)); __pyx_t_4 = 0;
__pyx_t_5 = __pyx_PyFloat_AsDouble(__pyx_t_3); if (unlikely((__pyx_t_5 == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 97; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0;
__pyx_r = __pyx_t_5;
__Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0;
goto __pyx_L0;
}
__Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0;
}
/* "sklearn/linear_model/sgd_fast.pyx":98
*
* cpdef double loss(self, double p, double y):
* raise NotImplementedError() # <<<<<<<<<<<<<<
*
* cpdef double dloss(self, double p, double y):
*/
__pyx_t_1 = PyObject_Call(__pyx_builtin_NotImplementedError, ((PyObject *)__pyx_empty_tuple), NULL); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 98; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_1);
__Pyx_Raise(__pyx_t_1, 0, 0, 0);
__Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0;
{__pyx_filename = __pyx_f[0]; __pyx_lineno = 98; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__pyx_r = 0;
goto __pyx_L0;
__pyx_L1_error:;
__Pyx_XDECREF(__pyx_t_1);
__Pyx_XDECREF(__pyx_t_2);
__Pyx_XDECREF(__pyx_t_3);
__Pyx_XDECREF(__pyx_t_4);
__Pyx_WriteUnraisable("sklearn.linear_model.sgd_fast.Classification.loss", __pyx_clineno, __pyx_lineno, __pyx_filename);
__pyx_r = 0;
__pyx_L0:;
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* Python wrapper */
static PyObject *__pyx_pw_7sklearn_12linear_model_8sgd_fast_14Classification_1loss(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/
static PyObject *__pyx_pw_7sklearn_12linear_model_8sgd_fast_14Classification_1loss(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds) {
double __pyx_v_p;
double __pyx_v_y;
PyObject *__pyx_r = 0;
__Pyx_RefNannyDeclarations
__Pyx_RefNannySetupContext("loss (wrapper)", 0);
{
static PyObject **__pyx_pyargnames[] = {&__pyx_n_s__p,&__pyx_n_s__y,0};
PyObject* values[2] = {0,0};
if (unlikely(__pyx_kwds)) {
Py_ssize_t kw_args;
const Py_ssize_t pos_args = PyTuple_GET_SIZE(__pyx_args);
switch (pos_args) {
case 2: values[1] = PyTuple_GET_ITEM(__pyx_args, 1);
case 1: values[0] = PyTuple_GET_ITEM(__pyx_args, 0);
case 0: break;
default: goto __pyx_L5_argtuple_error;
}
kw_args = PyDict_Size(__pyx_kwds);
switch (pos_args) {
case 0:
if (likely((values[0] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__p)) != 0)) kw_args--;
else goto __pyx_L5_argtuple_error;
case 1:
if (likely((values[1] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__y)) != 0)) kw_args--;
else {
__Pyx_RaiseArgtupleInvalid("loss", 1, 2, 2, 1); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 97; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
}
if (unlikely(kw_args > 0)) {
if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, pos_args, "loss") < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 97; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
} else if (PyTuple_GET_SIZE(__pyx_args) != 2) {
goto __pyx_L5_argtuple_error;
} else {
values[0] = PyTuple_GET_ITEM(__pyx_args, 0);
values[1] = PyTuple_GET_ITEM(__pyx_args, 1);
}
__pyx_v_p = __pyx_PyFloat_AsDouble(values[0]); if (unlikely((__pyx_v_p == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 97; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
__pyx_v_y = __pyx_PyFloat_AsDouble(values[1]); if (unlikely((__pyx_v_y == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 97; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
goto __pyx_L4_argument_unpacking_done;
__pyx_L5_argtuple_error:;
__Pyx_RaiseArgtupleInvalid("loss", 1, 2, 2, PyTuple_GET_SIZE(__pyx_args)); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 97; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
__pyx_L3_error:;
__Pyx_AddTraceback("sklearn.linear_model.sgd_fast.Classification.loss", __pyx_clineno, __pyx_lineno, __pyx_filename);
__Pyx_RefNannyFinishContext();
return NULL;
__pyx_L4_argument_unpacking_done:;
__pyx_r = __pyx_pf_7sklearn_12linear_model_8sgd_fast_14Classification_loss(((struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_Classification *)__pyx_v_self), __pyx_v_p, __pyx_v_y);
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* "sklearn/linear_model/sgd_fast.pyx":97
* """Base class for loss functions for classification"""
*
* cpdef double loss(self, double p, double y): # <<<<<<<<<<<<<<
* raise NotImplementedError()
*
*/
static PyObject *__pyx_pf_7sklearn_12linear_model_8sgd_fast_14Classification_loss(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_Classification *__pyx_v_self, double __pyx_v_p, double __pyx_v_y) {
PyObject *__pyx_r = NULL;
__Pyx_RefNannyDeclarations
PyObject *__pyx_t_1 = NULL;
int __pyx_lineno = 0;
const char *__pyx_filename = NULL;
int __pyx_clineno = 0;
__Pyx_RefNannySetupContext("loss", 0);
__Pyx_XDECREF(__pyx_r);
__pyx_t_1 = PyFloat_FromDouble(((struct __pyx_vtabstruct_7sklearn_12linear_model_8sgd_fast_Classification *)__pyx_v_self->__pyx_base.__pyx_vtab)->__pyx_base.loss(((struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_LossFunction *)__pyx_v_self), __pyx_v_p, __pyx_v_y, 1)); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 97; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_1);
__pyx_r = __pyx_t_1;
__pyx_t_1 = 0;
goto __pyx_L0;
__pyx_r = Py_None; __Pyx_INCREF(Py_None);
goto __pyx_L0;
__pyx_L1_error:;
__Pyx_XDECREF(__pyx_t_1);
__Pyx_AddTraceback("sklearn.linear_model.sgd_fast.Classification.loss", __pyx_clineno, __pyx_lineno, __pyx_filename);
__pyx_r = NULL;
__pyx_L0:;
__Pyx_XGIVEREF(__pyx_r);
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* "sklearn/linear_model/sgd_fast.pyx":100
* raise NotImplementedError()
*
* cpdef double dloss(self, double p, double y): # <<<<<<<<<<<<<<
* raise NotImplementedError()
*
*/
static PyObject *__pyx_pw_7sklearn_12linear_model_8sgd_fast_14Classification_3dloss(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/
static double __pyx_f_7sklearn_12linear_model_8sgd_fast_14Classification_dloss(CYTHON_UNUSED struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_Classification *__pyx_v_self, CYTHON_UNUSED double __pyx_v_p, CYTHON_UNUSED double __pyx_v_y, int __pyx_skip_dispatch) {
double __pyx_r;
__Pyx_RefNannyDeclarations
PyObject *__pyx_t_1 = NULL;
PyObject *__pyx_t_2 = NULL;
PyObject *__pyx_t_3 = NULL;
PyObject *__pyx_t_4 = NULL;
double __pyx_t_5;
int __pyx_lineno = 0;
const char *__pyx_filename = NULL;
int __pyx_clineno = 0;
__Pyx_RefNannySetupContext("dloss", 0);
/* Check if called by wrapper */
if (unlikely(__pyx_skip_dispatch)) ;
/* Check if overriden in Python */
else if (unlikely(Py_TYPE(((PyObject *)__pyx_v_self))->tp_dictoffset != 0)) {
__pyx_t_1 = PyObject_GetAttr(((PyObject *)__pyx_v_self), __pyx_n_s__dloss); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 100; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_1);
if (!PyCFunction_Check(__pyx_t_1) || (PyCFunction_GET_FUNCTION(__pyx_t_1) != (PyCFunction)__pyx_pw_7sklearn_12linear_model_8sgd_fast_14Classification_3dloss)) {
__pyx_t_2 = PyFloat_FromDouble(__pyx_v_p); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 100; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_2);
__pyx_t_3 = PyFloat_FromDouble(__pyx_v_y); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 100; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_3);
__pyx_t_4 = PyTuple_New(2); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 100; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_4);
PyTuple_SET_ITEM(__pyx_t_4, 0, __pyx_t_2);
__Pyx_GIVEREF(__pyx_t_2);
PyTuple_SET_ITEM(__pyx_t_4, 1, __pyx_t_3);
__Pyx_GIVEREF(__pyx_t_3);
__pyx_t_2 = 0;
__pyx_t_3 = 0;
__pyx_t_3 = PyObject_Call(__pyx_t_1, ((PyObject *)__pyx_t_4), NULL); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 100; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_3);
__Pyx_DECREF(((PyObject *)__pyx_t_4)); __pyx_t_4 = 0;
__pyx_t_5 = __pyx_PyFloat_AsDouble(__pyx_t_3); if (unlikely((__pyx_t_5 == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 100; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0;
__pyx_r = __pyx_t_5;
__Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0;
goto __pyx_L0;
}
__Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0;
}
/* "sklearn/linear_model/sgd_fast.pyx":101
*
* cpdef double dloss(self, double p, double y):
* raise NotImplementedError() # <<<<<<<<<<<<<<
*
*
*/
__pyx_t_1 = PyObject_Call(__pyx_builtin_NotImplementedError, ((PyObject *)__pyx_empty_tuple), NULL); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 101; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_1);
__Pyx_Raise(__pyx_t_1, 0, 0, 0);
__Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0;
{__pyx_filename = __pyx_f[0]; __pyx_lineno = 101; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__pyx_r = 0;
goto __pyx_L0;
__pyx_L1_error:;
__Pyx_XDECREF(__pyx_t_1);
__Pyx_XDECREF(__pyx_t_2);
__Pyx_XDECREF(__pyx_t_3);
__Pyx_XDECREF(__pyx_t_4);
__Pyx_WriteUnraisable("sklearn.linear_model.sgd_fast.Classification.dloss", __pyx_clineno, __pyx_lineno, __pyx_filename);
__pyx_r = 0;
__pyx_L0:;
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* Python wrapper */
static PyObject *__pyx_pw_7sklearn_12linear_model_8sgd_fast_14Classification_3dloss(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/
static PyObject *__pyx_pw_7sklearn_12linear_model_8sgd_fast_14Classification_3dloss(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds) {
double __pyx_v_p;
double __pyx_v_y;
PyObject *__pyx_r = 0;
__Pyx_RefNannyDeclarations
__Pyx_RefNannySetupContext("dloss (wrapper)", 0);
{
static PyObject **__pyx_pyargnames[] = {&__pyx_n_s__p,&__pyx_n_s__y,0};
PyObject* values[2] = {0,0};
if (unlikely(__pyx_kwds)) {
Py_ssize_t kw_args;
const Py_ssize_t pos_args = PyTuple_GET_SIZE(__pyx_args);
switch (pos_args) {
case 2: values[1] = PyTuple_GET_ITEM(__pyx_args, 1);
case 1: values[0] = PyTuple_GET_ITEM(__pyx_args, 0);
case 0: break;
default: goto __pyx_L5_argtuple_error;
}
kw_args = PyDict_Size(__pyx_kwds);
switch (pos_args) {
case 0:
if (likely((values[0] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__p)) != 0)) kw_args--;
else goto __pyx_L5_argtuple_error;
case 1:
if (likely((values[1] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__y)) != 0)) kw_args--;
else {
__Pyx_RaiseArgtupleInvalid("dloss", 1, 2, 2, 1); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 100; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
}
if (unlikely(kw_args > 0)) {
if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, pos_args, "dloss") < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 100; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
} else if (PyTuple_GET_SIZE(__pyx_args) != 2) {
goto __pyx_L5_argtuple_error;
} else {
values[0] = PyTuple_GET_ITEM(__pyx_args, 0);
values[1] = PyTuple_GET_ITEM(__pyx_args, 1);
}
__pyx_v_p = __pyx_PyFloat_AsDouble(values[0]); if (unlikely((__pyx_v_p == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 100; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
__pyx_v_y = __pyx_PyFloat_AsDouble(values[1]); if (unlikely((__pyx_v_y == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 100; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
goto __pyx_L4_argument_unpacking_done;
__pyx_L5_argtuple_error:;
__Pyx_RaiseArgtupleInvalid("dloss", 1, 2, 2, PyTuple_GET_SIZE(__pyx_args)); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 100; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
__pyx_L3_error:;
__Pyx_AddTraceback("sklearn.linear_model.sgd_fast.Classification.dloss", __pyx_clineno, __pyx_lineno, __pyx_filename);
__Pyx_RefNannyFinishContext();
return NULL;
__pyx_L4_argument_unpacking_done:;
__pyx_r = __pyx_pf_7sklearn_12linear_model_8sgd_fast_14Classification_2dloss(((struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_Classification *)__pyx_v_self), __pyx_v_p, __pyx_v_y);
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* "sklearn/linear_model/sgd_fast.pyx":100
* raise NotImplementedError()
*
* cpdef double dloss(self, double p, double y): # <<<<<<<<<<<<<<
* raise NotImplementedError()
*
*/
static PyObject *__pyx_pf_7sklearn_12linear_model_8sgd_fast_14Classification_2dloss(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_Classification *__pyx_v_self, double __pyx_v_p, double __pyx_v_y) {
PyObject *__pyx_r = NULL;
__Pyx_RefNannyDeclarations
PyObject *__pyx_t_1 = NULL;
int __pyx_lineno = 0;
const char *__pyx_filename = NULL;
int __pyx_clineno = 0;
__Pyx_RefNannySetupContext("dloss", 0);
__Pyx_XDECREF(__pyx_r);
__pyx_t_1 = PyFloat_FromDouble(((struct __pyx_vtabstruct_7sklearn_12linear_model_8sgd_fast_Classification *)__pyx_v_self->__pyx_base.__pyx_vtab)->__pyx_base.dloss(((struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_LossFunction *)__pyx_v_self), __pyx_v_p, __pyx_v_y, 1)); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 100; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_1);
__pyx_r = __pyx_t_1;
__pyx_t_1 = 0;
goto __pyx_L0;
__pyx_r = Py_None; __Pyx_INCREF(Py_None);
goto __pyx_L0;
__pyx_L1_error:;
__Pyx_XDECREF(__pyx_t_1);
__Pyx_AddTraceback("sklearn.linear_model.sgd_fast.Classification.dloss", __pyx_clineno, __pyx_lineno, __pyx_filename);
__pyx_r = NULL;
__pyx_L0:;
__Pyx_XGIVEREF(__pyx_r);
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* "sklearn/linear_model/sgd_fast.pyx":112
* Stochastic Gradient Descent', ICML'04.
* """
* cpdef double loss(self, double p, double y): # <<<<<<<<<<<<<<
* cdef double z = p * y
* if z >= 1.0:
*/
static PyObject *__pyx_pw_7sklearn_12linear_model_8sgd_fast_13ModifiedHuber_1loss(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/
static double __pyx_f_7sklearn_12linear_model_8sgd_fast_13ModifiedHuber_loss(CYTHON_UNUSED struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_ModifiedHuber *__pyx_v_self, double __pyx_v_p, double __pyx_v_y, int __pyx_skip_dispatch) {
double __pyx_v_z;
double __pyx_r;
__Pyx_RefNannyDeclarations
PyObject *__pyx_t_1 = NULL;
PyObject *__pyx_t_2 = NULL;
PyObject *__pyx_t_3 = NULL;
PyObject *__pyx_t_4 = NULL;
double __pyx_t_5;
int __pyx_t_6;
int __pyx_lineno = 0;
const char *__pyx_filename = NULL;
int __pyx_clineno = 0;
__Pyx_RefNannySetupContext("loss", 0);
/* Check if called by wrapper */
if (unlikely(__pyx_skip_dispatch)) ;
/* Check if overriden in Python */
else if (unlikely(Py_TYPE(((PyObject *)__pyx_v_self))->tp_dictoffset != 0)) {
__pyx_t_1 = PyObject_GetAttr(((PyObject *)__pyx_v_self), __pyx_n_s__loss); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 112; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_1);
if (!PyCFunction_Check(__pyx_t_1) || (PyCFunction_GET_FUNCTION(__pyx_t_1) != (PyCFunction)__pyx_pw_7sklearn_12linear_model_8sgd_fast_13ModifiedHuber_1loss)) {
__pyx_t_2 = PyFloat_FromDouble(__pyx_v_p); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 112; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_2);
__pyx_t_3 = PyFloat_FromDouble(__pyx_v_y); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 112; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_3);
__pyx_t_4 = PyTuple_New(2); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 112; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_4);
PyTuple_SET_ITEM(__pyx_t_4, 0, __pyx_t_2);
__Pyx_GIVEREF(__pyx_t_2);
PyTuple_SET_ITEM(__pyx_t_4, 1, __pyx_t_3);
__Pyx_GIVEREF(__pyx_t_3);
__pyx_t_2 = 0;
__pyx_t_3 = 0;
__pyx_t_3 = PyObject_Call(__pyx_t_1, ((PyObject *)__pyx_t_4), NULL); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 112; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_3);
__Pyx_DECREF(((PyObject *)__pyx_t_4)); __pyx_t_4 = 0;
__pyx_t_5 = __pyx_PyFloat_AsDouble(__pyx_t_3); if (unlikely((__pyx_t_5 == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 112; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0;
__pyx_r = __pyx_t_5;
__Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0;
goto __pyx_L0;
}
__Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0;
}
/* "sklearn/linear_model/sgd_fast.pyx":113
* """
* cpdef double loss(self, double p, double y):
* cdef double z = p * y # <<<<<<<<<<<<<<
* if z >= 1.0:
* return 0.0
*/
__pyx_v_z = (__pyx_v_p * __pyx_v_y);
/* "sklearn/linear_model/sgd_fast.pyx":114
* cpdef double loss(self, double p, double y):
* cdef double z = p * y
* if z >= 1.0: # <<<<<<<<<<<<<<
* return 0.0
* elif z >= -1.0:
*/
__pyx_t_6 = (__pyx_v_z >= 1.0);
if (__pyx_t_6) {
/* "sklearn/linear_model/sgd_fast.pyx":115
* cdef double z = p * y
* if z >= 1.0:
* return 0.0 # <<<<<<<<<<<<<<
* elif z >= -1.0:
* return (1.0 - z) * (1.0 - z)
*/
__pyx_r = 0.0;
goto __pyx_L0;
goto __pyx_L3;
}
/* "sklearn/linear_model/sgd_fast.pyx":116
* if z >= 1.0:
* return 0.0
* elif z >= -1.0: # <<<<<<<<<<<<<<
* return (1.0 - z) * (1.0 - z)
* else:
*/
__pyx_t_6 = (__pyx_v_z >= -1.0);
if (__pyx_t_6) {
/* "sklearn/linear_model/sgd_fast.pyx":117
* return 0.0
* elif z >= -1.0:
* return (1.0 - z) * (1.0 - z) # <<<<<<<<<<<<<<
* else:
* return -4.0 * z
*/
__pyx_r = ((1.0 - __pyx_v_z) * (1.0 - __pyx_v_z));
goto __pyx_L0;
goto __pyx_L3;
}
/*else*/ {
/* "sklearn/linear_model/sgd_fast.pyx":119
* return (1.0 - z) * (1.0 - z)
* else:
* return -4.0 * z # <<<<<<<<<<<<<<
*
* cpdef double dloss(self, double p, double y):
*/
__pyx_r = (-4.0 * __pyx_v_z);
goto __pyx_L0;
}
__pyx_L3:;
__pyx_r = 0;
goto __pyx_L0;
__pyx_L1_error:;
__Pyx_XDECREF(__pyx_t_1);
__Pyx_XDECREF(__pyx_t_2);
__Pyx_XDECREF(__pyx_t_3);
__Pyx_XDECREF(__pyx_t_4);
__Pyx_WriteUnraisable("sklearn.linear_model.sgd_fast.ModifiedHuber.loss", __pyx_clineno, __pyx_lineno, __pyx_filename);
__pyx_r = 0;
__pyx_L0:;
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* Python wrapper */
static PyObject *__pyx_pw_7sklearn_12linear_model_8sgd_fast_13ModifiedHuber_1loss(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/
static PyObject *__pyx_pw_7sklearn_12linear_model_8sgd_fast_13ModifiedHuber_1loss(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds) {
double __pyx_v_p;
double __pyx_v_y;
PyObject *__pyx_r = 0;
__Pyx_RefNannyDeclarations
__Pyx_RefNannySetupContext("loss (wrapper)", 0);
{
static PyObject **__pyx_pyargnames[] = {&__pyx_n_s__p,&__pyx_n_s__y,0};
PyObject* values[2] = {0,0};
if (unlikely(__pyx_kwds)) {
Py_ssize_t kw_args;
const Py_ssize_t pos_args = PyTuple_GET_SIZE(__pyx_args);
switch (pos_args) {
case 2: values[1] = PyTuple_GET_ITEM(__pyx_args, 1);
case 1: values[0] = PyTuple_GET_ITEM(__pyx_args, 0);
case 0: break;
default: goto __pyx_L5_argtuple_error;
}
kw_args = PyDict_Size(__pyx_kwds);
switch (pos_args) {
case 0:
if (likely((values[0] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__p)) != 0)) kw_args--;
else goto __pyx_L5_argtuple_error;
case 1:
if (likely((values[1] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__y)) != 0)) kw_args--;
else {
__Pyx_RaiseArgtupleInvalid("loss", 1, 2, 2, 1); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 112; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
}
if (unlikely(kw_args > 0)) {
if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, pos_args, "loss") < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 112; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
} else if (PyTuple_GET_SIZE(__pyx_args) != 2) {
goto __pyx_L5_argtuple_error;
} else {
values[0] = PyTuple_GET_ITEM(__pyx_args, 0);
values[1] = PyTuple_GET_ITEM(__pyx_args, 1);
}
__pyx_v_p = __pyx_PyFloat_AsDouble(values[0]); if (unlikely((__pyx_v_p == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 112; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
__pyx_v_y = __pyx_PyFloat_AsDouble(values[1]); if (unlikely((__pyx_v_y == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 112; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
goto __pyx_L4_argument_unpacking_done;
__pyx_L5_argtuple_error:;
__Pyx_RaiseArgtupleInvalid("loss", 1, 2, 2, PyTuple_GET_SIZE(__pyx_args)); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 112; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
__pyx_L3_error:;
__Pyx_AddTraceback("sklearn.linear_model.sgd_fast.ModifiedHuber.loss", __pyx_clineno, __pyx_lineno, __pyx_filename);
__Pyx_RefNannyFinishContext();
return NULL;
__pyx_L4_argument_unpacking_done:;
__pyx_r = __pyx_pf_7sklearn_12linear_model_8sgd_fast_13ModifiedHuber_loss(((struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_ModifiedHuber *)__pyx_v_self), __pyx_v_p, __pyx_v_y);
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* "sklearn/linear_model/sgd_fast.pyx":112
* Stochastic Gradient Descent', ICML'04.
* """
* cpdef double loss(self, double p, double y): # <<<<<<<<<<<<<<
* cdef double z = p * y
* if z >= 1.0:
*/
static PyObject *__pyx_pf_7sklearn_12linear_model_8sgd_fast_13ModifiedHuber_loss(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_ModifiedHuber *__pyx_v_self, double __pyx_v_p, double __pyx_v_y) {
PyObject *__pyx_r = NULL;
__Pyx_RefNannyDeclarations
PyObject *__pyx_t_1 = NULL;
int __pyx_lineno = 0;
const char *__pyx_filename = NULL;
int __pyx_clineno = 0;
__Pyx_RefNannySetupContext("loss", 0);
__Pyx_XDECREF(__pyx_r);
__pyx_t_1 = PyFloat_FromDouble(((struct __pyx_vtabstruct_7sklearn_12linear_model_8sgd_fast_ModifiedHuber *)__pyx_v_self->__pyx_base.__pyx_base.__pyx_vtab)->__pyx_base.__pyx_base.loss(((struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_LossFunction *)__pyx_v_self), __pyx_v_p, __pyx_v_y, 1)); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 112; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_1);
__pyx_r = __pyx_t_1;
__pyx_t_1 = 0;
goto __pyx_L0;
__pyx_r = Py_None; __Pyx_INCREF(Py_None);
goto __pyx_L0;
__pyx_L1_error:;
__Pyx_XDECREF(__pyx_t_1);
__Pyx_AddTraceback("sklearn.linear_model.sgd_fast.ModifiedHuber.loss", __pyx_clineno, __pyx_lineno, __pyx_filename);
__pyx_r = NULL;
__pyx_L0:;
__Pyx_XGIVEREF(__pyx_r);
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* "sklearn/linear_model/sgd_fast.pyx":121
* return -4.0 * z
*
* cpdef double dloss(self, double p, double y): # <<<<<<<<<<<<<<
* cdef double z = p * y
* if z >= 1.0:
*/
static PyObject *__pyx_pw_7sklearn_12linear_model_8sgd_fast_13ModifiedHuber_3dloss(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/
static double __pyx_f_7sklearn_12linear_model_8sgd_fast_13ModifiedHuber_dloss(CYTHON_UNUSED struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_ModifiedHuber *__pyx_v_self, double __pyx_v_p, double __pyx_v_y, int __pyx_skip_dispatch) {
double __pyx_v_z;
double __pyx_r;
__Pyx_RefNannyDeclarations
PyObject *__pyx_t_1 = NULL;
PyObject *__pyx_t_2 = NULL;
PyObject *__pyx_t_3 = NULL;
PyObject *__pyx_t_4 = NULL;
double __pyx_t_5;
int __pyx_t_6;
int __pyx_lineno = 0;
const char *__pyx_filename = NULL;
int __pyx_clineno = 0;
__Pyx_RefNannySetupContext("dloss", 0);
/* Check if called by wrapper */
if (unlikely(__pyx_skip_dispatch)) ;
/* Check if overriden in Python */
else if (unlikely(Py_TYPE(((PyObject *)__pyx_v_self))->tp_dictoffset != 0)) {
__pyx_t_1 = PyObject_GetAttr(((PyObject *)__pyx_v_self), __pyx_n_s__dloss); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 121; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_1);
if (!PyCFunction_Check(__pyx_t_1) || (PyCFunction_GET_FUNCTION(__pyx_t_1) != (PyCFunction)__pyx_pw_7sklearn_12linear_model_8sgd_fast_13ModifiedHuber_3dloss)) {
__pyx_t_2 = PyFloat_FromDouble(__pyx_v_p); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 121; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_2);
__pyx_t_3 = PyFloat_FromDouble(__pyx_v_y); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 121; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_3);
__pyx_t_4 = PyTuple_New(2); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 121; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_4);
PyTuple_SET_ITEM(__pyx_t_4, 0, __pyx_t_2);
__Pyx_GIVEREF(__pyx_t_2);
PyTuple_SET_ITEM(__pyx_t_4, 1, __pyx_t_3);
__Pyx_GIVEREF(__pyx_t_3);
__pyx_t_2 = 0;
__pyx_t_3 = 0;
__pyx_t_3 = PyObject_Call(__pyx_t_1, ((PyObject *)__pyx_t_4), NULL); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 121; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_3);
__Pyx_DECREF(((PyObject *)__pyx_t_4)); __pyx_t_4 = 0;
__pyx_t_5 = __pyx_PyFloat_AsDouble(__pyx_t_3); if (unlikely((__pyx_t_5 == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 121; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0;
__pyx_r = __pyx_t_5;
__Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0;
goto __pyx_L0;
}
__Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0;
}
/* "sklearn/linear_model/sgd_fast.pyx":122
*
* cpdef double dloss(self, double p, double y):
* cdef double z = p * y # <<<<<<<<<<<<<<
* if z >= 1.0:
* return 0.0
*/
__pyx_v_z = (__pyx_v_p * __pyx_v_y);
/* "sklearn/linear_model/sgd_fast.pyx":123
* cpdef double dloss(self, double p, double y):
* cdef double z = p * y
* if z >= 1.0: # <<<<<<<<<<<<<<
* return 0.0
* elif z >= -1.0:
*/
__pyx_t_6 = (__pyx_v_z >= 1.0);
if (__pyx_t_6) {
/* "sklearn/linear_model/sgd_fast.pyx":124
* cdef double z = p * y
* if z >= 1.0:
* return 0.0 # <<<<<<<<<<<<<<
* elif z >= -1.0:
* return 2.0 * (1.0 - z) * -y
*/
__pyx_r = 0.0;
goto __pyx_L0;
goto __pyx_L3;
}
/* "sklearn/linear_model/sgd_fast.pyx":125
* if z >= 1.0:
* return 0.0
* elif z >= -1.0: # <<<<<<<<<<<<<<
* return 2.0 * (1.0 - z) * -y
* else:
*/
__pyx_t_6 = (__pyx_v_z >= -1.0);
if (__pyx_t_6) {
/* "sklearn/linear_model/sgd_fast.pyx":126
* return 0.0
* elif z >= -1.0:
* return 2.0 * (1.0 - z) * -y # <<<<<<<<<<<<<<
* else:
* return -4.0 * y
*/
__pyx_r = ((2.0 * (1.0 - __pyx_v_z)) * (-__pyx_v_y));
goto __pyx_L0;
goto __pyx_L3;
}
/*else*/ {
/* "sklearn/linear_model/sgd_fast.pyx":128
* return 2.0 * (1.0 - z) * -y
* else:
* return -4.0 * y # <<<<<<<<<<<<<<
*
* def __reduce__(self):
*/
__pyx_r = (-4.0 * __pyx_v_y);
goto __pyx_L0;
}
__pyx_L3:;
__pyx_r = 0;
goto __pyx_L0;
__pyx_L1_error:;
__Pyx_XDECREF(__pyx_t_1);
__Pyx_XDECREF(__pyx_t_2);
__Pyx_XDECREF(__pyx_t_3);
__Pyx_XDECREF(__pyx_t_4);
__Pyx_WriteUnraisable("sklearn.linear_model.sgd_fast.ModifiedHuber.dloss", __pyx_clineno, __pyx_lineno, __pyx_filename);
__pyx_r = 0;
__pyx_L0:;
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* Python wrapper */
static PyObject *__pyx_pw_7sklearn_12linear_model_8sgd_fast_13ModifiedHuber_3dloss(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/
static PyObject *__pyx_pw_7sklearn_12linear_model_8sgd_fast_13ModifiedHuber_3dloss(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds) {
double __pyx_v_p;
double __pyx_v_y;
PyObject *__pyx_r = 0;
__Pyx_RefNannyDeclarations
__Pyx_RefNannySetupContext("dloss (wrapper)", 0);
{
static PyObject **__pyx_pyargnames[] = {&__pyx_n_s__p,&__pyx_n_s__y,0};
PyObject* values[2] = {0,0};
if (unlikely(__pyx_kwds)) {
Py_ssize_t kw_args;
const Py_ssize_t pos_args = PyTuple_GET_SIZE(__pyx_args);
switch (pos_args) {
case 2: values[1] = PyTuple_GET_ITEM(__pyx_args, 1);
case 1: values[0] = PyTuple_GET_ITEM(__pyx_args, 0);
case 0: break;
default: goto __pyx_L5_argtuple_error;
}
kw_args = PyDict_Size(__pyx_kwds);
switch (pos_args) {
case 0:
if (likely((values[0] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__p)) != 0)) kw_args--;
else goto __pyx_L5_argtuple_error;
case 1:
if (likely((values[1] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__y)) != 0)) kw_args--;
else {
__Pyx_RaiseArgtupleInvalid("dloss", 1, 2, 2, 1); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 121; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
}
if (unlikely(kw_args > 0)) {
if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, pos_args, "dloss") < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 121; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
} else if (PyTuple_GET_SIZE(__pyx_args) != 2) {
goto __pyx_L5_argtuple_error;
} else {
values[0] = PyTuple_GET_ITEM(__pyx_args, 0);
values[1] = PyTuple_GET_ITEM(__pyx_args, 1);
}
__pyx_v_p = __pyx_PyFloat_AsDouble(values[0]); if (unlikely((__pyx_v_p == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 121; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
__pyx_v_y = __pyx_PyFloat_AsDouble(values[1]); if (unlikely((__pyx_v_y == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 121; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
goto __pyx_L4_argument_unpacking_done;
__pyx_L5_argtuple_error:;
__Pyx_RaiseArgtupleInvalid("dloss", 1, 2, 2, PyTuple_GET_SIZE(__pyx_args)); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 121; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
__pyx_L3_error:;
__Pyx_AddTraceback("sklearn.linear_model.sgd_fast.ModifiedHuber.dloss", __pyx_clineno, __pyx_lineno, __pyx_filename);
__Pyx_RefNannyFinishContext();
return NULL;
__pyx_L4_argument_unpacking_done:;
__pyx_r = __pyx_pf_7sklearn_12linear_model_8sgd_fast_13ModifiedHuber_2dloss(((struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_ModifiedHuber *)__pyx_v_self), __pyx_v_p, __pyx_v_y);
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* "sklearn/linear_model/sgd_fast.pyx":121
* return -4.0 * z
*
* cpdef double dloss(self, double p, double y): # <<<<<<<<<<<<<<
* cdef double z = p * y
* if z >= 1.0:
*/
static PyObject *__pyx_pf_7sklearn_12linear_model_8sgd_fast_13ModifiedHuber_2dloss(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_ModifiedHuber *__pyx_v_self, double __pyx_v_p, double __pyx_v_y) {
PyObject *__pyx_r = NULL;
__Pyx_RefNannyDeclarations
PyObject *__pyx_t_1 = NULL;
int __pyx_lineno = 0;
const char *__pyx_filename = NULL;
int __pyx_clineno = 0;
__Pyx_RefNannySetupContext("dloss", 0);
__Pyx_XDECREF(__pyx_r);
__pyx_t_1 = PyFloat_FromDouble(((struct __pyx_vtabstruct_7sklearn_12linear_model_8sgd_fast_ModifiedHuber *)__pyx_v_self->__pyx_base.__pyx_base.__pyx_vtab)->__pyx_base.__pyx_base.dloss(((struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_LossFunction *)__pyx_v_self), __pyx_v_p, __pyx_v_y, 1)); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 121; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_1);
__pyx_r = __pyx_t_1;
__pyx_t_1 = 0;
goto __pyx_L0;
__pyx_r = Py_None; __Pyx_INCREF(Py_None);
goto __pyx_L0;
__pyx_L1_error:;
__Pyx_XDECREF(__pyx_t_1);
__Pyx_AddTraceback("sklearn.linear_model.sgd_fast.ModifiedHuber.dloss", __pyx_clineno, __pyx_lineno, __pyx_filename);
__pyx_r = NULL;
__pyx_L0:;
__Pyx_XGIVEREF(__pyx_r);
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* Python wrapper */
static PyObject *__pyx_pw_7sklearn_12linear_model_8sgd_fast_13ModifiedHuber_5__reduce__(PyObject *__pyx_v_self, CYTHON_UNUSED PyObject *unused); /*proto*/
static PyObject *__pyx_pw_7sklearn_12linear_model_8sgd_fast_13ModifiedHuber_5__reduce__(PyObject *__pyx_v_self, CYTHON_UNUSED PyObject *unused) {
PyObject *__pyx_r = 0;
__Pyx_RefNannyDeclarations
__Pyx_RefNannySetupContext("__reduce__ (wrapper)", 0);
__pyx_r = __pyx_pf_7sklearn_12linear_model_8sgd_fast_13ModifiedHuber_4__reduce__(((struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_ModifiedHuber *)__pyx_v_self));
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* "sklearn/linear_model/sgd_fast.pyx":130
* return -4.0 * y
*
* def __reduce__(self): # <<<<<<<<<<<<<<
* return ModifiedHuber, ()
*
*/
static PyObject *__pyx_pf_7sklearn_12linear_model_8sgd_fast_13ModifiedHuber_4__reduce__(CYTHON_UNUSED struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_ModifiedHuber *__pyx_v_self) {
PyObject *__pyx_r = NULL;
__Pyx_RefNannyDeclarations
PyObject *__pyx_t_1 = NULL;
int __pyx_lineno = 0;
const char *__pyx_filename = NULL;
int __pyx_clineno = 0;
__Pyx_RefNannySetupContext("__reduce__", 0);
/* "sklearn/linear_model/sgd_fast.pyx":131
*
* def __reduce__(self):
* return ModifiedHuber, () # <<<<<<<<<<<<<<
*
*
*/
__Pyx_XDECREF(__pyx_r);
__pyx_t_1 = PyTuple_New(2); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 131; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_1);
__Pyx_INCREF(((PyObject *)((PyObject*)__pyx_ptype_7sklearn_12linear_model_8sgd_fast_ModifiedHuber)));
PyTuple_SET_ITEM(__pyx_t_1, 0, ((PyObject *)((PyObject*)__pyx_ptype_7sklearn_12linear_model_8sgd_fast_ModifiedHuber)));
__Pyx_GIVEREF(((PyObject *)((PyObject*)__pyx_ptype_7sklearn_12linear_model_8sgd_fast_ModifiedHuber)));
__Pyx_INCREF(((PyObject *)__pyx_empty_tuple));
PyTuple_SET_ITEM(__pyx_t_1, 1, ((PyObject *)__pyx_empty_tuple));
__Pyx_GIVEREF(((PyObject *)__pyx_empty_tuple));
__pyx_r = ((PyObject *)__pyx_t_1);
__pyx_t_1 = 0;
goto __pyx_L0;
__pyx_r = Py_None; __Pyx_INCREF(Py_None);
goto __pyx_L0;
__pyx_L1_error:;
__Pyx_XDECREF(__pyx_t_1);
__Pyx_AddTraceback("sklearn.linear_model.sgd_fast.ModifiedHuber.__reduce__", __pyx_clineno, __pyx_lineno, __pyx_filename);
__pyx_r = NULL;
__pyx_L0:;
__Pyx_XGIVEREF(__pyx_r);
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* Python wrapper */
static int __pyx_pw_7sklearn_12linear_model_8sgd_fast_5Hinge_1__init__(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/
static int __pyx_pw_7sklearn_12linear_model_8sgd_fast_5Hinge_1__init__(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds) {
double __pyx_v_threshold;
int __pyx_r;
__Pyx_RefNannyDeclarations
__Pyx_RefNannySetupContext("__init__ (wrapper)", 0);
{
static PyObject **__pyx_pyargnames[] = {&__pyx_n_s__threshold,0};
PyObject* values[1] = {0};
if (unlikely(__pyx_kwds)) {
Py_ssize_t kw_args;
const Py_ssize_t pos_args = PyTuple_GET_SIZE(__pyx_args);
switch (pos_args) {
case 1: values[0] = PyTuple_GET_ITEM(__pyx_args, 0);
case 0: break;
default: goto __pyx_L5_argtuple_error;
}
kw_args = PyDict_Size(__pyx_kwds);
switch (pos_args) {
case 0:
if (kw_args > 0) {
PyObject* value = PyDict_GetItem(__pyx_kwds, __pyx_n_s__threshold);
if (value) { values[0] = value; kw_args--; }
}
}
if (unlikely(kw_args > 0)) {
if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, pos_args, "__init__") < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 147; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
} else {
switch (PyTuple_GET_SIZE(__pyx_args)) {
case 1: values[0] = PyTuple_GET_ITEM(__pyx_args, 0);
case 0: break;
default: goto __pyx_L5_argtuple_error;
}
}
if (values[0]) {
__pyx_v_threshold = __pyx_PyFloat_AsDouble(values[0]); if (unlikely((__pyx_v_threshold == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 147; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
} else {
/* "sklearn/linear_model/sgd_fast.pyx":147
* cdef double threshold
*
* def __init__(self, double threshold=1.0): # <<<<<<<<<<<<<<
* self.threshold = threshold
*
*/
__pyx_v_threshold = ((double)1.0);
}
}
goto __pyx_L4_argument_unpacking_done;
__pyx_L5_argtuple_error:;
__Pyx_RaiseArgtupleInvalid("__init__", 0, 0, 1, PyTuple_GET_SIZE(__pyx_args)); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 147; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
__pyx_L3_error:;
__Pyx_AddTraceback("sklearn.linear_model.sgd_fast.Hinge.__init__", __pyx_clineno, __pyx_lineno, __pyx_filename);
__Pyx_RefNannyFinishContext();
return -1;
__pyx_L4_argument_unpacking_done:;
__pyx_r = __pyx_pf_7sklearn_12linear_model_8sgd_fast_5Hinge___init__(((struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_Hinge *)__pyx_v_self), __pyx_v_threshold);
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
static int __pyx_pf_7sklearn_12linear_model_8sgd_fast_5Hinge___init__(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_Hinge *__pyx_v_self, double __pyx_v_threshold) {
int __pyx_r;
__Pyx_RefNannyDeclarations
__Pyx_RefNannySetupContext("__init__", 0);
/* "sklearn/linear_model/sgd_fast.pyx":148
*
* def __init__(self, double threshold=1.0):
* self.threshold = threshold # <<<<<<<<<<<<<<
*
* cpdef double loss(self, double p, double y):
*/
__pyx_v_self->threshold = __pyx_v_threshold;
__pyx_r = 0;
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* "sklearn/linear_model/sgd_fast.pyx":150
* self.threshold = threshold
*
* cpdef double loss(self, double p, double y): # <<<<<<<<<<<<<<
* cdef double z = p * y
* if z <= self.threshold:
*/
static PyObject *__pyx_pw_7sklearn_12linear_model_8sgd_fast_5Hinge_3loss(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/
static double __pyx_f_7sklearn_12linear_model_8sgd_fast_5Hinge_loss(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_Hinge *__pyx_v_self, double __pyx_v_p, double __pyx_v_y, int __pyx_skip_dispatch) {
double __pyx_v_z;
double __pyx_r;
__Pyx_RefNannyDeclarations
PyObject *__pyx_t_1 = NULL;
PyObject *__pyx_t_2 = NULL;
PyObject *__pyx_t_3 = NULL;
PyObject *__pyx_t_4 = NULL;
double __pyx_t_5;
int __pyx_t_6;
int __pyx_lineno = 0;
const char *__pyx_filename = NULL;
int __pyx_clineno = 0;
__Pyx_RefNannySetupContext("loss", 0);
/* Check if called by wrapper */
if (unlikely(__pyx_skip_dispatch)) ;
/* Check if overriden in Python */
else if (unlikely(Py_TYPE(((PyObject *)__pyx_v_self))->tp_dictoffset != 0)) {
__pyx_t_1 = PyObject_GetAttr(((PyObject *)__pyx_v_self), __pyx_n_s__loss); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 150; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_1);
if (!PyCFunction_Check(__pyx_t_1) || (PyCFunction_GET_FUNCTION(__pyx_t_1) != (PyCFunction)__pyx_pw_7sklearn_12linear_model_8sgd_fast_5Hinge_3loss)) {
__pyx_t_2 = PyFloat_FromDouble(__pyx_v_p); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 150; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_2);
__pyx_t_3 = PyFloat_FromDouble(__pyx_v_y); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 150; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_3);
__pyx_t_4 = PyTuple_New(2); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 150; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_4);
PyTuple_SET_ITEM(__pyx_t_4, 0, __pyx_t_2);
__Pyx_GIVEREF(__pyx_t_2);
PyTuple_SET_ITEM(__pyx_t_4, 1, __pyx_t_3);
__Pyx_GIVEREF(__pyx_t_3);
__pyx_t_2 = 0;
__pyx_t_3 = 0;
__pyx_t_3 = PyObject_Call(__pyx_t_1, ((PyObject *)__pyx_t_4), NULL); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 150; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_3);
__Pyx_DECREF(((PyObject *)__pyx_t_4)); __pyx_t_4 = 0;
__pyx_t_5 = __pyx_PyFloat_AsDouble(__pyx_t_3); if (unlikely((__pyx_t_5 == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 150; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0;
__pyx_r = __pyx_t_5;
__Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0;
goto __pyx_L0;
}
__Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0;
}
/* "sklearn/linear_model/sgd_fast.pyx":151
*
* cpdef double loss(self, double p, double y):
* cdef double z = p * y # <<<<<<<<<<<<<<
* if z <= self.threshold:
* return (self.threshold - z)
*/
__pyx_v_z = (__pyx_v_p * __pyx_v_y);
/* "sklearn/linear_model/sgd_fast.pyx":152
* cpdef double loss(self, double p, double y):
* cdef double z = p * y
* if z <= self.threshold: # <<<<<<<<<<<<<<
* return (self.threshold - z)
* return 0.0
*/
__pyx_t_6 = (__pyx_v_z <= __pyx_v_self->threshold);
if (__pyx_t_6) {
/* "sklearn/linear_model/sgd_fast.pyx":153
* cdef double z = p * y
* if z <= self.threshold:
* return (self.threshold - z) # <<<<<<<<<<<<<<
* return 0.0
*
*/
__pyx_r = (__pyx_v_self->threshold - __pyx_v_z);
goto __pyx_L0;
goto __pyx_L3;
}
__pyx_L3:;
/* "sklearn/linear_model/sgd_fast.pyx":154
* if z <= self.threshold:
* return (self.threshold - z)
* return 0.0 # <<<<<<<<<<<<<<
*
* cpdef double dloss(self, double p, double y):
*/
__pyx_r = 0.0;
goto __pyx_L0;
__pyx_r = 0;
goto __pyx_L0;
__pyx_L1_error:;
__Pyx_XDECREF(__pyx_t_1);
__Pyx_XDECREF(__pyx_t_2);
__Pyx_XDECREF(__pyx_t_3);
__Pyx_XDECREF(__pyx_t_4);
__Pyx_WriteUnraisable("sklearn.linear_model.sgd_fast.Hinge.loss", __pyx_clineno, __pyx_lineno, __pyx_filename);
__pyx_r = 0;
__pyx_L0:;
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* Python wrapper */
static PyObject *__pyx_pw_7sklearn_12linear_model_8sgd_fast_5Hinge_3loss(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/
static PyObject *__pyx_pw_7sklearn_12linear_model_8sgd_fast_5Hinge_3loss(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds) {
double __pyx_v_p;
double __pyx_v_y;
PyObject *__pyx_r = 0;
__Pyx_RefNannyDeclarations
__Pyx_RefNannySetupContext("loss (wrapper)", 0);
{
static PyObject **__pyx_pyargnames[] = {&__pyx_n_s__p,&__pyx_n_s__y,0};
PyObject* values[2] = {0,0};
if (unlikely(__pyx_kwds)) {
Py_ssize_t kw_args;
const Py_ssize_t pos_args = PyTuple_GET_SIZE(__pyx_args);
switch (pos_args) {
case 2: values[1] = PyTuple_GET_ITEM(__pyx_args, 1);
case 1: values[0] = PyTuple_GET_ITEM(__pyx_args, 0);
case 0: break;
default: goto __pyx_L5_argtuple_error;
}
kw_args = PyDict_Size(__pyx_kwds);
switch (pos_args) {
case 0:
if (likely((values[0] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__p)) != 0)) kw_args--;
else goto __pyx_L5_argtuple_error;
case 1:
if (likely((values[1] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__y)) != 0)) kw_args--;
else {
__Pyx_RaiseArgtupleInvalid("loss", 1, 2, 2, 1); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 150; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
}
if (unlikely(kw_args > 0)) {
if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, pos_args, "loss") < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 150; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
} else if (PyTuple_GET_SIZE(__pyx_args) != 2) {
goto __pyx_L5_argtuple_error;
} else {
values[0] = PyTuple_GET_ITEM(__pyx_args, 0);
values[1] = PyTuple_GET_ITEM(__pyx_args, 1);
}
__pyx_v_p = __pyx_PyFloat_AsDouble(values[0]); if (unlikely((__pyx_v_p == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 150; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
__pyx_v_y = __pyx_PyFloat_AsDouble(values[1]); if (unlikely((__pyx_v_y == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 150; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
goto __pyx_L4_argument_unpacking_done;
__pyx_L5_argtuple_error:;
__Pyx_RaiseArgtupleInvalid("loss", 1, 2, 2, PyTuple_GET_SIZE(__pyx_args)); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 150; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
__pyx_L3_error:;
__Pyx_AddTraceback("sklearn.linear_model.sgd_fast.Hinge.loss", __pyx_clineno, __pyx_lineno, __pyx_filename);
__Pyx_RefNannyFinishContext();
return NULL;
__pyx_L4_argument_unpacking_done:;
__pyx_r = __pyx_pf_7sklearn_12linear_model_8sgd_fast_5Hinge_2loss(((struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_Hinge *)__pyx_v_self), __pyx_v_p, __pyx_v_y);
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* "sklearn/linear_model/sgd_fast.pyx":150
* self.threshold = threshold
*
* cpdef double loss(self, double p, double y): # <<<<<<<<<<<<<<
* cdef double z = p * y
* if z <= self.threshold:
*/
static PyObject *__pyx_pf_7sklearn_12linear_model_8sgd_fast_5Hinge_2loss(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_Hinge *__pyx_v_self, double __pyx_v_p, double __pyx_v_y) {
PyObject *__pyx_r = NULL;
__Pyx_RefNannyDeclarations
PyObject *__pyx_t_1 = NULL;
int __pyx_lineno = 0;
const char *__pyx_filename = NULL;
int __pyx_clineno = 0;
__Pyx_RefNannySetupContext("loss", 0);
__Pyx_XDECREF(__pyx_r);
__pyx_t_1 = PyFloat_FromDouble(((struct __pyx_vtabstruct_7sklearn_12linear_model_8sgd_fast_Hinge *)__pyx_v_self->__pyx_base.__pyx_base.__pyx_vtab)->__pyx_base.__pyx_base.loss(((struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_LossFunction *)__pyx_v_self), __pyx_v_p, __pyx_v_y, 1)); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 150; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_1);
__pyx_r = __pyx_t_1;
__pyx_t_1 = 0;
goto __pyx_L0;
__pyx_r = Py_None; __Pyx_INCREF(Py_None);
goto __pyx_L0;
__pyx_L1_error:;
__Pyx_XDECREF(__pyx_t_1);
__Pyx_AddTraceback("sklearn.linear_model.sgd_fast.Hinge.loss", __pyx_clineno, __pyx_lineno, __pyx_filename);
__pyx_r = NULL;
__pyx_L0:;
__Pyx_XGIVEREF(__pyx_r);
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* "sklearn/linear_model/sgd_fast.pyx":156
* return 0.0
*
* cpdef double dloss(self, double p, double y): # <<<<<<<<<<<<<<
* cdef double z = p * y
* if z <= self.threshold:
*/
static PyObject *__pyx_pw_7sklearn_12linear_model_8sgd_fast_5Hinge_5dloss(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/
static double __pyx_f_7sklearn_12linear_model_8sgd_fast_5Hinge_dloss(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_Hinge *__pyx_v_self, double __pyx_v_p, double __pyx_v_y, int __pyx_skip_dispatch) {
double __pyx_v_z;
double __pyx_r;
__Pyx_RefNannyDeclarations
PyObject *__pyx_t_1 = NULL;
PyObject *__pyx_t_2 = NULL;
PyObject *__pyx_t_3 = NULL;
PyObject *__pyx_t_4 = NULL;
double __pyx_t_5;
int __pyx_t_6;
int __pyx_lineno = 0;
const char *__pyx_filename = NULL;
int __pyx_clineno = 0;
__Pyx_RefNannySetupContext("dloss", 0);
/* Check if called by wrapper */
if (unlikely(__pyx_skip_dispatch)) ;
/* Check if overriden in Python */
else if (unlikely(Py_TYPE(((PyObject *)__pyx_v_self))->tp_dictoffset != 0)) {
__pyx_t_1 = PyObject_GetAttr(((PyObject *)__pyx_v_self), __pyx_n_s__dloss); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 156; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_1);
if (!PyCFunction_Check(__pyx_t_1) || (PyCFunction_GET_FUNCTION(__pyx_t_1) != (PyCFunction)__pyx_pw_7sklearn_12linear_model_8sgd_fast_5Hinge_5dloss)) {
__pyx_t_2 = PyFloat_FromDouble(__pyx_v_p); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 156; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_2);
__pyx_t_3 = PyFloat_FromDouble(__pyx_v_y); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 156; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_3);
__pyx_t_4 = PyTuple_New(2); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 156; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_4);
PyTuple_SET_ITEM(__pyx_t_4, 0, __pyx_t_2);
__Pyx_GIVEREF(__pyx_t_2);
PyTuple_SET_ITEM(__pyx_t_4, 1, __pyx_t_3);
__Pyx_GIVEREF(__pyx_t_3);
__pyx_t_2 = 0;
__pyx_t_3 = 0;
__pyx_t_3 = PyObject_Call(__pyx_t_1, ((PyObject *)__pyx_t_4), NULL); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 156; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_3);
__Pyx_DECREF(((PyObject *)__pyx_t_4)); __pyx_t_4 = 0;
__pyx_t_5 = __pyx_PyFloat_AsDouble(__pyx_t_3); if (unlikely((__pyx_t_5 == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 156; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0;
__pyx_r = __pyx_t_5;
__Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0;
goto __pyx_L0;
}
__Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0;
}
/* "sklearn/linear_model/sgd_fast.pyx":157
*
* cpdef double dloss(self, double p, double y):
* cdef double z = p * y # <<<<<<<<<<<<<<
* if z <= self.threshold:
* return -y
*/
__pyx_v_z = (__pyx_v_p * __pyx_v_y);
/* "sklearn/linear_model/sgd_fast.pyx":158
* cpdef double dloss(self, double p, double y):
* cdef double z = p * y
* if z <= self.threshold: # <<<<<<<<<<<<<<
* return -y
* return 0.0
*/
__pyx_t_6 = (__pyx_v_z <= __pyx_v_self->threshold);
if (__pyx_t_6) {
/* "sklearn/linear_model/sgd_fast.pyx":159
* cdef double z = p * y
* if z <= self.threshold:
* return -y # <<<<<<<<<<<<<<
* return 0.0
*
*/
__pyx_r = (-__pyx_v_y);
goto __pyx_L0;
goto __pyx_L3;
}
__pyx_L3:;
/* "sklearn/linear_model/sgd_fast.pyx":160
* if z <= self.threshold:
* return -y
* return 0.0 # <<<<<<<<<<<<<<
*
* def __reduce__(self):
*/
__pyx_r = 0.0;
goto __pyx_L0;
__pyx_r = 0;
goto __pyx_L0;
__pyx_L1_error:;
__Pyx_XDECREF(__pyx_t_1);
__Pyx_XDECREF(__pyx_t_2);
__Pyx_XDECREF(__pyx_t_3);
__Pyx_XDECREF(__pyx_t_4);
__Pyx_WriteUnraisable("sklearn.linear_model.sgd_fast.Hinge.dloss", __pyx_clineno, __pyx_lineno, __pyx_filename);
__pyx_r = 0;
__pyx_L0:;
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* Python wrapper */
static PyObject *__pyx_pw_7sklearn_12linear_model_8sgd_fast_5Hinge_5dloss(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/
static PyObject *__pyx_pw_7sklearn_12linear_model_8sgd_fast_5Hinge_5dloss(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds) {
double __pyx_v_p;
double __pyx_v_y;
PyObject *__pyx_r = 0;
__Pyx_RefNannyDeclarations
__Pyx_RefNannySetupContext("dloss (wrapper)", 0);
{
static PyObject **__pyx_pyargnames[] = {&__pyx_n_s__p,&__pyx_n_s__y,0};
PyObject* values[2] = {0,0};
if (unlikely(__pyx_kwds)) {
Py_ssize_t kw_args;
const Py_ssize_t pos_args = PyTuple_GET_SIZE(__pyx_args);
switch (pos_args) {
case 2: values[1] = PyTuple_GET_ITEM(__pyx_args, 1);
case 1: values[0] = PyTuple_GET_ITEM(__pyx_args, 0);
case 0: break;
default: goto __pyx_L5_argtuple_error;
}
kw_args = PyDict_Size(__pyx_kwds);
switch (pos_args) {
case 0:
if (likely((values[0] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__p)) != 0)) kw_args--;
else goto __pyx_L5_argtuple_error;
case 1:
if (likely((values[1] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__y)) != 0)) kw_args--;
else {
__Pyx_RaiseArgtupleInvalid("dloss", 1, 2, 2, 1); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 156; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
}
if (unlikely(kw_args > 0)) {
if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, pos_args, "dloss") < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 156; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
} else if (PyTuple_GET_SIZE(__pyx_args) != 2) {
goto __pyx_L5_argtuple_error;
} else {
values[0] = PyTuple_GET_ITEM(__pyx_args, 0);
values[1] = PyTuple_GET_ITEM(__pyx_args, 1);
}
__pyx_v_p = __pyx_PyFloat_AsDouble(values[0]); if (unlikely((__pyx_v_p == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 156; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
__pyx_v_y = __pyx_PyFloat_AsDouble(values[1]); if (unlikely((__pyx_v_y == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 156; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
goto __pyx_L4_argument_unpacking_done;
__pyx_L5_argtuple_error:;
__Pyx_RaiseArgtupleInvalid("dloss", 1, 2, 2, PyTuple_GET_SIZE(__pyx_args)); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 156; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
__pyx_L3_error:;
__Pyx_AddTraceback("sklearn.linear_model.sgd_fast.Hinge.dloss", __pyx_clineno, __pyx_lineno, __pyx_filename);
__Pyx_RefNannyFinishContext();
return NULL;
__pyx_L4_argument_unpacking_done:;
__pyx_r = __pyx_pf_7sklearn_12linear_model_8sgd_fast_5Hinge_4dloss(((struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_Hinge *)__pyx_v_self), __pyx_v_p, __pyx_v_y);
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* "sklearn/linear_model/sgd_fast.pyx":156
* return 0.0
*
* cpdef double dloss(self, double p, double y): # <<<<<<<<<<<<<<
* cdef double z = p * y
* if z <= self.threshold:
*/
static PyObject *__pyx_pf_7sklearn_12linear_model_8sgd_fast_5Hinge_4dloss(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_Hinge *__pyx_v_self, double __pyx_v_p, double __pyx_v_y) {
PyObject *__pyx_r = NULL;
__Pyx_RefNannyDeclarations
PyObject *__pyx_t_1 = NULL;
int __pyx_lineno = 0;
const char *__pyx_filename = NULL;
int __pyx_clineno = 0;
__Pyx_RefNannySetupContext("dloss", 0);
__Pyx_XDECREF(__pyx_r);
__pyx_t_1 = PyFloat_FromDouble(((struct __pyx_vtabstruct_7sklearn_12linear_model_8sgd_fast_Hinge *)__pyx_v_self->__pyx_base.__pyx_base.__pyx_vtab)->__pyx_base.__pyx_base.dloss(((struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_LossFunction *)__pyx_v_self), __pyx_v_p, __pyx_v_y, 1)); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 156; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_1);
__pyx_r = __pyx_t_1;
__pyx_t_1 = 0;
goto __pyx_L0;
__pyx_r = Py_None; __Pyx_INCREF(Py_None);
goto __pyx_L0;
__pyx_L1_error:;
__Pyx_XDECREF(__pyx_t_1);
__Pyx_AddTraceback("sklearn.linear_model.sgd_fast.Hinge.dloss", __pyx_clineno, __pyx_lineno, __pyx_filename);
__pyx_r = NULL;
__pyx_L0:;
__Pyx_XGIVEREF(__pyx_r);
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* Python wrapper */
static PyObject *__pyx_pw_7sklearn_12linear_model_8sgd_fast_5Hinge_7__reduce__(PyObject *__pyx_v_self, CYTHON_UNUSED PyObject *unused); /*proto*/
static PyObject *__pyx_pw_7sklearn_12linear_model_8sgd_fast_5Hinge_7__reduce__(PyObject *__pyx_v_self, CYTHON_UNUSED PyObject *unused) {
PyObject *__pyx_r = 0;
__Pyx_RefNannyDeclarations
__Pyx_RefNannySetupContext("__reduce__ (wrapper)", 0);
__pyx_r = __pyx_pf_7sklearn_12linear_model_8sgd_fast_5Hinge_6__reduce__(((struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_Hinge *)__pyx_v_self));
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* "sklearn/linear_model/sgd_fast.pyx":162
* return 0.0
*
* def __reduce__(self): # <<<<<<<<<<<<<<
* return Hinge, (self.threshold,)
*
*/
static PyObject *__pyx_pf_7sklearn_12linear_model_8sgd_fast_5Hinge_6__reduce__(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_Hinge *__pyx_v_self) {
PyObject *__pyx_r = NULL;
__Pyx_RefNannyDeclarations
PyObject *__pyx_t_1 = NULL;
PyObject *__pyx_t_2 = NULL;
int __pyx_lineno = 0;
const char *__pyx_filename = NULL;
int __pyx_clineno = 0;
__Pyx_RefNannySetupContext("__reduce__", 0);
/* "sklearn/linear_model/sgd_fast.pyx":163
*
* def __reduce__(self):
* return Hinge, (self.threshold,) # <<<<<<<<<<<<<<
*
*
*/
__Pyx_XDECREF(__pyx_r);
__pyx_t_1 = PyFloat_FromDouble(__pyx_v_self->threshold); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 163; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_1);
__pyx_t_2 = PyTuple_New(1); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 163; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_2);
PyTuple_SET_ITEM(__pyx_t_2, 0, __pyx_t_1);
__Pyx_GIVEREF(__pyx_t_1);
__pyx_t_1 = 0;
__pyx_t_1 = PyTuple_New(2); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 163; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_1);
__Pyx_INCREF(((PyObject *)((PyObject*)__pyx_ptype_7sklearn_12linear_model_8sgd_fast_Hinge)));
PyTuple_SET_ITEM(__pyx_t_1, 0, ((PyObject *)((PyObject*)__pyx_ptype_7sklearn_12linear_model_8sgd_fast_Hinge)));
__Pyx_GIVEREF(((PyObject *)((PyObject*)__pyx_ptype_7sklearn_12linear_model_8sgd_fast_Hinge)));
PyTuple_SET_ITEM(__pyx_t_1, 1, ((PyObject *)__pyx_t_2));
__Pyx_GIVEREF(((PyObject *)__pyx_t_2));
__pyx_t_2 = 0;
__pyx_r = ((PyObject *)__pyx_t_1);
__pyx_t_1 = 0;
goto __pyx_L0;
__pyx_r = Py_None; __Pyx_INCREF(Py_None);
goto __pyx_L0;
__pyx_L1_error:;
__Pyx_XDECREF(__pyx_t_1);
__Pyx_XDECREF(__pyx_t_2);
__Pyx_AddTraceback("sklearn.linear_model.sgd_fast.Hinge.__reduce__", __pyx_clineno, __pyx_lineno, __pyx_filename);
__pyx_r = NULL;
__pyx_L0:;
__Pyx_XGIVEREF(__pyx_r);
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* Python wrapper */
static int __pyx_pw_7sklearn_12linear_model_8sgd_fast_12SquaredHinge_1__init__(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/
static int __pyx_pw_7sklearn_12linear_model_8sgd_fast_12SquaredHinge_1__init__(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds) {
double __pyx_v_threshold;
int __pyx_r;
__Pyx_RefNannyDeclarations
__Pyx_RefNannySetupContext("__init__ (wrapper)", 0);
{
static PyObject **__pyx_pyargnames[] = {&__pyx_n_s__threshold,0};
PyObject* values[1] = {0};
if (unlikely(__pyx_kwds)) {
Py_ssize_t kw_args;
const Py_ssize_t pos_args = PyTuple_GET_SIZE(__pyx_args);
switch (pos_args) {
case 1: values[0] = PyTuple_GET_ITEM(__pyx_args, 0);
case 0: break;
default: goto __pyx_L5_argtuple_error;
}
kw_args = PyDict_Size(__pyx_kwds);
switch (pos_args) {
case 0:
if (kw_args > 0) {
PyObject* value = PyDict_GetItem(__pyx_kwds, __pyx_n_s__threshold);
if (value) { values[0] = value; kw_args--; }
}
}
if (unlikely(kw_args > 0)) {
if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, pos_args, "__init__") < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 179; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
} else {
switch (PyTuple_GET_SIZE(__pyx_args)) {
case 1: values[0] = PyTuple_GET_ITEM(__pyx_args, 0);
case 0: break;
default: goto __pyx_L5_argtuple_error;
}
}
if (values[0]) {
__pyx_v_threshold = __pyx_PyFloat_AsDouble(values[0]); if (unlikely((__pyx_v_threshold == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 179; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
} else {
/* "sklearn/linear_model/sgd_fast.pyx":179
* cdef double threshold
*
* def __init__(self, double threshold=1.0): # <<<<<<<<<<<<<<
* self.threshold = threshold
*
*/
__pyx_v_threshold = ((double)1.0);
}
}
goto __pyx_L4_argument_unpacking_done;
__pyx_L5_argtuple_error:;
__Pyx_RaiseArgtupleInvalid("__init__", 0, 0, 1, PyTuple_GET_SIZE(__pyx_args)); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 179; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
__pyx_L3_error:;
__Pyx_AddTraceback("sklearn.linear_model.sgd_fast.SquaredHinge.__init__", __pyx_clineno, __pyx_lineno, __pyx_filename);
__Pyx_RefNannyFinishContext();
return -1;
__pyx_L4_argument_unpacking_done:;
__pyx_r = __pyx_pf_7sklearn_12linear_model_8sgd_fast_12SquaredHinge___init__(((struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_SquaredHinge *)__pyx_v_self), __pyx_v_threshold);
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
static int __pyx_pf_7sklearn_12linear_model_8sgd_fast_12SquaredHinge___init__(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_SquaredHinge *__pyx_v_self, double __pyx_v_threshold) {
int __pyx_r;
__Pyx_RefNannyDeclarations
__Pyx_RefNannySetupContext("__init__", 0);
/* "sklearn/linear_model/sgd_fast.pyx":180
*
* def __init__(self, double threshold=1.0):
* self.threshold = threshold # <<<<<<<<<<<<<<
*
* cpdef double loss(self, double p, double y):
*/
__pyx_v_self->threshold = __pyx_v_threshold;
__pyx_r = 0;
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* "sklearn/linear_model/sgd_fast.pyx":182
* self.threshold = threshold
*
* cpdef double loss(self, double p, double y): # <<<<<<<<<<<<<<
* cdef double z = self.threshold - p * y
* if z > 0:
*/
static PyObject *__pyx_pw_7sklearn_12linear_model_8sgd_fast_12SquaredHinge_3loss(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/
static double __pyx_f_7sklearn_12linear_model_8sgd_fast_12SquaredHinge_loss(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_SquaredHinge *__pyx_v_self, double __pyx_v_p, double __pyx_v_y, int __pyx_skip_dispatch) {
double __pyx_v_z;
double __pyx_r;
__Pyx_RefNannyDeclarations
PyObject *__pyx_t_1 = NULL;
PyObject *__pyx_t_2 = NULL;
PyObject *__pyx_t_3 = NULL;
PyObject *__pyx_t_4 = NULL;
double __pyx_t_5;
int __pyx_t_6;
int __pyx_lineno = 0;
const char *__pyx_filename = NULL;
int __pyx_clineno = 0;
__Pyx_RefNannySetupContext("loss", 0);
/* Check if called by wrapper */
if (unlikely(__pyx_skip_dispatch)) ;
/* Check if overriden in Python */
else if (unlikely(Py_TYPE(((PyObject *)__pyx_v_self))->tp_dictoffset != 0)) {
__pyx_t_1 = PyObject_GetAttr(((PyObject *)__pyx_v_self), __pyx_n_s__loss); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 182; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_1);
if (!PyCFunction_Check(__pyx_t_1) || (PyCFunction_GET_FUNCTION(__pyx_t_1) != (PyCFunction)__pyx_pw_7sklearn_12linear_model_8sgd_fast_12SquaredHinge_3loss)) {
__pyx_t_2 = PyFloat_FromDouble(__pyx_v_p); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 182; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_2);
__pyx_t_3 = PyFloat_FromDouble(__pyx_v_y); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 182; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_3);
__pyx_t_4 = PyTuple_New(2); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 182; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_4);
PyTuple_SET_ITEM(__pyx_t_4, 0, __pyx_t_2);
__Pyx_GIVEREF(__pyx_t_2);
PyTuple_SET_ITEM(__pyx_t_4, 1, __pyx_t_3);
__Pyx_GIVEREF(__pyx_t_3);
__pyx_t_2 = 0;
__pyx_t_3 = 0;
__pyx_t_3 = PyObject_Call(__pyx_t_1, ((PyObject *)__pyx_t_4), NULL); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 182; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_3);
__Pyx_DECREF(((PyObject *)__pyx_t_4)); __pyx_t_4 = 0;
__pyx_t_5 = __pyx_PyFloat_AsDouble(__pyx_t_3); if (unlikely((__pyx_t_5 == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 182; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0;
__pyx_r = __pyx_t_5;
__Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0;
goto __pyx_L0;
}
__Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0;
}
/* "sklearn/linear_model/sgd_fast.pyx":183
*
* cpdef double loss(self, double p, double y):
* cdef double z = self.threshold - p * y # <<<<<<<<<<<<<<
* if z > 0:
* return z * z
*/
__pyx_v_z = (__pyx_v_self->threshold - (__pyx_v_p * __pyx_v_y));
/* "sklearn/linear_model/sgd_fast.pyx":184
* cpdef double loss(self, double p, double y):
* cdef double z = self.threshold - p * y
* if z > 0: # <<<<<<<<<<<<<<
* return z * z
* return 0.0
*/
__pyx_t_6 = (__pyx_v_z > 0.0);
if (__pyx_t_6) {
/* "sklearn/linear_model/sgd_fast.pyx":185
* cdef double z = self.threshold - p * y
* if z > 0:
* return z * z # <<<<<<<<<<<<<<
* return 0.0
*
*/
__pyx_r = (__pyx_v_z * __pyx_v_z);
goto __pyx_L0;
goto __pyx_L3;
}
__pyx_L3:;
/* "sklearn/linear_model/sgd_fast.pyx":186
* if z > 0:
* return z * z
* return 0.0 # <<<<<<<<<<<<<<
*
* cpdef double dloss(self, double p, double y):
*/
__pyx_r = 0.0;
goto __pyx_L0;
__pyx_r = 0;
goto __pyx_L0;
__pyx_L1_error:;
__Pyx_XDECREF(__pyx_t_1);
__Pyx_XDECREF(__pyx_t_2);
__Pyx_XDECREF(__pyx_t_3);
__Pyx_XDECREF(__pyx_t_4);
__Pyx_WriteUnraisable("sklearn.linear_model.sgd_fast.SquaredHinge.loss", __pyx_clineno, __pyx_lineno, __pyx_filename);
__pyx_r = 0;
__pyx_L0:;
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* Python wrapper */
static PyObject *__pyx_pw_7sklearn_12linear_model_8sgd_fast_12SquaredHinge_3loss(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/
static PyObject *__pyx_pw_7sklearn_12linear_model_8sgd_fast_12SquaredHinge_3loss(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds) {
double __pyx_v_p;
double __pyx_v_y;
PyObject *__pyx_r = 0;
__Pyx_RefNannyDeclarations
__Pyx_RefNannySetupContext("loss (wrapper)", 0);
{
static PyObject **__pyx_pyargnames[] = {&__pyx_n_s__p,&__pyx_n_s__y,0};
PyObject* values[2] = {0,0};
if (unlikely(__pyx_kwds)) {
Py_ssize_t kw_args;
const Py_ssize_t pos_args = PyTuple_GET_SIZE(__pyx_args);
switch (pos_args) {
case 2: values[1] = PyTuple_GET_ITEM(__pyx_args, 1);
case 1: values[0] = PyTuple_GET_ITEM(__pyx_args, 0);
case 0: break;
default: goto __pyx_L5_argtuple_error;
}
kw_args = PyDict_Size(__pyx_kwds);
switch (pos_args) {
case 0:
if (likely((values[0] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__p)) != 0)) kw_args--;
else goto __pyx_L5_argtuple_error;
case 1:
if (likely((values[1] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__y)) != 0)) kw_args--;
else {
__Pyx_RaiseArgtupleInvalid("loss", 1, 2, 2, 1); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 182; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
}
if (unlikely(kw_args > 0)) {
if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, pos_args, "loss") < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 182; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
} else if (PyTuple_GET_SIZE(__pyx_args) != 2) {
goto __pyx_L5_argtuple_error;
} else {
values[0] = PyTuple_GET_ITEM(__pyx_args, 0);
values[1] = PyTuple_GET_ITEM(__pyx_args, 1);
}
__pyx_v_p = __pyx_PyFloat_AsDouble(values[0]); if (unlikely((__pyx_v_p == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 182; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
__pyx_v_y = __pyx_PyFloat_AsDouble(values[1]); if (unlikely((__pyx_v_y == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 182; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
goto __pyx_L4_argument_unpacking_done;
__pyx_L5_argtuple_error:;
__Pyx_RaiseArgtupleInvalid("loss", 1, 2, 2, PyTuple_GET_SIZE(__pyx_args)); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 182; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
__pyx_L3_error:;
__Pyx_AddTraceback("sklearn.linear_model.sgd_fast.SquaredHinge.loss", __pyx_clineno, __pyx_lineno, __pyx_filename);
__Pyx_RefNannyFinishContext();
return NULL;
__pyx_L4_argument_unpacking_done:;
__pyx_r = __pyx_pf_7sklearn_12linear_model_8sgd_fast_12SquaredHinge_2loss(((struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_SquaredHinge *)__pyx_v_self), __pyx_v_p, __pyx_v_y);
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* "sklearn/linear_model/sgd_fast.pyx":182
* self.threshold = threshold
*
* cpdef double loss(self, double p, double y): # <<<<<<<<<<<<<<
* cdef double z = self.threshold - p * y
* if z > 0:
*/
static PyObject *__pyx_pf_7sklearn_12linear_model_8sgd_fast_12SquaredHinge_2loss(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_SquaredHinge *__pyx_v_self, double __pyx_v_p, double __pyx_v_y) {
PyObject *__pyx_r = NULL;
__Pyx_RefNannyDeclarations
PyObject *__pyx_t_1 = NULL;
int __pyx_lineno = 0;
const char *__pyx_filename = NULL;
int __pyx_clineno = 0;
__Pyx_RefNannySetupContext("loss", 0);
__Pyx_XDECREF(__pyx_r);
__pyx_t_1 = PyFloat_FromDouble(((struct __pyx_vtabstruct_7sklearn_12linear_model_8sgd_fast_SquaredHinge *)__pyx_v_self->__pyx_base.__pyx_vtab)->__pyx_base.loss(((struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_LossFunction *)__pyx_v_self), __pyx_v_p, __pyx_v_y, 1)); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 182; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_1);
__pyx_r = __pyx_t_1;
__pyx_t_1 = 0;
goto __pyx_L0;
__pyx_r = Py_None; __Pyx_INCREF(Py_None);
goto __pyx_L0;
__pyx_L1_error:;
__Pyx_XDECREF(__pyx_t_1);
__Pyx_AddTraceback("sklearn.linear_model.sgd_fast.SquaredHinge.loss", __pyx_clineno, __pyx_lineno, __pyx_filename);
__pyx_r = NULL;
__pyx_L0:;
__Pyx_XGIVEREF(__pyx_r);
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* "sklearn/linear_model/sgd_fast.pyx":188
* return 0.0
*
* cpdef double dloss(self, double p, double y): # <<<<<<<<<<<<<<
* cdef double z = self.threshold - p * y
* if z > 0:
*/
static PyObject *__pyx_pw_7sklearn_12linear_model_8sgd_fast_12SquaredHinge_5dloss(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/
static double __pyx_f_7sklearn_12linear_model_8sgd_fast_12SquaredHinge_dloss(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_SquaredHinge *__pyx_v_self, double __pyx_v_p, double __pyx_v_y, int __pyx_skip_dispatch) {
double __pyx_v_z;
double __pyx_r;
__Pyx_RefNannyDeclarations
PyObject *__pyx_t_1 = NULL;
PyObject *__pyx_t_2 = NULL;
PyObject *__pyx_t_3 = NULL;
PyObject *__pyx_t_4 = NULL;
double __pyx_t_5;
int __pyx_t_6;
int __pyx_lineno = 0;
const char *__pyx_filename = NULL;
int __pyx_clineno = 0;
__Pyx_RefNannySetupContext("dloss", 0);
/* Check if called by wrapper */
if (unlikely(__pyx_skip_dispatch)) ;
/* Check if overriden in Python */
else if (unlikely(Py_TYPE(((PyObject *)__pyx_v_self))->tp_dictoffset != 0)) {
__pyx_t_1 = PyObject_GetAttr(((PyObject *)__pyx_v_self), __pyx_n_s__dloss); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 188; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_1);
if (!PyCFunction_Check(__pyx_t_1) || (PyCFunction_GET_FUNCTION(__pyx_t_1) != (PyCFunction)__pyx_pw_7sklearn_12linear_model_8sgd_fast_12SquaredHinge_5dloss)) {
__pyx_t_2 = PyFloat_FromDouble(__pyx_v_p); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 188; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_2);
__pyx_t_3 = PyFloat_FromDouble(__pyx_v_y); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 188; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_3);
__pyx_t_4 = PyTuple_New(2); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 188; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_4);
PyTuple_SET_ITEM(__pyx_t_4, 0, __pyx_t_2);
__Pyx_GIVEREF(__pyx_t_2);
PyTuple_SET_ITEM(__pyx_t_4, 1, __pyx_t_3);
__Pyx_GIVEREF(__pyx_t_3);
__pyx_t_2 = 0;
__pyx_t_3 = 0;
__pyx_t_3 = PyObject_Call(__pyx_t_1, ((PyObject *)__pyx_t_4), NULL); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 188; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_3);
__Pyx_DECREF(((PyObject *)__pyx_t_4)); __pyx_t_4 = 0;
__pyx_t_5 = __pyx_PyFloat_AsDouble(__pyx_t_3); if (unlikely((__pyx_t_5 == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 188; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0;
__pyx_r = __pyx_t_5;
__Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0;
goto __pyx_L0;
}
__Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0;
}
/* "sklearn/linear_model/sgd_fast.pyx":189
*
* cpdef double dloss(self, double p, double y):
* cdef double z = self.threshold - p * y # <<<<<<<<<<<<<<
* if z > 0:
* return -2 * y * z
*/
__pyx_v_z = (__pyx_v_self->threshold - (__pyx_v_p * __pyx_v_y));
/* "sklearn/linear_model/sgd_fast.pyx":190
* cpdef double dloss(self, double p, double y):
* cdef double z = self.threshold - p * y
* if z > 0: # <<<<<<<<<<<<<<
* return -2 * y * z
* return 0.0
*/
__pyx_t_6 = (__pyx_v_z > 0.0);
if (__pyx_t_6) {
/* "sklearn/linear_model/sgd_fast.pyx":191
* cdef double z = self.threshold - p * y
* if z > 0:
* return -2 * y * z # <<<<<<<<<<<<<<
* return 0.0
*
*/
__pyx_r = ((-2.0 * __pyx_v_y) * __pyx_v_z);
goto __pyx_L0;
goto __pyx_L3;
}
__pyx_L3:;
/* "sklearn/linear_model/sgd_fast.pyx":192
* if z > 0:
* return -2 * y * z
* return 0.0 # <<<<<<<<<<<<<<
*
* def __reduce__(self):
*/
__pyx_r = 0.0;
goto __pyx_L0;
__pyx_r = 0;
goto __pyx_L0;
__pyx_L1_error:;
__Pyx_XDECREF(__pyx_t_1);
__Pyx_XDECREF(__pyx_t_2);
__Pyx_XDECREF(__pyx_t_3);
__Pyx_XDECREF(__pyx_t_4);
__Pyx_WriteUnraisable("sklearn.linear_model.sgd_fast.SquaredHinge.dloss", __pyx_clineno, __pyx_lineno, __pyx_filename);
__pyx_r = 0;
__pyx_L0:;
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* Python wrapper */
static PyObject *__pyx_pw_7sklearn_12linear_model_8sgd_fast_12SquaredHinge_5dloss(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/
static PyObject *__pyx_pw_7sklearn_12linear_model_8sgd_fast_12SquaredHinge_5dloss(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds) {
double __pyx_v_p;
double __pyx_v_y;
PyObject *__pyx_r = 0;
__Pyx_RefNannyDeclarations
__Pyx_RefNannySetupContext("dloss (wrapper)", 0);
{
static PyObject **__pyx_pyargnames[] = {&__pyx_n_s__p,&__pyx_n_s__y,0};
PyObject* values[2] = {0,0};
if (unlikely(__pyx_kwds)) {
Py_ssize_t kw_args;
const Py_ssize_t pos_args = PyTuple_GET_SIZE(__pyx_args);
switch (pos_args) {
case 2: values[1] = PyTuple_GET_ITEM(__pyx_args, 1);
case 1: values[0] = PyTuple_GET_ITEM(__pyx_args, 0);
case 0: break;
default: goto __pyx_L5_argtuple_error;
}
kw_args = PyDict_Size(__pyx_kwds);
switch (pos_args) {
case 0:
if (likely((values[0] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__p)) != 0)) kw_args--;
else goto __pyx_L5_argtuple_error;
case 1:
if (likely((values[1] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__y)) != 0)) kw_args--;
else {
__Pyx_RaiseArgtupleInvalid("dloss", 1, 2, 2, 1); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 188; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
}
if (unlikely(kw_args > 0)) {
if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, pos_args, "dloss") < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 188; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
} else if (PyTuple_GET_SIZE(__pyx_args) != 2) {
goto __pyx_L5_argtuple_error;
} else {
values[0] = PyTuple_GET_ITEM(__pyx_args, 0);
values[1] = PyTuple_GET_ITEM(__pyx_args, 1);
}
__pyx_v_p = __pyx_PyFloat_AsDouble(values[0]); if (unlikely((__pyx_v_p == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 188; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
__pyx_v_y = __pyx_PyFloat_AsDouble(values[1]); if (unlikely((__pyx_v_y == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 188; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
goto __pyx_L4_argument_unpacking_done;
__pyx_L5_argtuple_error:;
__Pyx_RaiseArgtupleInvalid("dloss", 1, 2, 2, PyTuple_GET_SIZE(__pyx_args)); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 188; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
__pyx_L3_error:;
__Pyx_AddTraceback("sklearn.linear_model.sgd_fast.SquaredHinge.dloss", __pyx_clineno, __pyx_lineno, __pyx_filename);
__Pyx_RefNannyFinishContext();
return NULL;
__pyx_L4_argument_unpacking_done:;
__pyx_r = __pyx_pf_7sklearn_12linear_model_8sgd_fast_12SquaredHinge_4dloss(((struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_SquaredHinge *)__pyx_v_self), __pyx_v_p, __pyx_v_y);
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* "sklearn/linear_model/sgd_fast.pyx":188
* return 0.0
*
* cpdef double dloss(self, double p, double y): # <<<<<<<<<<<<<<
* cdef double z = self.threshold - p * y
* if z > 0:
*/
static PyObject *__pyx_pf_7sklearn_12linear_model_8sgd_fast_12SquaredHinge_4dloss(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_SquaredHinge *__pyx_v_self, double __pyx_v_p, double __pyx_v_y) {
PyObject *__pyx_r = NULL;
__Pyx_RefNannyDeclarations
PyObject *__pyx_t_1 = NULL;
int __pyx_lineno = 0;
const char *__pyx_filename = NULL;
int __pyx_clineno = 0;
__Pyx_RefNannySetupContext("dloss", 0);
__Pyx_XDECREF(__pyx_r);
__pyx_t_1 = PyFloat_FromDouble(((struct __pyx_vtabstruct_7sklearn_12linear_model_8sgd_fast_SquaredHinge *)__pyx_v_self->__pyx_base.__pyx_vtab)->__pyx_base.dloss(((struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_LossFunction *)__pyx_v_self), __pyx_v_p, __pyx_v_y, 1)); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 188; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_1);
__pyx_r = __pyx_t_1;
__pyx_t_1 = 0;
goto __pyx_L0;
__pyx_r = Py_None; __Pyx_INCREF(Py_None);
goto __pyx_L0;
__pyx_L1_error:;
__Pyx_XDECREF(__pyx_t_1);
__Pyx_AddTraceback("sklearn.linear_model.sgd_fast.SquaredHinge.dloss", __pyx_clineno, __pyx_lineno, __pyx_filename);
__pyx_r = NULL;
__pyx_L0:;
__Pyx_XGIVEREF(__pyx_r);
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* Python wrapper */
static PyObject *__pyx_pw_7sklearn_12linear_model_8sgd_fast_12SquaredHinge_7__reduce__(PyObject *__pyx_v_self, CYTHON_UNUSED PyObject *unused); /*proto*/
static PyObject *__pyx_pw_7sklearn_12linear_model_8sgd_fast_12SquaredHinge_7__reduce__(PyObject *__pyx_v_self, CYTHON_UNUSED PyObject *unused) {
PyObject *__pyx_r = 0;
__Pyx_RefNannyDeclarations
__Pyx_RefNannySetupContext("__reduce__ (wrapper)", 0);
__pyx_r = __pyx_pf_7sklearn_12linear_model_8sgd_fast_12SquaredHinge_6__reduce__(((struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_SquaredHinge *)__pyx_v_self));
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* "sklearn/linear_model/sgd_fast.pyx":194
* return 0.0
*
* def __reduce__(self): # <<<<<<<<<<<<<<
* return SquaredHinge, (self.threshold,)
*
*/
static PyObject *__pyx_pf_7sklearn_12linear_model_8sgd_fast_12SquaredHinge_6__reduce__(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_SquaredHinge *__pyx_v_self) {
PyObject *__pyx_r = NULL;
__Pyx_RefNannyDeclarations
PyObject *__pyx_t_1 = NULL;
PyObject *__pyx_t_2 = NULL;
int __pyx_lineno = 0;
const char *__pyx_filename = NULL;
int __pyx_clineno = 0;
__Pyx_RefNannySetupContext("__reduce__", 0);
/* "sklearn/linear_model/sgd_fast.pyx":195
*
* def __reduce__(self):
* return SquaredHinge, (self.threshold,) # <<<<<<<<<<<<<<
*
*
*/
__Pyx_XDECREF(__pyx_r);
__pyx_t_1 = PyFloat_FromDouble(__pyx_v_self->threshold); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 195; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_1);
__pyx_t_2 = PyTuple_New(1); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 195; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_2);
PyTuple_SET_ITEM(__pyx_t_2, 0, __pyx_t_1);
__Pyx_GIVEREF(__pyx_t_1);
__pyx_t_1 = 0;
__pyx_t_1 = PyTuple_New(2); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 195; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_1);
__Pyx_INCREF(((PyObject *)((PyObject*)__pyx_ptype_7sklearn_12linear_model_8sgd_fast_SquaredHinge)));
PyTuple_SET_ITEM(__pyx_t_1, 0, ((PyObject *)((PyObject*)__pyx_ptype_7sklearn_12linear_model_8sgd_fast_SquaredHinge)));
__Pyx_GIVEREF(((PyObject *)((PyObject*)__pyx_ptype_7sklearn_12linear_model_8sgd_fast_SquaredHinge)));
PyTuple_SET_ITEM(__pyx_t_1, 1, ((PyObject *)__pyx_t_2));
__Pyx_GIVEREF(((PyObject *)__pyx_t_2));
__pyx_t_2 = 0;
__pyx_r = ((PyObject *)__pyx_t_1);
__pyx_t_1 = 0;
goto __pyx_L0;
__pyx_r = Py_None; __Pyx_INCREF(Py_None);
goto __pyx_L0;
__pyx_L1_error:;
__Pyx_XDECREF(__pyx_t_1);
__Pyx_XDECREF(__pyx_t_2);
__Pyx_AddTraceback("sklearn.linear_model.sgd_fast.SquaredHinge.__reduce__", __pyx_clineno, __pyx_lineno, __pyx_filename);
__pyx_r = NULL;
__pyx_L0:;
__Pyx_XGIVEREF(__pyx_r);
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* "sklearn/linear_model/sgd_fast.pyx":201
* """Logistic regression loss for binary classification with y in {-1, 1}"""
*
* cpdef double loss(self, double p, double y): # <<<<<<<<<<<<<<
* cdef double z = p * y
* # approximately equal and saves the computation of the log
*/
static PyObject *__pyx_pw_7sklearn_12linear_model_8sgd_fast_3Log_1loss(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/
static double __pyx_f_7sklearn_12linear_model_8sgd_fast_3Log_loss(CYTHON_UNUSED struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_Log *__pyx_v_self, double __pyx_v_p, double __pyx_v_y, int __pyx_skip_dispatch) {
double __pyx_v_z;
double __pyx_r;
__Pyx_RefNannyDeclarations
PyObject *__pyx_t_1 = NULL;
PyObject *__pyx_t_2 = NULL;
PyObject *__pyx_t_3 = NULL;
PyObject *__pyx_t_4 = NULL;
double __pyx_t_5;
int __pyx_t_6;
int __pyx_lineno = 0;
const char *__pyx_filename = NULL;
int __pyx_clineno = 0;
__Pyx_RefNannySetupContext("loss", 0);
/* Check if called by wrapper */
if (unlikely(__pyx_skip_dispatch)) ;
/* Check if overriden in Python */
else if (unlikely(Py_TYPE(((PyObject *)__pyx_v_self))->tp_dictoffset != 0)) {
__pyx_t_1 = PyObject_GetAttr(((PyObject *)__pyx_v_self), __pyx_n_s__loss); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 201; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_1);
if (!PyCFunction_Check(__pyx_t_1) || (PyCFunction_GET_FUNCTION(__pyx_t_1) != (PyCFunction)__pyx_pw_7sklearn_12linear_model_8sgd_fast_3Log_1loss)) {
__pyx_t_2 = PyFloat_FromDouble(__pyx_v_p); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 201; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_2);
__pyx_t_3 = PyFloat_FromDouble(__pyx_v_y); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 201; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_3);
__pyx_t_4 = PyTuple_New(2); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 201; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_4);
PyTuple_SET_ITEM(__pyx_t_4, 0, __pyx_t_2);
__Pyx_GIVEREF(__pyx_t_2);
PyTuple_SET_ITEM(__pyx_t_4, 1, __pyx_t_3);
__Pyx_GIVEREF(__pyx_t_3);
__pyx_t_2 = 0;
__pyx_t_3 = 0;
__pyx_t_3 = PyObject_Call(__pyx_t_1, ((PyObject *)__pyx_t_4), NULL); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 201; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_3);
__Pyx_DECREF(((PyObject *)__pyx_t_4)); __pyx_t_4 = 0;
__pyx_t_5 = __pyx_PyFloat_AsDouble(__pyx_t_3); if (unlikely((__pyx_t_5 == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 201; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0;
__pyx_r = __pyx_t_5;
__Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0;
goto __pyx_L0;
}
__Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0;
}
/* "sklearn/linear_model/sgd_fast.pyx":202
*
* cpdef double loss(self, double p, double y):
* cdef double z = p * y # <<<<<<<<<<<<<<
* # approximately equal and saves the computation of the log
* if z > 18:
*/
__pyx_v_z = (__pyx_v_p * __pyx_v_y);
/* "sklearn/linear_model/sgd_fast.pyx":204
* cdef double z = p * y
* # approximately equal and saves the computation of the log
* if z > 18: # <<<<<<<<<<<<<<
* return exp(-z)
* if z < -18:
*/
__pyx_t_6 = (__pyx_v_z > 18.0);
if (__pyx_t_6) {
/* "sklearn/linear_model/sgd_fast.pyx":205
* # approximately equal and saves the computation of the log
* if z > 18:
* return exp(-z) # <<<<<<<<<<<<<<
* if z < -18:
* return -z
*/
__pyx_r = exp((-__pyx_v_z));
goto __pyx_L0;
goto __pyx_L3;
}
__pyx_L3:;
/* "sklearn/linear_model/sgd_fast.pyx":206
* if z > 18:
* return exp(-z)
* if z < -18: # <<<<<<<<<<<<<<
* return -z
* return log(1.0 + exp(-z))
*/
__pyx_t_6 = (__pyx_v_z < -18.0);
if (__pyx_t_6) {
/* "sklearn/linear_model/sgd_fast.pyx":207
* return exp(-z)
* if z < -18:
* return -z # <<<<<<<<<<<<<<
* return log(1.0 + exp(-z))
*
*/
__pyx_r = (-__pyx_v_z);
goto __pyx_L0;
goto __pyx_L4;
}
__pyx_L4:;
/* "sklearn/linear_model/sgd_fast.pyx":208
* if z < -18:
* return -z
* return log(1.0 + exp(-z)) # <<<<<<<<<<<<<<
*
* cpdef double dloss(self, double p, double y):
*/
__pyx_r = log((1.0 + exp((-__pyx_v_z))));
goto __pyx_L0;
__pyx_r = 0;
goto __pyx_L0;
__pyx_L1_error:;
__Pyx_XDECREF(__pyx_t_1);
__Pyx_XDECREF(__pyx_t_2);
__Pyx_XDECREF(__pyx_t_3);
__Pyx_XDECREF(__pyx_t_4);
__Pyx_WriteUnraisable("sklearn.linear_model.sgd_fast.Log.loss", __pyx_clineno, __pyx_lineno, __pyx_filename);
__pyx_r = 0;
__pyx_L0:;
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* Python wrapper */
static PyObject *__pyx_pw_7sklearn_12linear_model_8sgd_fast_3Log_1loss(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/
static PyObject *__pyx_pw_7sklearn_12linear_model_8sgd_fast_3Log_1loss(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds) {
double __pyx_v_p;
double __pyx_v_y;
PyObject *__pyx_r = 0;
__Pyx_RefNannyDeclarations
__Pyx_RefNannySetupContext("loss (wrapper)", 0);
{
static PyObject **__pyx_pyargnames[] = {&__pyx_n_s__p,&__pyx_n_s__y,0};
PyObject* values[2] = {0,0};
if (unlikely(__pyx_kwds)) {
Py_ssize_t kw_args;
const Py_ssize_t pos_args = PyTuple_GET_SIZE(__pyx_args);
switch (pos_args) {
case 2: values[1] = PyTuple_GET_ITEM(__pyx_args, 1);
case 1: values[0] = PyTuple_GET_ITEM(__pyx_args, 0);
case 0: break;
default: goto __pyx_L5_argtuple_error;
}
kw_args = PyDict_Size(__pyx_kwds);
switch (pos_args) {
case 0:
if (likely((values[0] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__p)) != 0)) kw_args--;
else goto __pyx_L5_argtuple_error;
case 1:
if (likely((values[1] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__y)) != 0)) kw_args--;
else {
__Pyx_RaiseArgtupleInvalid("loss", 1, 2, 2, 1); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 201; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
}
if (unlikely(kw_args > 0)) {
if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, pos_args, "loss") < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 201; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
} else if (PyTuple_GET_SIZE(__pyx_args) != 2) {
goto __pyx_L5_argtuple_error;
} else {
values[0] = PyTuple_GET_ITEM(__pyx_args, 0);
values[1] = PyTuple_GET_ITEM(__pyx_args, 1);
}
__pyx_v_p = __pyx_PyFloat_AsDouble(values[0]); if (unlikely((__pyx_v_p == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 201; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
__pyx_v_y = __pyx_PyFloat_AsDouble(values[1]); if (unlikely((__pyx_v_y == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 201; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
goto __pyx_L4_argument_unpacking_done;
__pyx_L5_argtuple_error:;
__Pyx_RaiseArgtupleInvalid("loss", 1, 2, 2, PyTuple_GET_SIZE(__pyx_args)); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 201; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
__pyx_L3_error:;
__Pyx_AddTraceback("sklearn.linear_model.sgd_fast.Log.loss", __pyx_clineno, __pyx_lineno, __pyx_filename);
__Pyx_RefNannyFinishContext();
return NULL;
__pyx_L4_argument_unpacking_done:;
__pyx_r = __pyx_pf_7sklearn_12linear_model_8sgd_fast_3Log_loss(((struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_Log *)__pyx_v_self), __pyx_v_p, __pyx_v_y);
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* "sklearn/linear_model/sgd_fast.pyx":201
* """Logistic regression loss for binary classification with y in {-1, 1}"""
*
* cpdef double loss(self, double p, double y): # <<<<<<<<<<<<<<
* cdef double z = p * y
* # approximately equal and saves the computation of the log
*/
static PyObject *__pyx_pf_7sklearn_12linear_model_8sgd_fast_3Log_loss(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_Log *__pyx_v_self, double __pyx_v_p, double __pyx_v_y) {
PyObject *__pyx_r = NULL;
__Pyx_RefNannyDeclarations
PyObject *__pyx_t_1 = NULL;
int __pyx_lineno = 0;
const char *__pyx_filename = NULL;
int __pyx_clineno = 0;
__Pyx_RefNannySetupContext("loss", 0);
__Pyx_XDECREF(__pyx_r);
__pyx_t_1 = PyFloat_FromDouble(((struct __pyx_vtabstruct_7sklearn_12linear_model_8sgd_fast_Log *)__pyx_v_self->__pyx_base.__pyx_base.__pyx_vtab)->__pyx_base.__pyx_base.loss(((struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_LossFunction *)__pyx_v_self), __pyx_v_p, __pyx_v_y, 1)); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 201; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_1);
__pyx_r = __pyx_t_1;
__pyx_t_1 = 0;
goto __pyx_L0;
__pyx_r = Py_None; __Pyx_INCREF(Py_None);
goto __pyx_L0;
__pyx_L1_error:;
__Pyx_XDECREF(__pyx_t_1);
__Pyx_AddTraceback("sklearn.linear_model.sgd_fast.Log.loss", __pyx_clineno, __pyx_lineno, __pyx_filename);
__pyx_r = NULL;
__pyx_L0:;
__Pyx_XGIVEREF(__pyx_r);
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* "sklearn/linear_model/sgd_fast.pyx":210
* return log(1.0 + exp(-z))
*
* cpdef double dloss(self, double p, double y): # <<<<<<<<<<<<<<
* cdef double z = p * y
* # approximately equal and saves the computation of the log
*/
static PyObject *__pyx_pw_7sklearn_12linear_model_8sgd_fast_3Log_3dloss(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/
static double __pyx_f_7sklearn_12linear_model_8sgd_fast_3Log_dloss(CYTHON_UNUSED struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_Log *__pyx_v_self, double __pyx_v_p, double __pyx_v_y, int __pyx_skip_dispatch) {
double __pyx_v_z;
double __pyx_r;
__Pyx_RefNannyDeclarations
PyObject *__pyx_t_1 = NULL;
PyObject *__pyx_t_2 = NULL;
PyObject *__pyx_t_3 = NULL;
PyObject *__pyx_t_4 = NULL;
double __pyx_t_5;
int __pyx_t_6;
int __pyx_lineno = 0;
const char *__pyx_filename = NULL;
int __pyx_clineno = 0;
__Pyx_RefNannySetupContext("dloss", 0);
/* Check if called by wrapper */
if (unlikely(__pyx_skip_dispatch)) ;
/* Check if overriden in Python */
else if (unlikely(Py_TYPE(((PyObject *)__pyx_v_self))->tp_dictoffset != 0)) {
__pyx_t_1 = PyObject_GetAttr(((PyObject *)__pyx_v_self), __pyx_n_s__dloss); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 210; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_1);
if (!PyCFunction_Check(__pyx_t_1) || (PyCFunction_GET_FUNCTION(__pyx_t_1) != (PyCFunction)__pyx_pw_7sklearn_12linear_model_8sgd_fast_3Log_3dloss)) {
__pyx_t_2 = PyFloat_FromDouble(__pyx_v_p); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 210; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_2);
__pyx_t_3 = PyFloat_FromDouble(__pyx_v_y); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 210; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_3);
__pyx_t_4 = PyTuple_New(2); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 210; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_4);
PyTuple_SET_ITEM(__pyx_t_4, 0, __pyx_t_2);
__Pyx_GIVEREF(__pyx_t_2);
PyTuple_SET_ITEM(__pyx_t_4, 1, __pyx_t_3);
__Pyx_GIVEREF(__pyx_t_3);
__pyx_t_2 = 0;
__pyx_t_3 = 0;
__pyx_t_3 = PyObject_Call(__pyx_t_1, ((PyObject *)__pyx_t_4), NULL); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 210; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_3);
__Pyx_DECREF(((PyObject *)__pyx_t_4)); __pyx_t_4 = 0;
__pyx_t_5 = __pyx_PyFloat_AsDouble(__pyx_t_3); if (unlikely((__pyx_t_5 == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 210; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0;
__pyx_r = __pyx_t_5;
__Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0;
goto __pyx_L0;
}
__Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0;
}
/* "sklearn/linear_model/sgd_fast.pyx":211
*
* cpdef double dloss(self, double p, double y):
* cdef double z = p * y # <<<<<<<<<<<<<<
* # approximately equal and saves the computation of the log
* if z > 18.0:
*/
__pyx_v_z = (__pyx_v_p * __pyx_v_y);
/* "sklearn/linear_model/sgd_fast.pyx":213
* cdef double z = p * y
* # approximately equal and saves the computation of the log
* if z > 18.0: # <<<<<<<<<<<<<<
* return exp(-z) * -y
* if z < -18.0:
*/
__pyx_t_6 = (__pyx_v_z > 18.0);
if (__pyx_t_6) {
/* "sklearn/linear_model/sgd_fast.pyx":214
* # approximately equal and saves the computation of the log
* if z > 18.0:
* return exp(-z) * -y # <<<<<<<<<<<<<<
* if z < -18.0:
* return -y
*/
__pyx_r = (exp((-__pyx_v_z)) * (-__pyx_v_y));
goto __pyx_L0;
goto __pyx_L3;
}
__pyx_L3:;
/* "sklearn/linear_model/sgd_fast.pyx":215
* if z > 18.0:
* return exp(-z) * -y
* if z < -18.0: # <<<<<<<<<<<<<<
* return -y
* return -y / (exp(z) + 1.0)
*/
__pyx_t_6 = (__pyx_v_z < -18.0);
if (__pyx_t_6) {
/* "sklearn/linear_model/sgd_fast.pyx":216
* return exp(-z) * -y
* if z < -18.0:
* return -y # <<<<<<<<<<<<<<
* return -y / (exp(z) + 1.0)
*
*/
__pyx_r = (-__pyx_v_y);
goto __pyx_L0;
goto __pyx_L4;
}
__pyx_L4:;
/* "sklearn/linear_model/sgd_fast.pyx":217
* if z < -18.0:
* return -y
* return -y / (exp(z) + 1.0) # <<<<<<<<<<<<<<
*
* def __reduce__(self):
*/
__pyx_r = ((-__pyx_v_y) / (exp(__pyx_v_z) + 1.0));
goto __pyx_L0;
__pyx_r = 0;
goto __pyx_L0;
__pyx_L1_error:;
__Pyx_XDECREF(__pyx_t_1);
__Pyx_XDECREF(__pyx_t_2);
__Pyx_XDECREF(__pyx_t_3);
__Pyx_XDECREF(__pyx_t_4);
__Pyx_WriteUnraisable("sklearn.linear_model.sgd_fast.Log.dloss", __pyx_clineno, __pyx_lineno, __pyx_filename);
__pyx_r = 0;
__pyx_L0:;
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* Python wrapper */
static PyObject *__pyx_pw_7sklearn_12linear_model_8sgd_fast_3Log_3dloss(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/
static PyObject *__pyx_pw_7sklearn_12linear_model_8sgd_fast_3Log_3dloss(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds) {
double __pyx_v_p;
double __pyx_v_y;
PyObject *__pyx_r = 0;
__Pyx_RefNannyDeclarations
__Pyx_RefNannySetupContext("dloss (wrapper)", 0);
{
static PyObject **__pyx_pyargnames[] = {&__pyx_n_s__p,&__pyx_n_s__y,0};
PyObject* values[2] = {0,0};
if (unlikely(__pyx_kwds)) {
Py_ssize_t kw_args;
const Py_ssize_t pos_args = PyTuple_GET_SIZE(__pyx_args);
switch (pos_args) {
case 2: values[1] = PyTuple_GET_ITEM(__pyx_args, 1);
case 1: values[0] = PyTuple_GET_ITEM(__pyx_args, 0);
case 0: break;
default: goto __pyx_L5_argtuple_error;
}
kw_args = PyDict_Size(__pyx_kwds);
switch (pos_args) {
case 0:
if (likely((values[0] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__p)) != 0)) kw_args--;
else goto __pyx_L5_argtuple_error;
case 1:
if (likely((values[1] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__y)) != 0)) kw_args--;
else {
__Pyx_RaiseArgtupleInvalid("dloss", 1, 2, 2, 1); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 210; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
}
if (unlikely(kw_args > 0)) {
if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, pos_args, "dloss") < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 210; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
} else if (PyTuple_GET_SIZE(__pyx_args) != 2) {
goto __pyx_L5_argtuple_error;
} else {
values[0] = PyTuple_GET_ITEM(__pyx_args, 0);
values[1] = PyTuple_GET_ITEM(__pyx_args, 1);
}
__pyx_v_p = __pyx_PyFloat_AsDouble(values[0]); if (unlikely((__pyx_v_p == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 210; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
__pyx_v_y = __pyx_PyFloat_AsDouble(values[1]); if (unlikely((__pyx_v_y == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 210; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
goto __pyx_L4_argument_unpacking_done;
__pyx_L5_argtuple_error:;
__Pyx_RaiseArgtupleInvalid("dloss", 1, 2, 2, PyTuple_GET_SIZE(__pyx_args)); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 210; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
__pyx_L3_error:;
__Pyx_AddTraceback("sklearn.linear_model.sgd_fast.Log.dloss", __pyx_clineno, __pyx_lineno, __pyx_filename);
__Pyx_RefNannyFinishContext();
return NULL;
__pyx_L4_argument_unpacking_done:;
__pyx_r = __pyx_pf_7sklearn_12linear_model_8sgd_fast_3Log_2dloss(((struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_Log *)__pyx_v_self), __pyx_v_p, __pyx_v_y);
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* "sklearn/linear_model/sgd_fast.pyx":210
* return log(1.0 + exp(-z))
*
* cpdef double dloss(self, double p, double y): # <<<<<<<<<<<<<<
* cdef double z = p * y
* # approximately equal and saves the computation of the log
*/
static PyObject *__pyx_pf_7sklearn_12linear_model_8sgd_fast_3Log_2dloss(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_Log *__pyx_v_self, double __pyx_v_p, double __pyx_v_y) {
PyObject *__pyx_r = NULL;
__Pyx_RefNannyDeclarations
PyObject *__pyx_t_1 = NULL;
int __pyx_lineno = 0;
const char *__pyx_filename = NULL;
int __pyx_clineno = 0;
__Pyx_RefNannySetupContext("dloss", 0);
__Pyx_XDECREF(__pyx_r);
__pyx_t_1 = PyFloat_FromDouble(((struct __pyx_vtabstruct_7sklearn_12linear_model_8sgd_fast_Log *)__pyx_v_self->__pyx_base.__pyx_base.__pyx_vtab)->__pyx_base.__pyx_base.dloss(((struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_LossFunction *)__pyx_v_self), __pyx_v_p, __pyx_v_y, 1)); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 210; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_1);
__pyx_r = __pyx_t_1;
__pyx_t_1 = 0;
goto __pyx_L0;
__pyx_r = Py_None; __Pyx_INCREF(Py_None);
goto __pyx_L0;
__pyx_L1_error:;
__Pyx_XDECREF(__pyx_t_1);
__Pyx_AddTraceback("sklearn.linear_model.sgd_fast.Log.dloss", __pyx_clineno, __pyx_lineno, __pyx_filename);
__pyx_r = NULL;
__pyx_L0:;
__Pyx_XGIVEREF(__pyx_r);
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* Python wrapper */
static PyObject *__pyx_pw_7sklearn_12linear_model_8sgd_fast_3Log_5__reduce__(PyObject *__pyx_v_self, CYTHON_UNUSED PyObject *unused); /*proto*/
static PyObject *__pyx_pw_7sklearn_12linear_model_8sgd_fast_3Log_5__reduce__(PyObject *__pyx_v_self, CYTHON_UNUSED PyObject *unused) {
PyObject *__pyx_r = 0;
__Pyx_RefNannyDeclarations
__Pyx_RefNannySetupContext("__reduce__ (wrapper)", 0);
__pyx_r = __pyx_pf_7sklearn_12linear_model_8sgd_fast_3Log_4__reduce__(((struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_Log *)__pyx_v_self));
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* "sklearn/linear_model/sgd_fast.pyx":219
* return -y / (exp(z) + 1.0)
*
* def __reduce__(self): # <<<<<<<<<<<<<<
* return Log, ()
*
*/
static PyObject *__pyx_pf_7sklearn_12linear_model_8sgd_fast_3Log_4__reduce__(CYTHON_UNUSED struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_Log *__pyx_v_self) {
PyObject *__pyx_r = NULL;
__Pyx_RefNannyDeclarations
PyObject *__pyx_t_1 = NULL;
int __pyx_lineno = 0;
const char *__pyx_filename = NULL;
int __pyx_clineno = 0;
__Pyx_RefNannySetupContext("__reduce__", 0);
/* "sklearn/linear_model/sgd_fast.pyx":220
*
* def __reduce__(self):
* return Log, () # <<<<<<<<<<<<<<
*
*
*/
__Pyx_XDECREF(__pyx_r);
__pyx_t_1 = PyTuple_New(2); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 220; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_1);
__Pyx_INCREF(((PyObject *)((PyObject*)__pyx_ptype_7sklearn_12linear_model_8sgd_fast_Log)));
PyTuple_SET_ITEM(__pyx_t_1, 0, ((PyObject *)((PyObject*)__pyx_ptype_7sklearn_12linear_model_8sgd_fast_Log)));
__Pyx_GIVEREF(((PyObject *)((PyObject*)__pyx_ptype_7sklearn_12linear_model_8sgd_fast_Log)));
__Pyx_INCREF(((PyObject *)__pyx_empty_tuple));
PyTuple_SET_ITEM(__pyx_t_1, 1, ((PyObject *)__pyx_empty_tuple));
__Pyx_GIVEREF(((PyObject *)__pyx_empty_tuple));
__pyx_r = ((PyObject *)__pyx_t_1);
__pyx_t_1 = 0;
goto __pyx_L0;
__pyx_r = Py_None; __Pyx_INCREF(Py_None);
goto __pyx_L0;
__pyx_L1_error:;
__Pyx_XDECREF(__pyx_t_1);
__Pyx_AddTraceback("sklearn.linear_model.sgd_fast.Log.__reduce__", __pyx_clineno, __pyx_lineno, __pyx_filename);
__pyx_r = NULL;
__pyx_L0:;
__Pyx_XGIVEREF(__pyx_r);
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* "sklearn/linear_model/sgd_fast.pyx":225
* cdef class SquaredLoss(Regression):
* """Squared loss traditional used in linear regression."""
* cpdef double loss(self, double p, double y): # <<<<<<<<<<<<<<
* return 0.5 * (p - y) * (p - y)
*
*/
static PyObject *__pyx_pw_7sklearn_12linear_model_8sgd_fast_11SquaredLoss_1loss(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/
static double __pyx_f_7sklearn_12linear_model_8sgd_fast_11SquaredLoss_loss(CYTHON_UNUSED struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_SquaredLoss *__pyx_v_self, double __pyx_v_p, double __pyx_v_y, int __pyx_skip_dispatch) {
double __pyx_r;
__Pyx_RefNannyDeclarations
PyObject *__pyx_t_1 = NULL;
PyObject *__pyx_t_2 = NULL;
PyObject *__pyx_t_3 = NULL;
PyObject *__pyx_t_4 = NULL;
double __pyx_t_5;
int __pyx_lineno = 0;
const char *__pyx_filename = NULL;
int __pyx_clineno = 0;
__Pyx_RefNannySetupContext("loss", 0);
/* Check if called by wrapper */
if (unlikely(__pyx_skip_dispatch)) ;
/* Check if overriden in Python */
else if (unlikely(Py_TYPE(((PyObject *)__pyx_v_self))->tp_dictoffset != 0)) {
__pyx_t_1 = PyObject_GetAttr(((PyObject *)__pyx_v_self), __pyx_n_s__loss); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 225; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_1);
if (!PyCFunction_Check(__pyx_t_1) || (PyCFunction_GET_FUNCTION(__pyx_t_1) != (PyCFunction)__pyx_pw_7sklearn_12linear_model_8sgd_fast_11SquaredLoss_1loss)) {
__pyx_t_2 = PyFloat_FromDouble(__pyx_v_p); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 225; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_2);
__pyx_t_3 = PyFloat_FromDouble(__pyx_v_y); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 225; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_3);
__pyx_t_4 = PyTuple_New(2); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 225; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_4);
PyTuple_SET_ITEM(__pyx_t_4, 0, __pyx_t_2);
__Pyx_GIVEREF(__pyx_t_2);
PyTuple_SET_ITEM(__pyx_t_4, 1, __pyx_t_3);
__Pyx_GIVEREF(__pyx_t_3);
__pyx_t_2 = 0;
__pyx_t_3 = 0;
__pyx_t_3 = PyObject_Call(__pyx_t_1, ((PyObject *)__pyx_t_4), NULL); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 225; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_3);
__Pyx_DECREF(((PyObject *)__pyx_t_4)); __pyx_t_4 = 0;
__pyx_t_5 = __pyx_PyFloat_AsDouble(__pyx_t_3); if (unlikely((__pyx_t_5 == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 225; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0;
__pyx_r = __pyx_t_5;
__Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0;
goto __pyx_L0;
}
__Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0;
}
/* "sklearn/linear_model/sgd_fast.pyx":226
* """Squared loss traditional used in linear regression."""
* cpdef double loss(self, double p, double y):
* return 0.5 * (p - y) * (p - y) # <<<<<<<<<<<<<<
*
* cpdef double dloss(self, double p, double y):
*/
__pyx_r = ((0.5 * (__pyx_v_p - __pyx_v_y)) * (__pyx_v_p - __pyx_v_y));
goto __pyx_L0;
__pyx_r = 0;
goto __pyx_L0;
__pyx_L1_error:;
__Pyx_XDECREF(__pyx_t_1);
__Pyx_XDECREF(__pyx_t_2);
__Pyx_XDECREF(__pyx_t_3);
__Pyx_XDECREF(__pyx_t_4);
__Pyx_WriteUnraisable("sklearn.linear_model.sgd_fast.SquaredLoss.loss", __pyx_clineno, __pyx_lineno, __pyx_filename);
__pyx_r = 0;
__pyx_L0:;
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* Python wrapper */
static PyObject *__pyx_pw_7sklearn_12linear_model_8sgd_fast_11SquaredLoss_1loss(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/
static PyObject *__pyx_pw_7sklearn_12linear_model_8sgd_fast_11SquaredLoss_1loss(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds) {
double __pyx_v_p;
double __pyx_v_y;
PyObject *__pyx_r = 0;
__Pyx_RefNannyDeclarations
__Pyx_RefNannySetupContext("loss (wrapper)", 0);
{
static PyObject **__pyx_pyargnames[] = {&__pyx_n_s__p,&__pyx_n_s__y,0};
PyObject* values[2] = {0,0};
if (unlikely(__pyx_kwds)) {
Py_ssize_t kw_args;
const Py_ssize_t pos_args = PyTuple_GET_SIZE(__pyx_args);
switch (pos_args) {
case 2: values[1] = PyTuple_GET_ITEM(__pyx_args, 1);
case 1: values[0] = PyTuple_GET_ITEM(__pyx_args, 0);
case 0: break;
default: goto __pyx_L5_argtuple_error;
}
kw_args = PyDict_Size(__pyx_kwds);
switch (pos_args) {
case 0:
if (likely((values[0] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__p)) != 0)) kw_args--;
else goto __pyx_L5_argtuple_error;
case 1:
if (likely((values[1] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__y)) != 0)) kw_args--;
else {
__Pyx_RaiseArgtupleInvalid("loss", 1, 2, 2, 1); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 225; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
}
if (unlikely(kw_args > 0)) {
if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, pos_args, "loss") < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 225; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
} else if (PyTuple_GET_SIZE(__pyx_args) != 2) {
goto __pyx_L5_argtuple_error;
} else {
values[0] = PyTuple_GET_ITEM(__pyx_args, 0);
values[1] = PyTuple_GET_ITEM(__pyx_args, 1);
}
__pyx_v_p = __pyx_PyFloat_AsDouble(values[0]); if (unlikely((__pyx_v_p == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 225; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
__pyx_v_y = __pyx_PyFloat_AsDouble(values[1]); if (unlikely((__pyx_v_y == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 225; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
goto __pyx_L4_argument_unpacking_done;
__pyx_L5_argtuple_error:;
__Pyx_RaiseArgtupleInvalid("loss", 1, 2, 2, PyTuple_GET_SIZE(__pyx_args)); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 225; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
__pyx_L3_error:;
__Pyx_AddTraceback("sklearn.linear_model.sgd_fast.SquaredLoss.loss", __pyx_clineno, __pyx_lineno, __pyx_filename);
__Pyx_RefNannyFinishContext();
return NULL;
__pyx_L4_argument_unpacking_done:;
__pyx_r = __pyx_pf_7sklearn_12linear_model_8sgd_fast_11SquaredLoss_loss(((struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_SquaredLoss *)__pyx_v_self), __pyx_v_p, __pyx_v_y);
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* "sklearn/linear_model/sgd_fast.pyx":225
* cdef class SquaredLoss(Regression):
* """Squared loss traditional used in linear regression."""
* cpdef double loss(self, double p, double y): # <<<<<<<<<<<<<<
* return 0.5 * (p - y) * (p - y)
*
*/
static PyObject *__pyx_pf_7sklearn_12linear_model_8sgd_fast_11SquaredLoss_loss(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_SquaredLoss *__pyx_v_self, double __pyx_v_p, double __pyx_v_y) {
PyObject *__pyx_r = NULL;
__Pyx_RefNannyDeclarations
PyObject *__pyx_t_1 = NULL;
int __pyx_lineno = 0;
const char *__pyx_filename = NULL;
int __pyx_clineno = 0;
__Pyx_RefNannySetupContext("loss", 0);
__Pyx_XDECREF(__pyx_r);
__pyx_t_1 = PyFloat_FromDouble(((struct __pyx_vtabstruct_7sklearn_12linear_model_8sgd_fast_SquaredLoss *)__pyx_v_self->__pyx_base.__pyx_base.__pyx_vtab)->__pyx_base.__pyx_base.loss(((struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_LossFunction *)__pyx_v_self), __pyx_v_p, __pyx_v_y, 1)); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 225; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_1);
__pyx_r = __pyx_t_1;
__pyx_t_1 = 0;
goto __pyx_L0;
__pyx_r = Py_None; __Pyx_INCREF(Py_None);
goto __pyx_L0;
__pyx_L1_error:;
__Pyx_XDECREF(__pyx_t_1);
__Pyx_AddTraceback("sklearn.linear_model.sgd_fast.SquaredLoss.loss", __pyx_clineno, __pyx_lineno, __pyx_filename);
__pyx_r = NULL;
__pyx_L0:;
__Pyx_XGIVEREF(__pyx_r);
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* "sklearn/linear_model/sgd_fast.pyx":228
* return 0.5 * (p - y) * (p - y)
*
* cpdef double dloss(self, double p, double y): # <<<<<<<<<<<<<<
* return p - y
*
*/
static PyObject *__pyx_pw_7sklearn_12linear_model_8sgd_fast_11SquaredLoss_3dloss(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/
static double __pyx_f_7sklearn_12linear_model_8sgd_fast_11SquaredLoss_dloss(CYTHON_UNUSED struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_SquaredLoss *__pyx_v_self, double __pyx_v_p, double __pyx_v_y, int __pyx_skip_dispatch) {
double __pyx_r;
__Pyx_RefNannyDeclarations
PyObject *__pyx_t_1 = NULL;
PyObject *__pyx_t_2 = NULL;
PyObject *__pyx_t_3 = NULL;
PyObject *__pyx_t_4 = NULL;
double __pyx_t_5;
int __pyx_lineno = 0;
const char *__pyx_filename = NULL;
int __pyx_clineno = 0;
__Pyx_RefNannySetupContext("dloss", 0);
/* Check if called by wrapper */
if (unlikely(__pyx_skip_dispatch)) ;
/* Check if overriden in Python */
else if (unlikely(Py_TYPE(((PyObject *)__pyx_v_self))->tp_dictoffset != 0)) {
__pyx_t_1 = PyObject_GetAttr(((PyObject *)__pyx_v_self), __pyx_n_s__dloss); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 228; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_1);
if (!PyCFunction_Check(__pyx_t_1) || (PyCFunction_GET_FUNCTION(__pyx_t_1) != (PyCFunction)__pyx_pw_7sklearn_12linear_model_8sgd_fast_11SquaredLoss_3dloss)) {
__pyx_t_2 = PyFloat_FromDouble(__pyx_v_p); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 228; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_2);
__pyx_t_3 = PyFloat_FromDouble(__pyx_v_y); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 228; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_3);
__pyx_t_4 = PyTuple_New(2); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 228; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_4);
PyTuple_SET_ITEM(__pyx_t_4, 0, __pyx_t_2);
__Pyx_GIVEREF(__pyx_t_2);
PyTuple_SET_ITEM(__pyx_t_4, 1, __pyx_t_3);
__Pyx_GIVEREF(__pyx_t_3);
__pyx_t_2 = 0;
__pyx_t_3 = 0;
__pyx_t_3 = PyObject_Call(__pyx_t_1, ((PyObject *)__pyx_t_4), NULL); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 228; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_3);
__Pyx_DECREF(((PyObject *)__pyx_t_4)); __pyx_t_4 = 0;
__pyx_t_5 = __pyx_PyFloat_AsDouble(__pyx_t_3); if (unlikely((__pyx_t_5 == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 228; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0;
__pyx_r = __pyx_t_5;
__Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0;
goto __pyx_L0;
}
__Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0;
}
/* "sklearn/linear_model/sgd_fast.pyx":229
*
* cpdef double dloss(self, double p, double y):
* return p - y # <<<<<<<<<<<<<<
*
* def __reduce__(self):
*/
__pyx_r = (__pyx_v_p - __pyx_v_y);
goto __pyx_L0;
__pyx_r = 0;
goto __pyx_L0;
__pyx_L1_error:;
__Pyx_XDECREF(__pyx_t_1);
__Pyx_XDECREF(__pyx_t_2);
__Pyx_XDECREF(__pyx_t_3);
__Pyx_XDECREF(__pyx_t_4);
__Pyx_WriteUnraisable("sklearn.linear_model.sgd_fast.SquaredLoss.dloss", __pyx_clineno, __pyx_lineno, __pyx_filename);
__pyx_r = 0;
__pyx_L0:;
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* Python wrapper */
static PyObject *__pyx_pw_7sklearn_12linear_model_8sgd_fast_11SquaredLoss_3dloss(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/
static PyObject *__pyx_pw_7sklearn_12linear_model_8sgd_fast_11SquaredLoss_3dloss(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds) {
double __pyx_v_p;
double __pyx_v_y;
PyObject *__pyx_r = 0;
__Pyx_RefNannyDeclarations
__Pyx_RefNannySetupContext("dloss (wrapper)", 0);
{
static PyObject **__pyx_pyargnames[] = {&__pyx_n_s__p,&__pyx_n_s__y,0};
PyObject* values[2] = {0,0};
if (unlikely(__pyx_kwds)) {
Py_ssize_t kw_args;
const Py_ssize_t pos_args = PyTuple_GET_SIZE(__pyx_args);
switch (pos_args) {
case 2: values[1] = PyTuple_GET_ITEM(__pyx_args, 1);
case 1: values[0] = PyTuple_GET_ITEM(__pyx_args, 0);
case 0: break;
default: goto __pyx_L5_argtuple_error;
}
kw_args = PyDict_Size(__pyx_kwds);
switch (pos_args) {
case 0:
if (likely((values[0] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__p)) != 0)) kw_args--;
else goto __pyx_L5_argtuple_error;
case 1:
if (likely((values[1] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__y)) != 0)) kw_args--;
else {
__Pyx_RaiseArgtupleInvalid("dloss", 1, 2, 2, 1); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 228; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
}
if (unlikely(kw_args > 0)) {
if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, pos_args, "dloss") < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 228; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
} else if (PyTuple_GET_SIZE(__pyx_args) != 2) {
goto __pyx_L5_argtuple_error;
} else {
values[0] = PyTuple_GET_ITEM(__pyx_args, 0);
values[1] = PyTuple_GET_ITEM(__pyx_args, 1);
}
__pyx_v_p = __pyx_PyFloat_AsDouble(values[0]); if (unlikely((__pyx_v_p == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 228; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
__pyx_v_y = __pyx_PyFloat_AsDouble(values[1]); if (unlikely((__pyx_v_y == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 228; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
goto __pyx_L4_argument_unpacking_done;
__pyx_L5_argtuple_error:;
__Pyx_RaiseArgtupleInvalid("dloss", 1, 2, 2, PyTuple_GET_SIZE(__pyx_args)); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 228; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
__pyx_L3_error:;
__Pyx_AddTraceback("sklearn.linear_model.sgd_fast.SquaredLoss.dloss", __pyx_clineno, __pyx_lineno, __pyx_filename);
__Pyx_RefNannyFinishContext();
return NULL;
__pyx_L4_argument_unpacking_done:;
__pyx_r = __pyx_pf_7sklearn_12linear_model_8sgd_fast_11SquaredLoss_2dloss(((struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_SquaredLoss *)__pyx_v_self), __pyx_v_p, __pyx_v_y);
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* "sklearn/linear_model/sgd_fast.pyx":228
* return 0.5 * (p - y) * (p - y)
*
* cpdef double dloss(self, double p, double y): # <<<<<<<<<<<<<<
* return p - y
*
*/
static PyObject *__pyx_pf_7sklearn_12linear_model_8sgd_fast_11SquaredLoss_2dloss(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_SquaredLoss *__pyx_v_self, double __pyx_v_p, double __pyx_v_y) {
PyObject *__pyx_r = NULL;
__Pyx_RefNannyDeclarations
PyObject *__pyx_t_1 = NULL;
int __pyx_lineno = 0;
const char *__pyx_filename = NULL;
int __pyx_clineno = 0;
__Pyx_RefNannySetupContext("dloss", 0);
__Pyx_XDECREF(__pyx_r);
__pyx_t_1 = PyFloat_FromDouble(((struct __pyx_vtabstruct_7sklearn_12linear_model_8sgd_fast_SquaredLoss *)__pyx_v_self->__pyx_base.__pyx_base.__pyx_vtab)->__pyx_base.__pyx_base.dloss(((struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_LossFunction *)__pyx_v_self), __pyx_v_p, __pyx_v_y, 1)); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 228; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_1);
__pyx_r = __pyx_t_1;
__pyx_t_1 = 0;
goto __pyx_L0;
__pyx_r = Py_None; __Pyx_INCREF(Py_None);
goto __pyx_L0;
__pyx_L1_error:;
__Pyx_XDECREF(__pyx_t_1);
__Pyx_AddTraceback("sklearn.linear_model.sgd_fast.SquaredLoss.dloss", __pyx_clineno, __pyx_lineno, __pyx_filename);
__pyx_r = NULL;
__pyx_L0:;
__Pyx_XGIVEREF(__pyx_r);
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* Python wrapper */
static PyObject *__pyx_pw_7sklearn_12linear_model_8sgd_fast_11SquaredLoss_5__reduce__(PyObject *__pyx_v_self, CYTHON_UNUSED PyObject *unused); /*proto*/
static PyObject *__pyx_pw_7sklearn_12linear_model_8sgd_fast_11SquaredLoss_5__reduce__(PyObject *__pyx_v_self, CYTHON_UNUSED PyObject *unused) {
PyObject *__pyx_r = 0;
__Pyx_RefNannyDeclarations
__Pyx_RefNannySetupContext("__reduce__ (wrapper)", 0);
__pyx_r = __pyx_pf_7sklearn_12linear_model_8sgd_fast_11SquaredLoss_4__reduce__(((struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_SquaredLoss *)__pyx_v_self));
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* "sklearn/linear_model/sgd_fast.pyx":231
* return p - y
*
* def __reduce__(self): # <<<<<<<<<<<<<<
* return SquaredLoss, ()
*
*/
static PyObject *__pyx_pf_7sklearn_12linear_model_8sgd_fast_11SquaredLoss_4__reduce__(CYTHON_UNUSED struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_SquaredLoss *__pyx_v_self) {
PyObject *__pyx_r = NULL;
__Pyx_RefNannyDeclarations
PyObject *__pyx_t_1 = NULL;
int __pyx_lineno = 0;
const char *__pyx_filename = NULL;
int __pyx_clineno = 0;
__Pyx_RefNannySetupContext("__reduce__", 0);
/* "sklearn/linear_model/sgd_fast.pyx":232
*
* def __reduce__(self):
* return SquaredLoss, () # <<<<<<<<<<<<<<
*
*
*/
__Pyx_XDECREF(__pyx_r);
__pyx_t_1 = PyTuple_New(2); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 232; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_1);
__Pyx_INCREF(((PyObject *)((PyObject*)__pyx_ptype_7sklearn_12linear_model_8sgd_fast_SquaredLoss)));
PyTuple_SET_ITEM(__pyx_t_1, 0, ((PyObject *)((PyObject*)__pyx_ptype_7sklearn_12linear_model_8sgd_fast_SquaredLoss)));
__Pyx_GIVEREF(((PyObject *)((PyObject*)__pyx_ptype_7sklearn_12linear_model_8sgd_fast_SquaredLoss)));
__Pyx_INCREF(((PyObject *)__pyx_empty_tuple));
PyTuple_SET_ITEM(__pyx_t_1, 1, ((PyObject *)__pyx_empty_tuple));
__Pyx_GIVEREF(((PyObject *)__pyx_empty_tuple));
__pyx_r = ((PyObject *)__pyx_t_1);
__pyx_t_1 = 0;
goto __pyx_L0;
__pyx_r = Py_None; __Pyx_INCREF(Py_None);
goto __pyx_L0;
__pyx_L1_error:;
__Pyx_XDECREF(__pyx_t_1);
__Pyx_AddTraceback("sklearn.linear_model.sgd_fast.SquaredLoss.__reduce__", __pyx_clineno, __pyx_lineno, __pyx_filename);
__pyx_r = NULL;
__pyx_L0:;
__Pyx_XGIVEREF(__pyx_r);
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* Python wrapper */
static int __pyx_pw_7sklearn_12linear_model_8sgd_fast_5Huber_1__init__(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/
static int __pyx_pw_7sklearn_12linear_model_8sgd_fast_5Huber_1__init__(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds) {
double __pyx_v_c;
int __pyx_r;
__Pyx_RefNannyDeclarations
__Pyx_RefNannySetupContext("__init__ (wrapper)", 0);
{
static PyObject **__pyx_pyargnames[] = {&__pyx_n_s__c,0};
PyObject* values[1] = {0};
if (unlikely(__pyx_kwds)) {
Py_ssize_t kw_args;
const Py_ssize_t pos_args = PyTuple_GET_SIZE(__pyx_args);
switch (pos_args) {
case 1: values[0] = PyTuple_GET_ITEM(__pyx_args, 0);
case 0: break;
default: goto __pyx_L5_argtuple_error;
}
kw_args = PyDict_Size(__pyx_kwds);
switch (pos_args) {
case 0:
if (likely((values[0] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__c)) != 0)) kw_args--;
else goto __pyx_L5_argtuple_error;
}
if (unlikely(kw_args > 0)) {
if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, pos_args, "__init__") < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 246; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
} else if (PyTuple_GET_SIZE(__pyx_args) != 1) {
goto __pyx_L5_argtuple_error;
} else {
values[0] = PyTuple_GET_ITEM(__pyx_args, 0);
}
__pyx_v_c = __pyx_PyFloat_AsDouble(values[0]); if (unlikely((__pyx_v_c == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 246; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
goto __pyx_L4_argument_unpacking_done;
__pyx_L5_argtuple_error:;
__Pyx_RaiseArgtupleInvalid("__init__", 1, 1, 1, PyTuple_GET_SIZE(__pyx_args)); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 246; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
__pyx_L3_error:;
__Pyx_AddTraceback("sklearn.linear_model.sgd_fast.Huber.__init__", __pyx_clineno, __pyx_lineno, __pyx_filename);
__Pyx_RefNannyFinishContext();
return -1;
__pyx_L4_argument_unpacking_done:;
__pyx_r = __pyx_pf_7sklearn_12linear_model_8sgd_fast_5Huber___init__(((struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_Huber *)__pyx_v_self), __pyx_v_c);
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* "sklearn/linear_model/sgd_fast.pyx":246
* cdef double c
*
* def __init__(self, double c): # <<<<<<<<<<<<<<
* self.c = c
*
*/
static int __pyx_pf_7sklearn_12linear_model_8sgd_fast_5Huber___init__(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_Huber *__pyx_v_self, double __pyx_v_c) {
int __pyx_r;
__Pyx_RefNannyDeclarations
__Pyx_RefNannySetupContext("__init__", 0);
/* "sklearn/linear_model/sgd_fast.pyx":247
*
* def __init__(self, double c):
* self.c = c # <<<<<<<<<<<<<<
*
* cpdef double loss(self, double p, double y):
*/
__pyx_v_self->c = __pyx_v_c;
__pyx_r = 0;
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* "sklearn/linear_model/sgd_fast.pyx":249
* self.c = c
*
* cpdef double loss(self, double p, double y): # <<<<<<<<<<<<<<
* cdef double r = p - y
* cdef double abs_r = abs(r)
*/
static PyObject *__pyx_pw_7sklearn_12linear_model_8sgd_fast_5Huber_3loss(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/
static double __pyx_f_7sklearn_12linear_model_8sgd_fast_5Huber_loss(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_Huber *__pyx_v_self, double __pyx_v_p, double __pyx_v_y, int __pyx_skip_dispatch) {
double __pyx_v_r;
double __pyx_v_abs_r;
double __pyx_r;
__Pyx_RefNannyDeclarations
PyObject *__pyx_t_1 = NULL;
PyObject *__pyx_t_2 = NULL;
PyObject *__pyx_t_3 = NULL;
PyObject *__pyx_t_4 = NULL;
double __pyx_t_5;
int __pyx_t_6;
int __pyx_lineno = 0;
const char *__pyx_filename = NULL;
int __pyx_clineno = 0;
__Pyx_RefNannySetupContext("loss", 0);
/* Check if called by wrapper */
if (unlikely(__pyx_skip_dispatch)) ;
/* Check if overriden in Python */
else if (unlikely(Py_TYPE(((PyObject *)__pyx_v_self))->tp_dictoffset != 0)) {
__pyx_t_1 = PyObject_GetAttr(((PyObject *)__pyx_v_self), __pyx_n_s__loss); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 249; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_1);
if (!PyCFunction_Check(__pyx_t_1) || (PyCFunction_GET_FUNCTION(__pyx_t_1) != (PyCFunction)__pyx_pw_7sklearn_12linear_model_8sgd_fast_5Huber_3loss)) {
__pyx_t_2 = PyFloat_FromDouble(__pyx_v_p); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 249; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_2);
__pyx_t_3 = PyFloat_FromDouble(__pyx_v_y); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 249; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_3);
__pyx_t_4 = PyTuple_New(2); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 249; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_4);
PyTuple_SET_ITEM(__pyx_t_4, 0, __pyx_t_2);
__Pyx_GIVEREF(__pyx_t_2);
PyTuple_SET_ITEM(__pyx_t_4, 1, __pyx_t_3);
__Pyx_GIVEREF(__pyx_t_3);
__pyx_t_2 = 0;
__pyx_t_3 = 0;
__pyx_t_3 = PyObject_Call(__pyx_t_1, ((PyObject *)__pyx_t_4), NULL); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 249; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_3);
__Pyx_DECREF(((PyObject *)__pyx_t_4)); __pyx_t_4 = 0;
__pyx_t_5 = __pyx_PyFloat_AsDouble(__pyx_t_3); if (unlikely((__pyx_t_5 == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 249; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0;
__pyx_r = __pyx_t_5;
__Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0;
goto __pyx_L0;
}
__Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0;
}
/* "sklearn/linear_model/sgd_fast.pyx":250
*
* cpdef double loss(self, double p, double y):
* cdef double r = p - y # <<<<<<<<<<<<<<
* cdef double abs_r = abs(r)
* if abs_r <= self.c:
*/
__pyx_v_r = (__pyx_v_p - __pyx_v_y);
/* "sklearn/linear_model/sgd_fast.pyx":251
* cpdef double loss(self, double p, double y):
* cdef double r = p - y
* cdef double abs_r = abs(r) # <<<<<<<<<<<<<<
* if abs_r <= self.c:
* return 0.5 * r * r
*/
__pyx_v_abs_r = fabs(__pyx_v_r);
/* "sklearn/linear_model/sgd_fast.pyx":252
* cdef double r = p - y
* cdef double abs_r = abs(r)
* if abs_r <= self.c: # <<<<<<<<<<<<<<
* return 0.5 * r * r
* else:
*/
__pyx_t_6 = (__pyx_v_abs_r <= __pyx_v_self->c);
if (__pyx_t_6) {
/* "sklearn/linear_model/sgd_fast.pyx":253
* cdef double abs_r = abs(r)
* if abs_r <= self.c:
* return 0.5 * r * r # <<<<<<<<<<<<<<
* else:
* return self.c * abs_r - (0.5 * self.c * self.c)
*/
__pyx_r = ((0.5 * __pyx_v_r) * __pyx_v_r);
goto __pyx_L0;
goto __pyx_L3;
}
/*else*/ {
/* "sklearn/linear_model/sgd_fast.pyx":255
* return 0.5 * r * r
* else:
* return self.c * abs_r - (0.5 * self.c * self.c) # <<<<<<<<<<<<<<
*
* cpdef double dloss(self, double p, double y):
*/
__pyx_r = ((__pyx_v_self->c * __pyx_v_abs_r) - ((0.5 * __pyx_v_self->c) * __pyx_v_self->c));
goto __pyx_L0;
}
__pyx_L3:;
__pyx_r = 0;
goto __pyx_L0;
__pyx_L1_error:;
__Pyx_XDECREF(__pyx_t_1);
__Pyx_XDECREF(__pyx_t_2);
__Pyx_XDECREF(__pyx_t_3);
__Pyx_XDECREF(__pyx_t_4);
__Pyx_WriteUnraisable("sklearn.linear_model.sgd_fast.Huber.loss", __pyx_clineno, __pyx_lineno, __pyx_filename);
__pyx_r = 0;
__pyx_L0:;
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* Python wrapper */
static PyObject *__pyx_pw_7sklearn_12linear_model_8sgd_fast_5Huber_3loss(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/
static PyObject *__pyx_pw_7sklearn_12linear_model_8sgd_fast_5Huber_3loss(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds) {
double __pyx_v_p;
double __pyx_v_y;
PyObject *__pyx_r = 0;
__Pyx_RefNannyDeclarations
__Pyx_RefNannySetupContext("loss (wrapper)", 0);
{
static PyObject **__pyx_pyargnames[] = {&__pyx_n_s__p,&__pyx_n_s__y,0};
PyObject* values[2] = {0,0};
if (unlikely(__pyx_kwds)) {
Py_ssize_t kw_args;
const Py_ssize_t pos_args = PyTuple_GET_SIZE(__pyx_args);
switch (pos_args) {
case 2: values[1] = PyTuple_GET_ITEM(__pyx_args, 1);
case 1: values[0] = PyTuple_GET_ITEM(__pyx_args, 0);
case 0: break;
default: goto __pyx_L5_argtuple_error;
}
kw_args = PyDict_Size(__pyx_kwds);
switch (pos_args) {
case 0:
if (likely((values[0] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__p)) != 0)) kw_args--;
else goto __pyx_L5_argtuple_error;
case 1:
if (likely((values[1] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__y)) != 0)) kw_args--;
else {
__Pyx_RaiseArgtupleInvalid("loss", 1, 2, 2, 1); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 249; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
}
if (unlikely(kw_args > 0)) {
if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, pos_args, "loss") < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 249; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
} else if (PyTuple_GET_SIZE(__pyx_args) != 2) {
goto __pyx_L5_argtuple_error;
} else {
values[0] = PyTuple_GET_ITEM(__pyx_args, 0);
values[1] = PyTuple_GET_ITEM(__pyx_args, 1);
}
__pyx_v_p = __pyx_PyFloat_AsDouble(values[0]); if (unlikely((__pyx_v_p == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 249; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
__pyx_v_y = __pyx_PyFloat_AsDouble(values[1]); if (unlikely((__pyx_v_y == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 249; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
goto __pyx_L4_argument_unpacking_done;
__pyx_L5_argtuple_error:;
__Pyx_RaiseArgtupleInvalid("loss", 1, 2, 2, PyTuple_GET_SIZE(__pyx_args)); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 249; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
__pyx_L3_error:;
__Pyx_AddTraceback("sklearn.linear_model.sgd_fast.Huber.loss", __pyx_clineno, __pyx_lineno, __pyx_filename);
__Pyx_RefNannyFinishContext();
return NULL;
__pyx_L4_argument_unpacking_done:;
__pyx_r = __pyx_pf_7sklearn_12linear_model_8sgd_fast_5Huber_2loss(((struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_Huber *)__pyx_v_self), __pyx_v_p, __pyx_v_y);
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* "sklearn/linear_model/sgd_fast.pyx":249
* self.c = c
*
* cpdef double loss(self, double p, double y): # <<<<<<<<<<<<<<
* cdef double r = p - y
* cdef double abs_r = abs(r)
*/
static PyObject *__pyx_pf_7sklearn_12linear_model_8sgd_fast_5Huber_2loss(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_Huber *__pyx_v_self, double __pyx_v_p, double __pyx_v_y) {
PyObject *__pyx_r = NULL;
__Pyx_RefNannyDeclarations
PyObject *__pyx_t_1 = NULL;
int __pyx_lineno = 0;
const char *__pyx_filename = NULL;
int __pyx_clineno = 0;
__Pyx_RefNannySetupContext("loss", 0);
__Pyx_XDECREF(__pyx_r);
__pyx_t_1 = PyFloat_FromDouble(((struct __pyx_vtabstruct_7sklearn_12linear_model_8sgd_fast_Huber *)__pyx_v_self->__pyx_base.__pyx_base.__pyx_vtab)->__pyx_base.__pyx_base.loss(((struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_LossFunction *)__pyx_v_self), __pyx_v_p, __pyx_v_y, 1)); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 249; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_1);
__pyx_r = __pyx_t_1;
__pyx_t_1 = 0;
goto __pyx_L0;
__pyx_r = Py_None; __Pyx_INCREF(Py_None);
goto __pyx_L0;
__pyx_L1_error:;
__Pyx_XDECREF(__pyx_t_1);
__Pyx_AddTraceback("sklearn.linear_model.sgd_fast.Huber.loss", __pyx_clineno, __pyx_lineno, __pyx_filename);
__pyx_r = NULL;
__pyx_L0:;
__Pyx_XGIVEREF(__pyx_r);
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* "sklearn/linear_model/sgd_fast.pyx":257
* return self.c * abs_r - (0.5 * self.c * self.c)
*
* cpdef double dloss(self, double p, double y): # <<<<<<<<<<<<<<
* cdef double r = p - y
* cdef double abs_r = abs(r)
*/
static PyObject *__pyx_pw_7sklearn_12linear_model_8sgd_fast_5Huber_5dloss(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/
static double __pyx_f_7sklearn_12linear_model_8sgd_fast_5Huber_dloss(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_Huber *__pyx_v_self, double __pyx_v_p, double __pyx_v_y, int __pyx_skip_dispatch) {
double __pyx_v_r;
double __pyx_v_abs_r;
double __pyx_r;
__Pyx_RefNannyDeclarations
PyObject *__pyx_t_1 = NULL;
PyObject *__pyx_t_2 = NULL;
PyObject *__pyx_t_3 = NULL;
PyObject *__pyx_t_4 = NULL;
double __pyx_t_5;
int __pyx_t_6;
int __pyx_lineno = 0;
const char *__pyx_filename = NULL;
int __pyx_clineno = 0;
__Pyx_RefNannySetupContext("dloss", 0);
/* Check if called by wrapper */
if (unlikely(__pyx_skip_dispatch)) ;
/* Check if overriden in Python */
else if (unlikely(Py_TYPE(((PyObject *)__pyx_v_self))->tp_dictoffset != 0)) {
__pyx_t_1 = PyObject_GetAttr(((PyObject *)__pyx_v_self), __pyx_n_s__dloss); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 257; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_1);
if (!PyCFunction_Check(__pyx_t_1) || (PyCFunction_GET_FUNCTION(__pyx_t_1) != (PyCFunction)__pyx_pw_7sklearn_12linear_model_8sgd_fast_5Huber_5dloss)) {
__pyx_t_2 = PyFloat_FromDouble(__pyx_v_p); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 257; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_2);
__pyx_t_3 = PyFloat_FromDouble(__pyx_v_y); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 257; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_3);
__pyx_t_4 = PyTuple_New(2); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 257; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_4);
PyTuple_SET_ITEM(__pyx_t_4, 0, __pyx_t_2);
__Pyx_GIVEREF(__pyx_t_2);
PyTuple_SET_ITEM(__pyx_t_4, 1, __pyx_t_3);
__Pyx_GIVEREF(__pyx_t_3);
__pyx_t_2 = 0;
__pyx_t_3 = 0;
__pyx_t_3 = PyObject_Call(__pyx_t_1, ((PyObject *)__pyx_t_4), NULL); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 257; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_3);
__Pyx_DECREF(((PyObject *)__pyx_t_4)); __pyx_t_4 = 0;
__pyx_t_5 = __pyx_PyFloat_AsDouble(__pyx_t_3); if (unlikely((__pyx_t_5 == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 257; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0;
__pyx_r = __pyx_t_5;
__Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0;
goto __pyx_L0;
}
__Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0;
}
/* "sklearn/linear_model/sgd_fast.pyx":258
*
* cpdef double dloss(self, double p, double y):
* cdef double r = p - y # <<<<<<<<<<<<<<
* cdef double abs_r = abs(r)
* if abs_r <= self.c:
*/
__pyx_v_r = (__pyx_v_p - __pyx_v_y);
/* "sklearn/linear_model/sgd_fast.pyx":259
* cpdef double dloss(self, double p, double y):
* cdef double r = p - y
* cdef double abs_r = abs(r) # <<<<<<<<<<<<<<
* if abs_r <= self.c:
* return r
*/
__pyx_v_abs_r = fabs(__pyx_v_r);
/* "sklearn/linear_model/sgd_fast.pyx":260
* cdef double r = p - y
* cdef double abs_r = abs(r)
* if abs_r <= self.c: # <<<<<<<<<<<<<<
* return r
* elif r > 0.0:
*/
__pyx_t_6 = (__pyx_v_abs_r <= __pyx_v_self->c);
if (__pyx_t_6) {
/* "sklearn/linear_model/sgd_fast.pyx":261
* cdef double abs_r = abs(r)
* if abs_r <= self.c:
* return r # <<<<<<<<<<<<<<
* elif r > 0.0:
* return self.c
*/
__pyx_r = __pyx_v_r;
goto __pyx_L0;
goto __pyx_L3;
}
/* "sklearn/linear_model/sgd_fast.pyx":262
* if abs_r <= self.c:
* return r
* elif r > 0.0: # <<<<<<<<<<<<<<
* return self.c
* else:
*/
__pyx_t_6 = (__pyx_v_r > 0.0);
if (__pyx_t_6) {
/* "sklearn/linear_model/sgd_fast.pyx":263
* return r
* elif r > 0.0:
* return self.c # <<<<<<<<<<<<<<
* else:
* return -self.c
*/
__pyx_r = __pyx_v_self->c;
goto __pyx_L0;
goto __pyx_L3;
}
/*else*/ {
/* "sklearn/linear_model/sgd_fast.pyx":265
* return self.c
* else:
* return -self.c # <<<<<<<<<<<<<<
*
* def __reduce__(self):
*/
__pyx_r = (-__pyx_v_self->c);
goto __pyx_L0;
}
__pyx_L3:;
__pyx_r = 0;
goto __pyx_L0;
__pyx_L1_error:;
__Pyx_XDECREF(__pyx_t_1);
__Pyx_XDECREF(__pyx_t_2);
__Pyx_XDECREF(__pyx_t_3);
__Pyx_XDECREF(__pyx_t_4);
__Pyx_WriteUnraisable("sklearn.linear_model.sgd_fast.Huber.dloss", __pyx_clineno, __pyx_lineno, __pyx_filename);
__pyx_r = 0;
__pyx_L0:;
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* Python wrapper */
static PyObject *__pyx_pw_7sklearn_12linear_model_8sgd_fast_5Huber_5dloss(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/
static PyObject *__pyx_pw_7sklearn_12linear_model_8sgd_fast_5Huber_5dloss(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds) {
double __pyx_v_p;
double __pyx_v_y;
PyObject *__pyx_r = 0;
__Pyx_RefNannyDeclarations
__Pyx_RefNannySetupContext("dloss (wrapper)", 0);
{
static PyObject **__pyx_pyargnames[] = {&__pyx_n_s__p,&__pyx_n_s__y,0};
PyObject* values[2] = {0,0};
if (unlikely(__pyx_kwds)) {
Py_ssize_t kw_args;
const Py_ssize_t pos_args = PyTuple_GET_SIZE(__pyx_args);
switch (pos_args) {
case 2: values[1] = PyTuple_GET_ITEM(__pyx_args, 1);
case 1: values[0] = PyTuple_GET_ITEM(__pyx_args, 0);
case 0: break;
default: goto __pyx_L5_argtuple_error;
}
kw_args = PyDict_Size(__pyx_kwds);
switch (pos_args) {
case 0:
if (likely((values[0] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__p)) != 0)) kw_args--;
else goto __pyx_L5_argtuple_error;
case 1:
if (likely((values[1] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__y)) != 0)) kw_args--;
else {
__Pyx_RaiseArgtupleInvalid("dloss", 1, 2, 2, 1); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 257; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
}
if (unlikely(kw_args > 0)) {
if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, pos_args, "dloss") < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 257; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
} else if (PyTuple_GET_SIZE(__pyx_args) != 2) {
goto __pyx_L5_argtuple_error;
} else {
values[0] = PyTuple_GET_ITEM(__pyx_args, 0);
values[1] = PyTuple_GET_ITEM(__pyx_args, 1);
}
__pyx_v_p = __pyx_PyFloat_AsDouble(values[0]); if (unlikely((__pyx_v_p == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 257; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
__pyx_v_y = __pyx_PyFloat_AsDouble(values[1]); if (unlikely((__pyx_v_y == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 257; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
goto __pyx_L4_argument_unpacking_done;
__pyx_L5_argtuple_error:;
__Pyx_RaiseArgtupleInvalid("dloss", 1, 2, 2, PyTuple_GET_SIZE(__pyx_args)); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 257; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
__pyx_L3_error:;
__Pyx_AddTraceback("sklearn.linear_model.sgd_fast.Huber.dloss", __pyx_clineno, __pyx_lineno, __pyx_filename);
__Pyx_RefNannyFinishContext();
return NULL;
__pyx_L4_argument_unpacking_done:;
__pyx_r = __pyx_pf_7sklearn_12linear_model_8sgd_fast_5Huber_4dloss(((struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_Huber *)__pyx_v_self), __pyx_v_p, __pyx_v_y);
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* "sklearn/linear_model/sgd_fast.pyx":257
* return self.c * abs_r - (0.5 * self.c * self.c)
*
* cpdef double dloss(self, double p, double y): # <<<<<<<<<<<<<<
* cdef double r = p - y
* cdef double abs_r = abs(r)
*/
static PyObject *__pyx_pf_7sklearn_12linear_model_8sgd_fast_5Huber_4dloss(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_Huber *__pyx_v_self, double __pyx_v_p, double __pyx_v_y) {
PyObject *__pyx_r = NULL;
__Pyx_RefNannyDeclarations
PyObject *__pyx_t_1 = NULL;
int __pyx_lineno = 0;
const char *__pyx_filename = NULL;
int __pyx_clineno = 0;
__Pyx_RefNannySetupContext("dloss", 0);
__Pyx_XDECREF(__pyx_r);
__pyx_t_1 = PyFloat_FromDouble(((struct __pyx_vtabstruct_7sklearn_12linear_model_8sgd_fast_Huber *)__pyx_v_self->__pyx_base.__pyx_base.__pyx_vtab)->__pyx_base.__pyx_base.dloss(((struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_LossFunction *)__pyx_v_self), __pyx_v_p, __pyx_v_y, 1)); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 257; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_1);
__pyx_r = __pyx_t_1;
__pyx_t_1 = 0;
goto __pyx_L0;
__pyx_r = Py_None; __Pyx_INCREF(Py_None);
goto __pyx_L0;
__pyx_L1_error:;
__Pyx_XDECREF(__pyx_t_1);
__Pyx_AddTraceback("sklearn.linear_model.sgd_fast.Huber.dloss", __pyx_clineno, __pyx_lineno, __pyx_filename);
__pyx_r = NULL;
__pyx_L0:;
__Pyx_XGIVEREF(__pyx_r);
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* Python wrapper */
static PyObject *__pyx_pw_7sklearn_12linear_model_8sgd_fast_5Huber_7__reduce__(PyObject *__pyx_v_self, CYTHON_UNUSED PyObject *unused); /*proto*/
static PyObject *__pyx_pw_7sklearn_12linear_model_8sgd_fast_5Huber_7__reduce__(PyObject *__pyx_v_self, CYTHON_UNUSED PyObject *unused) {
PyObject *__pyx_r = 0;
__Pyx_RefNannyDeclarations
__Pyx_RefNannySetupContext("__reduce__ (wrapper)", 0);
__pyx_r = __pyx_pf_7sklearn_12linear_model_8sgd_fast_5Huber_6__reduce__(((struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_Huber *)__pyx_v_self));
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* "sklearn/linear_model/sgd_fast.pyx":267
* return -self.c
*
* def __reduce__(self): # <<<<<<<<<<<<<<
* return Huber, (self.c,)
*
*/
static PyObject *__pyx_pf_7sklearn_12linear_model_8sgd_fast_5Huber_6__reduce__(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_Huber *__pyx_v_self) {
PyObject *__pyx_r = NULL;
__Pyx_RefNannyDeclarations
PyObject *__pyx_t_1 = NULL;
PyObject *__pyx_t_2 = NULL;
int __pyx_lineno = 0;
const char *__pyx_filename = NULL;
int __pyx_clineno = 0;
__Pyx_RefNannySetupContext("__reduce__", 0);
/* "sklearn/linear_model/sgd_fast.pyx":268
*
* def __reduce__(self):
* return Huber, (self.c,) # <<<<<<<<<<<<<<
*
*
*/
__Pyx_XDECREF(__pyx_r);
__pyx_t_1 = PyFloat_FromDouble(__pyx_v_self->c); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 268; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_1);
__pyx_t_2 = PyTuple_New(1); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 268; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_2);
PyTuple_SET_ITEM(__pyx_t_2, 0, __pyx_t_1);
__Pyx_GIVEREF(__pyx_t_1);
__pyx_t_1 = 0;
__pyx_t_1 = PyTuple_New(2); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 268; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_1);
__Pyx_INCREF(((PyObject *)((PyObject*)__pyx_ptype_7sklearn_12linear_model_8sgd_fast_Huber)));
PyTuple_SET_ITEM(__pyx_t_1, 0, ((PyObject *)((PyObject*)__pyx_ptype_7sklearn_12linear_model_8sgd_fast_Huber)));
__Pyx_GIVEREF(((PyObject *)((PyObject*)__pyx_ptype_7sklearn_12linear_model_8sgd_fast_Huber)));
PyTuple_SET_ITEM(__pyx_t_1, 1, ((PyObject *)__pyx_t_2));
__Pyx_GIVEREF(((PyObject *)__pyx_t_2));
__pyx_t_2 = 0;
__pyx_r = ((PyObject *)__pyx_t_1);
__pyx_t_1 = 0;
goto __pyx_L0;
__pyx_r = Py_None; __Pyx_INCREF(Py_None);
goto __pyx_L0;
__pyx_L1_error:;
__Pyx_XDECREF(__pyx_t_1);
__Pyx_XDECREF(__pyx_t_2);
__Pyx_AddTraceback("sklearn.linear_model.sgd_fast.Huber.__reduce__", __pyx_clineno, __pyx_lineno, __pyx_filename);
__pyx_r = NULL;
__pyx_L0:;
__Pyx_XGIVEREF(__pyx_r);
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* Python wrapper */
static int __pyx_pw_7sklearn_12linear_model_8sgd_fast_18EpsilonInsensitive_1__init__(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/
static int __pyx_pw_7sklearn_12linear_model_8sgd_fast_18EpsilonInsensitive_1__init__(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds) {
double __pyx_v_epsilon;
int __pyx_r;
__Pyx_RefNannyDeclarations
__Pyx_RefNannySetupContext("__init__ (wrapper)", 0);
{
static PyObject **__pyx_pyargnames[] = {&__pyx_n_s__epsilon,0};
PyObject* values[1] = {0};
if (unlikely(__pyx_kwds)) {
Py_ssize_t kw_args;
const Py_ssize_t pos_args = PyTuple_GET_SIZE(__pyx_args);
switch (pos_args) {
case 1: values[0] = PyTuple_GET_ITEM(__pyx_args, 0);
case 0: break;
default: goto __pyx_L5_argtuple_error;
}
kw_args = PyDict_Size(__pyx_kwds);
switch (pos_args) {
case 0:
if (likely((values[0] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__epsilon)) != 0)) kw_args--;
else goto __pyx_L5_argtuple_error;
}
if (unlikely(kw_args > 0)) {
if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, pos_args, "__init__") < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 279; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
} else if (PyTuple_GET_SIZE(__pyx_args) != 1) {
goto __pyx_L5_argtuple_error;
} else {
values[0] = PyTuple_GET_ITEM(__pyx_args, 0);
}
__pyx_v_epsilon = __pyx_PyFloat_AsDouble(values[0]); if (unlikely((__pyx_v_epsilon == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 279; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
goto __pyx_L4_argument_unpacking_done;
__pyx_L5_argtuple_error:;
__Pyx_RaiseArgtupleInvalid("__init__", 1, 1, 1, PyTuple_GET_SIZE(__pyx_args)); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 279; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
__pyx_L3_error:;
__Pyx_AddTraceback("sklearn.linear_model.sgd_fast.EpsilonInsensitive.__init__", __pyx_clineno, __pyx_lineno, __pyx_filename);
__Pyx_RefNannyFinishContext();
return -1;
__pyx_L4_argument_unpacking_done:;
__pyx_r = __pyx_pf_7sklearn_12linear_model_8sgd_fast_18EpsilonInsensitive___init__(((struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_EpsilonInsensitive *)__pyx_v_self), __pyx_v_epsilon);
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* "sklearn/linear_model/sgd_fast.pyx":279
* cdef double epsilon
*
* def __init__(self, double epsilon): # <<<<<<<<<<<<<<
* self.epsilon = epsilon
*
*/
static int __pyx_pf_7sklearn_12linear_model_8sgd_fast_18EpsilonInsensitive___init__(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_EpsilonInsensitive *__pyx_v_self, double __pyx_v_epsilon) {
int __pyx_r;
__Pyx_RefNannyDeclarations
__Pyx_RefNannySetupContext("__init__", 0);
/* "sklearn/linear_model/sgd_fast.pyx":280
*
* def __init__(self, double epsilon):
* self.epsilon = epsilon # <<<<<<<<<<<<<<
*
* cpdef double loss(self, double p, double y):
*/
__pyx_v_self->epsilon = __pyx_v_epsilon;
__pyx_r = 0;
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* "sklearn/linear_model/sgd_fast.pyx":282
* self.epsilon = epsilon
*
* cpdef double loss(self, double p, double y): # <<<<<<<<<<<<<<
* cdef double ret = abs(y - p) - self.epsilon
* return ret if ret > 0 else 0
*/
static PyObject *__pyx_pw_7sklearn_12linear_model_8sgd_fast_18EpsilonInsensitive_3loss(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/
static double __pyx_f_7sklearn_12linear_model_8sgd_fast_18EpsilonInsensitive_loss(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_EpsilonInsensitive *__pyx_v_self, double __pyx_v_p, double __pyx_v_y, int __pyx_skip_dispatch) {
double __pyx_v_ret;
double __pyx_r;
__Pyx_RefNannyDeclarations
PyObject *__pyx_t_1 = NULL;
PyObject *__pyx_t_2 = NULL;
PyObject *__pyx_t_3 = NULL;
PyObject *__pyx_t_4 = NULL;
double __pyx_t_5;
int __pyx_lineno = 0;
const char *__pyx_filename = NULL;
int __pyx_clineno = 0;
__Pyx_RefNannySetupContext("loss", 0);
/* Check if called by wrapper */
if (unlikely(__pyx_skip_dispatch)) ;
/* Check if overriden in Python */
else if (unlikely(Py_TYPE(((PyObject *)__pyx_v_self))->tp_dictoffset != 0)) {
__pyx_t_1 = PyObject_GetAttr(((PyObject *)__pyx_v_self), __pyx_n_s__loss); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 282; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_1);
if (!PyCFunction_Check(__pyx_t_1) || (PyCFunction_GET_FUNCTION(__pyx_t_1) != (PyCFunction)__pyx_pw_7sklearn_12linear_model_8sgd_fast_18EpsilonInsensitive_3loss)) {
__pyx_t_2 = PyFloat_FromDouble(__pyx_v_p); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 282; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_2);
__pyx_t_3 = PyFloat_FromDouble(__pyx_v_y); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 282; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_3);
__pyx_t_4 = PyTuple_New(2); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 282; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_4);
PyTuple_SET_ITEM(__pyx_t_4, 0, __pyx_t_2);
__Pyx_GIVEREF(__pyx_t_2);
PyTuple_SET_ITEM(__pyx_t_4, 1, __pyx_t_3);
__Pyx_GIVEREF(__pyx_t_3);
__pyx_t_2 = 0;
__pyx_t_3 = 0;
__pyx_t_3 = PyObject_Call(__pyx_t_1, ((PyObject *)__pyx_t_4), NULL); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 282; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_3);
__Pyx_DECREF(((PyObject *)__pyx_t_4)); __pyx_t_4 = 0;
__pyx_t_5 = __pyx_PyFloat_AsDouble(__pyx_t_3); if (unlikely((__pyx_t_5 == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 282; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0;
__pyx_r = __pyx_t_5;
__Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0;
goto __pyx_L0;
}
__Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0;
}
/* "sklearn/linear_model/sgd_fast.pyx":283
*
* cpdef double loss(self, double p, double y):
* cdef double ret = abs(y - p) - self.epsilon # <<<<<<<<<<<<<<
* return ret if ret > 0 else 0
*
*/
__pyx_v_ret = (fabs((__pyx_v_y - __pyx_v_p)) - __pyx_v_self->epsilon);
/* "sklearn/linear_model/sgd_fast.pyx":284
* cpdef double loss(self, double p, double y):
* cdef double ret = abs(y - p) - self.epsilon
* return ret if ret > 0 else 0 # <<<<<<<<<<<<<<
*
* cpdef double dloss(self, double p, double y):
*/
if ((__pyx_v_ret > 0.0)) {
__pyx_t_5 = __pyx_v_ret;
} else {
__pyx_t_5 = 0;
}
__pyx_r = __pyx_t_5;
goto __pyx_L0;
__pyx_r = 0;
goto __pyx_L0;
__pyx_L1_error:;
__Pyx_XDECREF(__pyx_t_1);
__Pyx_XDECREF(__pyx_t_2);
__Pyx_XDECREF(__pyx_t_3);
__Pyx_XDECREF(__pyx_t_4);
__Pyx_WriteUnraisable("sklearn.linear_model.sgd_fast.EpsilonInsensitive.loss", __pyx_clineno, __pyx_lineno, __pyx_filename);
__pyx_r = 0;
__pyx_L0:;
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* Python wrapper */
static PyObject *__pyx_pw_7sklearn_12linear_model_8sgd_fast_18EpsilonInsensitive_3loss(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/
static PyObject *__pyx_pw_7sklearn_12linear_model_8sgd_fast_18EpsilonInsensitive_3loss(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds) {
double __pyx_v_p;
double __pyx_v_y;
PyObject *__pyx_r = 0;
__Pyx_RefNannyDeclarations
__Pyx_RefNannySetupContext("loss (wrapper)", 0);
{
static PyObject **__pyx_pyargnames[] = {&__pyx_n_s__p,&__pyx_n_s__y,0};
PyObject* values[2] = {0,0};
if (unlikely(__pyx_kwds)) {
Py_ssize_t kw_args;
const Py_ssize_t pos_args = PyTuple_GET_SIZE(__pyx_args);
switch (pos_args) {
case 2: values[1] = PyTuple_GET_ITEM(__pyx_args, 1);
case 1: values[0] = PyTuple_GET_ITEM(__pyx_args, 0);
case 0: break;
default: goto __pyx_L5_argtuple_error;
}
kw_args = PyDict_Size(__pyx_kwds);
switch (pos_args) {
case 0:
if (likely((values[0] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__p)) != 0)) kw_args--;
else goto __pyx_L5_argtuple_error;
case 1:
if (likely((values[1] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__y)) != 0)) kw_args--;
else {
__Pyx_RaiseArgtupleInvalid("loss", 1, 2, 2, 1); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 282; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
}
if (unlikely(kw_args > 0)) {
if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, pos_args, "loss") < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 282; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
} else if (PyTuple_GET_SIZE(__pyx_args) != 2) {
goto __pyx_L5_argtuple_error;
} else {
values[0] = PyTuple_GET_ITEM(__pyx_args, 0);
values[1] = PyTuple_GET_ITEM(__pyx_args, 1);
}
__pyx_v_p = __pyx_PyFloat_AsDouble(values[0]); if (unlikely((__pyx_v_p == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 282; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
__pyx_v_y = __pyx_PyFloat_AsDouble(values[1]); if (unlikely((__pyx_v_y == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 282; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
goto __pyx_L4_argument_unpacking_done;
__pyx_L5_argtuple_error:;
__Pyx_RaiseArgtupleInvalid("loss", 1, 2, 2, PyTuple_GET_SIZE(__pyx_args)); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 282; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
__pyx_L3_error:;
__Pyx_AddTraceback("sklearn.linear_model.sgd_fast.EpsilonInsensitive.loss", __pyx_clineno, __pyx_lineno, __pyx_filename);
__Pyx_RefNannyFinishContext();
return NULL;
__pyx_L4_argument_unpacking_done:;
__pyx_r = __pyx_pf_7sklearn_12linear_model_8sgd_fast_18EpsilonInsensitive_2loss(((struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_EpsilonInsensitive *)__pyx_v_self), __pyx_v_p, __pyx_v_y);
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* "sklearn/linear_model/sgd_fast.pyx":282
* self.epsilon = epsilon
*
* cpdef double loss(self, double p, double y): # <<<<<<<<<<<<<<
* cdef double ret = abs(y - p) - self.epsilon
* return ret if ret > 0 else 0
*/
static PyObject *__pyx_pf_7sklearn_12linear_model_8sgd_fast_18EpsilonInsensitive_2loss(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_EpsilonInsensitive *__pyx_v_self, double __pyx_v_p, double __pyx_v_y) {
PyObject *__pyx_r = NULL;
__Pyx_RefNannyDeclarations
PyObject *__pyx_t_1 = NULL;
int __pyx_lineno = 0;
const char *__pyx_filename = NULL;
int __pyx_clineno = 0;
__Pyx_RefNannySetupContext("loss", 0);
__Pyx_XDECREF(__pyx_r);
__pyx_t_1 = PyFloat_FromDouble(((struct __pyx_vtabstruct_7sklearn_12linear_model_8sgd_fast_EpsilonInsensitive *)__pyx_v_self->__pyx_base.__pyx_base.__pyx_vtab)->__pyx_base.__pyx_base.loss(((struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_LossFunction *)__pyx_v_self), __pyx_v_p, __pyx_v_y, 1)); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 282; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_1);
__pyx_r = __pyx_t_1;
__pyx_t_1 = 0;
goto __pyx_L0;
__pyx_r = Py_None; __Pyx_INCREF(Py_None);
goto __pyx_L0;
__pyx_L1_error:;
__Pyx_XDECREF(__pyx_t_1);
__Pyx_AddTraceback("sklearn.linear_model.sgd_fast.EpsilonInsensitive.loss", __pyx_clineno, __pyx_lineno, __pyx_filename);
__pyx_r = NULL;
__pyx_L0:;
__Pyx_XGIVEREF(__pyx_r);
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* "sklearn/linear_model/sgd_fast.pyx":286
* return ret if ret > 0 else 0
*
* cpdef double dloss(self, double p, double y): # <<<<<<<<<<<<<<
* if y - p > self.epsilon:
* return -1
*/
static PyObject *__pyx_pw_7sklearn_12linear_model_8sgd_fast_18EpsilonInsensitive_5dloss(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/
static double __pyx_f_7sklearn_12linear_model_8sgd_fast_18EpsilonInsensitive_dloss(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_EpsilonInsensitive *__pyx_v_self, double __pyx_v_p, double __pyx_v_y, int __pyx_skip_dispatch) {
double __pyx_r;
__Pyx_RefNannyDeclarations
PyObject *__pyx_t_1 = NULL;
PyObject *__pyx_t_2 = NULL;
PyObject *__pyx_t_3 = NULL;
PyObject *__pyx_t_4 = NULL;
double __pyx_t_5;
int __pyx_t_6;
int __pyx_lineno = 0;
const char *__pyx_filename = NULL;
int __pyx_clineno = 0;
__Pyx_RefNannySetupContext("dloss", 0);
/* Check if called by wrapper */
if (unlikely(__pyx_skip_dispatch)) ;
/* Check if overriden in Python */
else if (unlikely(Py_TYPE(((PyObject *)__pyx_v_self))->tp_dictoffset != 0)) {
__pyx_t_1 = PyObject_GetAttr(((PyObject *)__pyx_v_self), __pyx_n_s__dloss); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 286; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_1);
if (!PyCFunction_Check(__pyx_t_1) || (PyCFunction_GET_FUNCTION(__pyx_t_1) != (PyCFunction)__pyx_pw_7sklearn_12linear_model_8sgd_fast_18EpsilonInsensitive_5dloss)) {
__pyx_t_2 = PyFloat_FromDouble(__pyx_v_p); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 286; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_2);
__pyx_t_3 = PyFloat_FromDouble(__pyx_v_y); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 286; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_3);
__pyx_t_4 = PyTuple_New(2); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 286; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_4);
PyTuple_SET_ITEM(__pyx_t_4, 0, __pyx_t_2);
__Pyx_GIVEREF(__pyx_t_2);
PyTuple_SET_ITEM(__pyx_t_4, 1, __pyx_t_3);
__Pyx_GIVEREF(__pyx_t_3);
__pyx_t_2 = 0;
__pyx_t_3 = 0;
__pyx_t_3 = PyObject_Call(__pyx_t_1, ((PyObject *)__pyx_t_4), NULL); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 286; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_3);
__Pyx_DECREF(((PyObject *)__pyx_t_4)); __pyx_t_4 = 0;
__pyx_t_5 = __pyx_PyFloat_AsDouble(__pyx_t_3); if (unlikely((__pyx_t_5 == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 286; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0;
__pyx_r = __pyx_t_5;
__Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0;
goto __pyx_L0;
}
__Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0;
}
/* "sklearn/linear_model/sgd_fast.pyx":287
*
* cpdef double dloss(self, double p, double y):
* if y - p > self.epsilon: # <<<<<<<<<<<<<<
* return -1
* elif p - y > self.epsilon:
*/
__pyx_t_6 = ((__pyx_v_y - __pyx_v_p) > __pyx_v_self->epsilon);
if (__pyx_t_6) {
/* "sklearn/linear_model/sgd_fast.pyx":288
* cpdef double dloss(self, double p, double y):
* if y - p > self.epsilon:
* return -1 # <<<<<<<<<<<<<<
* elif p - y > self.epsilon:
* return 1
*/
__pyx_r = -1.0;
goto __pyx_L0;
goto __pyx_L3;
}
/* "sklearn/linear_model/sgd_fast.pyx":289
* if y - p > self.epsilon:
* return -1
* elif p - y > self.epsilon: # <<<<<<<<<<<<<<
* return 1
* else:
*/
__pyx_t_6 = ((__pyx_v_p - __pyx_v_y) > __pyx_v_self->epsilon);
if (__pyx_t_6) {
/* "sklearn/linear_model/sgd_fast.pyx":290
* return -1
* elif p - y > self.epsilon:
* return 1 # <<<<<<<<<<<<<<
* else:
* return 0
*/
__pyx_r = 1.0;
goto __pyx_L0;
goto __pyx_L3;
}
/*else*/ {
/* "sklearn/linear_model/sgd_fast.pyx":292
* return 1
* else:
* return 0 # <<<<<<<<<<<<<<
*
* def __reduce__(self):
*/
__pyx_r = 0.0;
goto __pyx_L0;
}
__pyx_L3:;
__pyx_r = 0;
goto __pyx_L0;
__pyx_L1_error:;
__Pyx_XDECREF(__pyx_t_1);
__Pyx_XDECREF(__pyx_t_2);
__Pyx_XDECREF(__pyx_t_3);
__Pyx_XDECREF(__pyx_t_4);
__Pyx_WriteUnraisable("sklearn.linear_model.sgd_fast.EpsilonInsensitive.dloss", __pyx_clineno, __pyx_lineno, __pyx_filename);
__pyx_r = 0;
__pyx_L0:;
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* Python wrapper */
static PyObject *__pyx_pw_7sklearn_12linear_model_8sgd_fast_18EpsilonInsensitive_5dloss(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/
static PyObject *__pyx_pw_7sklearn_12linear_model_8sgd_fast_18EpsilonInsensitive_5dloss(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds) {
double __pyx_v_p;
double __pyx_v_y;
PyObject *__pyx_r = 0;
__Pyx_RefNannyDeclarations
__Pyx_RefNannySetupContext("dloss (wrapper)", 0);
{
static PyObject **__pyx_pyargnames[] = {&__pyx_n_s__p,&__pyx_n_s__y,0};
PyObject* values[2] = {0,0};
if (unlikely(__pyx_kwds)) {
Py_ssize_t kw_args;
const Py_ssize_t pos_args = PyTuple_GET_SIZE(__pyx_args);
switch (pos_args) {
case 2: values[1] = PyTuple_GET_ITEM(__pyx_args, 1);
case 1: values[0] = PyTuple_GET_ITEM(__pyx_args, 0);
case 0: break;
default: goto __pyx_L5_argtuple_error;
}
kw_args = PyDict_Size(__pyx_kwds);
switch (pos_args) {
case 0:
if (likely((values[0] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__p)) != 0)) kw_args--;
else goto __pyx_L5_argtuple_error;
case 1:
if (likely((values[1] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__y)) != 0)) kw_args--;
else {
__Pyx_RaiseArgtupleInvalid("dloss", 1, 2, 2, 1); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 286; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
}
if (unlikely(kw_args > 0)) {
if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, pos_args, "dloss") < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 286; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
} else if (PyTuple_GET_SIZE(__pyx_args) != 2) {
goto __pyx_L5_argtuple_error;
} else {
values[0] = PyTuple_GET_ITEM(__pyx_args, 0);
values[1] = PyTuple_GET_ITEM(__pyx_args, 1);
}
__pyx_v_p = __pyx_PyFloat_AsDouble(values[0]); if (unlikely((__pyx_v_p == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 286; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
__pyx_v_y = __pyx_PyFloat_AsDouble(values[1]); if (unlikely((__pyx_v_y == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 286; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
goto __pyx_L4_argument_unpacking_done;
__pyx_L5_argtuple_error:;
__Pyx_RaiseArgtupleInvalid("dloss", 1, 2, 2, PyTuple_GET_SIZE(__pyx_args)); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 286; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
__pyx_L3_error:;
__Pyx_AddTraceback("sklearn.linear_model.sgd_fast.EpsilonInsensitive.dloss", __pyx_clineno, __pyx_lineno, __pyx_filename);
__Pyx_RefNannyFinishContext();
return NULL;
__pyx_L4_argument_unpacking_done:;
__pyx_r = __pyx_pf_7sklearn_12linear_model_8sgd_fast_18EpsilonInsensitive_4dloss(((struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_EpsilonInsensitive *)__pyx_v_self), __pyx_v_p, __pyx_v_y);
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* "sklearn/linear_model/sgd_fast.pyx":286
* return ret if ret > 0 else 0
*
* cpdef double dloss(self, double p, double y): # <<<<<<<<<<<<<<
* if y - p > self.epsilon:
* return -1
*/
static PyObject *__pyx_pf_7sklearn_12linear_model_8sgd_fast_18EpsilonInsensitive_4dloss(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_EpsilonInsensitive *__pyx_v_self, double __pyx_v_p, double __pyx_v_y) {
PyObject *__pyx_r = NULL;
__Pyx_RefNannyDeclarations
PyObject *__pyx_t_1 = NULL;
int __pyx_lineno = 0;
const char *__pyx_filename = NULL;
int __pyx_clineno = 0;
__Pyx_RefNannySetupContext("dloss", 0);
__Pyx_XDECREF(__pyx_r);
__pyx_t_1 = PyFloat_FromDouble(((struct __pyx_vtabstruct_7sklearn_12linear_model_8sgd_fast_EpsilonInsensitive *)__pyx_v_self->__pyx_base.__pyx_base.__pyx_vtab)->__pyx_base.__pyx_base.dloss(((struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_LossFunction *)__pyx_v_self), __pyx_v_p, __pyx_v_y, 1)); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 286; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_1);
__pyx_r = __pyx_t_1;
__pyx_t_1 = 0;
goto __pyx_L0;
__pyx_r = Py_None; __Pyx_INCREF(Py_None);
goto __pyx_L0;
__pyx_L1_error:;
__Pyx_XDECREF(__pyx_t_1);
__Pyx_AddTraceback("sklearn.linear_model.sgd_fast.EpsilonInsensitive.dloss", __pyx_clineno, __pyx_lineno, __pyx_filename);
__pyx_r = NULL;
__pyx_L0:;
__Pyx_XGIVEREF(__pyx_r);
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* Python wrapper */
static PyObject *__pyx_pw_7sklearn_12linear_model_8sgd_fast_18EpsilonInsensitive_7__reduce__(PyObject *__pyx_v_self, CYTHON_UNUSED PyObject *unused); /*proto*/
static PyObject *__pyx_pw_7sklearn_12linear_model_8sgd_fast_18EpsilonInsensitive_7__reduce__(PyObject *__pyx_v_self, CYTHON_UNUSED PyObject *unused) {
PyObject *__pyx_r = 0;
__Pyx_RefNannyDeclarations
__Pyx_RefNannySetupContext("__reduce__ (wrapper)", 0);
__pyx_r = __pyx_pf_7sklearn_12linear_model_8sgd_fast_18EpsilonInsensitive_6__reduce__(((struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_EpsilonInsensitive *)__pyx_v_self));
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* "sklearn/linear_model/sgd_fast.pyx":294
* return 0
*
* def __reduce__(self): # <<<<<<<<<<<<<<
* return EpsilonInsensitive, (self.epsilon,)
*
*/
static PyObject *__pyx_pf_7sklearn_12linear_model_8sgd_fast_18EpsilonInsensitive_6__reduce__(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_EpsilonInsensitive *__pyx_v_self) {
PyObject *__pyx_r = NULL;
__Pyx_RefNannyDeclarations
PyObject *__pyx_t_1 = NULL;
PyObject *__pyx_t_2 = NULL;
int __pyx_lineno = 0;
const char *__pyx_filename = NULL;
int __pyx_clineno = 0;
__Pyx_RefNannySetupContext("__reduce__", 0);
/* "sklearn/linear_model/sgd_fast.pyx":295
*
* def __reduce__(self):
* return EpsilonInsensitive, (self.epsilon,) # <<<<<<<<<<<<<<
*
*
*/
__Pyx_XDECREF(__pyx_r);
__pyx_t_1 = PyFloat_FromDouble(__pyx_v_self->epsilon); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 295; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_1);
__pyx_t_2 = PyTuple_New(1); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 295; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_2);
PyTuple_SET_ITEM(__pyx_t_2, 0, __pyx_t_1);
__Pyx_GIVEREF(__pyx_t_1);
__pyx_t_1 = 0;
__pyx_t_1 = PyTuple_New(2); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 295; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_1);
__Pyx_INCREF(((PyObject *)((PyObject*)__pyx_ptype_7sklearn_12linear_model_8sgd_fast_EpsilonInsensitive)));
PyTuple_SET_ITEM(__pyx_t_1, 0, ((PyObject *)((PyObject*)__pyx_ptype_7sklearn_12linear_model_8sgd_fast_EpsilonInsensitive)));
__Pyx_GIVEREF(((PyObject *)((PyObject*)__pyx_ptype_7sklearn_12linear_model_8sgd_fast_EpsilonInsensitive)));
PyTuple_SET_ITEM(__pyx_t_1, 1, ((PyObject *)__pyx_t_2));
__Pyx_GIVEREF(((PyObject *)__pyx_t_2));
__pyx_t_2 = 0;
__pyx_r = ((PyObject *)__pyx_t_1);
__pyx_t_1 = 0;
goto __pyx_L0;
__pyx_r = Py_None; __Pyx_INCREF(Py_None);
goto __pyx_L0;
__pyx_L1_error:;
__Pyx_XDECREF(__pyx_t_1);
__Pyx_XDECREF(__pyx_t_2);
__Pyx_AddTraceback("sklearn.linear_model.sgd_fast.EpsilonInsensitive.__reduce__", __pyx_clineno, __pyx_lineno, __pyx_filename);
__pyx_r = NULL;
__pyx_L0:;
__Pyx_XGIVEREF(__pyx_r);
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* Python wrapper */
static int __pyx_pw_7sklearn_12linear_model_8sgd_fast_25SquaredEpsilonInsensitive_1__init__(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/
static int __pyx_pw_7sklearn_12linear_model_8sgd_fast_25SquaredEpsilonInsensitive_1__init__(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds) {
double __pyx_v_epsilon;
int __pyx_r;
__Pyx_RefNannyDeclarations
__Pyx_RefNannySetupContext("__init__ (wrapper)", 0);
{
static PyObject **__pyx_pyargnames[] = {&__pyx_n_s__epsilon,0};
PyObject* values[1] = {0};
if (unlikely(__pyx_kwds)) {
Py_ssize_t kw_args;
const Py_ssize_t pos_args = PyTuple_GET_SIZE(__pyx_args);
switch (pos_args) {
case 1: values[0] = PyTuple_GET_ITEM(__pyx_args, 0);
case 0: break;
default: goto __pyx_L5_argtuple_error;
}
kw_args = PyDict_Size(__pyx_kwds);
switch (pos_args) {
case 0:
if (likely((values[0] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__epsilon)) != 0)) kw_args--;
else goto __pyx_L5_argtuple_error;
}
if (unlikely(kw_args > 0)) {
if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, pos_args, "__init__") < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 306; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
} else if (PyTuple_GET_SIZE(__pyx_args) != 1) {
goto __pyx_L5_argtuple_error;
} else {
values[0] = PyTuple_GET_ITEM(__pyx_args, 0);
}
__pyx_v_epsilon = __pyx_PyFloat_AsDouble(values[0]); if (unlikely((__pyx_v_epsilon == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 306; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
goto __pyx_L4_argument_unpacking_done;
__pyx_L5_argtuple_error:;
__Pyx_RaiseArgtupleInvalid("__init__", 1, 1, 1, PyTuple_GET_SIZE(__pyx_args)); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 306; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
__pyx_L3_error:;
__Pyx_AddTraceback("sklearn.linear_model.sgd_fast.SquaredEpsilonInsensitive.__init__", __pyx_clineno, __pyx_lineno, __pyx_filename);
__Pyx_RefNannyFinishContext();
return -1;
__pyx_L4_argument_unpacking_done:;
__pyx_r = __pyx_pf_7sklearn_12linear_model_8sgd_fast_25SquaredEpsilonInsensitive___init__(((struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_SquaredEpsilonInsensitive *)__pyx_v_self), __pyx_v_epsilon);
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* "sklearn/linear_model/sgd_fast.pyx":306
* cdef double epsilon
*
* def __init__(self, double epsilon): # <<<<<<<<<<<<<<
* self.epsilon = epsilon
*
*/
static int __pyx_pf_7sklearn_12linear_model_8sgd_fast_25SquaredEpsilonInsensitive___init__(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_SquaredEpsilonInsensitive *__pyx_v_self, double __pyx_v_epsilon) {
int __pyx_r;
__Pyx_RefNannyDeclarations
__Pyx_RefNannySetupContext("__init__", 0);
/* "sklearn/linear_model/sgd_fast.pyx":307
*
* def __init__(self, double epsilon):
* self.epsilon = epsilon # <<<<<<<<<<<<<<
*
* cpdef double loss(self, double p, double y):
*/
__pyx_v_self->epsilon = __pyx_v_epsilon;
__pyx_r = 0;
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* "sklearn/linear_model/sgd_fast.pyx":309
* self.epsilon = epsilon
*
* cpdef double loss(self, double p, double y): # <<<<<<<<<<<<<<
* cdef double ret = abs(y - p) - self.epsilon
* return ret * ret if ret > 0 else 0
*/
static PyObject *__pyx_pw_7sklearn_12linear_model_8sgd_fast_25SquaredEpsilonInsensitive_3loss(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/
static double __pyx_f_7sklearn_12linear_model_8sgd_fast_25SquaredEpsilonInsensitive_loss(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_SquaredEpsilonInsensitive *__pyx_v_self, double __pyx_v_p, double __pyx_v_y, int __pyx_skip_dispatch) {
double __pyx_v_ret;
double __pyx_r;
__Pyx_RefNannyDeclarations
PyObject *__pyx_t_1 = NULL;
PyObject *__pyx_t_2 = NULL;
PyObject *__pyx_t_3 = NULL;
PyObject *__pyx_t_4 = NULL;
double __pyx_t_5;
int __pyx_lineno = 0;
const char *__pyx_filename = NULL;
int __pyx_clineno = 0;
__Pyx_RefNannySetupContext("loss", 0);
/* Check if called by wrapper */
if (unlikely(__pyx_skip_dispatch)) ;
/* Check if overriden in Python */
else if (unlikely(Py_TYPE(((PyObject *)__pyx_v_self))->tp_dictoffset != 0)) {
__pyx_t_1 = PyObject_GetAttr(((PyObject *)__pyx_v_self), __pyx_n_s__loss); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 309; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_1);
if (!PyCFunction_Check(__pyx_t_1) || (PyCFunction_GET_FUNCTION(__pyx_t_1) != (PyCFunction)__pyx_pw_7sklearn_12linear_model_8sgd_fast_25SquaredEpsilonInsensitive_3loss)) {
__pyx_t_2 = PyFloat_FromDouble(__pyx_v_p); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 309; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_2);
__pyx_t_3 = PyFloat_FromDouble(__pyx_v_y); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 309; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_3);
__pyx_t_4 = PyTuple_New(2); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 309; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_4);
PyTuple_SET_ITEM(__pyx_t_4, 0, __pyx_t_2);
__Pyx_GIVEREF(__pyx_t_2);
PyTuple_SET_ITEM(__pyx_t_4, 1, __pyx_t_3);
__Pyx_GIVEREF(__pyx_t_3);
__pyx_t_2 = 0;
__pyx_t_3 = 0;
__pyx_t_3 = PyObject_Call(__pyx_t_1, ((PyObject *)__pyx_t_4), NULL); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 309; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_3);
__Pyx_DECREF(((PyObject *)__pyx_t_4)); __pyx_t_4 = 0;
__pyx_t_5 = __pyx_PyFloat_AsDouble(__pyx_t_3); if (unlikely((__pyx_t_5 == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 309; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0;
__pyx_r = __pyx_t_5;
__Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0;
goto __pyx_L0;
}
__Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0;
}
/* "sklearn/linear_model/sgd_fast.pyx":310
*
* cpdef double loss(self, double p, double y):
* cdef double ret = abs(y - p) - self.epsilon # <<<<<<<<<<<<<<
* return ret * ret if ret > 0 else 0
*
*/
__pyx_v_ret = (fabs((__pyx_v_y - __pyx_v_p)) - __pyx_v_self->epsilon);
/* "sklearn/linear_model/sgd_fast.pyx":311
* cpdef double loss(self, double p, double y):
* cdef double ret = abs(y - p) - self.epsilon
* return ret * ret if ret > 0 else 0 # <<<<<<<<<<<<<<
*
* cpdef double dloss(self, double p, double y):
*/
if ((__pyx_v_ret > 0.0)) {
__pyx_t_5 = (__pyx_v_ret * __pyx_v_ret);
} else {
__pyx_t_5 = 0;
}
__pyx_r = __pyx_t_5;
goto __pyx_L0;
__pyx_r = 0;
goto __pyx_L0;
__pyx_L1_error:;
__Pyx_XDECREF(__pyx_t_1);
__Pyx_XDECREF(__pyx_t_2);
__Pyx_XDECREF(__pyx_t_3);
__Pyx_XDECREF(__pyx_t_4);
__Pyx_WriteUnraisable("sklearn.linear_model.sgd_fast.SquaredEpsilonInsensitive.loss", __pyx_clineno, __pyx_lineno, __pyx_filename);
__pyx_r = 0;
__pyx_L0:;
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* Python wrapper */
static PyObject *__pyx_pw_7sklearn_12linear_model_8sgd_fast_25SquaredEpsilonInsensitive_3loss(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/
static PyObject *__pyx_pw_7sklearn_12linear_model_8sgd_fast_25SquaredEpsilonInsensitive_3loss(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds) {
double __pyx_v_p;
double __pyx_v_y;
PyObject *__pyx_r = 0;
__Pyx_RefNannyDeclarations
__Pyx_RefNannySetupContext("loss (wrapper)", 0);
{
static PyObject **__pyx_pyargnames[] = {&__pyx_n_s__p,&__pyx_n_s__y,0};
PyObject* values[2] = {0,0};
if (unlikely(__pyx_kwds)) {
Py_ssize_t kw_args;
const Py_ssize_t pos_args = PyTuple_GET_SIZE(__pyx_args);
switch (pos_args) {
case 2: values[1] = PyTuple_GET_ITEM(__pyx_args, 1);
case 1: values[0] = PyTuple_GET_ITEM(__pyx_args, 0);
case 0: break;
default: goto __pyx_L5_argtuple_error;
}
kw_args = PyDict_Size(__pyx_kwds);
switch (pos_args) {
case 0:
if (likely((values[0] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__p)) != 0)) kw_args--;
else goto __pyx_L5_argtuple_error;
case 1:
if (likely((values[1] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__y)) != 0)) kw_args--;
else {
__Pyx_RaiseArgtupleInvalid("loss", 1, 2, 2, 1); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 309; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
}
if (unlikely(kw_args > 0)) {
if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, pos_args, "loss") < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 309; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
} else if (PyTuple_GET_SIZE(__pyx_args) != 2) {
goto __pyx_L5_argtuple_error;
} else {
values[0] = PyTuple_GET_ITEM(__pyx_args, 0);
values[1] = PyTuple_GET_ITEM(__pyx_args, 1);
}
__pyx_v_p = __pyx_PyFloat_AsDouble(values[0]); if (unlikely((__pyx_v_p == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 309; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
__pyx_v_y = __pyx_PyFloat_AsDouble(values[1]); if (unlikely((__pyx_v_y == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 309; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
goto __pyx_L4_argument_unpacking_done;
__pyx_L5_argtuple_error:;
__Pyx_RaiseArgtupleInvalid("loss", 1, 2, 2, PyTuple_GET_SIZE(__pyx_args)); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 309; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
__pyx_L3_error:;
__Pyx_AddTraceback("sklearn.linear_model.sgd_fast.SquaredEpsilonInsensitive.loss", __pyx_clineno, __pyx_lineno, __pyx_filename);
__Pyx_RefNannyFinishContext();
return NULL;
__pyx_L4_argument_unpacking_done:;
__pyx_r = __pyx_pf_7sklearn_12linear_model_8sgd_fast_25SquaredEpsilonInsensitive_2loss(((struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_SquaredEpsilonInsensitive *)__pyx_v_self), __pyx_v_p, __pyx_v_y);
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* "sklearn/linear_model/sgd_fast.pyx":309
* self.epsilon = epsilon
*
* cpdef double loss(self, double p, double y): # <<<<<<<<<<<<<<
* cdef double ret = abs(y - p) - self.epsilon
* return ret * ret if ret > 0 else 0
*/
static PyObject *__pyx_pf_7sklearn_12linear_model_8sgd_fast_25SquaredEpsilonInsensitive_2loss(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_SquaredEpsilonInsensitive *__pyx_v_self, double __pyx_v_p, double __pyx_v_y) {
PyObject *__pyx_r = NULL;
__Pyx_RefNannyDeclarations
PyObject *__pyx_t_1 = NULL;
int __pyx_lineno = 0;
const char *__pyx_filename = NULL;
int __pyx_clineno = 0;
__Pyx_RefNannySetupContext("loss", 0);
__Pyx_XDECREF(__pyx_r);
__pyx_t_1 = PyFloat_FromDouble(((struct __pyx_vtabstruct_7sklearn_12linear_model_8sgd_fast_SquaredEpsilonInsensitive *)__pyx_v_self->__pyx_base.__pyx_base.__pyx_vtab)->__pyx_base.__pyx_base.loss(((struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_LossFunction *)__pyx_v_self), __pyx_v_p, __pyx_v_y, 1)); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 309; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_1);
__pyx_r = __pyx_t_1;
__pyx_t_1 = 0;
goto __pyx_L0;
__pyx_r = Py_None; __Pyx_INCREF(Py_None);
goto __pyx_L0;
__pyx_L1_error:;
__Pyx_XDECREF(__pyx_t_1);
__Pyx_AddTraceback("sklearn.linear_model.sgd_fast.SquaredEpsilonInsensitive.loss", __pyx_clineno, __pyx_lineno, __pyx_filename);
__pyx_r = NULL;
__pyx_L0:;
__Pyx_XGIVEREF(__pyx_r);
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* "sklearn/linear_model/sgd_fast.pyx":313
* return ret * ret if ret > 0 else 0
*
* cpdef double dloss(self, double p, double y): # <<<<<<<<<<<<<<
* cdef double z
* z = y - p
*/
static PyObject *__pyx_pw_7sklearn_12linear_model_8sgd_fast_25SquaredEpsilonInsensitive_5dloss(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/
static double __pyx_f_7sklearn_12linear_model_8sgd_fast_25SquaredEpsilonInsensitive_dloss(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_SquaredEpsilonInsensitive *__pyx_v_self, double __pyx_v_p, double __pyx_v_y, int __pyx_skip_dispatch) {
double __pyx_v_z;
double __pyx_r;
__Pyx_RefNannyDeclarations
PyObject *__pyx_t_1 = NULL;
PyObject *__pyx_t_2 = NULL;
PyObject *__pyx_t_3 = NULL;
PyObject *__pyx_t_4 = NULL;
double __pyx_t_5;
int __pyx_t_6;
int __pyx_lineno = 0;
const char *__pyx_filename = NULL;
int __pyx_clineno = 0;
__Pyx_RefNannySetupContext("dloss", 0);
/* Check if called by wrapper */
if (unlikely(__pyx_skip_dispatch)) ;
/* Check if overriden in Python */
else if (unlikely(Py_TYPE(((PyObject *)__pyx_v_self))->tp_dictoffset != 0)) {
__pyx_t_1 = PyObject_GetAttr(((PyObject *)__pyx_v_self), __pyx_n_s__dloss); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 313; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_1);
if (!PyCFunction_Check(__pyx_t_1) || (PyCFunction_GET_FUNCTION(__pyx_t_1) != (PyCFunction)__pyx_pw_7sklearn_12linear_model_8sgd_fast_25SquaredEpsilonInsensitive_5dloss)) {
__pyx_t_2 = PyFloat_FromDouble(__pyx_v_p); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 313; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_2);
__pyx_t_3 = PyFloat_FromDouble(__pyx_v_y); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 313; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_3);
__pyx_t_4 = PyTuple_New(2); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 313; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_4);
PyTuple_SET_ITEM(__pyx_t_4, 0, __pyx_t_2);
__Pyx_GIVEREF(__pyx_t_2);
PyTuple_SET_ITEM(__pyx_t_4, 1, __pyx_t_3);
__Pyx_GIVEREF(__pyx_t_3);
__pyx_t_2 = 0;
__pyx_t_3 = 0;
__pyx_t_3 = PyObject_Call(__pyx_t_1, ((PyObject *)__pyx_t_4), NULL); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 313; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_3);
__Pyx_DECREF(((PyObject *)__pyx_t_4)); __pyx_t_4 = 0;
__pyx_t_5 = __pyx_PyFloat_AsDouble(__pyx_t_3); if (unlikely((__pyx_t_5 == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 313; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0;
__pyx_r = __pyx_t_5;
__Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0;
goto __pyx_L0;
}
__Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0;
}
/* "sklearn/linear_model/sgd_fast.pyx":315
* cpdef double dloss(self, double p, double y):
* cdef double z
* z = y - p # <<<<<<<<<<<<<<
* if z > self.epsilon:
* return -2 * (z - self.epsilon)
*/
__pyx_v_z = (__pyx_v_y - __pyx_v_p);
/* "sklearn/linear_model/sgd_fast.pyx":316
* cdef double z
* z = y - p
* if z > self.epsilon: # <<<<<<<<<<<<<<
* return -2 * (z - self.epsilon)
* elif z < self.epsilon:
*/
__pyx_t_6 = (__pyx_v_z > __pyx_v_self->epsilon);
if (__pyx_t_6) {
/* "sklearn/linear_model/sgd_fast.pyx":317
* z = y - p
* if z > self.epsilon:
* return -2 * (z - self.epsilon) # <<<<<<<<<<<<<<
* elif z < self.epsilon:
* return 2 * (-z - self.epsilon)
*/
__pyx_r = (-2.0 * (__pyx_v_z - __pyx_v_self->epsilon));
goto __pyx_L0;
goto __pyx_L3;
}
/* "sklearn/linear_model/sgd_fast.pyx":318
* if z > self.epsilon:
* return -2 * (z - self.epsilon)
* elif z < self.epsilon: # <<<<<<<<<<<<<<
* return 2 * (-z - self.epsilon)
* else:
*/
__pyx_t_6 = (__pyx_v_z < __pyx_v_self->epsilon);
if (__pyx_t_6) {
/* "sklearn/linear_model/sgd_fast.pyx":319
* return -2 * (z - self.epsilon)
* elif z < self.epsilon:
* return 2 * (-z - self.epsilon) # <<<<<<<<<<<<<<
* else:
* return 0
*/
__pyx_r = (2.0 * ((-__pyx_v_z) - __pyx_v_self->epsilon));
goto __pyx_L0;
goto __pyx_L3;
}
/*else*/ {
/* "sklearn/linear_model/sgd_fast.pyx":321
* return 2 * (-z - self.epsilon)
* else:
* return 0 # <<<<<<<<<<<<<<
*
* def __reduce__(self):
*/
__pyx_r = 0.0;
goto __pyx_L0;
}
__pyx_L3:;
__pyx_r = 0;
goto __pyx_L0;
__pyx_L1_error:;
__Pyx_XDECREF(__pyx_t_1);
__Pyx_XDECREF(__pyx_t_2);
__Pyx_XDECREF(__pyx_t_3);
__Pyx_XDECREF(__pyx_t_4);
__Pyx_WriteUnraisable("sklearn.linear_model.sgd_fast.SquaredEpsilonInsensitive.dloss", __pyx_clineno, __pyx_lineno, __pyx_filename);
__pyx_r = 0;
__pyx_L0:;
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* Python wrapper */
static PyObject *__pyx_pw_7sklearn_12linear_model_8sgd_fast_25SquaredEpsilonInsensitive_5dloss(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/
static PyObject *__pyx_pw_7sklearn_12linear_model_8sgd_fast_25SquaredEpsilonInsensitive_5dloss(PyObject *__pyx_v_self, PyObject *__pyx_args, PyObject *__pyx_kwds) {
double __pyx_v_p;
double __pyx_v_y;
PyObject *__pyx_r = 0;
__Pyx_RefNannyDeclarations
__Pyx_RefNannySetupContext("dloss (wrapper)", 0);
{
static PyObject **__pyx_pyargnames[] = {&__pyx_n_s__p,&__pyx_n_s__y,0};
PyObject* values[2] = {0,0};
if (unlikely(__pyx_kwds)) {
Py_ssize_t kw_args;
const Py_ssize_t pos_args = PyTuple_GET_SIZE(__pyx_args);
switch (pos_args) {
case 2: values[1] = PyTuple_GET_ITEM(__pyx_args, 1);
case 1: values[0] = PyTuple_GET_ITEM(__pyx_args, 0);
case 0: break;
default: goto __pyx_L5_argtuple_error;
}
kw_args = PyDict_Size(__pyx_kwds);
switch (pos_args) {
case 0:
if (likely((values[0] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__p)) != 0)) kw_args--;
else goto __pyx_L5_argtuple_error;
case 1:
if (likely((values[1] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__y)) != 0)) kw_args--;
else {
__Pyx_RaiseArgtupleInvalid("dloss", 1, 2, 2, 1); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 313; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
}
if (unlikely(kw_args > 0)) {
if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, pos_args, "dloss") < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 313; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
} else if (PyTuple_GET_SIZE(__pyx_args) != 2) {
goto __pyx_L5_argtuple_error;
} else {
values[0] = PyTuple_GET_ITEM(__pyx_args, 0);
values[1] = PyTuple_GET_ITEM(__pyx_args, 1);
}
__pyx_v_p = __pyx_PyFloat_AsDouble(values[0]); if (unlikely((__pyx_v_p == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 313; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
__pyx_v_y = __pyx_PyFloat_AsDouble(values[1]); if (unlikely((__pyx_v_y == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 313; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
goto __pyx_L4_argument_unpacking_done;
__pyx_L5_argtuple_error:;
__Pyx_RaiseArgtupleInvalid("dloss", 1, 2, 2, PyTuple_GET_SIZE(__pyx_args)); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 313; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
__pyx_L3_error:;
__Pyx_AddTraceback("sklearn.linear_model.sgd_fast.SquaredEpsilonInsensitive.dloss", __pyx_clineno, __pyx_lineno, __pyx_filename);
__Pyx_RefNannyFinishContext();
return NULL;
__pyx_L4_argument_unpacking_done:;
__pyx_r = __pyx_pf_7sklearn_12linear_model_8sgd_fast_25SquaredEpsilonInsensitive_4dloss(((struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_SquaredEpsilonInsensitive *)__pyx_v_self), __pyx_v_p, __pyx_v_y);
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* "sklearn/linear_model/sgd_fast.pyx":313
* return ret * ret if ret > 0 else 0
*
* cpdef double dloss(self, double p, double y): # <<<<<<<<<<<<<<
* cdef double z
* z = y - p
*/
static PyObject *__pyx_pf_7sklearn_12linear_model_8sgd_fast_25SquaredEpsilonInsensitive_4dloss(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_SquaredEpsilonInsensitive *__pyx_v_self, double __pyx_v_p, double __pyx_v_y) {
PyObject *__pyx_r = NULL;
__Pyx_RefNannyDeclarations
PyObject *__pyx_t_1 = NULL;
int __pyx_lineno = 0;
const char *__pyx_filename = NULL;
int __pyx_clineno = 0;
__Pyx_RefNannySetupContext("dloss", 0);
__Pyx_XDECREF(__pyx_r);
__pyx_t_1 = PyFloat_FromDouble(((struct __pyx_vtabstruct_7sklearn_12linear_model_8sgd_fast_SquaredEpsilonInsensitive *)__pyx_v_self->__pyx_base.__pyx_base.__pyx_vtab)->__pyx_base.__pyx_base.dloss(((struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_LossFunction *)__pyx_v_self), __pyx_v_p, __pyx_v_y, 1)); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 313; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_1);
__pyx_r = __pyx_t_1;
__pyx_t_1 = 0;
goto __pyx_L0;
__pyx_r = Py_None; __Pyx_INCREF(Py_None);
goto __pyx_L0;
__pyx_L1_error:;
__Pyx_XDECREF(__pyx_t_1);
__Pyx_AddTraceback("sklearn.linear_model.sgd_fast.SquaredEpsilonInsensitive.dloss", __pyx_clineno, __pyx_lineno, __pyx_filename);
__pyx_r = NULL;
__pyx_L0:;
__Pyx_XGIVEREF(__pyx_r);
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* Python wrapper */
static PyObject *__pyx_pw_7sklearn_12linear_model_8sgd_fast_25SquaredEpsilonInsensitive_7__reduce__(PyObject *__pyx_v_self, CYTHON_UNUSED PyObject *unused); /*proto*/
static PyObject *__pyx_pw_7sklearn_12linear_model_8sgd_fast_25SquaredEpsilonInsensitive_7__reduce__(PyObject *__pyx_v_self, CYTHON_UNUSED PyObject *unused) {
PyObject *__pyx_r = 0;
__Pyx_RefNannyDeclarations
__Pyx_RefNannySetupContext("__reduce__ (wrapper)", 0);
__pyx_r = __pyx_pf_7sklearn_12linear_model_8sgd_fast_25SquaredEpsilonInsensitive_6__reduce__(((struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_SquaredEpsilonInsensitive *)__pyx_v_self));
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* "sklearn/linear_model/sgd_fast.pyx":323
* return 0
*
* def __reduce__(self): # <<<<<<<<<<<<<<
* return SquaredEpsilonInsensitive, (self.epsilon,)
*
*/
static PyObject *__pyx_pf_7sklearn_12linear_model_8sgd_fast_25SquaredEpsilonInsensitive_6__reduce__(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_SquaredEpsilonInsensitive *__pyx_v_self) {
PyObject *__pyx_r = NULL;
__Pyx_RefNannyDeclarations
PyObject *__pyx_t_1 = NULL;
PyObject *__pyx_t_2 = NULL;
int __pyx_lineno = 0;
const char *__pyx_filename = NULL;
int __pyx_clineno = 0;
__Pyx_RefNannySetupContext("__reduce__", 0);
/* "sklearn/linear_model/sgd_fast.pyx":324
*
* def __reduce__(self):
* return SquaredEpsilonInsensitive, (self.epsilon,) # <<<<<<<<<<<<<<
*
*
*/
__Pyx_XDECREF(__pyx_r);
__pyx_t_1 = PyFloat_FromDouble(__pyx_v_self->epsilon); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 324; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_1);
__pyx_t_2 = PyTuple_New(1); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 324; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_2);
PyTuple_SET_ITEM(__pyx_t_2, 0, __pyx_t_1);
__Pyx_GIVEREF(__pyx_t_1);
__pyx_t_1 = 0;
__pyx_t_1 = PyTuple_New(2); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 324; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_1);
__Pyx_INCREF(((PyObject *)((PyObject*)__pyx_ptype_7sklearn_12linear_model_8sgd_fast_SquaredEpsilonInsensitive)));
PyTuple_SET_ITEM(__pyx_t_1, 0, ((PyObject *)((PyObject*)__pyx_ptype_7sklearn_12linear_model_8sgd_fast_SquaredEpsilonInsensitive)));
__Pyx_GIVEREF(((PyObject *)((PyObject*)__pyx_ptype_7sklearn_12linear_model_8sgd_fast_SquaredEpsilonInsensitive)));
PyTuple_SET_ITEM(__pyx_t_1, 1, ((PyObject *)__pyx_t_2));
__Pyx_GIVEREF(((PyObject *)__pyx_t_2));
__pyx_t_2 = 0;
__pyx_r = ((PyObject *)__pyx_t_1);
__pyx_t_1 = 0;
goto __pyx_L0;
__pyx_r = Py_None; __Pyx_INCREF(Py_None);
goto __pyx_L0;
__pyx_L1_error:;
__Pyx_XDECREF(__pyx_t_1);
__Pyx_XDECREF(__pyx_t_2);
__Pyx_AddTraceback("sklearn.linear_model.sgd_fast.SquaredEpsilonInsensitive.__reduce__", __pyx_clineno, __pyx_lineno, __pyx_filename);
__pyx_r = NULL;
__pyx_L0:;
__Pyx_XGIVEREF(__pyx_r);
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* Python wrapper */
static PyObject *__pyx_pw_7sklearn_12linear_model_8sgd_fast_1plain_sgd(PyObject *__pyx_self, PyObject *__pyx_args, PyObject *__pyx_kwds); /*proto*/
static char __pyx_doc_7sklearn_12linear_model_8sgd_fast_plain_sgd[] = "Plain SGD for generic loss functions and penalties.\n\n Parameters\n ----------\n weights : ndarray[double, ndim=1]\n The allocated coef_ vector.\n intercept : double\n The initial intercept.\n loss : LossFunction\n A concrete ``LossFunction`` object.\n penalty_type : int\n The penalty 2 for L2, 1 for L1, and 3 for Elastic-Net.\n alpha : float\n The regularization parameter.\n rho : float\n The elastic net hyperparameter.\n dataset : SequentialDataset\n A concrete ``SequentialDataset`` object.\n n_iter : int\n The number of iterations (epochs).\n fit_intercept : int\n Whether or not to fit the intercept (1 or 0).\n verbose : int\n Print verbose output; 0 for quite.\n shuffle : int\n Whether to shuffle the training data before each epoch.\n weight_pos : float\n The weight of the positive class.\n weight_neg : float\n The weight of the negative class.\n seed : int or RandomState object\n The seed of the pseudo random number generator to use when\n shuffling the data\n learning_rate : int\n The learning rate:\n (1) constant, eta = eta0\n (2) optimal, eta = 1.0/(t+t0)\n (3) inverse scaling, eta = eta0 / pow(t, power_t)\n (4) Passive Agressive-I, eta = min(alpha, loss/norm(x))\n (5) Passive Agressive-II, eta = 1.0 / (norm(x) + 0.5*alpha)\n eta0 : double\n The initial learning rate.\n power_t : double\n The exponent for inverse scaling learning rate.\n t : double\n Initial state of the learning rate. This value is equal to the\n iteration count except when the learning rate is set to `optimal`.\n Default: 1.0.\n\n Returns\n -------\n weights : array, shape=[n_features]\n The fitted weight vector.\n intercept : float\n The fitted intercept term.\n\n ";
static PyMethodDef __pyx_mdef_7sklearn_12linear_model_8sgd_fast_1plain_sgd = {__Pyx_NAMESTR("plain_sgd"), (PyCFunction)__pyx_pw_7sklearn_12linear_model_8sgd_fast_1plain_sgd, METH_VARARGS|METH_KEYWORDS, __Pyx_DOCSTR(__pyx_doc_7sklearn_12linear_model_8sgd_fast_plain_sgd)};
static PyObject *__pyx_pw_7sklearn_12linear_model_8sgd_fast_1plain_sgd(PyObject *__pyx_self, PyObject *__pyx_args, PyObject *__pyx_kwds) {
PyArrayObject *__pyx_v_weights = 0;
double __pyx_v_intercept;
struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_LossFunction *__pyx_v_loss = 0;
int __pyx_v_penalty_type;
double __pyx_v_alpha;
double __pyx_v_C;
double __pyx_v_rho;
struct __pyx_obj_7sklearn_5utils_11seq_dataset_SequentialDataset *__pyx_v_dataset = 0;
int __pyx_v_n_iter;
int __pyx_v_fit_intercept;
int __pyx_v_verbose;
int __pyx_v_shuffle;
PyObject *__pyx_v_seed = 0;
double __pyx_v_weight_pos;
double __pyx_v_weight_neg;
int __pyx_v_learning_rate;
double __pyx_v_eta0;
double __pyx_v_power_t;
double __pyx_v_t;
double __pyx_v_intercept_decay;
PyObject *__pyx_r = 0;
__Pyx_RefNannyDeclarations
__Pyx_RefNannySetupContext("plain_sgd (wrapper)", 0);
{
static PyObject **__pyx_pyargnames[] = {&__pyx_n_s__weights,&__pyx_n_s__intercept,&__pyx_n_s__loss,&__pyx_n_s__penalty_type,&__pyx_n_s__alpha,&__pyx_n_s__C,&__pyx_n_s__rho,&__pyx_n_s__dataset,&__pyx_n_s__n_iter,&__pyx_n_s__fit_intercept,&__pyx_n_s__verbose,&__pyx_n_s__shuffle,&__pyx_n_s__seed,&__pyx_n_s__weight_pos,&__pyx_n_s__weight_neg,&__pyx_n_s__learning_rate,&__pyx_n_s__eta0,&__pyx_n_s__power_t,&__pyx_n_s__t,&__pyx_n_s__intercept_decay,0};
PyObject* values[20] = {0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0};
if (unlikely(__pyx_kwds)) {
Py_ssize_t kw_args;
const Py_ssize_t pos_args = PyTuple_GET_SIZE(__pyx_args);
switch (pos_args) {
case 20: values[19] = PyTuple_GET_ITEM(__pyx_args, 19);
case 19: values[18] = PyTuple_GET_ITEM(__pyx_args, 18);
case 18: values[17] = PyTuple_GET_ITEM(__pyx_args, 17);
case 17: values[16] = PyTuple_GET_ITEM(__pyx_args, 16);
case 16: values[15] = PyTuple_GET_ITEM(__pyx_args, 15);
case 15: values[14] = PyTuple_GET_ITEM(__pyx_args, 14);
case 14: values[13] = PyTuple_GET_ITEM(__pyx_args, 13);
case 13: values[12] = PyTuple_GET_ITEM(__pyx_args, 12);
case 12: values[11] = PyTuple_GET_ITEM(__pyx_args, 11);
case 11: values[10] = PyTuple_GET_ITEM(__pyx_args, 10);
case 10: values[9] = PyTuple_GET_ITEM(__pyx_args, 9);
case 9: values[8] = PyTuple_GET_ITEM(__pyx_args, 8);
case 8: values[7] = PyTuple_GET_ITEM(__pyx_args, 7);
case 7: values[6] = PyTuple_GET_ITEM(__pyx_args, 6);
case 6: values[5] = PyTuple_GET_ITEM(__pyx_args, 5);
case 5: values[4] = PyTuple_GET_ITEM(__pyx_args, 4);
case 4: values[3] = PyTuple_GET_ITEM(__pyx_args, 3);
case 3: values[2] = PyTuple_GET_ITEM(__pyx_args, 2);
case 2: values[1] = PyTuple_GET_ITEM(__pyx_args, 1);
case 1: values[0] = PyTuple_GET_ITEM(__pyx_args, 0);
case 0: break;
default: goto __pyx_L5_argtuple_error;
}
kw_args = PyDict_Size(__pyx_kwds);
switch (pos_args) {
case 0:
if (likely((values[0] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__weights)) != 0)) kw_args--;
else goto __pyx_L5_argtuple_error;
case 1:
if (likely((values[1] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__intercept)) != 0)) kw_args--;
else {
__Pyx_RaiseArgtupleInvalid("plain_sgd", 0, 18, 20, 1); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 327; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
case 2:
if (likely((values[2] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__loss)) != 0)) kw_args--;
else {
__Pyx_RaiseArgtupleInvalid("plain_sgd", 0, 18, 20, 2); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 327; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
case 3:
if (likely((values[3] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__penalty_type)) != 0)) kw_args--;
else {
__Pyx_RaiseArgtupleInvalid("plain_sgd", 0, 18, 20, 3); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 327; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
case 4:
if (likely((values[4] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__alpha)) != 0)) kw_args--;
else {
__Pyx_RaiseArgtupleInvalid("plain_sgd", 0, 18, 20, 4); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 327; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
case 5:
if (likely((values[5] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__C)) != 0)) kw_args--;
else {
__Pyx_RaiseArgtupleInvalid("plain_sgd", 0, 18, 20, 5); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 327; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
case 6:
if (likely((values[6] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__rho)) != 0)) kw_args--;
else {
__Pyx_RaiseArgtupleInvalid("plain_sgd", 0, 18, 20, 6); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 327; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
case 7:
if (likely((values[7] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__dataset)) != 0)) kw_args--;
else {
__Pyx_RaiseArgtupleInvalid("plain_sgd", 0, 18, 20, 7); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 327; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
case 8:
if (likely((values[8] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__n_iter)) != 0)) kw_args--;
else {
__Pyx_RaiseArgtupleInvalid("plain_sgd", 0, 18, 20, 8); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 327; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
case 9:
if (likely((values[9] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__fit_intercept)) != 0)) kw_args--;
else {
__Pyx_RaiseArgtupleInvalid("plain_sgd", 0, 18, 20, 9); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 327; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
case 10:
if (likely((values[10] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__verbose)) != 0)) kw_args--;
else {
__Pyx_RaiseArgtupleInvalid("plain_sgd", 0, 18, 20, 10); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 327; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
case 11:
if (likely((values[11] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__shuffle)) != 0)) kw_args--;
else {
__Pyx_RaiseArgtupleInvalid("plain_sgd", 0, 18, 20, 11); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 327; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
case 12:
if (likely((values[12] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__seed)) != 0)) kw_args--;
else {
__Pyx_RaiseArgtupleInvalid("plain_sgd", 0, 18, 20, 12); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 327; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
case 13:
if (likely((values[13] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__weight_pos)) != 0)) kw_args--;
else {
__Pyx_RaiseArgtupleInvalid("plain_sgd", 0, 18, 20, 13); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 327; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
case 14:
if (likely((values[14] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__weight_neg)) != 0)) kw_args--;
else {
__Pyx_RaiseArgtupleInvalid("plain_sgd", 0, 18, 20, 14); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 327; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
case 15:
if (likely((values[15] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__learning_rate)) != 0)) kw_args--;
else {
__Pyx_RaiseArgtupleInvalid("plain_sgd", 0, 18, 20, 15); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 327; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
case 16:
if (likely((values[16] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__eta0)) != 0)) kw_args--;
else {
__Pyx_RaiseArgtupleInvalid("plain_sgd", 0, 18, 20, 16); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 327; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
case 17:
if (likely((values[17] = PyDict_GetItem(__pyx_kwds, __pyx_n_s__power_t)) != 0)) kw_args--;
else {
__Pyx_RaiseArgtupleInvalid("plain_sgd", 0, 18, 20, 17); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 327; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
case 18:
if (kw_args > 0) {
PyObject* value = PyDict_GetItem(__pyx_kwds, __pyx_n_s__t);
if (value) { values[18] = value; kw_args--; }
}
case 19:
if (kw_args > 0) {
PyObject* value = PyDict_GetItem(__pyx_kwds, __pyx_n_s__intercept_decay);
if (value) { values[19] = value; kw_args--; }
}
}
if (unlikely(kw_args > 0)) {
if (unlikely(__Pyx_ParseOptionalKeywords(__pyx_kwds, __pyx_pyargnames, 0, values, pos_args, "plain_sgd") < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 327; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
}
} else {
switch (PyTuple_GET_SIZE(__pyx_args)) {
case 20: values[19] = PyTuple_GET_ITEM(__pyx_args, 19);
case 19: values[18] = PyTuple_GET_ITEM(__pyx_args, 18);
case 18: values[17] = PyTuple_GET_ITEM(__pyx_args, 17);
values[16] = PyTuple_GET_ITEM(__pyx_args, 16);
values[15] = PyTuple_GET_ITEM(__pyx_args, 15);
values[14] = PyTuple_GET_ITEM(__pyx_args, 14);
values[13] = PyTuple_GET_ITEM(__pyx_args, 13);
values[12] = PyTuple_GET_ITEM(__pyx_args, 12);
values[11] = PyTuple_GET_ITEM(__pyx_args, 11);
values[10] = PyTuple_GET_ITEM(__pyx_args, 10);
values[9] = PyTuple_GET_ITEM(__pyx_args, 9);
values[8] = PyTuple_GET_ITEM(__pyx_args, 8);
values[7] = PyTuple_GET_ITEM(__pyx_args, 7);
values[6] = PyTuple_GET_ITEM(__pyx_args, 6);
values[5] = PyTuple_GET_ITEM(__pyx_args, 5);
values[4] = PyTuple_GET_ITEM(__pyx_args, 4);
values[3] = PyTuple_GET_ITEM(__pyx_args, 3);
values[2] = PyTuple_GET_ITEM(__pyx_args, 2);
values[1] = PyTuple_GET_ITEM(__pyx_args, 1);
values[0] = PyTuple_GET_ITEM(__pyx_args, 0);
break;
default: goto __pyx_L5_argtuple_error;
}
}
__pyx_v_weights = ((PyArrayObject *)values[0]);
__pyx_v_intercept = __pyx_PyFloat_AsDouble(values[1]); if (unlikely((__pyx_v_intercept == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 328; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
__pyx_v_loss = ((struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_LossFunction *)values[2]);
__pyx_v_penalty_type = __Pyx_PyInt_AsInt(values[3]); if (unlikely((__pyx_v_penalty_type == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 330; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
__pyx_v_alpha = __pyx_PyFloat_AsDouble(values[4]); if (unlikely((__pyx_v_alpha == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 331; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
__pyx_v_C = __pyx_PyFloat_AsDouble(values[5]); if (unlikely((__pyx_v_C == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 331; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
__pyx_v_rho = __pyx_PyFloat_AsDouble(values[6]); if (unlikely((__pyx_v_rho == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 332; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
__pyx_v_dataset = ((struct __pyx_obj_7sklearn_5utils_11seq_dataset_SequentialDataset *)values[7]);
__pyx_v_n_iter = __Pyx_PyInt_AsInt(values[8]); if (unlikely((__pyx_v_n_iter == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 334; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
__pyx_v_fit_intercept = __Pyx_PyInt_AsInt(values[9]); if (unlikely((__pyx_v_fit_intercept == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 334; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
__pyx_v_verbose = __Pyx_PyInt_AsInt(values[10]); if (unlikely((__pyx_v_verbose == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 335; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
__pyx_v_shuffle = __Pyx_PyInt_AsInt(values[11]); if (unlikely((__pyx_v_shuffle == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 335; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
__pyx_v_seed = values[12];
__pyx_v_weight_pos = __pyx_PyFloat_AsDouble(values[13]); if (unlikely((__pyx_v_weight_pos == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 336; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
__pyx_v_weight_neg = __pyx_PyFloat_AsDouble(values[14]); if (unlikely((__pyx_v_weight_neg == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 336; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
__pyx_v_learning_rate = __Pyx_PyInt_AsInt(values[15]); if (unlikely((__pyx_v_learning_rate == (int)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 337; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
__pyx_v_eta0 = __pyx_PyFloat_AsDouble(values[16]); if (unlikely((__pyx_v_eta0 == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 337; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
__pyx_v_power_t = __pyx_PyFloat_AsDouble(values[17]); if (unlikely((__pyx_v_power_t == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 338; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
if (values[18]) {
__pyx_v_t = __pyx_PyFloat_AsDouble(values[18]); if (unlikely((__pyx_v_t == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 339; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
} else {
/* "sklearn/linear_model/sgd_fast.pyx":339
* int learning_rate, double eta0,
* double power_t,
* double t=1.0, # <<<<<<<<<<<<<<
* double intercept_decay=1.0):
* """Plain SGD for generic loss functions and penalties.
*/
__pyx_v_t = ((double)1.0);
}
if (values[19]) {
__pyx_v_intercept_decay = __pyx_PyFloat_AsDouble(values[19]); if (unlikely((__pyx_v_intercept_decay == (double)-1) && PyErr_Occurred())) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 340; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
} else {
/* "sklearn/linear_model/sgd_fast.pyx":340
* double power_t,
* double t=1.0,
* double intercept_decay=1.0): # <<<<<<<<<<<<<<
* """Plain SGD for generic loss functions and penalties.
*
*/
__pyx_v_intercept_decay = ((double)1.0);
}
}
goto __pyx_L4_argument_unpacking_done;
__pyx_L5_argtuple_error:;
__Pyx_RaiseArgtupleInvalid("plain_sgd", 0, 18, 20, PyTuple_GET_SIZE(__pyx_args)); {__pyx_filename = __pyx_f[0]; __pyx_lineno = 327; __pyx_clineno = __LINE__; goto __pyx_L3_error;}
__pyx_L3_error:;
__Pyx_AddTraceback("sklearn.linear_model.sgd_fast.plain_sgd", __pyx_clineno, __pyx_lineno, __pyx_filename);
__Pyx_RefNannyFinishContext();
return NULL;
__pyx_L4_argument_unpacking_done:;
if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v_weights), __pyx_ptype_5numpy_ndarray, 1, "weights", 0))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 327; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v_loss), __pyx_ptype_7sklearn_12linear_model_8sgd_fast_LossFunction, 1, "loss", 0))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 329; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
if (unlikely(!__Pyx_ArgTypeTest(((PyObject *)__pyx_v_dataset), __pyx_ptype_7sklearn_5utils_11seq_dataset_SequentialDataset, 1, "dataset", 0))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 333; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__pyx_r = __pyx_pf_7sklearn_12linear_model_8sgd_fast_plain_sgd(__pyx_self, __pyx_v_weights, __pyx_v_intercept, __pyx_v_loss, __pyx_v_penalty_type, __pyx_v_alpha, __pyx_v_C, __pyx_v_rho, __pyx_v_dataset, __pyx_v_n_iter, __pyx_v_fit_intercept, __pyx_v_verbose, __pyx_v_shuffle, __pyx_v_seed, __pyx_v_weight_pos, __pyx_v_weight_neg, __pyx_v_learning_rate, __pyx_v_eta0, __pyx_v_power_t, __pyx_v_t, __pyx_v_intercept_decay);
goto __pyx_L0;
__pyx_L1_error:;
__pyx_r = NULL;
__pyx_L0:;
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* "sklearn/linear_model/sgd_fast.pyx":327
*
*
* def plain_sgd(np.ndarray[DOUBLE, ndim=1, mode='c'] weights, # <<<<<<<<<<<<<<
* double intercept,
* LossFunction loss,
*/
static PyObject *__pyx_pf_7sklearn_12linear_model_8sgd_fast_plain_sgd(CYTHON_UNUSED PyObject *__pyx_self, PyArrayObject *__pyx_v_weights, double __pyx_v_intercept, struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_LossFunction *__pyx_v_loss, int __pyx_v_penalty_type, double __pyx_v_alpha, double __pyx_v_C, double __pyx_v_rho, struct __pyx_obj_7sklearn_5utils_11seq_dataset_SequentialDataset *__pyx_v_dataset, int __pyx_v_n_iter, int __pyx_v_fit_intercept, int __pyx_v_verbose, int __pyx_v_shuffle, PyObject *__pyx_v_seed, double __pyx_v_weight_pos, double __pyx_v_weight_neg, int __pyx_v_learning_rate, double __pyx_v_eta0, double __pyx_v_power_t, double __pyx_v_t, double __pyx_v_intercept_decay) {
Py_ssize_t __pyx_v_n_samples;
Py_ssize_t __pyx_v_n_features;
struct __pyx_obj_7sklearn_5utils_13weight_vector_WeightVector *__pyx_v_w = 0;
__pyx_t_7sklearn_12linear_model_8sgd_fast_DOUBLE *__pyx_v_x_data_ptr;
__pyx_t_7sklearn_12linear_model_8sgd_fast_INTEGER *__pyx_v_x_ind_ptr;
int __pyx_v_xnnz;
double __pyx_v_eta;
double __pyx_v_p;
double __pyx_v_update;
double __pyx_v_sumloss;
__pyx_t_7sklearn_12linear_model_8sgd_fast_DOUBLE __pyx_v_y;
__pyx_t_7sklearn_12linear_model_8sgd_fast_DOUBLE __pyx_v_sample_weight;
double __pyx_v_class_weight;
unsigned int __pyx_v_count;
unsigned int __pyx_v_epoch;
CYTHON_UNUSED unsigned int __pyx_v_i;
int __pyx_v_is_hinge;
PyArrayObject *__pyx_v_q = 0;
__pyx_t_7sklearn_12linear_model_8sgd_fast_DOUBLE *__pyx_v_q_data_ptr;
double __pyx_v_u;
PyObject *__pyx_v_t_start = NULL;
__Pyx_LocalBuf_ND __pyx_pybuffernd_q;
__Pyx_Buffer __pyx_pybuffer_q;
__Pyx_LocalBuf_ND __pyx_pybuffernd_weights;
__Pyx_Buffer __pyx_pybuffer_weights;
PyObject *__pyx_r = NULL;
__Pyx_RefNannyDeclarations
Py_ssize_t __pyx_t_1;
PyObject *__pyx_t_2 = NULL;
PyObject *__pyx_t_3 = NULL;
int __pyx_t_4;
PyArrayObject *__pyx_t_5 = NULL;
PyObject *__pyx_t_6 = NULL;
PyObject *__pyx_t_7 = NULL;
PyObject *__pyx_t_8 = NULL;
int __pyx_t_9;
PyObject *__pyx_t_10 = NULL;
PyObject *__pyx_t_11 = NULL;
PyObject *__pyx_t_12 = NULL;
unsigned int __pyx_t_13;
unsigned int __pyx_t_14;
PyObject *__pyx_t_15 = NULL;
int __pyx_t_16;
int __pyx_t_17;
int __pyx_t_18;
int __pyx_t_19;
int __pyx_lineno = 0;
const char *__pyx_filename = NULL;
int __pyx_clineno = 0;
__Pyx_RefNannySetupContext("plain_sgd", 0);
__pyx_pybuffer_q.pybuffer.buf = NULL;
__pyx_pybuffer_q.refcount = 0;
__pyx_pybuffernd_q.data = NULL;
__pyx_pybuffernd_q.rcbuffer = &__pyx_pybuffer_q;
__pyx_pybuffer_weights.pybuffer.buf = NULL;
__pyx_pybuffer_weights.refcount = 0;
__pyx_pybuffernd_weights.data = NULL;
__pyx_pybuffernd_weights.rcbuffer = &__pyx_pybuffer_weights;
{
__Pyx_BufFmt_StackElem __pyx_stack[1];
if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_pybuffernd_weights.rcbuffer->pybuffer, (PyObject*)__pyx_v_weights, &__Pyx_TypeInfo_nn___pyx_t_7sklearn_12linear_model_8sgd_fast_DOUBLE, PyBUF_FORMAT| PyBUF_C_CONTIGUOUS, 1, 0, __pyx_stack) == -1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 327; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
}
__pyx_pybuffernd_weights.diminfo[0].strides = __pyx_pybuffernd_weights.rcbuffer->pybuffer.strides[0]; __pyx_pybuffernd_weights.diminfo[0].shape = __pyx_pybuffernd_weights.rcbuffer->pybuffer.shape[0];
/* "sklearn/linear_model/sgd_fast.pyx":400
*
* # get the data information into easy vars
* cdef Py_ssize_t n_samples = dataset.n_samples # <<<<<<<<<<<<<<
* cdef Py_ssize_t n_features = weights.shape[0]
*
*/
__pyx_t_1 = __pyx_v_dataset->n_samples;
__pyx_v_n_samples = __pyx_t_1;
/* "sklearn/linear_model/sgd_fast.pyx":401
* # get the data information into easy vars
* cdef Py_ssize_t n_samples = dataset.n_samples
* cdef Py_ssize_t n_features = weights.shape[0] # <<<<<<<<<<<<<<
*
* cdef WeightVector w = WeightVector(weights)
*/
__pyx_v_n_features = (__pyx_v_weights->dimensions[0]);
/* "sklearn/linear_model/sgd_fast.pyx":403
* cdef Py_ssize_t n_features = weights.shape[0]
*
* cdef WeightVector w = WeightVector(weights) # <<<<<<<<<<<<<<
*
* cdef DOUBLE * x_data_ptr = NULL
*/
__pyx_t_2 = PyTuple_New(1); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 403; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_2);
__Pyx_INCREF(((PyObject *)__pyx_v_weights));
PyTuple_SET_ITEM(__pyx_t_2, 0, ((PyObject *)__pyx_v_weights));
__Pyx_GIVEREF(((PyObject *)__pyx_v_weights));
__pyx_t_3 = PyObject_Call(((PyObject *)((PyObject*)__pyx_ptype_7sklearn_5utils_13weight_vector_WeightVector)), ((PyObject *)__pyx_t_2), NULL); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 403; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_3);
__Pyx_DECREF(((PyObject *)__pyx_t_2)); __pyx_t_2 = 0;
__pyx_v_w = ((struct __pyx_obj_7sklearn_5utils_13weight_vector_WeightVector *)__pyx_t_3);
__pyx_t_3 = 0;
/* "sklearn/linear_model/sgd_fast.pyx":405
* cdef WeightVector w = WeightVector(weights)
*
* cdef DOUBLE * x_data_ptr = NULL # <<<<<<<<<<<<<<
* cdef INTEGER * x_ind_ptr = NULL
*
*/
__pyx_v_x_data_ptr = NULL;
/* "sklearn/linear_model/sgd_fast.pyx":406
*
* cdef DOUBLE * x_data_ptr = NULL
* cdef INTEGER * x_ind_ptr = NULL # <<<<<<<<<<<<<<
*
* # helper variable
*/
__pyx_v_x_ind_ptr = NULL;
/* "sklearn/linear_model/sgd_fast.pyx":410
* # helper variable
* cdef int xnnz
* cdef double eta = 0.0 # <<<<<<<<<<<<<<
* cdef double p = 0.0
* cdef double update = 0.0
*/
__pyx_v_eta = 0.0;
/* "sklearn/linear_model/sgd_fast.pyx":411
* cdef int xnnz
* cdef double eta = 0.0
* cdef double p = 0.0 # <<<<<<<<<<<<<<
* cdef double update = 0.0
* cdef double sumloss = 0.0
*/
__pyx_v_p = 0.0;
/* "sklearn/linear_model/sgd_fast.pyx":412
* cdef double eta = 0.0
* cdef double p = 0.0
* cdef double update = 0.0 # <<<<<<<<<<<<<<
* cdef double sumloss = 0.0
* cdef DOUBLE y = 0.0
*/
__pyx_v_update = 0.0;
/* "sklearn/linear_model/sgd_fast.pyx":413
* cdef double p = 0.0
* cdef double update = 0.0
* cdef double sumloss = 0.0 # <<<<<<<<<<<<<<
* cdef DOUBLE y = 0.0
* cdef DOUBLE sample_weight
*/
__pyx_v_sumloss = 0.0;
/* "sklearn/linear_model/sgd_fast.pyx":414
* cdef double update = 0.0
* cdef double sumloss = 0.0
* cdef DOUBLE y = 0.0 # <<<<<<<<<<<<<<
* cdef DOUBLE sample_weight
* cdef double class_weight = 1.0
*/
__pyx_v_y = 0.0;
/* "sklearn/linear_model/sgd_fast.pyx":416
* cdef DOUBLE y = 0.0
* cdef DOUBLE sample_weight
* cdef double class_weight = 1.0 # <<<<<<<<<<<<<<
* cdef unsigned int count = 0
* cdef unsigned int epoch = 0
*/
__pyx_v_class_weight = 1.0;
/* "sklearn/linear_model/sgd_fast.pyx":417
* cdef DOUBLE sample_weight
* cdef double class_weight = 1.0
* cdef unsigned int count = 0 # <<<<<<<<<<<<<<
* cdef unsigned int epoch = 0
* cdef unsigned int i = 0
*/
__pyx_v_count = 0;
/* "sklearn/linear_model/sgd_fast.pyx":418
* cdef double class_weight = 1.0
* cdef unsigned int count = 0
* cdef unsigned int epoch = 0 # <<<<<<<<<<<<<<
* cdef unsigned int i = 0
* cdef int is_hinge = isinstance(loss, Hinge)
*/
__pyx_v_epoch = 0;
/* "sklearn/linear_model/sgd_fast.pyx":419
* cdef unsigned int count = 0
* cdef unsigned int epoch = 0
* cdef unsigned int i = 0 # <<<<<<<<<<<<<<
* cdef int is_hinge = isinstance(loss, Hinge)
*
*/
__pyx_v_i = 0;
/* "sklearn/linear_model/sgd_fast.pyx":420
* cdef unsigned int epoch = 0
* cdef unsigned int i = 0
* cdef int is_hinge = isinstance(loss, Hinge) # <<<<<<<<<<<<<<
*
* # q vector is only used for L1 regularization
*/
__pyx_t_3 = ((PyObject *)((PyObject*)__pyx_ptype_7sklearn_12linear_model_8sgd_fast_Hinge));
__Pyx_INCREF(__pyx_t_3);
__pyx_t_4 = __Pyx_TypeCheck(((PyObject *)__pyx_v_loss), __pyx_t_3);
__Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0;
__pyx_v_is_hinge = __pyx_t_4;
/* "sklearn/linear_model/sgd_fast.pyx":423
*
* # q vector is only used for L1 regularization
* cdef np.ndarray[DOUBLE, ndim = 1, mode = "c"] q = None # <<<<<<<<<<<<<<
* cdef DOUBLE * q_data_ptr = NULL
* if penalty_type == L1 or penalty_type == ELASTICNET:
*/
__pyx_t_5 = ((PyArrayObject *)Py_None);
{
__Pyx_BufFmt_StackElem __pyx_stack[1];
if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_pybuffernd_q.rcbuffer->pybuffer, (PyObject*)__pyx_t_5, &__Pyx_TypeInfo_nn___pyx_t_7sklearn_12linear_model_8sgd_fast_DOUBLE, PyBUF_FORMAT| PyBUF_C_CONTIGUOUS, 1, 0, __pyx_stack) == -1)) {
__pyx_v_q = ((PyArrayObject *)Py_None); __Pyx_INCREF(Py_None); __pyx_pybuffernd_q.rcbuffer->pybuffer.buf = NULL;
{__pyx_filename = __pyx_f[0]; __pyx_lineno = 423; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
} else {__pyx_pybuffernd_q.diminfo[0].strides = __pyx_pybuffernd_q.rcbuffer->pybuffer.strides[0]; __pyx_pybuffernd_q.diminfo[0].shape = __pyx_pybuffernd_q.rcbuffer->pybuffer.shape[0];
}
}
__pyx_t_5 = 0;
__Pyx_INCREF(Py_None);
__pyx_v_q = ((PyArrayObject *)Py_None);
/* "sklearn/linear_model/sgd_fast.pyx":424
* # q vector is only used for L1 regularization
* cdef np.ndarray[DOUBLE, ndim = 1, mode = "c"] q = None
* cdef DOUBLE * q_data_ptr = NULL # <<<<<<<<<<<<<<
* if penalty_type == L1 or penalty_type == ELASTICNET:
* q = np.zeros((n_features,), dtype=np.float64, order="c")
*/
__pyx_v_q_data_ptr = NULL;
/* "sklearn/linear_model/sgd_fast.pyx":425
* cdef np.ndarray[DOUBLE, ndim = 1, mode = "c"] q = None
* cdef DOUBLE * q_data_ptr = NULL
* if penalty_type == L1 or penalty_type == ELASTICNET: # <<<<<<<<<<<<<<
* q = np.zeros((n_features,), dtype=np.float64, order="c")
* q_data_ptr = <DOUBLE * > q.data
*/
switch (__pyx_v_penalty_type) {
case 1:
case 3:
/* "sklearn/linear_model/sgd_fast.pyx":426
* cdef DOUBLE * q_data_ptr = NULL
* if penalty_type == L1 or penalty_type == ELASTICNET:
* q = np.zeros((n_features,), dtype=np.float64, order="c") # <<<<<<<<<<<<<<
* q_data_ptr = <DOUBLE * > q.data
* cdef double u = 0.0
*/
__pyx_t_3 = __Pyx_GetName(__pyx_m, __pyx_n_s__np); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 426; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_3);
__pyx_t_2 = PyObject_GetAttr(__pyx_t_3, __pyx_n_s__zeros); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 426; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_2);
__Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0;
__pyx_t_3 = PyInt_FromSsize_t(__pyx_v_n_features); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 426; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_3);
__pyx_t_6 = PyTuple_New(1); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 426; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_6);
PyTuple_SET_ITEM(__pyx_t_6, 0, __pyx_t_3);
__Pyx_GIVEREF(__pyx_t_3);
__pyx_t_3 = 0;
__pyx_t_3 = PyTuple_New(1); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 426; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_3);
PyTuple_SET_ITEM(__pyx_t_3, 0, ((PyObject *)__pyx_t_6));
__Pyx_GIVEREF(((PyObject *)__pyx_t_6));
__pyx_t_6 = 0;
__pyx_t_6 = PyDict_New(); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 426; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(((PyObject *)__pyx_t_6));
__pyx_t_7 = __Pyx_GetName(__pyx_m, __pyx_n_s__np); if (unlikely(!__pyx_t_7)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 426; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_7);
__pyx_t_8 = PyObject_GetAttr(__pyx_t_7, __pyx_n_s__float64); if (unlikely(!__pyx_t_8)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 426; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_8);
__Pyx_DECREF(__pyx_t_7); __pyx_t_7 = 0;
if (PyDict_SetItem(__pyx_t_6, ((PyObject *)__pyx_n_s__dtype), __pyx_t_8) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 426; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_DECREF(__pyx_t_8); __pyx_t_8 = 0;
if (PyDict_SetItem(__pyx_t_6, ((PyObject *)__pyx_n_s__order), ((PyObject *)__pyx_n_s__c)) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 426; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__pyx_t_8 = PyObject_Call(__pyx_t_2, ((PyObject *)__pyx_t_3), ((PyObject *)__pyx_t_6)); if (unlikely(!__pyx_t_8)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 426; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_8);
__Pyx_DECREF(__pyx_t_2); __pyx_t_2 = 0;
__Pyx_DECREF(((PyObject *)__pyx_t_3)); __pyx_t_3 = 0;
__Pyx_DECREF(((PyObject *)__pyx_t_6)); __pyx_t_6 = 0;
if (!(likely(((__pyx_t_8) == Py_None) || likely(__Pyx_TypeTest(__pyx_t_8, __pyx_ptype_5numpy_ndarray))))) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 426; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__pyx_t_5 = ((PyArrayObject *)__pyx_t_8);
{
__Pyx_BufFmt_StackElem __pyx_stack[1];
__Pyx_SafeReleaseBuffer(&__pyx_pybuffernd_q.rcbuffer->pybuffer);
__pyx_t_9 = __Pyx_GetBufferAndValidate(&__pyx_pybuffernd_q.rcbuffer->pybuffer, (PyObject*)__pyx_t_5, &__Pyx_TypeInfo_nn___pyx_t_7sklearn_12linear_model_8sgd_fast_DOUBLE, PyBUF_FORMAT| PyBUF_C_CONTIGUOUS, 1, 0, __pyx_stack);
if (unlikely(__pyx_t_9 < 0)) {
PyErr_Fetch(&__pyx_t_10, &__pyx_t_11, &__pyx_t_12);
if (unlikely(__Pyx_GetBufferAndValidate(&__pyx_pybuffernd_q.rcbuffer->pybuffer, (PyObject*)__pyx_v_q, &__Pyx_TypeInfo_nn___pyx_t_7sklearn_12linear_model_8sgd_fast_DOUBLE, PyBUF_FORMAT| PyBUF_C_CONTIGUOUS, 1, 0, __pyx_stack) == -1)) {
Py_XDECREF(__pyx_t_10); Py_XDECREF(__pyx_t_11); Py_XDECREF(__pyx_t_12);
__Pyx_RaiseBufferFallbackError();
} else {
PyErr_Restore(__pyx_t_10, __pyx_t_11, __pyx_t_12);
}
}
__pyx_pybuffernd_q.diminfo[0].strides = __pyx_pybuffernd_q.rcbuffer->pybuffer.strides[0]; __pyx_pybuffernd_q.diminfo[0].shape = __pyx_pybuffernd_q.rcbuffer->pybuffer.shape[0];
if (unlikely(__pyx_t_9 < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 426; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
}
__pyx_t_5 = 0;
__Pyx_DECREF(((PyObject *)__pyx_v_q));
__pyx_v_q = ((PyArrayObject *)__pyx_t_8);
__pyx_t_8 = 0;
/* "sklearn/linear_model/sgd_fast.pyx":427
* if penalty_type == L1 or penalty_type == ELASTICNET:
* q = np.zeros((n_features,), dtype=np.float64, order="c")
* q_data_ptr = <DOUBLE * > q.data # <<<<<<<<<<<<<<
* cdef double u = 0.0
*
*/
__pyx_v_q_data_ptr = ((__pyx_t_7sklearn_12linear_model_8sgd_fast_DOUBLE *)__pyx_v_q->data);
break;
}
/* "sklearn/linear_model/sgd_fast.pyx":428
* q = np.zeros((n_features,), dtype=np.float64, order="c")
* q_data_ptr = <DOUBLE * > q.data
* cdef double u = 0.0 # <<<<<<<<<<<<<<
*
* if penalty_type == L2:
*/
__pyx_v_u = 0.0;
/* "sklearn/linear_model/sgd_fast.pyx":432
* if penalty_type == L2:
* rho = 1.0
* elif penalty_type == L1: # <<<<<<<<<<<<<<
* rho = 0.0
*
*/
switch (__pyx_v_penalty_type) {
/* "sklearn/linear_model/sgd_fast.pyx":430
* cdef double u = 0.0
*
* if penalty_type == L2: # <<<<<<<<<<<<<<
* rho = 1.0
* elif penalty_type == L1:
*/
case 2:
/* "sklearn/linear_model/sgd_fast.pyx":431
*
* if penalty_type == L2:
* rho = 1.0 # <<<<<<<<<<<<<<
* elif penalty_type == L1:
* rho = 0.0
*/
__pyx_v_rho = 1.0;
break;
/* "sklearn/linear_model/sgd_fast.pyx":432
* if penalty_type == L2:
* rho = 1.0
* elif penalty_type == L1: # <<<<<<<<<<<<<<
* rho = 0.0
*
*/
case 1:
/* "sklearn/linear_model/sgd_fast.pyx":433
* rho = 1.0
* elif penalty_type == L1:
* rho = 0.0 # <<<<<<<<<<<<<<
*
* eta = eta0
*/
__pyx_v_rho = 0.0;
break;
}
/* "sklearn/linear_model/sgd_fast.pyx":435
* rho = 0.0
*
* eta = eta0 # <<<<<<<<<<<<<<
*
* t_start = time()
*/
__pyx_v_eta = __pyx_v_eta0;
/* "sklearn/linear_model/sgd_fast.pyx":437
* eta = eta0
*
* t_start = time() # <<<<<<<<<<<<<<
* for epoch in range(n_iter):
* if verbose > 0:
*/
__pyx_t_8 = __Pyx_GetName(__pyx_m, __pyx_n_s__time); if (unlikely(!__pyx_t_8)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 437; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_8);
__pyx_t_6 = PyObject_Call(__pyx_t_8, ((PyObject *)__pyx_empty_tuple), NULL); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 437; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_6);
__Pyx_DECREF(__pyx_t_8); __pyx_t_8 = 0;
__pyx_v_t_start = __pyx_t_6;
__pyx_t_6 = 0;
/* "sklearn/linear_model/sgd_fast.pyx":438
*
* t_start = time()
* for epoch in range(n_iter): # <<<<<<<<<<<<<<
* if verbose > 0:
* print("-- Epoch %d" % (epoch + 1))
*/
__pyx_t_9 = __pyx_v_n_iter;
for (__pyx_t_13 = 0; __pyx_t_13 < __pyx_t_9; __pyx_t_13+=1) {
__pyx_v_epoch = __pyx_t_13;
/* "sklearn/linear_model/sgd_fast.pyx":439
* t_start = time()
* for epoch in range(n_iter):
* if verbose > 0: # <<<<<<<<<<<<<<
* print("-- Epoch %d" % (epoch + 1))
* if shuffle:
*/
__pyx_t_4 = (__pyx_v_verbose > 0);
if (__pyx_t_4) {
/* "sklearn/linear_model/sgd_fast.pyx":440
* for epoch in range(n_iter):
* if verbose > 0:
* print("-- Epoch %d" % (epoch + 1)) # <<<<<<<<<<<<<<
* if shuffle:
* dataset.shuffle(seed)
*/
__pyx_t_6 = PyInt_FromLong((__pyx_v_epoch + 1)); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 440; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_6);
__pyx_t_8 = PyNumber_Remainder(((PyObject *)__pyx_kp_s_1), __pyx_t_6); if (unlikely(!__pyx_t_8)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 440; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(((PyObject *)__pyx_t_8));
__Pyx_DECREF(__pyx_t_6); __pyx_t_6 = 0;
if (__Pyx_PrintOne(0, ((PyObject *)__pyx_t_8)) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 440; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_DECREF(((PyObject *)__pyx_t_8)); __pyx_t_8 = 0;
goto __pyx_L5;
}
__pyx_L5:;
/* "sklearn/linear_model/sgd_fast.pyx":441
* if verbose > 0:
* print("-- Epoch %d" % (epoch + 1))
* if shuffle: # <<<<<<<<<<<<<<
* dataset.shuffle(seed)
* for i in range(n_samples):
*/
if (__pyx_v_shuffle) {
/* "sklearn/linear_model/sgd_fast.pyx":442
* print("-- Epoch %d" % (epoch + 1))
* if shuffle:
* dataset.shuffle(seed) # <<<<<<<<<<<<<<
* for i in range(n_samples):
* dataset.next( & x_data_ptr, & x_ind_ptr, & xnnz, & y,
*/
((struct __pyx_vtabstruct_7sklearn_5utils_11seq_dataset_SequentialDataset *)__pyx_v_dataset->__pyx_vtab)->shuffle(__pyx_v_dataset, __pyx_v_seed);
goto __pyx_L6;
}
__pyx_L6:;
/* "sklearn/linear_model/sgd_fast.pyx":443
* if shuffle:
* dataset.shuffle(seed)
* for i in range(n_samples): # <<<<<<<<<<<<<<
* dataset.next( & x_data_ptr, & x_ind_ptr, & xnnz, & y,
* & sample_weight)
*/
__pyx_t_1 = __pyx_v_n_samples;
for (__pyx_t_14 = 0; __pyx_t_14 < __pyx_t_1; __pyx_t_14+=1) {
__pyx_v_i = __pyx_t_14;
/* "sklearn/linear_model/sgd_fast.pyx":445
* for i in range(n_samples):
* dataset.next( & x_data_ptr, & x_ind_ptr, & xnnz, & y,
* & sample_weight) # <<<<<<<<<<<<<<
*
* p = w.dot(x_data_ptr, x_ind_ptr, xnnz) + intercept
*/
((struct __pyx_vtabstruct_7sklearn_5utils_11seq_dataset_SequentialDataset *)__pyx_v_dataset->__pyx_vtab)->next(__pyx_v_dataset, (&__pyx_v_x_data_ptr), (&__pyx_v_x_ind_ptr), (&__pyx_v_xnnz), (&__pyx_v_y), (&__pyx_v_sample_weight));
/* "sklearn/linear_model/sgd_fast.pyx":447
* & sample_weight)
*
* p = w.dot(x_data_ptr, x_ind_ptr, xnnz) + intercept # <<<<<<<<<<<<<<
*
* if learning_rate == OPTIMAL:
*/
__pyx_v_p = (((struct __pyx_vtabstruct_7sklearn_5utils_13weight_vector_WeightVector *)__pyx_v_w->__pyx_vtab)->dot(__pyx_v_w, __pyx_v_x_data_ptr, __pyx_v_x_ind_ptr, __pyx_v_xnnz) + __pyx_v_intercept);
/* "sklearn/linear_model/sgd_fast.pyx":451
* if learning_rate == OPTIMAL:
* eta = 1.0 / (alpha * t)
* elif learning_rate == INVSCALING: # <<<<<<<<<<<<<<
* eta = eta0 / pow(t, power_t)
*
*/
switch (__pyx_v_learning_rate) {
/* "sklearn/linear_model/sgd_fast.pyx":449
* p = w.dot(x_data_ptr, x_ind_ptr, xnnz) + intercept
*
* if learning_rate == OPTIMAL: # <<<<<<<<<<<<<<
* eta = 1.0 / (alpha * t)
* elif learning_rate == INVSCALING:
*/
case 2:
/* "sklearn/linear_model/sgd_fast.pyx":450
*
* if learning_rate == OPTIMAL:
* eta = 1.0 / (alpha * t) # <<<<<<<<<<<<<<
* elif learning_rate == INVSCALING:
* eta = eta0 / pow(t, power_t)
*/
__pyx_v_eta = (1.0 / (__pyx_v_alpha * __pyx_v_t));
break;
/* "sklearn/linear_model/sgd_fast.pyx":451
* if learning_rate == OPTIMAL:
* eta = 1.0 / (alpha * t)
* elif learning_rate == INVSCALING: # <<<<<<<<<<<<<<
* eta = eta0 / pow(t, power_t)
*
*/
case 3:
/* "sklearn/linear_model/sgd_fast.pyx":452
* eta = 1.0 / (alpha * t)
* elif learning_rate == INVSCALING:
* eta = eta0 / pow(t, power_t) # <<<<<<<<<<<<<<
*
* if verbose > 0:
*/
__pyx_v_eta = (__pyx_v_eta0 / pow(__pyx_v_t, __pyx_v_power_t));
break;
}
/* "sklearn/linear_model/sgd_fast.pyx":454
* eta = eta0 / pow(t, power_t)
*
* if verbose > 0: # <<<<<<<<<<<<<<
* sumloss += loss.loss(p, y)
*
*/
__pyx_t_4 = (__pyx_v_verbose > 0);
if (__pyx_t_4) {
/* "sklearn/linear_model/sgd_fast.pyx":455
*
* if verbose > 0:
* sumloss += loss.loss(p, y) # <<<<<<<<<<<<<<
*
* if y > 0.0:
*/
__pyx_v_sumloss = (__pyx_v_sumloss + ((struct __pyx_vtabstruct_7sklearn_12linear_model_8sgd_fast_LossFunction *)__pyx_v_loss->__pyx_vtab)->loss(__pyx_v_loss, __pyx_v_p, __pyx_v_y, 0));
goto __pyx_L9;
}
__pyx_L9:;
/* "sklearn/linear_model/sgd_fast.pyx":457
* sumloss += loss.loss(p, y)
*
* if y > 0.0: # <<<<<<<<<<<<<<
* class_weight = weight_pos
* else:
*/
__pyx_t_4 = (__pyx_v_y > 0.0);
if (__pyx_t_4) {
/* "sklearn/linear_model/sgd_fast.pyx":458
*
* if y > 0.0:
* class_weight = weight_pos # <<<<<<<<<<<<<<
* else:
* class_weight = weight_neg
*/
__pyx_v_class_weight = __pyx_v_weight_pos;
goto __pyx_L10;
}
/*else*/ {
/* "sklearn/linear_model/sgd_fast.pyx":460
* class_weight = weight_pos
* else:
* class_weight = weight_neg # <<<<<<<<<<<<<<
*
* if learning_rate == PA1:
*/
__pyx_v_class_weight = __pyx_v_weight_neg;
}
__pyx_L10:;
/* "sklearn/linear_model/sgd_fast.pyx":467
* continue
* update = min(C, loss.loss(p, y) / update)
* elif learning_rate == PA2: # <<<<<<<<<<<<<<
* update = sqnorm(x_data_ptr, x_ind_ptr, xnnz)
* update = loss.loss(p, y) / (update + 0.5 / C)
*/
switch (__pyx_v_learning_rate) {
/* "sklearn/linear_model/sgd_fast.pyx":462
* class_weight = weight_neg
*
* if learning_rate == PA1: # <<<<<<<<<<<<<<
* update = sqnorm(x_data_ptr, x_ind_ptr, xnnz)
* if update == 0:
*/
case 4:
/* "sklearn/linear_model/sgd_fast.pyx":463
*
* if learning_rate == PA1:
* update = sqnorm(x_data_ptr, x_ind_ptr, xnnz) # <<<<<<<<<<<<<<
* if update == 0:
* continue
*/
__pyx_v_update = __pyx_f_7sklearn_12linear_model_8sgd_fast_sqnorm(__pyx_v_x_data_ptr, __pyx_v_x_ind_ptr, __pyx_v_xnnz);
/* "sklearn/linear_model/sgd_fast.pyx":464
* if learning_rate == PA1:
* update = sqnorm(x_data_ptr, x_ind_ptr, xnnz)
* if update == 0: # <<<<<<<<<<<<<<
* continue
* update = min(C, loss.loss(p, y) / update)
*/
__pyx_t_4 = (__pyx_v_update == 0.0);
if (__pyx_t_4) {
/* "sklearn/linear_model/sgd_fast.pyx":465
* update = sqnorm(x_data_ptr, x_ind_ptr, xnnz)
* if update == 0:
* continue # <<<<<<<<<<<<<<
* update = min(C, loss.loss(p, y) / update)
* elif learning_rate == PA2:
*/
goto __pyx_L7_continue;
goto __pyx_L11;
}
__pyx_L11:;
/* "sklearn/linear_model/sgd_fast.pyx":466
* if update == 0:
* continue
* update = min(C, loss.loss(p, y) / update) # <<<<<<<<<<<<<<
* elif learning_rate == PA2:
* update = sqnorm(x_data_ptr, x_ind_ptr, xnnz)
*/
__pyx_v_update = __pyx_f_7sklearn_12linear_model_8sgd_fast_min(__pyx_v_C, (((struct __pyx_vtabstruct_7sklearn_12linear_model_8sgd_fast_LossFunction *)__pyx_v_loss->__pyx_vtab)->loss(__pyx_v_loss, __pyx_v_p, __pyx_v_y, 0) / __pyx_v_update));
break;
/* "sklearn/linear_model/sgd_fast.pyx":467
* continue
* update = min(C, loss.loss(p, y) / update)
* elif learning_rate == PA2: # <<<<<<<<<<<<<<
* update = sqnorm(x_data_ptr, x_ind_ptr, xnnz)
* update = loss.loss(p, y) / (update + 0.5 / C)
*/
case 5:
/* "sklearn/linear_model/sgd_fast.pyx":468
* update = min(C, loss.loss(p, y) / update)
* elif learning_rate == PA2:
* update = sqnorm(x_data_ptr, x_ind_ptr, xnnz) # <<<<<<<<<<<<<<
* update = loss.loss(p, y) / (update + 0.5 / C)
* else:
*/
__pyx_v_update = __pyx_f_7sklearn_12linear_model_8sgd_fast_sqnorm(__pyx_v_x_data_ptr, __pyx_v_x_ind_ptr, __pyx_v_xnnz);
/* "sklearn/linear_model/sgd_fast.pyx":469
* elif learning_rate == PA2:
* update = sqnorm(x_data_ptr, x_ind_ptr, xnnz)
* update = loss.loss(p, y) / (update + 0.5 / C) # <<<<<<<<<<<<<<
* else:
* update = -eta * loss.dloss(p, y)
*/
__pyx_v_update = (((struct __pyx_vtabstruct_7sklearn_12linear_model_8sgd_fast_LossFunction *)__pyx_v_loss->__pyx_vtab)->loss(__pyx_v_loss, __pyx_v_p, __pyx_v_y, 0) / (__pyx_v_update + (0.5 / __pyx_v_C)));
break;
default:
/* "sklearn/linear_model/sgd_fast.pyx":471
* update = loss.loss(p, y) / (update + 0.5 / C)
* else:
* update = -eta * loss.dloss(p, y) # <<<<<<<<<<<<<<
*
* if learning_rate >= PA1:
*/
__pyx_v_update = ((-__pyx_v_eta) * ((struct __pyx_vtabstruct_7sklearn_12linear_model_8sgd_fast_LossFunction *)__pyx_v_loss->__pyx_vtab)->dloss(__pyx_v_loss, __pyx_v_p, __pyx_v_y, 0));
break;
}
/* "sklearn/linear_model/sgd_fast.pyx":473
* update = -eta * loss.dloss(p, y)
*
* if learning_rate >= PA1: # <<<<<<<<<<<<<<
* if is_hinge:
* # classification
*/
__pyx_t_4 = (__pyx_v_learning_rate >= 4);
if (__pyx_t_4) {
/* "sklearn/linear_model/sgd_fast.pyx":474
*
* if learning_rate >= PA1:
* if is_hinge: # <<<<<<<<<<<<<<
* # classification
* update *= y
*/
if (__pyx_v_is_hinge) {
/* "sklearn/linear_model/sgd_fast.pyx":476
* if is_hinge:
* # classification
* update *= y # <<<<<<<<<<<<<<
* elif y - p < 0:
* # regression
*/
__pyx_v_update = (__pyx_v_update * __pyx_v_y);
goto __pyx_L13;
}
/* "sklearn/linear_model/sgd_fast.pyx":477
* # classification
* update *= y
* elif y - p < 0: # <<<<<<<<<<<<<<
* # regression
* update *= -1
*/
__pyx_t_4 = ((__pyx_v_y - __pyx_v_p) < 0.0);
if (__pyx_t_4) {
/* "sklearn/linear_model/sgd_fast.pyx":479
* elif y - p < 0:
* # regression
* update *= -1 # <<<<<<<<<<<<<<
*
* update *= class_weight * sample_weight
*/
__pyx_v_update = (__pyx_v_update * -1.0);
goto __pyx_L13;
}
__pyx_L13:;
goto __pyx_L12;
}
__pyx_L12:;
/* "sklearn/linear_model/sgd_fast.pyx":481
* update *= -1
*
* update *= class_weight * sample_weight # <<<<<<<<<<<<<<
*
* if update != 0.0:
*/
__pyx_v_update = (__pyx_v_update * (__pyx_v_class_weight * __pyx_v_sample_weight));
/* "sklearn/linear_model/sgd_fast.pyx":483
* update *= class_weight * sample_weight
*
* if update != 0.0: # <<<<<<<<<<<<<<
* w.add(x_data_ptr, x_ind_ptr, xnnz, update)
* if fit_intercept == 1:
*/
__pyx_t_4 = (__pyx_v_update != 0.0);
if (__pyx_t_4) {
/* "sklearn/linear_model/sgd_fast.pyx":484
*
* if update != 0.0:
* w.add(x_data_ptr, x_ind_ptr, xnnz, update) # <<<<<<<<<<<<<<
* if fit_intercept == 1:
* intercept += update * intercept_decay
*/
((struct __pyx_vtabstruct_7sklearn_5utils_13weight_vector_WeightVector *)__pyx_v_w->__pyx_vtab)->add(__pyx_v_w, __pyx_v_x_data_ptr, __pyx_v_x_ind_ptr, __pyx_v_xnnz, __pyx_v_update);
/* "sklearn/linear_model/sgd_fast.pyx":485
* if update != 0.0:
* w.add(x_data_ptr, x_ind_ptr, xnnz, update)
* if fit_intercept == 1: # <<<<<<<<<<<<<<
* intercept += update * intercept_decay
* if penalty_type >= L2:
*/
__pyx_t_4 = (__pyx_v_fit_intercept == 1);
if (__pyx_t_4) {
/* "sklearn/linear_model/sgd_fast.pyx":486
* w.add(x_data_ptr, x_ind_ptr, xnnz, update)
* if fit_intercept == 1:
* intercept += update * intercept_decay # <<<<<<<<<<<<<<
* if penalty_type >= L2:
* w.scale(1.0 - (rho * eta * alpha))
*/
__pyx_v_intercept = (__pyx_v_intercept + (__pyx_v_update * __pyx_v_intercept_decay));
goto __pyx_L15;
}
__pyx_L15:;
goto __pyx_L14;
}
__pyx_L14:;
/* "sklearn/linear_model/sgd_fast.pyx":487
* if fit_intercept == 1:
* intercept += update * intercept_decay
* if penalty_type >= L2: # <<<<<<<<<<<<<<
* w.scale(1.0 - (rho * eta * alpha))
*
*/
__pyx_t_4 = (__pyx_v_penalty_type >= 2);
if (__pyx_t_4) {
/* "sklearn/linear_model/sgd_fast.pyx":488
* intercept += update * intercept_decay
* if penalty_type >= L2:
* w.scale(1.0 - (rho * eta * alpha)) # <<<<<<<<<<<<<<
*
* if penalty_type == L1 or penalty_type == ELASTICNET:
*/
((struct __pyx_vtabstruct_7sklearn_5utils_13weight_vector_WeightVector *)__pyx_v_w->__pyx_vtab)->scale(__pyx_v_w, (1.0 - ((__pyx_v_rho * __pyx_v_eta) * __pyx_v_alpha)));
goto __pyx_L16;
}
__pyx_L16:;
/* "sklearn/linear_model/sgd_fast.pyx":490
* w.scale(1.0 - (rho * eta * alpha))
*
* if penalty_type == L1 or penalty_type == ELASTICNET: # <<<<<<<<<<<<<<
* u += ((1.0 - rho) * eta * alpha)
* l1penalty(w, q_data_ptr, x_ind_ptr, xnnz, u)
*/
switch (__pyx_v_penalty_type) {
case 1:
case 3:
/* "sklearn/linear_model/sgd_fast.pyx":491
*
* if penalty_type == L1 or penalty_type == ELASTICNET:
* u += ((1.0 - rho) * eta * alpha) # <<<<<<<<<<<<<<
* l1penalty(w, q_data_ptr, x_ind_ptr, xnnz, u)
* t += 1
*/
__pyx_v_u = (__pyx_v_u + (((1.0 - __pyx_v_rho) * __pyx_v_eta) * __pyx_v_alpha));
/* "sklearn/linear_model/sgd_fast.pyx":492
* if penalty_type == L1 or penalty_type == ELASTICNET:
* u += ((1.0 - rho) * eta * alpha)
* l1penalty(w, q_data_ptr, x_ind_ptr, xnnz, u) # <<<<<<<<<<<<<<
* t += 1
* count += 1
*/
__pyx_f_7sklearn_12linear_model_8sgd_fast_l1penalty(__pyx_v_w, __pyx_v_q_data_ptr, __pyx_v_x_ind_ptr, __pyx_v_xnnz, __pyx_v_u);
break;
}
/* "sklearn/linear_model/sgd_fast.pyx":493
* u += ((1.0 - rho) * eta * alpha)
* l1penalty(w, q_data_ptr, x_ind_ptr, xnnz, u)
* t += 1 # <<<<<<<<<<<<<<
* count += 1
*
*/
__pyx_v_t = (__pyx_v_t + 1.0);
/* "sklearn/linear_model/sgd_fast.pyx":494
* l1penalty(w, q_data_ptr, x_ind_ptr, xnnz, u)
* t += 1
* count += 1 # <<<<<<<<<<<<<<
*
* # report epoch information
*/
__pyx_v_count = (__pyx_v_count + 1);
__pyx_L7_continue:;
}
/* "sklearn/linear_model/sgd_fast.pyx":497
*
* # report epoch information
* if verbose > 0: # <<<<<<<<<<<<<<
* print("Norm: %.2f, NNZs: %d, "
* "Bias: %.6f, T: %d, Avg. loss: %.6f" % (w.norm(),
*/
__pyx_t_4 = (__pyx_v_verbose > 0);
if (__pyx_t_4) {
/* "sklearn/linear_model/sgd_fast.pyx":499
* if verbose > 0:
* print("Norm: %.2f, NNZs: %d, "
* "Bias: %.6f, T: %d, Avg. loss: %.6f" % (w.norm(), # <<<<<<<<<<<<<<
* weights.nonzero()[0].shape[0],
* intercept, count,
*/
__pyx_t_8 = PyFloat_FromDouble(((struct __pyx_vtabstruct_7sklearn_5utils_13weight_vector_WeightVector *)__pyx_v_w->__pyx_vtab)->norm(__pyx_v_w)); if (unlikely(!__pyx_t_8)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 499; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_8);
/* "sklearn/linear_model/sgd_fast.pyx":500
* print("Norm: %.2f, NNZs: %d, "
* "Bias: %.6f, T: %d, Avg. loss: %.6f" % (w.norm(),
* weights.nonzero()[0].shape[0], # <<<<<<<<<<<<<<
* intercept, count,
* sumloss / count))
*/
__pyx_t_6 = PyObject_GetAttr(((PyObject *)__pyx_v_weights), __pyx_n_s__nonzero); if (unlikely(!__pyx_t_6)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 500; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_6);
__pyx_t_3 = PyObject_Call(__pyx_t_6, ((PyObject *)__pyx_empty_tuple), NULL); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 500; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_3);
__Pyx_DECREF(__pyx_t_6); __pyx_t_6 = 0;
__pyx_t_6 = __Pyx_GetItemInt(__pyx_t_3, 0, sizeof(long), PyInt_FromLong); if (!__pyx_t_6) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 500; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_6);
__Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0;
__pyx_t_3 = PyObject_GetAttr(__pyx_t_6, __pyx_n_s__shape); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 500; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_3);
__Pyx_DECREF(__pyx_t_6); __pyx_t_6 = 0;
__pyx_t_6 = __Pyx_GetItemInt(__pyx_t_3, 0, sizeof(long), PyInt_FromLong); if (!__pyx_t_6) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 500; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_6);
__Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0;
/* "sklearn/linear_model/sgd_fast.pyx":501
* "Bias: %.6f, T: %d, Avg. loss: %.6f" % (w.norm(),
* weights.nonzero()[0].shape[0],
* intercept, count, # <<<<<<<<<<<<<<
* sumloss / count))
* print("Total training time: %.2f seconds." % (time() - t_start))
*/
__pyx_t_3 = PyFloat_FromDouble(__pyx_v_intercept); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 501; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_3);
__pyx_t_2 = PyLong_FromUnsignedLong(__pyx_v_count); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 501; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_2);
/* "sklearn/linear_model/sgd_fast.pyx":502
* weights.nonzero()[0].shape[0],
* intercept, count,
* sumloss / count)) # <<<<<<<<<<<<<<
* print("Total training time: %.2f seconds." % (time() - t_start))
*
*/
__pyx_t_7 = PyFloat_FromDouble((__pyx_v_sumloss / __pyx_v_count)); if (unlikely(!__pyx_t_7)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 502; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_7);
__pyx_t_15 = PyTuple_New(5); if (unlikely(!__pyx_t_15)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 499; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_15);
PyTuple_SET_ITEM(__pyx_t_15, 0, __pyx_t_8);
__Pyx_GIVEREF(__pyx_t_8);
PyTuple_SET_ITEM(__pyx_t_15, 1, __pyx_t_6);
__Pyx_GIVEREF(__pyx_t_6);
PyTuple_SET_ITEM(__pyx_t_15, 2, __pyx_t_3);
__Pyx_GIVEREF(__pyx_t_3);
PyTuple_SET_ITEM(__pyx_t_15, 3, __pyx_t_2);
__Pyx_GIVEREF(__pyx_t_2);
PyTuple_SET_ITEM(__pyx_t_15, 4, __pyx_t_7);
__Pyx_GIVEREF(__pyx_t_7);
__pyx_t_8 = 0;
__pyx_t_6 = 0;
__pyx_t_3 = 0;
__pyx_t_2 = 0;
__pyx_t_7 = 0;
__pyx_t_7 = PyNumber_Remainder(((PyObject *)__pyx_kp_s_2), ((PyObject *)__pyx_t_15)); if (unlikely(!__pyx_t_7)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 499; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(((PyObject *)__pyx_t_7));
__Pyx_DECREF(((PyObject *)__pyx_t_15)); __pyx_t_15 = 0;
if (__Pyx_PrintOne(0, ((PyObject *)__pyx_t_7)) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 498; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_DECREF(((PyObject *)__pyx_t_7)); __pyx_t_7 = 0;
/* "sklearn/linear_model/sgd_fast.pyx":503
* intercept, count,
* sumloss / count))
* print("Total training time: %.2f seconds." % (time() - t_start)) # <<<<<<<<<<<<<<
*
* # floating-point under-/overflow check.
*/
__pyx_t_7 = __Pyx_GetName(__pyx_m, __pyx_n_s__time); if (unlikely(!__pyx_t_7)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 503; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_7);
__pyx_t_15 = PyObject_Call(__pyx_t_7, ((PyObject *)__pyx_empty_tuple), NULL); if (unlikely(!__pyx_t_15)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 503; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_15);
__Pyx_DECREF(__pyx_t_7); __pyx_t_7 = 0;
__pyx_t_7 = PyNumber_Subtract(__pyx_t_15, __pyx_v_t_start); if (unlikely(!__pyx_t_7)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 503; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_7);
__Pyx_DECREF(__pyx_t_15); __pyx_t_15 = 0;
__pyx_t_15 = PyNumber_Remainder(((PyObject *)__pyx_kp_s_3), __pyx_t_7); if (unlikely(!__pyx_t_15)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 503; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(((PyObject *)__pyx_t_15));
__Pyx_DECREF(__pyx_t_7); __pyx_t_7 = 0;
if (__Pyx_PrintOne(0, ((PyObject *)__pyx_t_15)) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 503; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_DECREF(((PyObject *)__pyx_t_15)); __pyx_t_15 = 0;
goto __pyx_L17;
}
__pyx_L17:;
/* "sklearn/linear_model/sgd_fast.pyx":506
*
* # floating-point under-/overflow check.
* if np.any(np.isinf(weights)) or np.any(np.isnan(weights)) \ # <<<<<<<<<<<<<<
* or np.isnan(intercept) or np.isinf(intercept):
* raise ValueError("floating-point under-/overflow occured.")
*/
__pyx_t_15 = __Pyx_GetName(__pyx_m, __pyx_n_s__np); if (unlikely(!__pyx_t_15)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 506; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_15);
__pyx_t_7 = PyObject_GetAttr(__pyx_t_15, __pyx_n_s__any); if (unlikely(!__pyx_t_7)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 506; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_7);
__Pyx_DECREF(__pyx_t_15); __pyx_t_15 = 0;
__pyx_t_15 = __Pyx_GetName(__pyx_m, __pyx_n_s__np); if (unlikely(!__pyx_t_15)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 506; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_15);
__pyx_t_2 = PyObject_GetAttr(__pyx_t_15, __pyx_n_s__isinf); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 506; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_2);
__Pyx_DECREF(__pyx_t_15); __pyx_t_15 = 0;
__pyx_t_15 = PyTuple_New(1); if (unlikely(!__pyx_t_15)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 506; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_15);
__Pyx_INCREF(((PyObject *)__pyx_v_weights));
PyTuple_SET_ITEM(__pyx_t_15, 0, ((PyObject *)__pyx_v_weights));
__Pyx_GIVEREF(((PyObject *)__pyx_v_weights));
__pyx_t_3 = PyObject_Call(__pyx_t_2, ((PyObject *)__pyx_t_15), NULL); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 506; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_3);
__Pyx_DECREF(__pyx_t_2); __pyx_t_2 = 0;
__Pyx_DECREF(((PyObject *)__pyx_t_15)); __pyx_t_15 = 0;
__pyx_t_15 = PyTuple_New(1); if (unlikely(!__pyx_t_15)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 506; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_15);
PyTuple_SET_ITEM(__pyx_t_15, 0, __pyx_t_3);
__Pyx_GIVEREF(__pyx_t_3);
__pyx_t_3 = 0;
__pyx_t_3 = PyObject_Call(__pyx_t_7, ((PyObject *)__pyx_t_15), NULL); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 506; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_3);
__Pyx_DECREF(__pyx_t_7); __pyx_t_7 = 0;
__Pyx_DECREF(((PyObject *)__pyx_t_15)); __pyx_t_15 = 0;
__pyx_t_4 = __Pyx_PyObject_IsTrue(__pyx_t_3); if (unlikely(__pyx_t_4 < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 506; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0;
if (!__pyx_t_4) {
/* "sklearn/linear_model/sgd_fast.pyx":507
* # floating-point under-/overflow check.
* if np.any(np.isinf(weights)) or np.any(np.isnan(weights)) \
* or np.isnan(intercept) or np.isinf(intercept): # <<<<<<<<<<<<<<
* raise ValueError("floating-point under-/overflow occured.")
*
*/
__pyx_t_3 = __Pyx_GetName(__pyx_m, __pyx_n_s__np); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 506; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_3);
__pyx_t_15 = PyObject_GetAttr(__pyx_t_3, __pyx_n_s__any); if (unlikely(!__pyx_t_15)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 506; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_15);
__Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0;
/* "sklearn/linear_model/sgd_fast.pyx":506
*
* # floating-point under-/overflow check.
* if np.any(np.isinf(weights)) or np.any(np.isnan(weights)) \ # <<<<<<<<<<<<<<
* or np.isnan(intercept) or np.isinf(intercept):
* raise ValueError("floating-point under-/overflow occured.")
*/
__pyx_t_3 = __Pyx_GetName(__pyx_m, __pyx_n_s__np); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 506; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_3);
__pyx_t_7 = PyObject_GetAttr(__pyx_t_3, __pyx_n_s__isnan); if (unlikely(!__pyx_t_7)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 506; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_7);
__Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0;
__pyx_t_3 = PyTuple_New(1); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 506; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_3);
__Pyx_INCREF(((PyObject *)__pyx_v_weights));
PyTuple_SET_ITEM(__pyx_t_3, 0, ((PyObject *)__pyx_v_weights));
__Pyx_GIVEREF(((PyObject *)__pyx_v_weights));
__pyx_t_2 = PyObject_Call(__pyx_t_7, ((PyObject *)__pyx_t_3), NULL); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 506; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_2);
__Pyx_DECREF(__pyx_t_7); __pyx_t_7 = 0;
__Pyx_DECREF(((PyObject *)__pyx_t_3)); __pyx_t_3 = 0;
__pyx_t_3 = PyTuple_New(1); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 506; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_3);
PyTuple_SET_ITEM(__pyx_t_3, 0, __pyx_t_2);
__Pyx_GIVEREF(__pyx_t_2);
__pyx_t_2 = 0;
__pyx_t_2 = PyObject_Call(__pyx_t_15, ((PyObject *)__pyx_t_3), NULL); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 506; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_2);
__Pyx_DECREF(__pyx_t_15); __pyx_t_15 = 0;
__Pyx_DECREF(((PyObject *)__pyx_t_3)); __pyx_t_3 = 0;
__pyx_t_16 = __Pyx_PyObject_IsTrue(__pyx_t_2); if (unlikely(__pyx_t_16 < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 506; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_DECREF(__pyx_t_2); __pyx_t_2 = 0;
if (!__pyx_t_16) {
/* "sklearn/linear_model/sgd_fast.pyx":507
* # floating-point under-/overflow check.
* if np.any(np.isinf(weights)) or np.any(np.isnan(weights)) \
* or np.isnan(intercept) or np.isinf(intercept): # <<<<<<<<<<<<<<
* raise ValueError("floating-point under-/overflow occured.")
*
*/
__pyx_t_2 = __Pyx_GetName(__pyx_m, __pyx_n_s__np); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 507; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_2);
__pyx_t_3 = PyObject_GetAttr(__pyx_t_2, __pyx_n_s__isnan); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 507; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_3);
__Pyx_DECREF(__pyx_t_2); __pyx_t_2 = 0;
__pyx_t_2 = PyFloat_FromDouble(__pyx_v_intercept); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 507; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_2);
__pyx_t_15 = PyTuple_New(1); if (unlikely(!__pyx_t_15)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 507; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_15);
PyTuple_SET_ITEM(__pyx_t_15, 0, __pyx_t_2);
__Pyx_GIVEREF(__pyx_t_2);
__pyx_t_2 = 0;
__pyx_t_2 = PyObject_Call(__pyx_t_3, ((PyObject *)__pyx_t_15), NULL); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 507; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_2);
__Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0;
__Pyx_DECREF(((PyObject *)__pyx_t_15)); __pyx_t_15 = 0;
__pyx_t_17 = __Pyx_PyObject_IsTrue(__pyx_t_2); if (unlikely(__pyx_t_17 < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 507; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_DECREF(__pyx_t_2); __pyx_t_2 = 0;
if (!__pyx_t_17) {
__pyx_t_2 = __Pyx_GetName(__pyx_m, __pyx_n_s__np); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 507; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_2);
__pyx_t_15 = PyObject_GetAttr(__pyx_t_2, __pyx_n_s__isinf); if (unlikely(!__pyx_t_15)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 507; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_15);
__Pyx_DECREF(__pyx_t_2); __pyx_t_2 = 0;
__pyx_t_2 = PyFloat_FromDouble(__pyx_v_intercept); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 507; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_2);
__pyx_t_3 = PyTuple_New(1); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 507; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_3);
PyTuple_SET_ITEM(__pyx_t_3, 0, __pyx_t_2);
__Pyx_GIVEREF(__pyx_t_2);
__pyx_t_2 = 0;
__pyx_t_2 = PyObject_Call(__pyx_t_15, ((PyObject *)__pyx_t_3), NULL); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 507; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_2);
__Pyx_DECREF(__pyx_t_15); __pyx_t_15 = 0;
__Pyx_DECREF(((PyObject *)__pyx_t_3)); __pyx_t_3 = 0;
__pyx_t_18 = __Pyx_PyObject_IsTrue(__pyx_t_2); if (unlikely(__pyx_t_18 < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 507; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_DECREF(__pyx_t_2); __pyx_t_2 = 0;
__pyx_t_19 = __pyx_t_18;
} else {
__pyx_t_19 = __pyx_t_17;
}
__pyx_t_17 = __pyx_t_19;
} else {
__pyx_t_17 = __pyx_t_16;
}
__pyx_t_16 = __pyx_t_17;
} else {
__pyx_t_16 = __pyx_t_4;
}
if (__pyx_t_16) {
/* "sklearn/linear_model/sgd_fast.pyx":508
* if np.any(np.isinf(weights)) or np.any(np.isnan(weights)) \
* or np.isnan(intercept) or np.isinf(intercept):
* raise ValueError("floating-point under-/overflow occured.") # <<<<<<<<<<<<<<
*
* w.reset_wscale()
*/
__pyx_t_2 = PyObject_Call(__pyx_builtin_ValueError, ((PyObject *)__pyx_k_tuple_5), NULL); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 508; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_2);
__Pyx_Raise(__pyx_t_2, 0, 0, 0);
__Pyx_DECREF(__pyx_t_2); __pyx_t_2 = 0;
{__pyx_filename = __pyx_f[0]; __pyx_lineno = 508; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
goto __pyx_L18;
}
__pyx_L18:;
}
/* "sklearn/linear_model/sgd_fast.pyx":510
* raise ValueError("floating-point under-/overflow occured.")
*
* w.reset_wscale() # <<<<<<<<<<<<<<
*
* return weights, intercept
*/
((struct __pyx_vtabstruct_7sklearn_5utils_13weight_vector_WeightVector *)__pyx_v_w->__pyx_vtab)->reset_wscale(__pyx_v_w);
/* "sklearn/linear_model/sgd_fast.pyx":512
* w.reset_wscale()
*
* return weights, intercept # <<<<<<<<<<<<<<
*
*
*/
__Pyx_XDECREF(__pyx_r);
__pyx_t_2 = PyFloat_FromDouble(__pyx_v_intercept); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 512; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_2);
__pyx_t_3 = PyTuple_New(2); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 512; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_3);
__Pyx_INCREF(((PyObject *)__pyx_v_weights));
PyTuple_SET_ITEM(__pyx_t_3, 0, ((PyObject *)__pyx_v_weights));
__Pyx_GIVEREF(((PyObject *)__pyx_v_weights));
PyTuple_SET_ITEM(__pyx_t_3, 1, __pyx_t_2);
__Pyx_GIVEREF(__pyx_t_2);
__pyx_t_2 = 0;
__pyx_r = ((PyObject *)__pyx_t_3);
__pyx_t_3 = 0;
goto __pyx_L0;
__pyx_r = Py_None; __Pyx_INCREF(Py_None);
goto __pyx_L0;
__pyx_L1_error:;
__Pyx_XDECREF(__pyx_t_2);
__Pyx_XDECREF(__pyx_t_3);
__Pyx_XDECREF(__pyx_t_6);
__Pyx_XDECREF(__pyx_t_7);
__Pyx_XDECREF(__pyx_t_8);
__Pyx_XDECREF(__pyx_t_15);
{ PyObject *__pyx_type, *__pyx_value, *__pyx_tb;
__Pyx_ErrFetch(&__pyx_type, &__pyx_value, &__pyx_tb);
__Pyx_SafeReleaseBuffer(&__pyx_pybuffernd_q.rcbuffer->pybuffer);
__Pyx_SafeReleaseBuffer(&__pyx_pybuffernd_weights.rcbuffer->pybuffer);
__Pyx_ErrRestore(__pyx_type, __pyx_value, __pyx_tb);}
__Pyx_AddTraceback("sklearn.linear_model.sgd_fast.plain_sgd", __pyx_clineno, __pyx_lineno, __pyx_filename);
__pyx_r = NULL;
goto __pyx_L2;
__pyx_L0:;
__Pyx_SafeReleaseBuffer(&__pyx_pybuffernd_q.rcbuffer->pybuffer);
__Pyx_SafeReleaseBuffer(&__pyx_pybuffernd_weights.rcbuffer->pybuffer);
__pyx_L2:;
__Pyx_XDECREF((PyObject *)__pyx_v_w);
__Pyx_XDECREF((PyObject *)__pyx_v_q);
__Pyx_XDECREF(__pyx_v_t_start);
__Pyx_XGIVEREF(__pyx_r);
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* "sklearn/linear_model/sgd_fast.pyx":515
*
*
* cdef inline double max(double a, double b): # <<<<<<<<<<<<<<
* return a if a >= b else b
*
*/
static CYTHON_INLINE double __pyx_f_7sklearn_12linear_model_8sgd_fast_max(double __pyx_v_a, double __pyx_v_b) {
double __pyx_r;
__Pyx_RefNannyDeclarations
double __pyx_t_1;
__Pyx_RefNannySetupContext("max", 0);
/* "sklearn/linear_model/sgd_fast.pyx":516
*
* cdef inline double max(double a, double b):
* return a if a >= b else b # <<<<<<<<<<<<<<
*
*
*/
if ((__pyx_v_a >= __pyx_v_b)) {
__pyx_t_1 = __pyx_v_a;
} else {
__pyx_t_1 = __pyx_v_b;
}
__pyx_r = __pyx_t_1;
goto __pyx_L0;
__pyx_r = 0;
__pyx_L0:;
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* "sklearn/linear_model/sgd_fast.pyx":519
*
*
* cdef inline double min(double a, double b): # <<<<<<<<<<<<<<
* return a if a <= b else b
*
*/
static CYTHON_INLINE double __pyx_f_7sklearn_12linear_model_8sgd_fast_min(double __pyx_v_a, double __pyx_v_b) {
double __pyx_r;
__Pyx_RefNannyDeclarations
double __pyx_t_1;
__Pyx_RefNannySetupContext("min", 0);
/* "sklearn/linear_model/sgd_fast.pyx":520
*
* cdef inline double min(double a, double b):
* return a if a <= b else b # <<<<<<<<<<<<<<
*
* cdef double sqnorm(DOUBLE * x_data_ptr, INTEGER * x_ind_ptr, int xnnz):
*/
if ((__pyx_v_a <= __pyx_v_b)) {
__pyx_t_1 = __pyx_v_a;
} else {
__pyx_t_1 = __pyx_v_b;
}
__pyx_r = __pyx_t_1;
goto __pyx_L0;
__pyx_r = 0;
__pyx_L0:;
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* "sklearn/linear_model/sgd_fast.pyx":522
* return a if a <= b else b
*
* cdef double sqnorm(DOUBLE * x_data_ptr, INTEGER * x_ind_ptr, int xnnz): # <<<<<<<<<<<<<<
* cdef double x_norm = 0.0
* cdef int j
*/
static double __pyx_f_7sklearn_12linear_model_8sgd_fast_sqnorm(__pyx_t_7sklearn_12linear_model_8sgd_fast_DOUBLE *__pyx_v_x_data_ptr, CYTHON_UNUSED __pyx_t_7sklearn_12linear_model_8sgd_fast_INTEGER *__pyx_v_x_ind_ptr, int __pyx_v_xnnz) {
double __pyx_v_x_norm;
int __pyx_v_j;
double __pyx_v_z;
double __pyx_r;
__Pyx_RefNannyDeclarations
int __pyx_t_1;
int __pyx_t_2;
__Pyx_RefNannySetupContext("sqnorm", 0);
/* "sklearn/linear_model/sgd_fast.pyx":523
*
* cdef double sqnorm(DOUBLE * x_data_ptr, INTEGER * x_ind_ptr, int xnnz):
* cdef double x_norm = 0.0 # <<<<<<<<<<<<<<
* cdef int j
* cdef double z
*/
__pyx_v_x_norm = 0.0;
/* "sklearn/linear_model/sgd_fast.pyx":526
* cdef int j
* cdef double z
* for j in range(xnnz): # <<<<<<<<<<<<<<
* z = x_data_ptr[j]
* x_norm += z * z
*/
__pyx_t_1 = __pyx_v_xnnz;
for (__pyx_t_2 = 0; __pyx_t_2 < __pyx_t_1; __pyx_t_2+=1) {
__pyx_v_j = __pyx_t_2;
/* "sklearn/linear_model/sgd_fast.pyx":527
* cdef double z
* for j in range(xnnz):
* z = x_data_ptr[j] # <<<<<<<<<<<<<<
* x_norm += z * z
* return x_norm
*/
__pyx_v_z = (__pyx_v_x_data_ptr[__pyx_v_j]);
/* "sklearn/linear_model/sgd_fast.pyx":528
* for j in range(xnnz):
* z = x_data_ptr[j]
* x_norm += z * z # <<<<<<<<<<<<<<
* return x_norm
*
*/
__pyx_v_x_norm = (__pyx_v_x_norm + (__pyx_v_z * __pyx_v_z));
}
/* "sklearn/linear_model/sgd_fast.pyx":529
* z = x_data_ptr[j]
* x_norm += z * z
* return x_norm # <<<<<<<<<<<<<<
*
* cdef void l1penalty(WeightVector w, DOUBLE * q_data_ptr,
*/
__pyx_r = __pyx_v_x_norm;
goto __pyx_L0;
__pyx_r = 0;
__pyx_L0:;
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* "sklearn/linear_model/sgd_fast.pyx":531
* return x_norm
*
* cdef void l1penalty(WeightVector w, DOUBLE * q_data_ptr, # <<<<<<<<<<<<<<
* INTEGER * x_ind_ptr, int xnnz, double u):
* """Apply the L1 penalty to each updated feature
*/
static void __pyx_f_7sklearn_12linear_model_8sgd_fast_l1penalty(struct __pyx_obj_7sklearn_5utils_13weight_vector_WeightVector *__pyx_v_w, __pyx_t_7sklearn_12linear_model_8sgd_fast_DOUBLE *__pyx_v_q_data_ptr, __pyx_t_7sklearn_12linear_model_8sgd_fast_INTEGER *__pyx_v_x_ind_ptr, int __pyx_v_xnnz, double __pyx_v_u) {
double __pyx_v_z;
int __pyx_v_j;
int __pyx_v_idx;
double __pyx_v_wscale;
double *__pyx_v_w_data_ptr;
__Pyx_RefNannyDeclarations
double __pyx_t_1;
__pyx_t_7sklearn_5utils_13weight_vector_DOUBLE *__pyx_t_2;
int __pyx_t_3;
int __pyx_t_4;
int __pyx_t_5;
int __pyx_t_6;
__Pyx_RefNannySetupContext("l1penalty", 0);
/* "sklearn/linear_model/sgd_fast.pyx":538
* [Tsuruoka, Y., Tsujii, J., and Ananiadou, S., 2009].
* """
* cdef double z = 0.0 # <<<<<<<<<<<<<<
* cdef int j = 0
* cdef int idx = 0
*/
__pyx_v_z = 0.0;
/* "sklearn/linear_model/sgd_fast.pyx":539
* """
* cdef double z = 0.0
* cdef int j = 0 # <<<<<<<<<<<<<<
* cdef int idx = 0
* cdef double wscale = w.wscale
*/
__pyx_v_j = 0;
/* "sklearn/linear_model/sgd_fast.pyx":540
* cdef double z = 0.0
* cdef int j = 0
* cdef int idx = 0 # <<<<<<<<<<<<<<
* cdef double wscale = w.wscale
* cdef double * w_data_ptr = w.w_data_ptr
*/
__pyx_v_idx = 0;
/* "sklearn/linear_model/sgd_fast.pyx":541
* cdef int j = 0
* cdef int idx = 0
* cdef double wscale = w.wscale # <<<<<<<<<<<<<<
* cdef double * w_data_ptr = w.w_data_ptr
* for j in range(xnnz):
*/
__pyx_t_1 = __pyx_v_w->wscale;
__pyx_v_wscale = __pyx_t_1;
/* "sklearn/linear_model/sgd_fast.pyx":542
* cdef int idx = 0
* cdef double wscale = w.wscale
* cdef double * w_data_ptr = w.w_data_ptr # <<<<<<<<<<<<<<
* for j in range(xnnz):
* idx = x_ind_ptr[j]
*/
__pyx_t_2 = __pyx_v_w->w_data_ptr;
__pyx_v_w_data_ptr = __pyx_t_2;
/* "sklearn/linear_model/sgd_fast.pyx":543
* cdef double wscale = w.wscale
* cdef double * w_data_ptr = w.w_data_ptr
* for j in range(xnnz): # <<<<<<<<<<<<<<
* idx = x_ind_ptr[j]
* z = w_data_ptr[idx]
*/
__pyx_t_3 = __pyx_v_xnnz;
for (__pyx_t_4 = 0; __pyx_t_4 < __pyx_t_3; __pyx_t_4+=1) {
__pyx_v_j = __pyx_t_4;
/* "sklearn/linear_model/sgd_fast.pyx":544
* cdef double * w_data_ptr = w.w_data_ptr
* for j in range(xnnz):
* idx = x_ind_ptr[j] # <<<<<<<<<<<<<<
* z = w_data_ptr[idx]
* if (wscale * w_data_ptr[idx]) > 0.0:
*/
__pyx_v_idx = (__pyx_v_x_ind_ptr[__pyx_v_j]);
/* "sklearn/linear_model/sgd_fast.pyx":545
* for j in range(xnnz):
* idx = x_ind_ptr[j]
* z = w_data_ptr[idx] # <<<<<<<<<<<<<<
* if (wscale * w_data_ptr[idx]) > 0.0:
* w_data_ptr[idx] = max(
*/
__pyx_v_z = (__pyx_v_w_data_ptr[__pyx_v_idx]);
/* "sklearn/linear_model/sgd_fast.pyx":546
* idx = x_ind_ptr[j]
* z = w_data_ptr[idx]
* if (wscale * w_data_ptr[idx]) > 0.0: # <<<<<<<<<<<<<<
* w_data_ptr[idx] = max(
* 0.0, w_data_ptr[idx] - ((u + q_data_ptr[idx]) / wscale))
*/
__pyx_t_5 = ((__pyx_v_wscale * (__pyx_v_w_data_ptr[__pyx_v_idx])) > 0.0);
if (__pyx_t_5) {
/* "sklearn/linear_model/sgd_fast.pyx":547
* z = w_data_ptr[idx]
* if (wscale * w_data_ptr[idx]) > 0.0:
* w_data_ptr[idx] = max( # <<<<<<<<<<<<<<
* 0.0, w_data_ptr[idx] - ((u + q_data_ptr[idx]) / wscale))
*
*/
(__pyx_v_w_data_ptr[__pyx_v_idx]) = __pyx_f_7sklearn_12linear_model_8sgd_fast_max(0.0, ((__pyx_v_w_data_ptr[__pyx_v_idx]) - ((__pyx_v_u + (__pyx_v_q_data_ptr[__pyx_v_idx])) / __pyx_v_wscale)));
goto __pyx_L5;
}
/* "sklearn/linear_model/sgd_fast.pyx":550
* 0.0, w_data_ptr[idx] - ((u + q_data_ptr[idx]) / wscale))
*
* elif (wscale * w_data_ptr[idx]) < 0.0: # <<<<<<<<<<<<<<
* w_data_ptr[idx] = min(
* 0.0, w_data_ptr[idx] + ((u - q_data_ptr[idx]) / wscale))
*/
__pyx_t_5 = ((__pyx_v_wscale * (__pyx_v_w_data_ptr[__pyx_v_idx])) < 0.0);
if (__pyx_t_5) {
/* "sklearn/linear_model/sgd_fast.pyx":551
*
* elif (wscale * w_data_ptr[idx]) < 0.0:
* w_data_ptr[idx] = min( # <<<<<<<<<<<<<<
* 0.0, w_data_ptr[idx] + ((u - q_data_ptr[idx]) / wscale))
*
*/
(__pyx_v_w_data_ptr[__pyx_v_idx]) = __pyx_f_7sklearn_12linear_model_8sgd_fast_min(0.0, ((__pyx_v_w_data_ptr[__pyx_v_idx]) + ((__pyx_v_u - (__pyx_v_q_data_ptr[__pyx_v_idx])) / __pyx_v_wscale)));
goto __pyx_L5;
}
__pyx_L5:;
/* "sklearn/linear_model/sgd_fast.pyx":554
* 0.0, w_data_ptr[idx] + ((u - q_data_ptr[idx]) / wscale))
*
* q_data_ptr[idx] += (wscale * (w_data_ptr[idx] - z)) # <<<<<<<<<<<<<<
*/
__pyx_t_6 = __pyx_v_idx;
(__pyx_v_q_data_ptr[__pyx_t_6]) = ((__pyx_v_q_data_ptr[__pyx_t_6]) + (__pyx_v_wscale * ((__pyx_v_w_data_ptr[__pyx_v_idx]) - __pyx_v_z)));
}
__Pyx_RefNannyFinishContext();
}
/* Python wrapper */
static CYTHON_UNUSED int __pyx_pw_5numpy_7ndarray_1__getbuffer__(PyObject *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags); /*proto*/
static CYTHON_UNUSED int __pyx_pw_5numpy_7ndarray_1__getbuffer__(PyObject *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags) {
int __pyx_r;
__Pyx_RefNannyDeclarations
__Pyx_RefNannySetupContext("__getbuffer__ (wrapper)", 0);
__pyx_r = __pyx_pf_5numpy_7ndarray___getbuffer__(((PyArrayObject *)__pyx_v_self), ((Py_buffer *)__pyx_v_info), ((int)__pyx_v_flags));
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* "numpy.pxd":194
* # experimental exception made for __getbuffer__ and __releasebuffer__
* # -- the details of this may change.
* def __getbuffer__(ndarray self, Py_buffer* info, int flags): # <<<<<<<<<<<<<<
* # This implementation of getbuffer is geared towards Cython
* # requirements, and does not yet fullfill the PEP.
*/
static int __pyx_pf_5numpy_7ndarray___getbuffer__(PyArrayObject *__pyx_v_self, Py_buffer *__pyx_v_info, int __pyx_v_flags) {
int __pyx_v_copy_shape;
int __pyx_v_i;
int __pyx_v_ndim;
int __pyx_v_endian_detector;
int __pyx_v_little_endian;
int __pyx_v_t;
char *__pyx_v_f;
PyArray_Descr *__pyx_v_descr = 0;
int __pyx_v_offset;
int __pyx_v_hasfields;
int __pyx_r;
__Pyx_RefNannyDeclarations
int __pyx_t_1;
int __pyx_t_2;
int __pyx_t_3;
PyObject *__pyx_t_4 = NULL;
int __pyx_t_5;
int __pyx_t_6;
int __pyx_t_7;
PyObject *__pyx_t_8 = NULL;
char *__pyx_t_9;
int __pyx_lineno = 0;
const char *__pyx_filename = NULL;
int __pyx_clineno = 0;
__Pyx_RefNannySetupContext("__getbuffer__", 0);
if (__pyx_v_info != NULL) {
__pyx_v_info->obj = Py_None; __Pyx_INCREF(Py_None);
__Pyx_GIVEREF(__pyx_v_info->obj);
}
/* "numpy.pxd":200
* # of flags
*
* if info == NULL: return # <<<<<<<<<<<<<<
*
* cdef int copy_shape, i, ndim
*/
__pyx_t_1 = (__pyx_v_info == NULL);
if (__pyx_t_1) {
__pyx_r = 0;
goto __pyx_L0;
goto __pyx_L3;
}
__pyx_L3:;
/* "numpy.pxd":203
*
* cdef int copy_shape, i, ndim
* cdef int endian_detector = 1 # <<<<<<<<<<<<<<
* cdef bint little_endian = ((<char*>&endian_detector)[0] != 0)
*
*/
__pyx_v_endian_detector = 1;
/* "numpy.pxd":204
* cdef int copy_shape, i, ndim
* cdef int endian_detector = 1
* cdef bint little_endian = ((<char*>&endian_detector)[0] != 0) # <<<<<<<<<<<<<<
*
* ndim = PyArray_NDIM(self)
*/
__pyx_v_little_endian = ((((char *)(&__pyx_v_endian_detector))[0]) != 0);
/* "numpy.pxd":206
* cdef bint little_endian = ((<char*>&endian_detector)[0] != 0)
*
* ndim = PyArray_NDIM(self) # <<<<<<<<<<<<<<
*
* if sizeof(npy_intp) != sizeof(Py_ssize_t):
*/
__pyx_v_ndim = PyArray_NDIM(__pyx_v_self);
/* "numpy.pxd":208
* ndim = PyArray_NDIM(self)
*
* if sizeof(npy_intp) != sizeof(Py_ssize_t): # <<<<<<<<<<<<<<
* copy_shape = 1
* else:
*/
__pyx_t_1 = ((sizeof(npy_intp)) != (sizeof(Py_ssize_t)));
if (__pyx_t_1) {
/* "numpy.pxd":209
*
* if sizeof(npy_intp) != sizeof(Py_ssize_t):
* copy_shape = 1 # <<<<<<<<<<<<<<
* else:
* copy_shape = 0
*/
__pyx_v_copy_shape = 1;
goto __pyx_L4;
}
/*else*/ {
/* "numpy.pxd":211
* copy_shape = 1
* else:
* copy_shape = 0 # <<<<<<<<<<<<<<
*
* if ((flags & pybuf.PyBUF_C_CONTIGUOUS == pybuf.PyBUF_C_CONTIGUOUS)
*/
__pyx_v_copy_shape = 0;
}
__pyx_L4:;
/* "numpy.pxd":213
* copy_shape = 0
*
* if ((flags & pybuf.PyBUF_C_CONTIGUOUS == pybuf.PyBUF_C_CONTIGUOUS) # <<<<<<<<<<<<<<
* and not PyArray_CHKFLAGS(self, NPY_C_CONTIGUOUS)):
* raise ValueError(u"ndarray is not C contiguous")
*/
__pyx_t_1 = ((__pyx_v_flags & PyBUF_C_CONTIGUOUS) == PyBUF_C_CONTIGUOUS);
if (__pyx_t_1) {
/* "numpy.pxd":214
*
* if ((flags & pybuf.PyBUF_C_CONTIGUOUS == pybuf.PyBUF_C_CONTIGUOUS)
* and not PyArray_CHKFLAGS(self, NPY_C_CONTIGUOUS)): # <<<<<<<<<<<<<<
* raise ValueError(u"ndarray is not C contiguous")
*
*/
__pyx_t_2 = (!PyArray_CHKFLAGS(__pyx_v_self, NPY_C_CONTIGUOUS));
__pyx_t_3 = __pyx_t_2;
} else {
__pyx_t_3 = __pyx_t_1;
}
if (__pyx_t_3) {
/* "numpy.pxd":215
* if ((flags & pybuf.PyBUF_C_CONTIGUOUS == pybuf.PyBUF_C_CONTIGUOUS)
* and not PyArray_CHKFLAGS(self, NPY_C_CONTIGUOUS)):
* raise ValueError(u"ndarray is not C contiguous") # <<<<<<<<<<<<<<
*
* if ((flags & pybuf.PyBUF_F_CONTIGUOUS == pybuf.PyBUF_F_CONTIGUOUS)
*/
__pyx_t_4 = PyObject_Call(__pyx_builtin_ValueError, ((PyObject *)__pyx_k_tuple_7), NULL); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 215; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_4);
__Pyx_Raise(__pyx_t_4, 0, 0, 0);
__Pyx_DECREF(__pyx_t_4); __pyx_t_4 = 0;
{__pyx_filename = __pyx_f[1]; __pyx_lineno = 215; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
goto __pyx_L5;
}
__pyx_L5:;
/* "numpy.pxd":217
* raise ValueError(u"ndarray is not C contiguous")
*
* if ((flags & pybuf.PyBUF_F_CONTIGUOUS == pybuf.PyBUF_F_CONTIGUOUS) # <<<<<<<<<<<<<<
* and not PyArray_CHKFLAGS(self, NPY_F_CONTIGUOUS)):
* raise ValueError(u"ndarray is not Fortran contiguous")
*/
__pyx_t_3 = ((__pyx_v_flags & PyBUF_F_CONTIGUOUS) == PyBUF_F_CONTIGUOUS);
if (__pyx_t_3) {
/* "numpy.pxd":218
*
* if ((flags & pybuf.PyBUF_F_CONTIGUOUS == pybuf.PyBUF_F_CONTIGUOUS)
* and not PyArray_CHKFLAGS(self, NPY_F_CONTIGUOUS)): # <<<<<<<<<<<<<<
* raise ValueError(u"ndarray is not Fortran contiguous")
*
*/
__pyx_t_1 = (!PyArray_CHKFLAGS(__pyx_v_self, NPY_F_CONTIGUOUS));
__pyx_t_2 = __pyx_t_1;
} else {
__pyx_t_2 = __pyx_t_3;
}
if (__pyx_t_2) {
/* "numpy.pxd":219
* if ((flags & pybuf.PyBUF_F_CONTIGUOUS == pybuf.PyBUF_F_CONTIGUOUS)
* and not PyArray_CHKFLAGS(self, NPY_F_CONTIGUOUS)):
* raise ValueError(u"ndarray is not Fortran contiguous") # <<<<<<<<<<<<<<
*
* info.buf = PyArray_DATA(self)
*/
__pyx_t_4 = PyObject_Call(__pyx_builtin_ValueError, ((PyObject *)__pyx_k_tuple_9), NULL); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 219; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_4);
__Pyx_Raise(__pyx_t_4, 0, 0, 0);
__Pyx_DECREF(__pyx_t_4); __pyx_t_4 = 0;
{__pyx_filename = __pyx_f[1]; __pyx_lineno = 219; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
goto __pyx_L6;
}
__pyx_L6:;
/* "numpy.pxd":221
* raise ValueError(u"ndarray is not Fortran contiguous")
*
* info.buf = PyArray_DATA(self) # <<<<<<<<<<<<<<
* info.ndim = ndim
* if copy_shape:
*/
__pyx_v_info->buf = PyArray_DATA(__pyx_v_self);
/* "numpy.pxd":222
*
* info.buf = PyArray_DATA(self)
* info.ndim = ndim # <<<<<<<<<<<<<<
* if copy_shape:
* # Allocate new buffer for strides and shape info.
*/
__pyx_v_info->ndim = __pyx_v_ndim;
/* "numpy.pxd":223
* info.buf = PyArray_DATA(self)
* info.ndim = ndim
* if copy_shape: # <<<<<<<<<<<<<<
* # Allocate new buffer for strides and shape info.
* # This is allocated as one block, strides first.
*/
if (__pyx_v_copy_shape) {
/* "numpy.pxd":226
* # Allocate new buffer for strides and shape info.
* # This is allocated as one block, strides first.
* info.strides = <Py_ssize_t*>stdlib.malloc(sizeof(Py_ssize_t) * <size_t>ndim * 2) # <<<<<<<<<<<<<<
* info.shape = info.strides + ndim
* for i in range(ndim):
*/
__pyx_v_info->strides = ((Py_ssize_t *)malloc((((sizeof(Py_ssize_t)) * ((size_t)__pyx_v_ndim)) * 2)));
/* "numpy.pxd":227
* # This is allocated as one block, strides first.
* info.strides = <Py_ssize_t*>stdlib.malloc(sizeof(Py_ssize_t) * <size_t>ndim * 2)
* info.shape = info.strides + ndim # <<<<<<<<<<<<<<
* for i in range(ndim):
* info.strides[i] = PyArray_STRIDES(self)[i]
*/
__pyx_v_info->shape = (__pyx_v_info->strides + __pyx_v_ndim);
/* "numpy.pxd":228
* info.strides = <Py_ssize_t*>stdlib.malloc(sizeof(Py_ssize_t) * <size_t>ndim * 2)
* info.shape = info.strides + ndim
* for i in range(ndim): # <<<<<<<<<<<<<<
* info.strides[i] = PyArray_STRIDES(self)[i]
* info.shape[i] = PyArray_DIMS(self)[i]
*/
__pyx_t_5 = __pyx_v_ndim;
for (__pyx_t_6 = 0; __pyx_t_6 < __pyx_t_5; __pyx_t_6+=1) {
__pyx_v_i = __pyx_t_6;
/* "numpy.pxd":229
* info.shape = info.strides + ndim
* for i in range(ndim):
* info.strides[i] = PyArray_STRIDES(self)[i] # <<<<<<<<<<<<<<
* info.shape[i] = PyArray_DIMS(self)[i]
* else:
*/
(__pyx_v_info->strides[__pyx_v_i]) = (PyArray_STRIDES(__pyx_v_self)[__pyx_v_i]);
/* "numpy.pxd":230
* for i in range(ndim):
* info.strides[i] = PyArray_STRIDES(self)[i]
* info.shape[i] = PyArray_DIMS(self)[i] # <<<<<<<<<<<<<<
* else:
* info.strides = <Py_ssize_t*>PyArray_STRIDES(self)
*/
(__pyx_v_info->shape[__pyx_v_i]) = (PyArray_DIMS(__pyx_v_self)[__pyx_v_i]);
}
goto __pyx_L7;
}
/*else*/ {
/* "numpy.pxd":232
* info.shape[i] = PyArray_DIMS(self)[i]
* else:
* info.strides = <Py_ssize_t*>PyArray_STRIDES(self) # <<<<<<<<<<<<<<
* info.shape = <Py_ssize_t*>PyArray_DIMS(self)
* info.suboffsets = NULL
*/
__pyx_v_info->strides = ((Py_ssize_t *)PyArray_STRIDES(__pyx_v_self));
/* "numpy.pxd":233
* else:
* info.strides = <Py_ssize_t*>PyArray_STRIDES(self)
* info.shape = <Py_ssize_t*>PyArray_DIMS(self) # <<<<<<<<<<<<<<
* info.suboffsets = NULL
* info.itemsize = PyArray_ITEMSIZE(self)
*/
__pyx_v_info->shape = ((Py_ssize_t *)PyArray_DIMS(__pyx_v_self));
}
__pyx_L7:;
/* "numpy.pxd":234
* info.strides = <Py_ssize_t*>PyArray_STRIDES(self)
* info.shape = <Py_ssize_t*>PyArray_DIMS(self)
* info.suboffsets = NULL # <<<<<<<<<<<<<<
* info.itemsize = PyArray_ITEMSIZE(self)
* info.readonly = not PyArray_ISWRITEABLE(self)
*/
__pyx_v_info->suboffsets = NULL;
/* "numpy.pxd":235
* info.shape = <Py_ssize_t*>PyArray_DIMS(self)
* info.suboffsets = NULL
* info.itemsize = PyArray_ITEMSIZE(self) # <<<<<<<<<<<<<<
* info.readonly = not PyArray_ISWRITEABLE(self)
*
*/
__pyx_v_info->itemsize = PyArray_ITEMSIZE(__pyx_v_self);
/* "numpy.pxd":236
* info.suboffsets = NULL
* info.itemsize = PyArray_ITEMSIZE(self)
* info.readonly = not PyArray_ISWRITEABLE(self) # <<<<<<<<<<<<<<
*
* cdef int t
*/
__pyx_v_info->readonly = (!PyArray_ISWRITEABLE(__pyx_v_self));
/* "numpy.pxd":239
*
* cdef int t
* cdef char* f = NULL # <<<<<<<<<<<<<<
* cdef dtype descr = self.descr
* cdef list stack
*/
__pyx_v_f = NULL;
/* "numpy.pxd":240
* cdef int t
* cdef char* f = NULL
* cdef dtype descr = self.descr # <<<<<<<<<<<<<<
* cdef list stack
* cdef int offset
*/
__pyx_t_4 = ((PyObject *)__pyx_v_self->descr);
__Pyx_INCREF(__pyx_t_4);
__pyx_v_descr = ((PyArray_Descr *)__pyx_t_4);
__pyx_t_4 = 0;
/* "numpy.pxd":244
* cdef int offset
*
* cdef bint hasfields = PyDataType_HASFIELDS(descr) # <<<<<<<<<<<<<<
*
* if not hasfields and not copy_shape:
*/
__pyx_v_hasfields = PyDataType_HASFIELDS(__pyx_v_descr);
/* "numpy.pxd":246
* cdef bint hasfields = PyDataType_HASFIELDS(descr)
*
* if not hasfields and not copy_shape: # <<<<<<<<<<<<<<
* # do not call releasebuffer
* info.obj = None
*/
__pyx_t_2 = (!__pyx_v_hasfields);
if (__pyx_t_2) {
__pyx_t_3 = (!__pyx_v_copy_shape);
__pyx_t_1 = __pyx_t_3;
} else {
__pyx_t_1 = __pyx_t_2;
}
if (__pyx_t_1) {
/* "numpy.pxd":248
* if not hasfields and not copy_shape:
* # do not call releasebuffer
* info.obj = None # <<<<<<<<<<<<<<
* else:
* # need to call releasebuffer
*/
__Pyx_INCREF(Py_None);
__Pyx_GIVEREF(Py_None);
__Pyx_GOTREF(__pyx_v_info->obj);
__Pyx_DECREF(__pyx_v_info->obj);
__pyx_v_info->obj = Py_None;
goto __pyx_L10;
}
/*else*/ {
/* "numpy.pxd":251
* else:
* # need to call releasebuffer
* info.obj = self # <<<<<<<<<<<<<<
*
* if not hasfields:
*/
__Pyx_INCREF(((PyObject *)__pyx_v_self));
__Pyx_GIVEREF(((PyObject *)__pyx_v_self));
__Pyx_GOTREF(__pyx_v_info->obj);
__Pyx_DECREF(__pyx_v_info->obj);
__pyx_v_info->obj = ((PyObject *)__pyx_v_self);
}
__pyx_L10:;
/* "numpy.pxd":253
* info.obj = self
*
* if not hasfields: # <<<<<<<<<<<<<<
* t = descr.type_num
* if ((descr.byteorder == c'>' and little_endian) or
*/
__pyx_t_1 = (!__pyx_v_hasfields);
if (__pyx_t_1) {
/* "numpy.pxd":254
*
* if not hasfields:
* t = descr.type_num # <<<<<<<<<<<<<<
* if ((descr.byteorder == c'>' and little_endian) or
* (descr.byteorder == c'<' and not little_endian)):
*/
__pyx_t_5 = __pyx_v_descr->type_num;
__pyx_v_t = __pyx_t_5;
/* "numpy.pxd":255
* if not hasfields:
* t = descr.type_num
* if ((descr.byteorder == c'>' and little_endian) or # <<<<<<<<<<<<<<
* (descr.byteorder == c'<' and not little_endian)):
* raise ValueError(u"Non-native byte order not supported")
*/
__pyx_t_1 = (__pyx_v_descr->byteorder == '>');
if (__pyx_t_1) {
__pyx_t_2 = __pyx_v_little_endian;
} else {
__pyx_t_2 = __pyx_t_1;
}
if (!__pyx_t_2) {
/* "numpy.pxd":256
* t = descr.type_num
* if ((descr.byteorder == c'>' and little_endian) or
* (descr.byteorder == c'<' and not little_endian)): # <<<<<<<<<<<<<<
* raise ValueError(u"Non-native byte order not supported")
* if t == NPY_BYTE: f = "b"
*/
__pyx_t_1 = (__pyx_v_descr->byteorder == '<');
if (__pyx_t_1) {
__pyx_t_3 = (!__pyx_v_little_endian);
__pyx_t_7 = __pyx_t_3;
} else {
__pyx_t_7 = __pyx_t_1;
}
__pyx_t_1 = __pyx_t_7;
} else {
__pyx_t_1 = __pyx_t_2;
}
if (__pyx_t_1) {
/* "numpy.pxd":257
* if ((descr.byteorder == c'>' and little_endian) or
* (descr.byteorder == c'<' and not little_endian)):
* raise ValueError(u"Non-native byte order not supported") # <<<<<<<<<<<<<<
* if t == NPY_BYTE: f = "b"
* elif t == NPY_UBYTE: f = "B"
*/
__pyx_t_4 = PyObject_Call(__pyx_builtin_ValueError, ((PyObject *)__pyx_k_tuple_11), NULL); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 257; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_4);
__Pyx_Raise(__pyx_t_4, 0, 0, 0);
__Pyx_DECREF(__pyx_t_4); __pyx_t_4 = 0;
{__pyx_filename = __pyx_f[1]; __pyx_lineno = 257; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
goto __pyx_L12;
}
__pyx_L12:;
/* "numpy.pxd":258
* (descr.byteorder == c'<' and not little_endian)):
* raise ValueError(u"Non-native byte order not supported")
* if t == NPY_BYTE: f = "b" # <<<<<<<<<<<<<<
* elif t == NPY_UBYTE: f = "B"
* elif t == NPY_SHORT: f = "h"
*/
__pyx_t_1 = (__pyx_v_t == NPY_BYTE);
if (__pyx_t_1) {
__pyx_v_f = __pyx_k__b;
goto __pyx_L13;
}
/* "numpy.pxd":259
* raise ValueError(u"Non-native byte order not supported")
* if t == NPY_BYTE: f = "b"
* elif t == NPY_UBYTE: f = "B" # <<<<<<<<<<<<<<
* elif t == NPY_SHORT: f = "h"
* elif t == NPY_USHORT: f = "H"
*/
__pyx_t_1 = (__pyx_v_t == NPY_UBYTE);
if (__pyx_t_1) {
__pyx_v_f = __pyx_k__B;
goto __pyx_L13;
}
/* "numpy.pxd":260
* if t == NPY_BYTE: f = "b"
* elif t == NPY_UBYTE: f = "B"
* elif t == NPY_SHORT: f = "h" # <<<<<<<<<<<<<<
* elif t == NPY_USHORT: f = "H"
* elif t == NPY_INT: f = "i"
*/
__pyx_t_1 = (__pyx_v_t == NPY_SHORT);
if (__pyx_t_1) {
__pyx_v_f = __pyx_k__h;
goto __pyx_L13;
}
/* "numpy.pxd":261
* elif t == NPY_UBYTE: f = "B"
* elif t == NPY_SHORT: f = "h"
* elif t == NPY_USHORT: f = "H" # <<<<<<<<<<<<<<
* elif t == NPY_INT: f = "i"
* elif t == NPY_UINT: f = "I"
*/
__pyx_t_1 = (__pyx_v_t == NPY_USHORT);
if (__pyx_t_1) {
__pyx_v_f = __pyx_k__H;
goto __pyx_L13;
}
/* "numpy.pxd":262
* elif t == NPY_SHORT: f = "h"
* elif t == NPY_USHORT: f = "H"
* elif t == NPY_INT: f = "i" # <<<<<<<<<<<<<<
* elif t == NPY_UINT: f = "I"
* elif t == NPY_LONG: f = "l"
*/
__pyx_t_1 = (__pyx_v_t == NPY_INT);
if (__pyx_t_1) {
__pyx_v_f = __pyx_k__i;
goto __pyx_L13;
}
/* "numpy.pxd":263
* elif t == NPY_USHORT: f = "H"
* elif t == NPY_INT: f = "i"
* elif t == NPY_UINT: f = "I" # <<<<<<<<<<<<<<
* elif t == NPY_LONG: f = "l"
* elif t == NPY_ULONG: f = "L"
*/
__pyx_t_1 = (__pyx_v_t == NPY_UINT);
if (__pyx_t_1) {
__pyx_v_f = __pyx_k__I;
goto __pyx_L13;
}
/* "numpy.pxd":264
* elif t == NPY_INT: f = "i"
* elif t == NPY_UINT: f = "I"
* elif t == NPY_LONG: f = "l" # <<<<<<<<<<<<<<
* elif t == NPY_ULONG: f = "L"
* elif t == NPY_LONGLONG: f = "q"
*/
__pyx_t_1 = (__pyx_v_t == NPY_LONG);
if (__pyx_t_1) {
__pyx_v_f = __pyx_k__l;
goto __pyx_L13;
}
/* "numpy.pxd":265
* elif t == NPY_UINT: f = "I"
* elif t == NPY_LONG: f = "l"
* elif t == NPY_ULONG: f = "L" # <<<<<<<<<<<<<<
* elif t == NPY_LONGLONG: f = "q"
* elif t == NPY_ULONGLONG: f = "Q"
*/
__pyx_t_1 = (__pyx_v_t == NPY_ULONG);
if (__pyx_t_1) {
__pyx_v_f = __pyx_k__L;
goto __pyx_L13;
}
/* "numpy.pxd":266
* elif t == NPY_LONG: f = "l"
* elif t == NPY_ULONG: f = "L"
* elif t == NPY_LONGLONG: f = "q" # <<<<<<<<<<<<<<
* elif t == NPY_ULONGLONG: f = "Q"
* elif t == NPY_FLOAT: f = "f"
*/
__pyx_t_1 = (__pyx_v_t == NPY_LONGLONG);
if (__pyx_t_1) {
__pyx_v_f = __pyx_k__q;
goto __pyx_L13;
}
/* "numpy.pxd":267
* elif t == NPY_ULONG: f = "L"
* elif t == NPY_LONGLONG: f = "q"
* elif t == NPY_ULONGLONG: f = "Q" # <<<<<<<<<<<<<<
* elif t == NPY_FLOAT: f = "f"
* elif t == NPY_DOUBLE: f = "d"
*/
__pyx_t_1 = (__pyx_v_t == NPY_ULONGLONG);
if (__pyx_t_1) {
__pyx_v_f = __pyx_k__Q;
goto __pyx_L13;
}
/* "numpy.pxd":268
* elif t == NPY_LONGLONG: f = "q"
* elif t == NPY_ULONGLONG: f = "Q"
* elif t == NPY_FLOAT: f = "f" # <<<<<<<<<<<<<<
* elif t == NPY_DOUBLE: f = "d"
* elif t == NPY_LONGDOUBLE: f = "g"
*/
__pyx_t_1 = (__pyx_v_t == NPY_FLOAT);
if (__pyx_t_1) {
__pyx_v_f = __pyx_k__f;
goto __pyx_L13;
}
/* "numpy.pxd":269
* elif t == NPY_ULONGLONG: f = "Q"
* elif t == NPY_FLOAT: f = "f"
* elif t == NPY_DOUBLE: f = "d" # <<<<<<<<<<<<<<
* elif t == NPY_LONGDOUBLE: f = "g"
* elif t == NPY_CFLOAT: f = "Zf"
*/
__pyx_t_1 = (__pyx_v_t == NPY_DOUBLE);
if (__pyx_t_1) {
__pyx_v_f = __pyx_k__d;
goto __pyx_L13;
}
/* "numpy.pxd":270
* elif t == NPY_FLOAT: f = "f"
* elif t == NPY_DOUBLE: f = "d"
* elif t == NPY_LONGDOUBLE: f = "g" # <<<<<<<<<<<<<<
* elif t == NPY_CFLOAT: f = "Zf"
* elif t == NPY_CDOUBLE: f = "Zd"
*/
__pyx_t_1 = (__pyx_v_t == NPY_LONGDOUBLE);
if (__pyx_t_1) {
__pyx_v_f = __pyx_k__g;
goto __pyx_L13;
}
/* "numpy.pxd":271
* elif t == NPY_DOUBLE: f = "d"
* elif t == NPY_LONGDOUBLE: f = "g"
* elif t == NPY_CFLOAT: f = "Zf" # <<<<<<<<<<<<<<
* elif t == NPY_CDOUBLE: f = "Zd"
* elif t == NPY_CLONGDOUBLE: f = "Zg"
*/
__pyx_t_1 = (__pyx_v_t == NPY_CFLOAT);
if (__pyx_t_1) {
__pyx_v_f = __pyx_k__Zf;
goto __pyx_L13;
}
/* "numpy.pxd":272
* elif t == NPY_LONGDOUBLE: f = "g"
* elif t == NPY_CFLOAT: f = "Zf"
* elif t == NPY_CDOUBLE: f = "Zd" # <<<<<<<<<<<<<<
* elif t == NPY_CLONGDOUBLE: f = "Zg"
* elif t == NPY_OBJECT: f = "O"
*/
__pyx_t_1 = (__pyx_v_t == NPY_CDOUBLE);
if (__pyx_t_1) {
__pyx_v_f = __pyx_k__Zd;
goto __pyx_L13;
}
/* "numpy.pxd":273
* elif t == NPY_CFLOAT: f = "Zf"
* elif t == NPY_CDOUBLE: f = "Zd"
* elif t == NPY_CLONGDOUBLE: f = "Zg" # <<<<<<<<<<<<<<
* elif t == NPY_OBJECT: f = "O"
* else:
*/
__pyx_t_1 = (__pyx_v_t == NPY_CLONGDOUBLE);
if (__pyx_t_1) {
__pyx_v_f = __pyx_k__Zg;
goto __pyx_L13;
}
/* "numpy.pxd":274
* elif t == NPY_CDOUBLE: f = "Zd"
* elif t == NPY_CLONGDOUBLE: f = "Zg"
* elif t == NPY_OBJECT: f = "O" # <<<<<<<<<<<<<<
* else:
* raise ValueError(u"unknown dtype code in numpy.pxd (%d)" % t)
*/
__pyx_t_1 = (__pyx_v_t == NPY_OBJECT);
if (__pyx_t_1) {
__pyx_v_f = __pyx_k__O;
goto __pyx_L13;
}
/*else*/ {
/* "numpy.pxd":276
* elif t == NPY_OBJECT: f = "O"
* else:
* raise ValueError(u"unknown dtype code in numpy.pxd (%d)" % t) # <<<<<<<<<<<<<<
* info.format = f
* return
*/
__pyx_t_4 = PyInt_FromLong(__pyx_v_t); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 276; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_4);
__pyx_t_8 = PyNumber_Remainder(((PyObject *)__pyx_kp_u_12), __pyx_t_4); if (unlikely(!__pyx_t_8)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 276; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(((PyObject *)__pyx_t_8));
__Pyx_DECREF(__pyx_t_4); __pyx_t_4 = 0;
__pyx_t_4 = PyTuple_New(1); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 276; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_4);
PyTuple_SET_ITEM(__pyx_t_4, 0, ((PyObject *)__pyx_t_8));
__Pyx_GIVEREF(((PyObject *)__pyx_t_8));
__pyx_t_8 = 0;
__pyx_t_8 = PyObject_Call(__pyx_builtin_ValueError, ((PyObject *)__pyx_t_4), NULL); if (unlikely(!__pyx_t_8)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 276; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_8);
__Pyx_DECREF(((PyObject *)__pyx_t_4)); __pyx_t_4 = 0;
__Pyx_Raise(__pyx_t_8, 0, 0, 0);
__Pyx_DECREF(__pyx_t_8); __pyx_t_8 = 0;
{__pyx_filename = __pyx_f[1]; __pyx_lineno = 276; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
}
__pyx_L13:;
/* "numpy.pxd":277
* else:
* raise ValueError(u"unknown dtype code in numpy.pxd (%d)" % t)
* info.format = f # <<<<<<<<<<<<<<
* return
* else:
*/
__pyx_v_info->format = __pyx_v_f;
/* "numpy.pxd":278
* raise ValueError(u"unknown dtype code in numpy.pxd (%d)" % t)
* info.format = f
* return # <<<<<<<<<<<<<<
* else:
* info.format = <char*>stdlib.malloc(_buffer_format_string_len)
*/
__pyx_r = 0;
goto __pyx_L0;
goto __pyx_L11;
}
/*else*/ {
/* "numpy.pxd":280
* return
* else:
* info.format = <char*>stdlib.malloc(_buffer_format_string_len) # <<<<<<<<<<<<<<
* info.format[0] = c'^' # Native data types, manual alignment
* offset = 0
*/
__pyx_v_info->format = ((char *)malloc(255));
/* "numpy.pxd":281
* else:
* info.format = <char*>stdlib.malloc(_buffer_format_string_len)
* info.format[0] = c'^' # Native data types, manual alignment # <<<<<<<<<<<<<<
* offset = 0
* f = _util_dtypestring(descr, info.format + 1,
*/
(__pyx_v_info->format[0]) = '^';
/* "numpy.pxd":282
* info.format = <char*>stdlib.malloc(_buffer_format_string_len)
* info.format[0] = c'^' # Native data types, manual alignment
* offset = 0 # <<<<<<<<<<<<<<
* f = _util_dtypestring(descr, info.format + 1,
* info.format + _buffer_format_string_len,
*/
__pyx_v_offset = 0;
/* "numpy.pxd":285
* f = _util_dtypestring(descr, info.format + 1,
* info.format + _buffer_format_string_len,
* &offset) # <<<<<<<<<<<<<<
* f[0] = c'\0' # Terminate format string
*
*/
__pyx_t_9 = __pyx_f_5numpy__util_dtypestring(__pyx_v_descr, (__pyx_v_info->format + 1), (__pyx_v_info->format + 255), (&__pyx_v_offset)); if (unlikely(__pyx_t_9 == NULL)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 283; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__pyx_v_f = __pyx_t_9;
/* "numpy.pxd":286
* info.format + _buffer_format_string_len,
* &offset)
* f[0] = c'\0' # Terminate format string # <<<<<<<<<<<<<<
*
* def __releasebuffer__(ndarray self, Py_buffer* info):
*/
(__pyx_v_f[0]) = '\x00';
}
__pyx_L11:;
__pyx_r = 0;
goto __pyx_L0;
__pyx_L1_error:;
__Pyx_XDECREF(__pyx_t_4);
__Pyx_XDECREF(__pyx_t_8);
__Pyx_AddTraceback("numpy.ndarray.__getbuffer__", __pyx_clineno, __pyx_lineno, __pyx_filename);
__pyx_r = -1;
if (__pyx_v_info != NULL && __pyx_v_info->obj != NULL) {
__Pyx_GOTREF(__pyx_v_info->obj);
__Pyx_DECREF(__pyx_v_info->obj); __pyx_v_info->obj = NULL;
}
goto __pyx_L2;
__pyx_L0:;
if (__pyx_v_info != NULL && __pyx_v_info->obj == Py_None) {
__Pyx_GOTREF(Py_None);
__Pyx_DECREF(Py_None); __pyx_v_info->obj = NULL;
}
__pyx_L2:;
__Pyx_XDECREF((PyObject *)__pyx_v_descr);
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* Python wrapper */
static CYTHON_UNUSED void __pyx_pw_5numpy_7ndarray_3__releasebuffer__(PyObject *__pyx_v_self, Py_buffer *__pyx_v_info); /*proto*/
static CYTHON_UNUSED void __pyx_pw_5numpy_7ndarray_3__releasebuffer__(PyObject *__pyx_v_self, Py_buffer *__pyx_v_info) {
__Pyx_RefNannyDeclarations
__Pyx_RefNannySetupContext("__releasebuffer__ (wrapper)", 0);
__pyx_pf_5numpy_7ndarray_2__releasebuffer__(((PyArrayObject *)__pyx_v_self), ((Py_buffer *)__pyx_v_info));
__Pyx_RefNannyFinishContext();
}
/* "numpy.pxd":288
* f[0] = c'\0' # Terminate format string
*
* def __releasebuffer__(ndarray self, Py_buffer* info): # <<<<<<<<<<<<<<
* if PyArray_HASFIELDS(self):
* stdlib.free(info.format)
*/
static void __pyx_pf_5numpy_7ndarray_2__releasebuffer__(PyArrayObject *__pyx_v_self, Py_buffer *__pyx_v_info) {
__Pyx_RefNannyDeclarations
int __pyx_t_1;
__Pyx_RefNannySetupContext("__releasebuffer__", 0);
/* "numpy.pxd":289
*
* def __releasebuffer__(ndarray self, Py_buffer* info):
* if PyArray_HASFIELDS(self): # <<<<<<<<<<<<<<
* stdlib.free(info.format)
* if sizeof(npy_intp) != sizeof(Py_ssize_t):
*/
__pyx_t_1 = PyArray_HASFIELDS(__pyx_v_self);
if (__pyx_t_1) {
/* "numpy.pxd":290
* def __releasebuffer__(ndarray self, Py_buffer* info):
* if PyArray_HASFIELDS(self):
* stdlib.free(info.format) # <<<<<<<<<<<<<<
* if sizeof(npy_intp) != sizeof(Py_ssize_t):
* stdlib.free(info.strides)
*/
free(__pyx_v_info->format);
goto __pyx_L3;
}
__pyx_L3:;
/* "numpy.pxd":291
* if PyArray_HASFIELDS(self):
* stdlib.free(info.format)
* if sizeof(npy_intp) != sizeof(Py_ssize_t): # <<<<<<<<<<<<<<
* stdlib.free(info.strides)
* # info.shape was stored after info.strides in the same block
*/
__pyx_t_1 = ((sizeof(npy_intp)) != (sizeof(Py_ssize_t)));
if (__pyx_t_1) {
/* "numpy.pxd":292
* stdlib.free(info.format)
* if sizeof(npy_intp) != sizeof(Py_ssize_t):
* stdlib.free(info.strides) # <<<<<<<<<<<<<<
* # info.shape was stored after info.strides in the same block
*
*/
free(__pyx_v_info->strides);
goto __pyx_L4;
}
__pyx_L4:;
__Pyx_RefNannyFinishContext();
}
/* "numpy.pxd":768
* ctypedef npy_cdouble complex_t
*
* cdef inline object PyArray_MultiIterNew1(a): # <<<<<<<<<<<<<<
* return PyArray_MultiIterNew(1, <void*>a)
*
*/
static CYTHON_INLINE PyObject *__pyx_f_5numpy_PyArray_MultiIterNew1(PyObject *__pyx_v_a) {
PyObject *__pyx_r = NULL;
__Pyx_RefNannyDeclarations
PyObject *__pyx_t_1 = NULL;
int __pyx_lineno = 0;
const char *__pyx_filename = NULL;
int __pyx_clineno = 0;
__Pyx_RefNannySetupContext("PyArray_MultiIterNew1", 0);
/* "numpy.pxd":769
*
* cdef inline object PyArray_MultiIterNew1(a):
* return PyArray_MultiIterNew(1, <void*>a) # <<<<<<<<<<<<<<
*
* cdef inline object PyArray_MultiIterNew2(a, b):
*/
__Pyx_XDECREF(__pyx_r);
__pyx_t_1 = PyArray_MultiIterNew(1, ((void *)__pyx_v_a)); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 769; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_1);
__pyx_r = __pyx_t_1;
__pyx_t_1 = 0;
goto __pyx_L0;
__pyx_r = Py_None; __Pyx_INCREF(Py_None);
goto __pyx_L0;
__pyx_L1_error:;
__Pyx_XDECREF(__pyx_t_1);
__Pyx_AddTraceback("numpy.PyArray_MultiIterNew1", __pyx_clineno, __pyx_lineno, __pyx_filename);
__pyx_r = 0;
__pyx_L0:;
__Pyx_XGIVEREF(__pyx_r);
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* "numpy.pxd":771
* return PyArray_MultiIterNew(1, <void*>a)
*
* cdef inline object PyArray_MultiIterNew2(a, b): # <<<<<<<<<<<<<<
* return PyArray_MultiIterNew(2, <void*>a, <void*>b)
*
*/
static CYTHON_INLINE PyObject *__pyx_f_5numpy_PyArray_MultiIterNew2(PyObject *__pyx_v_a, PyObject *__pyx_v_b) {
PyObject *__pyx_r = NULL;
__Pyx_RefNannyDeclarations
PyObject *__pyx_t_1 = NULL;
int __pyx_lineno = 0;
const char *__pyx_filename = NULL;
int __pyx_clineno = 0;
__Pyx_RefNannySetupContext("PyArray_MultiIterNew2", 0);
/* "numpy.pxd":772
*
* cdef inline object PyArray_MultiIterNew2(a, b):
* return PyArray_MultiIterNew(2, <void*>a, <void*>b) # <<<<<<<<<<<<<<
*
* cdef inline object PyArray_MultiIterNew3(a, b, c):
*/
__Pyx_XDECREF(__pyx_r);
__pyx_t_1 = PyArray_MultiIterNew(2, ((void *)__pyx_v_a), ((void *)__pyx_v_b)); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 772; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_1);
__pyx_r = __pyx_t_1;
__pyx_t_1 = 0;
goto __pyx_L0;
__pyx_r = Py_None; __Pyx_INCREF(Py_None);
goto __pyx_L0;
__pyx_L1_error:;
__Pyx_XDECREF(__pyx_t_1);
__Pyx_AddTraceback("numpy.PyArray_MultiIterNew2", __pyx_clineno, __pyx_lineno, __pyx_filename);
__pyx_r = 0;
__pyx_L0:;
__Pyx_XGIVEREF(__pyx_r);
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* "numpy.pxd":774
* return PyArray_MultiIterNew(2, <void*>a, <void*>b)
*
* cdef inline object PyArray_MultiIterNew3(a, b, c): # <<<<<<<<<<<<<<
* return PyArray_MultiIterNew(3, <void*>a, <void*>b, <void*> c)
*
*/
static CYTHON_INLINE PyObject *__pyx_f_5numpy_PyArray_MultiIterNew3(PyObject *__pyx_v_a, PyObject *__pyx_v_b, PyObject *__pyx_v_c) {
PyObject *__pyx_r = NULL;
__Pyx_RefNannyDeclarations
PyObject *__pyx_t_1 = NULL;
int __pyx_lineno = 0;
const char *__pyx_filename = NULL;
int __pyx_clineno = 0;
__Pyx_RefNannySetupContext("PyArray_MultiIterNew3", 0);
/* "numpy.pxd":775
*
* cdef inline object PyArray_MultiIterNew3(a, b, c):
* return PyArray_MultiIterNew(3, <void*>a, <void*>b, <void*> c) # <<<<<<<<<<<<<<
*
* cdef inline object PyArray_MultiIterNew4(a, b, c, d):
*/
__Pyx_XDECREF(__pyx_r);
__pyx_t_1 = PyArray_MultiIterNew(3, ((void *)__pyx_v_a), ((void *)__pyx_v_b), ((void *)__pyx_v_c)); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 775; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_1);
__pyx_r = __pyx_t_1;
__pyx_t_1 = 0;
goto __pyx_L0;
__pyx_r = Py_None; __Pyx_INCREF(Py_None);
goto __pyx_L0;
__pyx_L1_error:;
__Pyx_XDECREF(__pyx_t_1);
__Pyx_AddTraceback("numpy.PyArray_MultiIterNew3", __pyx_clineno, __pyx_lineno, __pyx_filename);
__pyx_r = 0;
__pyx_L0:;
__Pyx_XGIVEREF(__pyx_r);
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* "numpy.pxd":777
* return PyArray_MultiIterNew(3, <void*>a, <void*>b, <void*> c)
*
* cdef inline object PyArray_MultiIterNew4(a, b, c, d): # <<<<<<<<<<<<<<
* return PyArray_MultiIterNew(4, <void*>a, <void*>b, <void*>c, <void*> d)
*
*/
static CYTHON_INLINE PyObject *__pyx_f_5numpy_PyArray_MultiIterNew4(PyObject *__pyx_v_a, PyObject *__pyx_v_b, PyObject *__pyx_v_c, PyObject *__pyx_v_d) {
PyObject *__pyx_r = NULL;
__Pyx_RefNannyDeclarations
PyObject *__pyx_t_1 = NULL;
int __pyx_lineno = 0;
const char *__pyx_filename = NULL;
int __pyx_clineno = 0;
__Pyx_RefNannySetupContext("PyArray_MultiIterNew4", 0);
/* "numpy.pxd":778
*
* cdef inline object PyArray_MultiIterNew4(a, b, c, d):
* return PyArray_MultiIterNew(4, <void*>a, <void*>b, <void*>c, <void*> d) # <<<<<<<<<<<<<<
*
* cdef inline object PyArray_MultiIterNew5(a, b, c, d, e):
*/
__Pyx_XDECREF(__pyx_r);
__pyx_t_1 = PyArray_MultiIterNew(4, ((void *)__pyx_v_a), ((void *)__pyx_v_b), ((void *)__pyx_v_c), ((void *)__pyx_v_d)); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 778; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_1);
__pyx_r = __pyx_t_1;
__pyx_t_1 = 0;
goto __pyx_L0;
__pyx_r = Py_None; __Pyx_INCREF(Py_None);
goto __pyx_L0;
__pyx_L1_error:;
__Pyx_XDECREF(__pyx_t_1);
__Pyx_AddTraceback("numpy.PyArray_MultiIterNew4", __pyx_clineno, __pyx_lineno, __pyx_filename);
__pyx_r = 0;
__pyx_L0:;
__Pyx_XGIVEREF(__pyx_r);
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* "numpy.pxd":780
* return PyArray_MultiIterNew(4, <void*>a, <void*>b, <void*>c, <void*> d)
*
* cdef inline object PyArray_MultiIterNew5(a, b, c, d, e): # <<<<<<<<<<<<<<
* return PyArray_MultiIterNew(5, <void*>a, <void*>b, <void*>c, <void*> d, <void*> e)
*
*/
static CYTHON_INLINE PyObject *__pyx_f_5numpy_PyArray_MultiIterNew5(PyObject *__pyx_v_a, PyObject *__pyx_v_b, PyObject *__pyx_v_c, PyObject *__pyx_v_d, PyObject *__pyx_v_e) {
PyObject *__pyx_r = NULL;
__Pyx_RefNannyDeclarations
PyObject *__pyx_t_1 = NULL;
int __pyx_lineno = 0;
const char *__pyx_filename = NULL;
int __pyx_clineno = 0;
__Pyx_RefNannySetupContext("PyArray_MultiIterNew5", 0);
/* "numpy.pxd":781
*
* cdef inline object PyArray_MultiIterNew5(a, b, c, d, e):
* return PyArray_MultiIterNew(5, <void*>a, <void*>b, <void*>c, <void*> d, <void*> e) # <<<<<<<<<<<<<<
*
* cdef inline char* _util_dtypestring(dtype descr, char* f, char* end, int* offset) except NULL:
*/
__Pyx_XDECREF(__pyx_r);
__pyx_t_1 = PyArray_MultiIterNew(5, ((void *)__pyx_v_a), ((void *)__pyx_v_b), ((void *)__pyx_v_c), ((void *)__pyx_v_d), ((void *)__pyx_v_e)); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 781; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_1);
__pyx_r = __pyx_t_1;
__pyx_t_1 = 0;
goto __pyx_L0;
__pyx_r = Py_None; __Pyx_INCREF(Py_None);
goto __pyx_L0;
__pyx_L1_error:;
__Pyx_XDECREF(__pyx_t_1);
__Pyx_AddTraceback("numpy.PyArray_MultiIterNew5", __pyx_clineno, __pyx_lineno, __pyx_filename);
__pyx_r = 0;
__pyx_L0:;
__Pyx_XGIVEREF(__pyx_r);
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* "numpy.pxd":783
* return PyArray_MultiIterNew(5, <void*>a, <void*>b, <void*>c, <void*> d, <void*> e)
*
* cdef inline char* _util_dtypestring(dtype descr, char* f, char* end, int* offset) except NULL: # <<<<<<<<<<<<<<
* # Recursive utility function used in __getbuffer__ to get format
* # string. The new location in the format string is returned.
*/
static CYTHON_INLINE char *__pyx_f_5numpy__util_dtypestring(PyArray_Descr *__pyx_v_descr, char *__pyx_v_f, char *__pyx_v_end, int *__pyx_v_offset) {
PyArray_Descr *__pyx_v_child = 0;
int __pyx_v_endian_detector;
int __pyx_v_little_endian;
PyObject *__pyx_v_fields = 0;
PyObject *__pyx_v_childname = NULL;
PyObject *__pyx_v_new_offset = NULL;
PyObject *__pyx_v_t = NULL;
char *__pyx_r;
__Pyx_RefNannyDeclarations
PyObject *__pyx_t_1 = NULL;
Py_ssize_t __pyx_t_2;
PyObject *__pyx_t_3 = NULL;
PyObject *__pyx_t_4 = NULL;
PyObject *__pyx_t_5 = NULL;
PyObject *(*__pyx_t_6)(PyObject *);
int __pyx_t_7;
int __pyx_t_8;
int __pyx_t_9;
int __pyx_t_10;
long __pyx_t_11;
char *__pyx_t_12;
int __pyx_lineno = 0;
const char *__pyx_filename = NULL;
int __pyx_clineno = 0;
__Pyx_RefNannySetupContext("_util_dtypestring", 0);
/* "numpy.pxd":790
* cdef int delta_offset
* cdef tuple i
* cdef int endian_detector = 1 # <<<<<<<<<<<<<<
* cdef bint little_endian = ((<char*>&endian_detector)[0] != 0)
* cdef tuple fields
*/
__pyx_v_endian_detector = 1;
/* "numpy.pxd":791
* cdef tuple i
* cdef int endian_detector = 1
* cdef bint little_endian = ((<char*>&endian_detector)[0] != 0) # <<<<<<<<<<<<<<
* cdef tuple fields
*
*/
__pyx_v_little_endian = ((((char *)(&__pyx_v_endian_detector))[0]) != 0);
/* "numpy.pxd":794
* cdef tuple fields
*
* for childname in descr.names: # <<<<<<<<<<<<<<
* fields = descr.fields[childname]
* child, new_offset = fields
*/
if (unlikely(((PyObject *)__pyx_v_descr->names) == Py_None)) {
PyErr_SetString(PyExc_TypeError, "'NoneType' object is not iterable");
{__pyx_filename = __pyx_f[1]; __pyx_lineno = 794; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
}
__pyx_t_1 = ((PyObject *)__pyx_v_descr->names); __Pyx_INCREF(__pyx_t_1); __pyx_t_2 = 0;
for (;;) {
if (__pyx_t_2 >= PyTuple_GET_SIZE(__pyx_t_1)) break;
#if CYTHON_COMPILING_IN_CPYTHON
__pyx_t_3 = PyTuple_GET_ITEM(__pyx_t_1, __pyx_t_2); __Pyx_INCREF(__pyx_t_3); __pyx_t_2++; if (unlikely(0 < 0)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 794; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
#else
__pyx_t_3 = PySequence_ITEM(__pyx_t_1, __pyx_t_2); __pyx_t_2++; if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 794; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
#endif
__Pyx_XDECREF(__pyx_v_childname);
__pyx_v_childname = __pyx_t_3;
__pyx_t_3 = 0;
/* "numpy.pxd":795
*
* for childname in descr.names:
* fields = descr.fields[childname] # <<<<<<<<<<<<<<
* child, new_offset = fields
*
*/
__pyx_t_3 = PyObject_GetItem(__pyx_v_descr->fields, __pyx_v_childname); if (!__pyx_t_3) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 795; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_3);
if (!(likely(PyTuple_CheckExact(__pyx_t_3))||((__pyx_t_3) == Py_None)||(PyErr_Format(PyExc_TypeError, "Expected tuple, got %.200s", Py_TYPE(__pyx_t_3)->tp_name), 0))) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 795; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_XDECREF(((PyObject *)__pyx_v_fields));
__pyx_v_fields = ((PyObject*)__pyx_t_3);
__pyx_t_3 = 0;
/* "numpy.pxd":796
* for childname in descr.names:
* fields = descr.fields[childname]
* child, new_offset = fields # <<<<<<<<<<<<<<
*
* if (end - f) - (new_offset - offset[0]) < 15:
*/
if (likely(PyTuple_CheckExact(((PyObject *)__pyx_v_fields)))) {
PyObject* sequence = ((PyObject *)__pyx_v_fields);
#if CYTHON_COMPILING_IN_CPYTHON
Py_ssize_t size = Py_SIZE(sequence);
#else
Py_ssize_t size = PySequence_Size(sequence);
#endif
if (unlikely(size != 2)) {
if (size > 2) __Pyx_RaiseTooManyValuesError(2);
else if (size >= 0) __Pyx_RaiseNeedMoreValuesError(size);
{__pyx_filename = __pyx_f[1]; __pyx_lineno = 796; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
}
#if CYTHON_COMPILING_IN_CPYTHON
__pyx_t_3 = PyTuple_GET_ITEM(sequence, 0);
__pyx_t_4 = PyTuple_GET_ITEM(sequence, 1);
__Pyx_INCREF(__pyx_t_3);
__Pyx_INCREF(__pyx_t_4);
#else
__pyx_t_3 = PySequence_ITEM(sequence, 0); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 796; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__pyx_t_4 = PySequence_ITEM(sequence, 1); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 796; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
#endif
} else if (1) {
__Pyx_RaiseNoneNotIterableError(); {__pyx_filename = __pyx_f[1]; __pyx_lineno = 796; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
} else
{
Py_ssize_t index = -1;
__pyx_t_5 = PyObject_GetIter(((PyObject *)__pyx_v_fields)); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 796; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_5);
__pyx_t_6 = Py_TYPE(__pyx_t_5)->tp_iternext;
index = 0; __pyx_t_3 = __pyx_t_6(__pyx_t_5); if (unlikely(!__pyx_t_3)) goto __pyx_L5_unpacking_failed;
__Pyx_GOTREF(__pyx_t_3);
index = 1; __pyx_t_4 = __pyx_t_6(__pyx_t_5); if (unlikely(!__pyx_t_4)) goto __pyx_L5_unpacking_failed;
__Pyx_GOTREF(__pyx_t_4);
if (__Pyx_IternextUnpackEndCheck(__pyx_t_6(__pyx_t_5), 2) < 0) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 796; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__pyx_t_6 = NULL;
__Pyx_DECREF(__pyx_t_5); __pyx_t_5 = 0;
goto __pyx_L6_unpacking_done;
__pyx_L5_unpacking_failed:;
__Pyx_DECREF(__pyx_t_5); __pyx_t_5 = 0;
__pyx_t_6 = NULL;
if (__Pyx_IterFinish() == 0) __Pyx_RaiseNeedMoreValuesError(index);
{__pyx_filename = __pyx_f[1]; __pyx_lineno = 796; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__pyx_L6_unpacking_done:;
}
if (!(likely(((__pyx_t_3) == Py_None) || likely(__Pyx_TypeTest(__pyx_t_3, __pyx_ptype_5numpy_dtype))))) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 796; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_XDECREF(((PyObject *)__pyx_v_child));
__pyx_v_child = ((PyArray_Descr *)__pyx_t_3);
__pyx_t_3 = 0;
__Pyx_XDECREF(__pyx_v_new_offset);
__pyx_v_new_offset = __pyx_t_4;
__pyx_t_4 = 0;
/* "numpy.pxd":798
* child, new_offset = fields
*
* if (end - f) - (new_offset - offset[0]) < 15: # <<<<<<<<<<<<<<
* raise RuntimeError(u"Format string allocated too short, see comment in numpy.pxd")
*
*/
__pyx_t_4 = PyInt_FromLong((__pyx_v_end - __pyx_v_f)); if (unlikely(!__pyx_t_4)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 798; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_4);
__pyx_t_3 = PyInt_FromLong((__pyx_v_offset[0])); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 798; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_3);
__pyx_t_5 = PyNumber_Subtract(__pyx_v_new_offset, __pyx_t_3); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 798; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_5);
__Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0;
__pyx_t_3 = PyNumber_Subtract(__pyx_t_4, __pyx_t_5); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 798; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_3);
__Pyx_DECREF(__pyx_t_4); __pyx_t_4 = 0;
__Pyx_DECREF(__pyx_t_5); __pyx_t_5 = 0;
__pyx_t_5 = PyObject_RichCompare(__pyx_t_3, __pyx_int_15, Py_LT); __Pyx_XGOTREF(__pyx_t_5); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 798; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0;
__pyx_t_7 = __Pyx_PyObject_IsTrue(__pyx_t_5); if (unlikely(__pyx_t_7 < 0)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 798; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_DECREF(__pyx_t_5); __pyx_t_5 = 0;
if (__pyx_t_7) {
/* "numpy.pxd":799
*
* if (end - f) - (new_offset - offset[0]) < 15:
* raise RuntimeError(u"Format string allocated too short, see comment in numpy.pxd") # <<<<<<<<<<<<<<
*
* if ((child.byteorder == c'>' and little_endian) or
*/
__pyx_t_5 = PyObject_Call(__pyx_builtin_RuntimeError, ((PyObject *)__pyx_k_tuple_14), NULL); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 799; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_5);
__Pyx_Raise(__pyx_t_5, 0, 0, 0);
__Pyx_DECREF(__pyx_t_5); __pyx_t_5 = 0;
{__pyx_filename = __pyx_f[1]; __pyx_lineno = 799; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
goto __pyx_L7;
}
__pyx_L7:;
/* "numpy.pxd":801
* raise RuntimeError(u"Format string allocated too short, see comment in numpy.pxd")
*
* if ((child.byteorder == c'>' and little_endian) or # <<<<<<<<<<<<<<
* (child.byteorder == c'<' and not little_endian)):
* raise ValueError(u"Non-native byte order not supported")
*/
__pyx_t_7 = (__pyx_v_child->byteorder == '>');
if (__pyx_t_7) {
__pyx_t_8 = __pyx_v_little_endian;
} else {
__pyx_t_8 = __pyx_t_7;
}
if (!__pyx_t_8) {
/* "numpy.pxd":802
*
* if ((child.byteorder == c'>' and little_endian) or
* (child.byteorder == c'<' and not little_endian)): # <<<<<<<<<<<<<<
* raise ValueError(u"Non-native byte order not supported")
* # One could encode it in the format string and have Cython
*/
__pyx_t_7 = (__pyx_v_child->byteorder == '<');
if (__pyx_t_7) {
__pyx_t_9 = (!__pyx_v_little_endian);
__pyx_t_10 = __pyx_t_9;
} else {
__pyx_t_10 = __pyx_t_7;
}
__pyx_t_7 = __pyx_t_10;
} else {
__pyx_t_7 = __pyx_t_8;
}
if (__pyx_t_7) {
/* "numpy.pxd":803
* if ((child.byteorder == c'>' and little_endian) or
* (child.byteorder == c'<' and not little_endian)):
* raise ValueError(u"Non-native byte order not supported") # <<<<<<<<<<<<<<
* # One could encode it in the format string and have Cython
* # complain instead, BUT: < and > in format strings also imply
*/
__pyx_t_5 = PyObject_Call(__pyx_builtin_ValueError, ((PyObject *)__pyx_k_tuple_15), NULL); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 803; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_5);
__Pyx_Raise(__pyx_t_5, 0, 0, 0);
__Pyx_DECREF(__pyx_t_5); __pyx_t_5 = 0;
{__pyx_filename = __pyx_f[1]; __pyx_lineno = 803; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
goto __pyx_L8;
}
__pyx_L8:;
/* "numpy.pxd":813
*
* # Output padding bytes
* while offset[0] < new_offset: # <<<<<<<<<<<<<<
* f[0] = 120 # "x"; pad byte
* f += 1
*/
while (1) {
__pyx_t_5 = PyInt_FromLong((__pyx_v_offset[0])); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 813; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_5);
__pyx_t_3 = PyObject_RichCompare(__pyx_t_5, __pyx_v_new_offset, Py_LT); __Pyx_XGOTREF(__pyx_t_3); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 813; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_DECREF(__pyx_t_5); __pyx_t_5 = 0;
__pyx_t_7 = __Pyx_PyObject_IsTrue(__pyx_t_3); if (unlikely(__pyx_t_7 < 0)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 813; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0;
if (!__pyx_t_7) break;
/* "numpy.pxd":814
* # Output padding bytes
* while offset[0] < new_offset:
* f[0] = 120 # "x"; pad byte # <<<<<<<<<<<<<<
* f += 1
* offset[0] += 1
*/
(__pyx_v_f[0]) = 120;
/* "numpy.pxd":815
* while offset[0] < new_offset:
* f[0] = 120 # "x"; pad byte
* f += 1 # <<<<<<<<<<<<<<
* offset[0] += 1
*
*/
__pyx_v_f = (__pyx_v_f + 1);
/* "numpy.pxd":816
* f[0] = 120 # "x"; pad byte
* f += 1
* offset[0] += 1 # <<<<<<<<<<<<<<
*
* offset[0] += child.itemsize
*/
__pyx_t_11 = 0;
(__pyx_v_offset[__pyx_t_11]) = ((__pyx_v_offset[__pyx_t_11]) + 1);
}
/* "numpy.pxd":818
* offset[0] += 1
*
* offset[0] += child.itemsize # <<<<<<<<<<<<<<
*
* if not PyDataType_HASFIELDS(child):
*/
__pyx_t_11 = 0;
(__pyx_v_offset[__pyx_t_11]) = ((__pyx_v_offset[__pyx_t_11]) + __pyx_v_child->elsize);
/* "numpy.pxd":820
* offset[0] += child.itemsize
*
* if not PyDataType_HASFIELDS(child): # <<<<<<<<<<<<<<
* t = child.type_num
* if end - f < 5:
*/
__pyx_t_7 = (!PyDataType_HASFIELDS(__pyx_v_child));
if (__pyx_t_7) {
/* "numpy.pxd":821
*
* if not PyDataType_HASFIELDS(child):
* t = child.type_num # <<<<<<<<<<<<<<
* if end - f < 5:
* raise RuntimeError(u"Format string allocated too short.")
*/
__pyx_t_3 = PyInt_FromLong(__pyx_v_child->type_num); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 821; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_3);
__Pyx_XDECREF(__pyx_v_t);
__pyx_v_t = __pyx_t_3;
__pyx_t_3 = 0;
/* "numpy.pxd":822
* if not PyDataType_HASFIELDS(child):
* t = child.type_num
* if end - f < 5: # <<<<<<<<<<<<<<
* raise RuntimeError(u"Format string allocated too short.")
*
*/
__pyx_t_7 = ((__pyx_v_end - __pyx_v_f) < 5);
if (__pyx_t_7) {
/* "numpy.pxd":823
* t = child.type_num
* if end - f < 5:
* raise RuntimeError(u"Format string allocated too short.") # <<<<<<<<<<<<<<
*
* # Until ticket #99 is fixed, use integers to avoid warnings
*/
__pyx_t_3 = PyObject_Call(__pyx_builtin_RuntimeError, ((PyObject *)__pyx_k_tuple_17), NULL); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 823; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_3);
__Pyx_Raise(__pyx_t_3, 0, 0, 0);
__Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0;
{__pyx_filename = __pyx_f[1]; __pyx_lineno = 823; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
goto __pyx_L12;
}
__pyx_L12:;
/* "numpy.pxd":826
*
* # Until ticket #99 is fixed, use integers to avoid warnings
* if t == NPY_BYTE: f[0] = 98 #"b" # <<<<<<<<<<<<<<
* elif t == NPY_UBYTE: f[0] = 66 #"B"
* elif t == NPY_SHORT: f[0] = 104 #"h"
*/
__pyx_t_3 = PyInt_FromLong(NPY_BYTE); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 826; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_3);
__pyx_t_5 = PyObject_RichCompare(__pyx_v_t, __pyx_t_3, Py_EQ); __Pyx_XGOTREF(__pyx_t_5); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 826; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0;
__pyx_t_7 = __Pyx_PyObject_IsTrue(__pyx_t_5); if (unlikely(__pyx_t_7 < 0)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 826; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_DECREF(__pyx_t_5); __pyx_t_5 = 0;
if (__pyx_t_7) {
(__pyx_v_f[0]) = 98;
goto __pyx_L13;
}
/* "numpy.pxd":827
* # Until ticket #99 is fixed, use integers to avoid warnings
* if t == NPY_BYTE: f[0] = 98 #"b"
* elif t == NPY_UBYTE: f[0] = 66 #"B" # <<<<<<<<<<<<<<
* elif t == NPY_SHORT: f[0] = 104 #"h"
* elif t == NPY_USHORT: f[0] = 72 #"H"
*/
__pyx_t_5 = PyInt_FromLong(NPY_UBYTE); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 827; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_5);
__pyx_t_3 = PyObject_RichCompare(__pyx_v_t, __pyx_t_5, Py_EQ); __Pyx_XGOTREF(__pyx_t_3); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 827; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_DECREF(__pyx_t_5); __pyx_t_5 = 0;
__pyx_t_7 = __Pyx_PyObject_IsTrue(__pyx_t_3); if (unlikely(__pyx_t_7 < 0)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 827; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0;
if (__pyx_t_7) {
(__pyx_v_f[0]) = 66;
goto __pyx_L13;
}
/* "numpy.pxd":828
* if t == NPY_BYTE: f[0] = 98 #"b"
* elif t == NPY_UBYTE: f[0] = 66 #"B"
* elif t == NPY_SHORT: f[0] = 104 #"h" # <<<<<<<<<<<<<<
* elif t == NPY_USHORT: f[0] = 72 #"H"
* elif t == NPY_INT: f[0] = 105 #"i"
*/
__pyx_t_3 = PyInt_FromLong(NPY_SHORT); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 828; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_3);
__pyx_t_5 = PyObject_RichCompare(__pyx_v_t, __pyx_t_3, Py_EQ); __Pyx_XGOTREF(__pyx_t_5); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 828; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0;
__pyx_t_7 = __Pyx_PyObject_IsTrue(__pyx_t_5); if (unlikely(__pyx_t_7 < 0)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 828; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_DECREF(__pyx_t_5); __pyx_t_5 = 0;
if (__pyx_t_7) {
(__pyx_v_f[0]) = 104;
goto __pyx_L13;
}
/* "numpy.pxd":829
* elif t == NPY_UBYTE: f[0] = 66 #"B"
* elif t == NPY_SHORT: f[0] = 104 #"h"
* elif t == NPY_USHORT: f[0] = 72 #"H" # <<<<<<<<<<<<<<
* elif t == NPY_INT: f[0] = 105 #"i"
* elif t == NPY_UINT: f[0] = 73 #"I"
*/
__pyx_t_5 = PyInt_FromLong(NPY_USHORT); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 829; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_5);
__pyx_t_3 = PyObject_RichCompare(__pyx_v_t, __pyx_t_5, Py_EQ); __Pyx_XGOTREF(__pyx_t_3); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 829; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_DECREF(__pyx_t_5); __pyx_t_5 = 0;
__pyx_t_7 = __Pyx_PyObject_IsTrue(__pyx_t_3); if (unlikely(__pyx_t_7 < 0)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 829; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0;
if (__pyx_t_7) {
(__pyx_v_f[0]) = 72;
goto __pyx_L13;
}
/* "numpy.pxd":830
* elif t == NPY_SHORT: f[0] = 104 #"h"
* elif t == NPY_USHORT: f[0] = 72 #"H"
* elif t == NPY_INT: f[0] = 105 #"i" # <<<<<<<<<<<<<<
* elif t == NPY_UINT: f[0] = 73 #"I"
* elif t == NPY_LONG: f[0] = 108 #"l"
*/
__pyx_t_3 = PyInt_FromLong(NPY_INT); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 830; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_3);
__pyx_t_5 = PyObject_RichCompare(__pyx_v_t, __pyx_t_3, Py_EQ); __Pyx_XGOTREF(__pyx_t_5); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 830; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0;
__pyx_t_7 = __Pyx_PyObject_IsTrue(__pyx_t_5); if (unlikely(__pyx_t_7 < 0)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 830; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_DECREF(__pyx_t_5); __pyx_t_5 = 0;
if (__pyx_t_7) {
(__pyx_v_f[0]) = 105;
goto __pyx_L13;
}
/* "numpy.pxd":831
* elif t == NPY_USHORT: f[0] = 72 #"H"
* elif t == NPY_INT: f[0] = 105 #"i"
* elif t == NPY_UINT: f[0] = 73 #"I" # <<<<<<<<<<<<<<
* elif t == NPY_LONG: f[0] = 108 #"l"
* elif t == NPY_ULONG: f[0] = 76 #"L"
*/
__pyx_t_5 = PyInt_FromLong(NPY_UINT); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 831; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_5);
__pyx_t_3 = PyObject_RichCompare(__pyx_v_t, __pyx_t_5, Py_EQ); __Pyx_XGOTREF(__pyx_t_3); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 831; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_DECREF(__pyx_t_5); __pyx_t_5 = 0;
__pyx_t_7 = __Pyx_PyObject_IsTrue(__pyx_t_3); if (unlikely(__pyx_t_7 < 0)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 831; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0;
if (__pyx_t_7) {
(__pyx_v_f[0]) = 73;
goto __pyx_L13;
}
/* "numpy.pxd":832
* elif t == NPY_INT: f[0] = 105 #"i"
* elif t == NPY_UINT: f[0] = 73 #"I"
* elif t == NPY_LONG: f[0] = 108 #"l" # <<<<<<<<<<<<<<
* elif t == NPY_ULONG: f[0] = 76 #"L"
* elif t == NPY_LONGLONG: f[0] = 113 #"q"
*/
__pyx_t_3 = PyInt_FromLong(NPY_LONG); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 832; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_3);
__pyx_t_5 = PyObject_RichCompare(__pyx_v_t, __pyx_t_3, Py_EQ); __Pyx_XGOTREF(__pyx_t_5); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 832; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0;
__pyx_t_7 = __Pyx_PyObject_IsTrue(__pyx_t_5); if (unlikely(__pyx_t_7 < 0)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 832; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_DECREF(__pyx_t_5); __pyx_t_5 = 0;
if (__pyx_t_7) {
(__pyx_v_f[0]) = 108;
goto __pyx_L13;
}
/* "numpy.pxd":833
* elif t == NPY_UINT: f[0] = 73 #"I"
* elif t == NPY_LONG: f[0] = 108 #"l"
* elif t == NPY_ULONG: f[0] = 76 #"L" # <<<<<<<<<<<<<<
* elif t == NPY_LONGLONG: f[0] = 113 #"q"
* elif t == NPY_ULONGLONG: f[0] = 81 #"Q"
*/
__pyx_t_5 = PyInt_FromLong(NPY_ULONG); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 833; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_5);
__pyx_t_3 = PyObject_RichCompare(__pyx_v_t, __pyx_t_5, Py_EQ); __Pyx_XGOTREF(__pyx_t_3); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 833; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_DECREF(__pyx_t_5); __pyx_t_5 = 0;
__pyx_t_7 = __Pyx_PyObject_IsTrue(__pyx_t_3); if (unlikely(__pyx_t_7 < 0)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 833; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0;
if (__pyx_t_7) {
(__pyx_v_f[0]) = 76;
goto __pyx_L13;
}
/* "numpy.pxd":834
* elif t == NPY_LONG: f[0] = 108 #"l"
* elif t == NPY_ULONG: f[0] = 76 #"L"
* elif t == NPY_LONGLONG: f[0] = 113 #"q" # <<<<<<<<<<<<<<
* elif t == NPY_ULONGLONG: f[0] = 81 #"Q"
* elif t == NPY_FLOAT: f[0] = 102 #"f"
*/
__pyx_t_3 = PyInt_FromLong(NPY_LONGLONG); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 834; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_3);
__pyx_t_5 = PyObject_RichCompare(__pyx_v_t, __pyx_t_3, Py_EQ); __Pyx_XGOTREF(__pyx_t_5); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 834; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0;
__pyx_t_7 = __Pyx_PyObject_IsTrue(__pyx_t_5); if (unlikely(__pyx_t_7 < 0)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 834; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_DECREF(__pyx_t_5); __pyx_t_5 = 0;
if (__pyx_t_7) {
(__pyx_v_f[0]) = 113;
goto __pyx_L13;
}
/* "numpy.pxd":835
* elif t == NPY_ULONG: f[0] = 76 #"L"
* elif t == NPY_LONGLONG: f[0] = 113 #"q"
* elif t == NPY_ULONGLONG: f[0] = 81 #"Q" # <<<<<<<<<<<<<<
* elif t == NPY_FLOAT: f[0] = 102 #"f"
* elif t == NPY_DOUBLE: f[0] = 100 #"d"
*/
__pyx_t_5 = PyInt_FromLong(NPY_ULONGLONG); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 835; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_5);
__pyx_t_3 = PyObject_RichCompare(__pyx_v_t, __pyx_t_5, Py_EQ); __Pyx_XGOTREF(__pyx_t_3); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 835; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_DECREF(__pyx_t_5); __pyx_t_5 = 0;
__pyx_t_7 = __Pyx_PyObject_IsTrue(__pyx_t_3); if (unlikely(__pyx_t_7 < 0)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 835; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0;
if (__pyx_t_7) {
(__pyx_v_f[0]) = 81;
goto __pyx_L13;
}
/* "numpy.pxd":836
* elif t == NPY_LONGLONG: f[0] = 113 #"q"
* elif t == NPY_ULONGLONG: f[0] = 81 #"Q"
* elif t == NPY_FLOAT: f[0] = 102 #"f" # <<<<<<<<<<<<<<
* elif t == NPY_DOUBLE: f[0] = 100 #"d"
* elif t == NPY_LONGDOUBLE: f[0] = 103 #"g"
*/
__pyx_t_3 = PyInt_FromLong(NPY_FLOAT); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 836; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_3);
__pyx_t_5 = PyObject_RichCompare(__pyx_v_t, __pyx_t_3, Py_EQ); __Pyx_XGOTREF(__pyx_t_5); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 836; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0;
__pyx_t_7 = __Pyx_PyObject_IsTrue(__pyx_t_5); if (unlikely(__pyx_t_7 < 0)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 836; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_DECREF(__pyx_t_5); __pyx_t_5 = 0;
if (__pyx_t_7) {
(__pyx_v_f[0]) = 102;
goto __pyx_L13;
}
/* "numpy.pxd":837
* elif t == NPY_ULONGLONG: f[0] = 81 #"Q"
* elif t == NPY_FLOAT: f[0] = 102 #"f"
* elif t == NPY_DOUBLE: f[0] = 100 #"d" # <<<<<<<<<<<<<<
* elif t == NPY_LONGDOUBLE: f[0] = 103 #"g"
* elif t == NPY_CFLOAT: f[0] = 90; f[1] = 102; f += 1 # Zf
*/
__pyx_t_5 = PyInt_FromLong(NPY_DOUBLE); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 837; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_5);
__pyx_t_3 = PyObject_RichCompare(__pyx_v_t, __pyx_t_5, Py_EQ); __Pyx_XGOTREF(__pyx_t_3); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 837; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_DECREF(__pyx_t_5); __pyx_t_5 = 0;
__pyx_t_7 = __Pyx_PyObject_IsTrue(__pyx_t_3); if (unlikely(__pyx_t_7 < 0)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 837; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0;
if (__pyx_t_7) {
(__pyx_v_f[0]) = 100;
goto __pyx_L13;
}
/* "numpy.pxd":838
* elif t == NPY_FLOAT: f[0] = 102 #"f"
* elif t == NPY_DOUBLE: f[0] = 100 #"d"
* elif t == NPY_LONGDOUBLE: f[0] = 103 #"g" # <<<<<<<<<<<<<<
* elif t == NPY_CFLOAT: f[0] = 90; f[1] = 102; f += 1 # Zf
* elif t == NPY_CDOUBLE: f[0] = 90; f[1] = 100; f += 1 # Zd
*/
__pyx_t_3 = PyInt_FromLong(NPY_LONGDOUBLE); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 838; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_3);
__pyx_t_5 = PyObject_RichCompare(__pyx_v_t, __pyx_t_3, Py_EQ); __Pyx_XGOTREF(__pyx_t_5); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 838; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0;
__pyx_t_7 = __Pyx_PyObject_IsTrue(__pyx_t_5); if (unlikely(__pyx_t_7 < 0)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 838; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_DECREF(__pyx_t_5); __pyx_t_5 = 0;
if (__pyx_t_7) {
(__pyx_v_f[0]) = 103;
goto __pyx_L13;
}
/* "numpy.pxd":839
* elif t == NPY_DOUBLE: f[0] = 100 #"d"
* elif t == NPY_LONGDOUBLE: f[0] = 103 #"g"
* elif t == NPY_CFLOAT: f[0] = 90; f[1] = 102; f += 1 # Zf # <<<<<<<<<<<<<<
* elif t == NPY_CDOUBLE: f[0] = 90; f[1] = 100; f += 1 # Zd
* elif t == NPY_CLONGDOUBLE: f[0] = 90; f[1] = 103; f += 1 # Zg
*/
__pyx_t_5 = PyInt_FromLong(NPY_CFLOAT); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 839; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_5);
__pyx_t_3 = PyObject_RichCompare(__pyx_v_t, __pyx_t_5, Py_EQ); __Pyx_XGOTREF(__pyx_t_3); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 839; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_DECREF(__pyx_t_5); __pyx_t_5 = 0;
__pyx_t_7 = __Pyx_PyObject_IsTrue(__pyx_t_3); if (unlikely(__pyx_t_7 < 0)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 839; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0;
if (__pyx_t_7) {
(__pyx_v_f[0]) = 90;
(__pyx_v_f[1]) = 102;
__pyx_v_f = (__pyx_v_f + 1);
goto __pyx_L13;
}
/* "numpy.pxd":840
* elif t == NPY_LONGDOUBLE: f[0] = 103 #"g"
* elif t == NPY_CFLOAT: f[0] = 90; f[1] = 102; f += 1 # Zf
* elif t == NPY_CDOUBLE: f[0] = 90; f[1] = 100; f += 1 # Zd # <<<<<<<<<<<<<<
* elif t == NPY_CLONGDOUBLE: f[0] = 90; f[1] = 103; f += 1 # Zg
* elif t == NPY_OBJECT: f[0] = 79 #"O"
*/
__pyx_t_3 = PyInt_FromLong(NPY_CDOUBLE); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 840; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_3);
__pyx_t_5 = PyObject_RichCompare(__pyx_v_t, __pyx_t_3, Py_EQ); __Pyx_XGOTREF(__pyx_t_5); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 840; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0;
__pyx_t_7 = __Pyx_PyObject_IsTrue(__pyx_t_5); if (unlikely(__pyx_t_7 < 0)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 840; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_DECREF(__pyx_t_5); __pyx_t_5 = 0;
if (__pyx_t_7) {
(__pyx_v_f[0]) = 90;
(__pyx_v_f[1]) = 100;
__pyx_v_f = (__pyx_v_f + 1);
goto __pyx_L13;
}
/* "numpy.pxd":841
* elif t == NPY_CFLOAT: f[0] = 90; f[1] = 102; f += 1 # Zf
* elif t == NPY_CDOUBLE: f[0] = 90; f[1] = 100; f += 1 # Zd
* elif t == NPY_CLONGDOUBLE: f[0] = 90; f[1] = 103; f += 1 # Zg # <<<<<<<<<<<<<<
* elif t == NPY_OBJECT: f[0] = 79 #"O"
* else:
*/
__pyx_t_5 = PyInt_FromLong(NPY_CLONGDOUBLE); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 841; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_5);
__pyx_t_3 = PyObject_RichCompare(__pyx_v_t, __pyx_t_5, Py_EQ); __Pyx_XGOTREF(__pyx_t_3); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 841; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_DECREF(__pyx_t_5); __pyx_t_5 = 0;
__pyx_t_7 = __Pyx_PyObject_IsTrue(__pyx_t_3); if (unlikely(__pyx_t_7 < 0)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 841; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0;
if (__pyx_t_7) {
(__pyx_v_f[0]) = 90;
(__pyx_v_f[1]) = 103;
__pyx_v_f = (__pyx_v_f + 1);
goto __pyx_L13;
}
/* "numpy.pxd":842
* elif t == NPY_CDOUBLE: f[0] = 90; f[1] = 100; f += 1 # Zd
* elif t == NPY_CLONGDOUBLE: f[0] = 90; f[1] = 103; f += 1 # Zg
* elif t == NPY_OBJECT: f[0] = 79 #"O" # <<<<<<<<<<<<<<
* else:
* raise ValueError(u"unknown dtype code in numpy.pxd (%d)" % t)
*/
__pyx_t_3 = PyInt_FromLong(NPY_OBJECT); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 842; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_3);
__pyx_t_5 = PyObject_RichCompare(__pyx_v_t, __pyx_t_3, Py_EQ); __Pyx_XGOTREF(__pyx_t_5); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 842; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_DECREF(__pyx_t_3); __pyx_t_3 = 0;
__pyx_t_7 = __Pyx_PyObject_IsTrue(__pyx_t_5); if (unlikely(__pyx_t_7 < 0)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 842; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_DECREF(__pyx_t_5); __pyx_t_5 = 0;
if (__pyx_t_7) {
(__pyx_v_f[0]) = 79;
goto __pyx_L13;
}
/*else*/ {
/* "numpy.pxd":844
* elif t == NPY_OBJECT: f[0] = 79 #"O"
* else:
* raise ValueError(u"unknown dtype code in numpy.pxd (%d)" % t) # <<<<<<<<<<<<<<
* f += 1
* else:
*/
__pyx_t_5 = PyNumber_Remainder(((PyObject *)__pyx_kp_u_12), __pyx_v_t); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 844; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(((PyObject *)__pyx_t_5));
__pyx_t_3 = PyTuple_New(1); if (unlikely(!__pyx_t_3)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 844; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_3);
PyTuple_SET_ITEM(__pyx_t_3, 0, ((PyObject *)__pyx_t_5));
__Pyx_GIVEREF(((PyObject *)__pyx_t_5));
__pyx_t_5 = 0;
__pyx_t_5 = PyObject_Call(__pyx_builtin_ValueError, ((PyObject *)__pyx_t_3), NULL); if (unlikely(!__pyx_t_5)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 844; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_5);
__Pyx_DECREF(((PyObject *)__pyx_t_3)); __pyx_t_3 = 0;
__Pyx_Raise(__pyx_t_5, 0, 0, 0);
__Pyx_DECREF(__pyx_t_5); __pyx_t_5 = 0;
{__pyx_filename = __pyx_f[1]; __pyx_lineno = 844; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
}
__pyx_L13:;
/* "numpy.pxd":845
* else:
* raise ValueError(u"unknown dtype code in numpy.pxd (%d)" % t)
* f += 1 # <<<<<<<<<<<<<<
* else:
* # Cython ignores struct boundary information ("T{...}"),
*/
__pyx_v_f = (__pyx_v_f + 1);
goto __pyx_L11;
}
/*else*/ {
/* "numpy.pxd":849
* # Cython ignores struct boundary information ("T{...}"),
* # so don't output it
* f = _util_dtypestring(child, f, end, offset) # <<<<<<<<<<<<<<
* return f
*
*/
__pyx_t_12 = __pyx_f_5numpy__util_dtypestring(__pyx_v_child, __pyx_v_f, __pyx_v_end, __pyx_v_offset); if (unlikely(__pyx_t_12 == NULL)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 849; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__pyx_v_f = __pyx_t_12;
}
__pyx_L11:;
}
__Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0;
/* "numpy.pxd":850
* # so don't output it
* f = _util_dtypestring(child, f, end, offset)
* return f # <<<<<<<<<<<<<<
*
*
*/
__pyx_r = __pyx_v_f;
goto __pyx_L0;
__pyx_r = 0;
goto __pyx_L0;
__pyx_L1_error:;
__Pyx_XDECREF(__pyx_t_1);
__Pyx_XDECREF(__pyx_t_3);
__Pyx_XDECREF(__pyx_t_4);
__Pyx_XDECREF(__pyx_t_5);
__Pyx_AddTraceback("numpy._util_dtypestring", __pyx_clineno, __pyx_lineno, __pyx_filename);
__pyx_r = NULL;
__pyx_L0:;
__Pyx_XDECREF((PyObject *)__pyx_v_child);
__Pyx_XDECREF(__pyx_v_fields);
__Pyx_XDECREF(__pyx_v_childname);
__Pyx_XDECREF(__pyx_v_new_offset);
__Pyx_XDECREF(__pyx_v_t);
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
/* "numpy.pxd":965
*
*
* cdef inline void set_array_base(ndarray arr, object base): # <<<<<<<<<<<<<<
* cdef PyObject* baseptr
* if base is None:
*/
static CYTHON_INLINE void __pyx_f_5numpy_set_array_base(PyArrayObject *__pyx_v_arr, PyObject *__pyx_v_base) {
PyObject *__pyx_v_baseptr;
__Pyx_RefNannyDeclarations
int __pyx_t_1;
__Pyx_RefNannySetupContext("set_array_base", 0);
/* "numpy.pxd":967
* cdef inline void set_array_base(ndarray arr, object base):
* cdef PyObject* baseptr
* if base is None: # <<<<<<<<<<<<<<
* baseptr = NULL
* else:
*/
__pyx_t_1 = (__pyx_v_base == Py_None);
if (__pyx_t_1) {
/* "numpy.pxd":968
* cdef PyObject* baseptr
* if base is None:
* baseptr = NULL # <<<<<<<<<<<<<<
* else:
* Py_INCREF(base) # important to do this before decref below!
*/
__pyx_v_baseptr = NULL;
goto __pyx_L3;
}
/*else*/ {
/* "numpy.pxd":970
* baseptr = NULL
* else:
* Py_INCREF(base) # important to do this before decref below! # <<<<<<<<<<<<<<
* baseptr = <PyObject*>base
* Py_XDECREF(arr.base)
*/
Py_INCREF(__pyx_v_base);
/* "numpy.pxd":971
* else:
* Py_INCREF(base) # important to do this before decref below!
* baseptr = <PyObject*>base # <<<<<<<<<<<<<<
* Py_XDECREF(arr.base)
* arr.base = baseptr
*/
__pyx_v_baseptr = ((PyObject *)__pyx_v_base);
}
__pyx_L3:;
/* "numpy.pxd":972
* Py_INCREF(base) # important to do this before decref below!
* baseptr = <PyObject*>base
* Py_XDECREF(arr.base) # <<<<<<<<<<<<<<
* arr.base = baseptr
*
*/
Py_XDECREF(__pyx_v_arr->base);
/* "numpy.pxd":973
* baseptr = <PyObject*>base
* Py_XDECREF(arr.base)
* arr.base = baseptr # <<<<<<<<<<<<<<
*
* cdef inline object get_array_base(ndarray arr):
*/
__pyx_v_arr->base = __pyx_v_baseptr;
__Pyx_RefNannyFinishContext();
}
/* "numpy.pxd":975
* arr.base = baseptr
*
* cdef inline object get_array_base(ndarray arr): # <<<<<<<<<<<<<<
* if arr.base is NULL:
* return None
*/
static CYTHON_INLINE PyObject *__pyx_f_5numpy_get_array_base(PyArrayObject *__pyx_v_arr) {
PyObject *__pyx_r = NULL;
__Pyx_RefNannyDeclarations
int __pyx_t_1;
__Pyx_RefNannySetupContext("get_array_base", 0);
/* "numpy.pxd":976
*
* cdef inline object get_array_base(ndarray arr):
* if arr.base is NULL: # <<<<<<<<<<<<<<
* return None
* else:
*/
__pyx_t_1 = (__pyx_v_arr->base == NULL);
if (__pyx_t_1) {
/* "numpy.pxd":977
* cdef inline object get_array_base(ndarray arr):
* if arr.base is NULL:
* return None # <<<<<<<<<<<<<<
* else:
* return <object>arr.base
*/
__Pyx_XDECREF(__pyx_r);
__Pyx_INCREF(Py_None);
__pyx_r = Py_None;
goto __pyx_L0;
goto __pyx_L3;
}
/*else*/ {
/* "numpy.pxd":979
* return None
* else:
* return <object>arr.base # <<<<<<<<<<<<<<
*/
__Pyx_XDECREF(__pyx_r);
__Pyx_INCREF(((PyObject *)__pyx_v_arr->base));
__pyx_r = ((PyObject *)__pyx_v_arr->base);
goto __pyx_L0;
}
__pyx_L3:;
__pyx_r = Py_None; __Pyx_INCREF(Py_None);
__pyx_L0:;
__Pyx_XGIVEREF(__pyx_r);
__Pyx_RefNannyFinishContext();
return __pyx_r;
}
static struct __pyx_vtabstruct_7sklearn_12linear_model_8sgd_fast_LossFunction __pyx_vtable_7sklearn_12linear_model_8sgd_fast_LossFunction;
static PyObject *__pyx_tp_new_7sklearn_12linear_model_8sgd_fast_LossFunction(PyTypeObject *t, CYTHON_UNUSED PyObject *a, CYTHON_UNUSED PyObject *k) {
struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_LossFunction *p;
PyObject *o = (*t->tp_alloc)(t, 0);
if (!o) return 0;
p = ((struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_LossFunction *)o);
p->__pyx_vtab = __pyx_vtabptr_7sklearn_12linear_model_8sgd_fast_LossFunction;
return o;
}
static void __pyx_tp_dealloc_7sklearn_12linear_model_8sgd_fast_LossFunction(PyObject *o) {
(*Py_TYPE(o)->tp_free)(o);
}
static PyMethodDef __pyx_methods_7sklearn_12linear_model_8sgd_fast_LossFunction[] = {
{__Pyx_NAMESTR("loss"), (PyCFunction)__pyx_pw_7sklearn_12linear_model_8sgd_fast_12LossFunction_1loss, METH_VARARGS|METH_KEYWORDS, __Pyx_DOCSTR(__pyx_doc_7sklearn_12linear_model_8sgd_fast_12LossFunction_loss)},
{__Pyx_NAMESTR("dloss"), (PyCFunction)__pyx_pw_7sklearn_12linear_model_8sgd_fast_12LossFunction_3dloss, METH_VARARGS|METH_KEYWORDS, __Pyx_DOCSTR(__pyx_doc_7sklearn_12linear_model_8sgd_fast_12LossFunction_2dloss)},
{0, 0, 0, 0}
};
static PyNumberMethods __pyx_tp_as_number_LossFunction = {
0, /*nb_add*/
0, /*nb_subtract*/
0, /*nb_multiply*/
#if PY_MAJOR_VERSION < 3
0, /*nb_divide*/
#endif
0, /*nb_remainder*/
0, /*nb_divmod*/
0, /*nb_power*/
0, /*nb_negative*/
0, /*nb_positive*/
0, /*nb_absolute*/
0, /*nb_nonzero*/
0, /*nb_invert*/
0, /*nb_lshift*/
0, /*nb_rshift*/
0, /*nb_and*/
0, /*nb_xor*/
0, /*nb_or*/
#if PY_MAJOR_VERSION < 3
0, /*nb_coerce*/
#endif
0, /*nb_int*/
#if PY_MAJOR_VERSION < 3
0, /*nb_long*/
#else
0, /*reserved*/
#endif
0, /*nb_float*/
#if PY_MAJOR_VERSION < 3
0, /*nb_oct*/
#endif
#if PY_MAJOR_VERSION < 3
0, /*nb_hex*/
#endif
0, /*nb_inplace_add*/
0, /*nb_inplace_subtract*/
0, /*nb_inplace_multiply*/
#if PY_MAJOR_VERSION < 3
0, /*nb_inplace_divide*/
#endif
0, /*nb_inplace_remainder*/
0, /*nb_inplace_power*/
0, /*nb_inplace_lshift*/
0, /*nb_inplace_rshift*/
0, /*nb_inplace_and*/
0, /*nb_inplace_xor*/
0, /*nb_inplace_or*/
0, /*nb_floor_divide*/
0, /*nb_true_divide*/
0, /*nb_inplace_floor_divide*/
0, /*nb_inplace_true_divide*/
#if PY_VERSION_HEX >= 0x02050000
0, /*nb_index*/
#endif
};
static PySequenceMethods __pyx_tp_as_sequence_LossFunction = {
0, /*sq_length*/
0, /*sq_concat*/
0, /*sq_repeat*/
0, /*sq_item*/
0, /*sq_slice*/
0, /*sq_ass_item*/
0, /*sq_ass_slice*/
0, /*sq_contains*/
0, /*sq_inplace_concat*/
0, /*sq_inplace_repeat*/
};
static PyMappingMethods __pyx_tp_as_mapping_LossFunction = {
0, /*mp_length*/
0, /*mp_subscript*/
0, /*mp_ass_subscript*/
};
static PyBufferProcs __pyx_tp_as_buffer_LossFunction = {
#if PY_MAJOR_VERSION < 3
0, /*bf_getreadbuffer*/
#endif
#if PY_MAJOR_VERSION < 3
0, /*bf_getwritebuffer*/
#endif
#if PY_MAJOR_VERSION < 3
0, /*bf_getsegcount*/
#endif
#if PY_MAJOR_VERSION < 3
0, /*bf_getcharbuffer*/
#endif
#if PY_VERSION_HEX >= 0x02060000
0, /*bf_getbuffer*/
#endif
#if PY_VERSION_HEX >= 0x02060000
0, /*bf_releasebuffer*/
#endif
};
static PyTypeObject __pyx_type_7sklearn_12linear_model_8sgd_fast_LossFunction = {
PyVarObject_HEAD_INIT(0, 0)
__Pyx_NAMESTR("sklearn.linear_model.sgd_fast.LossFunction"), /*tp_name*/
sizeof(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_LossFunction), /*tp_basicsize*/
0, /*tp_itemsize*/
__pyx_tp_dealloc_7sklearn_12linear_model_8sgd_fast_LossFunction, /*tp_dealloc*/
0, /*tp_print*/
0, /*tp_getattr*/
0, /*tp_setattr*/
#if PY_MAJOR_VERSION < 3
0, /*tp_compare*/
#else
0, /*reserved*/
#endif
0, /*tp_repr*/
&__pyx_tp_as_number_LossFunction, /*tp_as_number*/
&__pyx_tp_as_sequence_LossFunction, /*tp_as_sequence*/
&__pyx_tp_as_mapping_LossFunction, /*tp_as_mapping*/
0, /*tp_hash*/
0, /*tp_call*/
0, /*tp_str*/
0, /*tp_getattro*/
0, /*tp_setattro*/
&__pyx_tp_as_buffer_LossFunction, /*tp_as_buffer*/
Py_TPFLAGS_DEFAULT|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE, /*tp_flags*/
__Pyx_DOCSTR("Base class for convex loss functions"), /*tp_doc*/
0, /*tp_traverse*/
0, /*tp_clear*/
0, /*tp_richcompare*/
0, /*tp_weaklistoffset*/
0, /*tp_iter*/
0, /*tp_iternext*/
__pyx_methods_7sklearn_12linear_model_8sgd_fast_LossFunction, /*tp_methods*/
0, /*tp_members*/
0, /*tp_getset*/
0, /*tp_base*/
0, /*tp_dict*/
0, /*tp_descr_get*/
0, /*tp_descr_set*/
0, /*tp_dictoffset*/
0, /*tp_init*/
0, /*tp_alloc*/
__pyx_tp_new_7sklearn_12linear_model_8sgd_fast_LossFunction, /*tp_new*/
0, /*tp_free*/
0, /*tp_is_gc*/
0, /*tp_bases*/
0, /*tp_mro*/
0, /*tp_cache*/
0, /*tp_subclasses*/
0, /*tp_weaklist*/
0, /*tp_del*/
#if PY_VERSION_HEX >= 0x02060000
0, /*tp_version_tag*/
#endif
};
static struct __pyx_vtabstruct_7sklearn_12linear_model_8sgd_fast_Regression __pyx_vtable_7sklearn_12linear_model_8sgd_fast_Regression;
static PyObject *__pyx_tp_new_7sklearn_12linear_model_8sgd_fast_Regression(PyTypeObject *t, PyObject *a, PyObject *k) {
struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_Regression *p;
PyObject *o = __pyx_tp_new_7sklearn_12linear_model_8sgd_fast_LossFunction(t, a, k);
if (!o) return 0;
p = ((struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_Regression *)o);
p->__pyx_base.__pyx_vtab = (struct __pyx_vtabstruct_7sklearn_12linear_model_8sgd_fast_LossFunction*)__pyx_vtabptr_7sklearn_12linear_model_8sgd_fast_Regression;
return o;
}
static PyMethodDef __pyx_methods_7sklearn_12linear_model_8sgd_fast_Regression[] = {
{__Pyx_NAMESTR("loss"), (PyCFunction)__pyx_pw_7sklearn_12linear_model_8sgd_fast_10Regression_1loss, METH_VARARGS|METH_KEYWORDS, __Pyx_DOCSTR(0)},
{__Pyx_NAMESTR("dloss"), (PyCFunction)__pyx_pw_7sklearn_12linear_model_8sgd_fast_10Regression_3dloss, METH_VARARGS|METH_KEYWORDS, __Pyx_DOCSTR(0)},
{0, 0, 0, 0}
};
static PyNumberMethods __pyx_tp_as_number_Regression = {
0, /*nb_add*/
0, /*nb_subtract*/
0, /*nb_multiply*/
#if PY_MAJOR_VERSION < 3
0, /*nb_divide*/
#endif
0, /*nb_remainder*/
0, /*nb_divmod*/
0, /*nb_power*/
0, /*nb_negative*/
0, /*nb_positive*/
0, /*nb_absolute*/
0, /*nb_nonzero*/
0, /*nb_invert*/
0, /*nb_lshift*/
0, /*nb_rshift*/
0, /*nb_and*/
0, /*nb_xor*/
0, /*nb_or*/
#if PY_MAJOR_VERSION < 3
0, /*nb_coerce*/
#endif
0, /*nb_int*/
#if PY_MAJOR_VERSION < 3
0, /*nb_long*/
#else
0, /*reserved*/
#endif
0, /*nb_float*/
#if PY_MAJOR_VERSION < 3
0, /*nb_oct*/
#endif
#if PY_MAJOR_VERSION < 3
0, /*nb_hex*/
#endif
0, /*nb_inplace_add*/
0, /*nb_inplace_subtract*/
0, /*nb_inplace_multiply*/
#if PY_MAJOR_VERSION < 3
0, /*nb_inplace_divide*/
#endif
0, /*nb_inplace_remainder*/
0, /*nb_inplace_power*/
0, /*nb_inplace_lshift*/
0, /*nb_inplace_rshift*/
0, /*nb_inplace_and*/
0, /*nb_inplace_xor*/
0, /*nb_inplace_or*/
0, /*nb_floor_divide*/
0, /*nb_true_divide*/
0, /*nb_inplace_floor_divide*/
0, /*nb_inplace_true_divide*/
#if PY_VERSION_HEX >= 0x02050000
0, /*nb_index*/
#endif
};
static PySequenceMethods __pyx_tp_as_sequence_Regression = {
0, /*sq_length*/
0, /*sq_concat*/
0, /*sq_repeat*/
0, /*sq_item*/
0, /*sq_slice*/
0, /*sq_ass_item*/
0, /*sq_ass_slice*/
0, /*sq_contains*/
0, /*sq_inplace_concat*/
0, /*sq_inplace_repeat*/
};
static PyMappingMethods __pyx_tp_as_mapping_Regression = {
0, /*mp_length*/
0, /*mp_subscript*/
0, /*mp_ass_subscript*/
};
static PyBufferProcs __pyx_tp_as_buffer_Regression = {
#if PY_MAJOR_VERSION < 3
0, /*bf_getreadbuffer*/
#endif
#if PY_MAJOR_VERSION < 3
0, /*bf_getwritebuffer*/
#endif
#if PY_MAJOR_VERSION < 3
0, /*bf_getsegcount*/
#endif
#if PY_MAJOR_VERSION < 3
0, /*bf_getcharbuffer*/
#endif
#if PY_VERSION_HEX >= 0x02060000
0, /*bf_getbuffer*/
#endif
#if PY_VERSION_HEX >= 0x02060000
0, /*bf_releasebuffer*/
#endif
};
static PyTypeObject __pyx_type_7sklearn_12linear_model_8sgd_fast_Regression = {
PyVarObject_HEAD_INIT(0, 0)
__Pyx_NAMESTR("sklearn.linear_model.sgd_fast.Regression"), /*tp_name*/
sizeof(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_Regression), /*tp_basicsize*/
0, /*tp_itemsize*/
__pyx_tp_dealloc_7sklearn_12linear_model_8sgd_fast_LossFunction, /*tp_dealloc*/
0, /*tp_print*/
0, /*tp_getattr*/
0, /*tp_setattr*/
#if PY_MAJOR_VERSION < 3
0, /*tp_compare*/
#else
0, /*reserved*/
#endif
0, /*tp_repr*/
&__pyx_tp_as_number_Regression, /*tp_as_number*/
&__pyx_tp_as_sequence_Regression, /*tp_as_sequence*/
&__pyx_tp_as_mapping_Regression, /*tp_as_mapping*/
0, /*tp_hash*/
0, /*tp_call*/
0, /*tp_str*/
0, /*tp_getattro*/
0, /*tp_setattro*/
&__pyx_tp_as_buffer_Regression, /*tp_as_buffer*/
Py_TPFLAGS_DEFAULT|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE, /*tp_flags*/
__Pyx_DOCSTR("Base class for loss functions for regression"), /*tp_doc*/
0, /*tp_traverse*/
0, /*tp_clear*/
0, /*tp_richcompare*/
0, /*tp_weaklistoffset*/
0, /*tp_iter*/
0, /*tp_iternext*/
__pyx_methods_7sklearn_12linear_model_8sgd_fast_Regression, /*tp_methods*/
0, /*tp_members*/
0, /*tp_getset*/
0, /*tp_base*/
0, /*tp_dict*/
0, /*tp_descr_get*/
0, /*tp_descr_set*/
0, /*tp_dictoffset*/
0, /*tp_init*/
0, /*tp_alloc*/
__pyx_tp_new_7sklearn_12linear_model_8sgd_fast_Regression, /*tp_new*/
0, /*tp_free*/
0, /*tp_is_gc*/
0, /*tp_bases*/
0, /*tp_mro*/
0, /*tp_cache*/
0, /*tp_subclasses*/
0, /*tp_weaklist*/
0, /*tp_del*/
#if PY_VERSION_HEX >= 0x02060000
0, /*tp_version_tag*/
#endif
};
static struct __pyx_vtabstruct_7sklearn_12linear_model_8sgd_fast_Classification __pyx_vtable_7sklearn_12linear_model_8sgd_fast_Classification;
static PyObject *__pyx_tp_new_7sklearn_12linear_model_8sgd_fast_Classification(PyTypeObject *t, PyObject *a, PyObject *k) {
struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_Classification *p;
PyObject *o = __pyx_tp_new_7sklearn_12linear_model_8sgd_fast_LossFunction(t, a, k);
if (!o) return 0;
p = ((struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_Classification *)o);
p->__pyx_base.__pyx_vtab = (struct __pyx_vtabstruct_7sklearn_12linear_model_8sgd_fast_LossFunction*)__pyx_vtabptr_7sklearn_12linear_model_8sgd_fast_Classification;
return o;
}
static PyMethodDef __pyx_methods_7sklearn_12linear_model_8sgd_fast_Classification[] = {
{__Pyx_NAMESTR("loss"), (PyCFunction)__pyx_pw_7sklearn_12linear_model_8sgd_fast_14Classification_1loss, METH_VARARGS|METH_KEYWORDS, __Pyx_DOCSTR(0)},
{__Pyx_NAMESTR("dloss"), (PyCFunction)__pyx_pw_7sklearn_12linear_model_8sgd_fast_14Classification_3dloss, METH_VARARGS|METH_KEYWORDS, __Pyx_DOCSTR(0)},
{0, 0, 0, 0}
};
static PyNumberMethods __pyx_tp_as_number_Classification = {
0, /*nb_add*/
0, /*nb_subtract*/
0, /*nb_multiply*/
#if PY_MAJOR_VERSION < 3
0, /*nb_divide*/
#endif
0, /*nb_remainder*/
0, /*nb_divmod*/
0, /*nb_power*/
0, /*nb_negative*/
0, /*nb_positive*/
0, /*nb_absolute*/
0, /*nb_nonzero*/
0, /*nb_invert*/
0, /*nb_lshift*/
0, /*nb_rshift*/
0, /*nb_and*/
0, /*nb_xor*/
0, /*nb_or*/
#if PY_MAJOR_VERSION < 3
0, /*nb_coerce*/
#endif
0, /*nb_int*/
#if PY_MAJOR_VERSION < 3
0, /*nb_long*/
#else
0, /*reserved*/
#endif
0, /*nb_float*/
#if PY_MAJOR_VERSION < 3
0, /*nb_oct*/
#endif
#if PY_MAJOR_VERSION < 3
0, /*nb_hex*/
#endif
0, /*nb_inplace_add*/
0, /*nb_inplace_subtract*/
0, /*nb_inplace_multiply*/
#if PY_MAJOR_VERSION < 3
0, /*nb_inplace_divide*/
#endif
0, /*nb_inplace_remainder*/
0, /*nb_inplace_power*/
0, /*nb_inplace_lshift*/
0, /*nb_inplace_rshift*/
0, /*nb_inplace_and*/
0, /*nb_inplace_xor*/
0, /*nb_inplace_or*/
0, /*nb_floor_divide*/
0, /*nb_true_divide*/
0, /*nb_inplace_floor_divide*/
0, /*nb_inplace_true_divide*/
#if PY_VERSION_HEX >= 0x02050000
0, /*nb_index*/
#endif
};
static PySequenceMethods __pyx_tp_as_sequence_Classification = {
0, /*sq_length*/
0, /*sq_concat*/
0, /*sq_repeat*/
0, /*sq_item*/
0, /*sq_slice*/
0, /*sq_ass_item*/
0, /*sq_ass_slice*/
0, /*sq_contains*/
0, /*sq_inplace_concat*/
0, /*sq_inplace_repeat*/
};
static PyMappingMethods __pyx_tp_as_mapping_Classification = {
0, /*mp_length*/
0, /*mp_subscript*/
0, /*mp_ass_subscript*/
};
static PyBufferProcs __pyx_tp_as_buffer_Classification = {
#if PY_MAJOR_VERSION < 3
0, /*bf_getreadbuffer*/
#endif
#if PY_MAJOR_VERSION < 3
0, /*bf_getwritebuffer*/
#endif
#if PY_MAJOR_VERSION < 3
0, /*bf_getsegcount*/
#endif
#if PY_MAJOR_VERSION < 3
0, /*bf_getcharbuffer*/
#endif
#if PY_VERSION_HEX >= 0x02060000
0, /*bf_getbuffer*/
#endif
#if PY_VERSION_HEX >= 0x02060000
0, /*bf_releasebuffer*/
#endif
};
static PyTypeObject __pyx_type_7sklearn_12linear_model_8sgd_fast_Classification = {
PyVarObject_HEAD_INIT(0, 0)
__Pyx_NAMESTR("sklearn.linear_model.sgd_fast.Classification"), /*tp_name*/
sizeof(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_Classification), /*tp_basicsize*/
0, /*tp_itemsize*/
__pyx_tp_dealloc_7sklearn_12linear_model_8sgd_fast_LossFunction, /*tp_dealloc*/
0, /*tp_print*/
0, /*tp_getattr*/
0, /*tp_setattr*/
#if PY_MAJOR_VERSION < 3
0, /*tp_compare*/
#else
0, /*reserved*/
#endif
0, /*tp_repr*/
&__pyx_tp_as_number_Classification, /*tp_as_number*/
&__pyx_tp_as_sequence_Classification, /*tp_as_sequence*/
&__pyx_tp_as_mapping_Classification, /*tp_as_mapping*/
0, /*tp_hash*/
0, /*tp_call*/
0, /*tp_str*/
0, /*tp_getattro*/
0, /*tp_setattro*/
&__pyx_tp_as_buffer_Classification, /*tp_as_buffer*/
Py_TPFLAGS_DEFAULT|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE, /*tp_flags*/
__Pyx_DOCSTR("Base class for loss functions for classification"), /*tp_doc*/
0, /*tp_traverse*/
0, /*tp_clear*/
0, /*tp_richcompare*/
0, /*tp_weaklistoffset*/
0, /*tp_iter*/
0, /*tp_iternext*/
__pyx_methods_7sklearn_12linear_model_8sgd_fast_Classification, /*tp_methods*/
0, /*tp_members*/
0, /*tp_getset*/
0, /*tp_base*/
0, /*tp_dict*/
0, /*tp_descr_get*/
0, /*tp_descr_set*/
0, /*tp_dictoffset*/
0, /*tp_init*/
0, /*tp_alloc*/
__pyx_tp_new_7sklearn_12linear_model_8sgd_fast_Classification, /*tp_new*/
0, /*tp_free*/
0, /*tp_is_gc*/
0, /*tp_bases*/
0, /*tp_mro*/
0, /*tp_cache*/
0, /*tp_subclasses*/
0, /*tp_weaklist*/
0, /*tp_del*/
#if PY_VERSION_HEX >= 0x02060000
0, /*tp_version_tag*/
#endif
};
static struct __pyx_vtabstruct_7sklearn_12linear_model_8sgd_fast_ModifiedHuber __pyx_vtable_7sklearn_12linear_model_8sgd_fast_ModifiedHuber;
static PyObject *__pyx_tp_new_7sklearn_12linear_model_8sgd_fast_ModifiedHuber(PyTypeObject *t, PyObject *a, PyObject *k) {
struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_ModifiedHuber *p;
PyObject *o = __pyx_tp_new_7sklearn_12linear_model_8sgd_fast_LossFunction(t, a, k);
if (!o) return 0;
p = ((struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_ModifiedHuber *)o);
p->__pyx_base.__pyx_base.__pyx_vtab = (struct __pyx_vtabstruct_7sklearn_12linear_model_8sgd_fast_LossFunction*)__pyx_vtabptr_7sklearn_12linear_model_8sgd_fast_ModifiedHuber;
return o;
}
static PyMethodDef __pyx_methods_7sklearn_12linear_model_8sgd_fast_ModifiedHuber[] = {
{__Pyx_NAMESTR("loss"), (PyCFunction)__pyx_pw_7sklearn_12linear_model_8sgd_fast_13ModifiedHuber_1loss, METH_VARARGS|METH_KEYWORDS, __Pyx_DOCSTR(0)},
{__Pyx_NAMESTR("dloss"), (PyCFunction)__pyx_pw_7sklearn_12linear_model_8sgd_fast_13ModifiedHuber_3dloss, METH_VARARGS|METH_KEYWORDS, __Pyx_DOCSTR(0)},
{__Pyx_NAMESTR("__reduce__"), (PyCFunction)__pyx_pw_7sklearn_12linear_model_8sgd_fast_13ModifiedHuber_5__reduce__, METH_NOARGS, __Pyx_DOCSTR(0)},
{0, 0, 0, 0}
};
static PyNumberMethods __pyx_tp_as_number_ModifiedHuber = {
0, /*nb_add*/
0, /*nb_subtract*/
0, /*nb_multiply*/
#if PY_MAJOR_VERSION < 3
0, /*nb_divide*/
#endif
0, /*nb_remainder*/
0, /*nb_divmod*/
0, /*nb_power*/
0, /*nb_negative*/
0, /*nb_positive*/
0, /*nb_absolute*/
0, /*nb_nonzero*/
0, /*nb_invert*/
0, /*nb_lshift*/
0, /*nb_rshift*/
0, /*nb_and*/
0, /*nb_xor*/
0, /*nb_or*/
#if PY_MAJOR_VERSION < 3
0, /*nb_coerce*/
#endif
0, /*nb_int*/
#if PY_MAJOR_VERSION < 3
0, /*nb_long*/
#else
0, /*reserved*/
#endif
0, /*nb_float*/
#if PY_MAJOR_VERSION < 3
0, /*nb_oct*/
#endif
#if PY_MAJOR_VERSION < 3
0, /*nb_hex*/
#endif
0, /*nb_inplace_add*/
0, /*nb_inplace_subtract*/
0, /*nb_inplace_multiply*/
#if PY_MAJOR_VERSION < 3
0, /*nb_inplace_divide*/
#endif
0, /*nb_inplace_remainder*/
0, /*nb_inplace_power*/
0, /*nb_inplace_lshift*/
0, /*nb_inplace_rshift*/
0, /*nb_inplace_and*/
0, /*nb_inplace_xor*/
0, /*nb_inplace_or*/
0, /*nb_floor_divide*/
0, /*nb_true_divide*/
0, /*nb_inplace_floor_divide*/
0, /*nb_inplace_true_divide*/
#if PY_VERSION_HEX >= 0x02050000
0, /*nb_index*/
#endif
};
static PySequenceMethods __pyx_tp_as_sequence_ModifiedHuber = {
0, /*sq_length*/
0, /*sq_concat*/
0, /*sq_repeat*/
0, /*sq_item*/
0, /*sq_slice*/
0, /*sq_ass_item*/
0, /*sq_ass_slice*/
0, /*sq_contains*/
0, /*sq_inplace_concat*/
0, /*sq_inplace_repeat*/
};
static PyMappingMethods __pyx_tp_as_mapping_ModifiedHuber = {
0, /*mp_length*/
0, /*mp_subscript*/
0, /*mp_ass_subscript*/
};
static PyBufferProcs __pyx_tp_as_buffer_ModifiedHuber = {
#if PY_MAJOR_VERSION < 3
0, /*bf_getreadbuffer*/
#endif
#if PY_MAJOR_VERSION < 3
0, /*bf_getwritebuffer*/
#endif
#if PY_MAJOR_VERSION < 3
0, /*bf_getsegcount*/
#endif
#if PY_MAJOR_VERSION < 3
0, /*bf_getcharbuffer*/
#endif
#if PY_VERSION_HEX >= 0x02060000
0, /*bf_getbuffer*/
#endif
#if PY_VERSION_HEX >= 0x02060000
0, /*bf_releasebuffer*/
#endif
};
static PyTypeObject __pyx_type_7sklearn_12linear_model_8sgd_fast_ModifiedHuber = {
PyVarObject_HEAD_INIT(0, 0)
__Pyx_NAMESTR("sklearn.linear_model.sgd_fast.ModifiedHuber"), /*tp_name*/
sizeof(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_ModifiedHuber), /*tp_basicsize*/
0, /*tp_itemsize*/
__pyx_tp_dealloc_7sklearn_12linear_model_8sgd_fast_LossFunction, /*tp_dealloc*/
0, /*tp_print*/
0, /*tp_getattr*/
0, /*tp_setattr*/
#if PY_MAJOR_VERSION < 3
0, /*tp_compare*/
#else
0, /*reserved*/
#endif
0, /*tp_repr*/
&__pyx_tp_as_number_ModifiedHuber, /*tp_as_number*/
&__pyx_tp_as_sequence_ModifiedHuber, /*tp_as_sequence*/
&__pyx_tp_as_mapping_ModifiedHuber, /*tp_as_mapping*/
0, /*tp_hash*/
0, /*tp_call*/
0, /*tp_str*/
0, /*tp_getattro*/
0, /*tp_setattro*/
&__pyx_tp_as_buffer_ModifiedHuber, /*tp_as_buffer*/
Py_TPFLAGS_DEFAULT|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE, /*tp_flags*/
__Pyx_DOCSTR("Modified Huber loss for binary classification with y in {-1, 1}\n\n This is equivalent to quadratically smoothed SVM with gamma = 2.\n\n See T. Zhang 'Solving Large Scale Linear Prediction Problems Using\n Stochastic Gradient Descent', ICML'04.\n "), /*tp_doc*/
0, /*tp_traverse*/
0, /*tp_clear*/
0, /*tp_richcompare*/
0, /*tp_weaklistoffset*/
0, /*tp_iter*/
0, /*tp_iternext*/
__pyx_methods_7sklearn_12linear_model_8sgd_fast_ModifiedHuber, /*tp_methods*/
0, /*tp_members*/
0, /*tp_getset*/
0, /*tp_base*/
0, /*tp_dict*/
0, /*tp_descr_get*/
0, /*tp_descr_set*/
0, /*tp_dictoffset*/
0, /*tp_init*/
0, /*tp_alloc*/
__pyx_tp_new_7sklearn_12linear_model_8sgd_fast_ModifiedHuber, /*tp_new*/
0, /*tp_free*/
0, /*tp_is_gc*/
0, /*tp_bases*/
0, /*tp_mro*/
0, /*tp_cache*/
0, /*tp_subclasses*/
0, /*tp_weaklist*/
0, /*tp_del*/
#if PY_VERSION_HEX >= 0x02060000
0, /*tp_version_tag*/
#endif
};
static struct __pyx_vtabstruct_7sklearn_12linear_model_8sgd_fast_Hinge __pyx_vtable_7sklearn_12linear_model_8sgd_fast_Hinge;
static PyObject *__pyx_tp_new_7sklearn_12linear_model_8sgd_fast_Hinge(PyTypeObject *t, PyObject *a, PyObject *k) {
struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_Hinge *p;
PyObject *o = __pyx_tp_new_7sklearn_12linear_model_8sgd_fast_LossFunction(t, a, k);
if (!o) return 0;
p = ((struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_Hinge *)o);
p->__pyx_base.__pyx_base.__pyx_vtab = (struct __pyx_vtabstruct_7sklearn_12linear_model_8sgd_fast_LossFunction*)__pyx_vtabptr_7sklearn_12linear_model_8sgd_fast_Hinge;
return o;
}
static PyMethodDef __pyx_methods_7sklearn_12linear_model_8sgd_fast_Hinge[] = {
{__Pyx_NAMESTR("loss"), (PyCFunction)__pyx_pw_7sklearn_12linear_model_8sgd_fast_5Hinge_3loss, METH_VARARGS|METH_KEYWORDS, __Pyx_DOCSTR(0)},
{__Pyx_NAMESTR("dloss"), (PyCFunction)__pyx_pw_7sklearn_12linear_model_8sgd_fast_5Hinge_5dloss, METH_VARARGS|METH_KEYWORDS, __Pyx_DOCSTR(0)},
{__Pyx_NAMESTR("__reduce__"), (PyCFunction)__pyx_pw_7sklearn_12linear_model_8sgd_fast_5Hinge_7__reduce__, METH_NOARGS, __Pyx_DOCSTR(0)},
{0, 0, 0, 0}
};
static PyNumberMethods __pyx_tp_as_number_Hinge = {
0, /*nb_add*/
0, /*nb_subtract*/
0, /*nb_multiply*/
#if PY_MAJOR_VERSION < 3
0, /*nb_divide*/
#endif
0, /*nb_remainder*/
0, /*nb_divmod*/
0, /*nb_power*/
0, /*nb_negative*/
0, /*nb_positive*/
0, /*nb_absolute*/
0, /*nb_nonzero*/
0, /*nb_invert*/
0, /*nb_lshift*/
0, /*nb_rshift*/
0, /*nb_and*/
0, /*nb_xor*/
0, /*nb_or*/
#if PY_MAJOR_VERSION < 3
0, /*nb_coerce*/
#endif
0, /*nb_int*/
#if PY_MAJOR_VERSION < 3
0, /*nb_long*/
#else
0, /*reserved*/
#endif
0, /*nb_float*/
#if PY_MAJOR_VERSION < 3
0, /*nb_oct*/
#endif
#if PY_MAJOR_VERSION < 3
0, /*nb_hex*/
#endif
0, /*nb_inplace_add*/
0, /*nb_inplace_subtract*/
0, /*nb_inplace_multiply*/
#if PY_MAJOR_VERSION < 3
0, /*nb_inplace_divide*/
#endif
0, /*nb_inplace_remainder*/
0, /*nb_inplace_power*/
0, /*nb_inplace_lshift*/
0, /*nb_inplace_rshift*/
0, /*nb_inplace_and*/
0, /*nb_inplace_xor*/
0, /*nb_inplace_or*/
0, /*nb_floor_divide*/
0, /*nb_true_divide*/
0, /*nb_inplace_floor_divide*/
0, /*nb_inplace_true_divide*/
#if PY_VERSION_HEX >= 0x02050000
0, /*nb_index*/
#endif
};
static PySequenceMethods __pyx_tp_as_sequence_Hinge = {
0, /*sq_length*/
0, /*sq_concat*/
0, /*sq_repeat*/
0, /*sq_item*/
0, /*sq_slice*/
0, /*sq_ass_item*/
0, /*sq_ass_slice*/
0, /*sq_contains*/
0, /*sq_inplace_concat*/
0, /*sq_inplace_repeat*/
};
static PyMappingMethods __pyx_tp_as_mapping_Hinge = {
0, /*mp_length*/
0, /*mp_subscript*/
0, /*mp_ass_subscript*/
};
static PyBufferProcs __pyx_tp_as_buffer_Hinge = {
#if PY_MAJOR_VERSION < 3
0, /*bf_getreadbuffer*/
#endif
#if PY_MAJOR_VERSION < 3
0, /*bf_getwritebuffer*/
#endif
#if PY_MAJOR_VERSION < 3
0, /*bf_getsegcount*/
#endif
#if PY_MAJOR_VERSION < 3
0, /*bf_getcharbuffer*/
#endif
#if PY_VERSION_HEX >= 0x02060000
0, /*bf_getbuffer*/
#endif
#if PY_VERSION_HEX >= 0x02060000
0, /*bf_releasebuffer*/
#endif
};
static PyTypeObject __pyx_type_7sklearn_12linear_model_8sgd_fast_Hinge = {
PyVarObject_HEAD_INIT(0, 0)
__Pyx_NAMESTR("sklearn.linear_model.sgd_fast.Hinge"), /*tp_name*/
sizeof(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_Hinge), /*tp_basicsize*/
0, /*tp_itemsize*/
__pyx_tp_dealloc_7sklearn_12linear_model_8sgd_fast_LossFunction, /*tp_dealloc*/
0, /*tp_print*/
0, /*tp_getattr*/
0, /*tp_setattr*/
#if PY_MAJOR_VERSION < 3
0, /*tp_compare*/
#else
0, /*reserved*/
#endif
0, /*tp_repr*/
&__pyx_tp_as_number_Hinge, /*tp_as_number*/
&__pyx_tp_as_sequence_Hinge, /*tp_as_sequence*/
&__pyx_tp_as_mapping_Hinge, /*tp_as_mapping*/
0, /*tp_hash*/
0, /*tp_call*/
0, /*tp_str*/
0, /*tp_getattro*/
0, /*tp_setattro*/
&__pyx_tp_as_buffer_Hinge, /*tp_as_buffer*/
Py_TPFLAGS_DEFAULT|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE, /*tp_flags*/
__Pyx_DOCSTR("Hinge loss for binary classification tasks with y in {-1,1}\n\n Parameters\n ----------\n\n threshold : float > 0.0\n Margin threshold. When threshold=1.0, one gets the loss used by SVM.\n When threshold=0.0, one gets the loss used by the Perceptron.\n "), /*tp_doc*/
0, /*tp_traverse*/
0, /*tp_clear*/
0, /*tp_richcompare*/
0, /*tp_weaklistoffset*/
0, /*tp_iter*/
0, /*tp_iternext*/
__pyx_methods_7sklearn_12linear_model_8sgd_fast_Hinge, /*tp_methods*/
0, /*tp_members*/
0, /*tp_getset*/
0, /*tp_base*/
0, /*tp_dict*/
0, /*tp_descr_get*/
0, /*tp_descr_set*/
0, /*tp_dictoffset*/
__pyx_pw_7sklearn_12linear_model_8sgd_fast_5Hinge_1__init__, /*tp_init*/
0, /*tp_alloc*/
__pyx_tp_new_7sklearn_12linear_model_8sgd_fast_Hinge, /*tp_new*/
0, /*tp_free*/
0, /*tp_is_gc*/
0, /*tp_bases*/
0, /*tp_mro*/
0, /*tp_cache*/
0, /*tp_subclasses*/
0, /*tp_weaklist*/
0, /*tp_del*/
#if PY_VERSION_HEX >= 0x02060000
0, /*tp_version_tag*/
#endif
};
static struct __pyx_vtabstruct_7sklearn_12linear_model_8sgd_fast_SquaredHinge __pyx_vtable_7sklearn_12linear_model_8sgd_fast_SquaredHinge;
static PyObject *__pyx_tp_new_7sklearn_12linear_model_8sgd_fast_SquaredHinge(PyTypeObject *t, PyObject *a, PyObject *k) {
struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_SquaredHinge *p;
PyObject *o = __pyx_tp_new_7sklearn_12linear_model_8sgd_fast_LossFunction(t, a, k);
if (!o) return 0;
p = ((struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_SquaredHinge *)o);
p->__pyx_base.__pyx_vtab = (struct __pyx_vtabstruct_7sklearn_12linear_model_8sgd_fast_LossFunction*)__pyx_vtabptr_7sklearn_12linear_model_8sgd_fast_SquaredHinge;
return o;
}
static PyMethodDef __pyx_methods_7sklearn_12linear_model_8sgd_fast_SquaredHinge[] = {
{__Pyx_NAMESTR("loss"), (PyCFunction)__pyx_pw_7sklearn_12linear_model_8sgd_fast_12SquaredHinge_3loss, METH_VARARGS|METH_KEYWORDS, __Pyx_DOCSTR(0)},
{__Pyx_NAMESTR("dloss"), (PyCFunction)__pyx_pw_7sklearn_12linear_model_8sgd_fast_12SquaredHinge_5dloss, METH_VARARGS|METH_KEYWORDS, __Pyx_DOCSTR(0)},
{__Pyx_NAMESTR("__reduce__"), (PyCFunction)__pyx_pw_7sklearn_12linear_model_8sgd_fast_12SquaredHinge_7__reduce__, METH_NOARGS, __Pyx_DOCSTR(0)},
{0, 0, 0, 0}
};
static PyNumberMethods __pyx_tp_as_number_SquaredHinge = {
0, /*nb_add*/
0, /*nb_subtract*/
0, /*nb_multiply*/
#if PY_MAJOR_VERSION < 3
0, /*nb_divide*/
#endif
0, /*nb_remainder*/
0, /*nb_divmod*/
0, /*nb_power*/
0, /*nb_negative*/
0, /*nb_positive*/
0, /*nb_absolute*/
0, /*nb_nonzero*/
0, /*nb_invert*/
0, /*nb_lshift*/
0, /*nb_rshift*/
0, /*nb_and*/
0, /*nb_xor*/
0, /*nb_or*/
#if PY_MAJOR_VERSION < 3
0, /*nb_coerce*/
#endif
0, /*nb_int*/
#if PY_MAJOR_VERSION < 3
0, /*nb_long*/
#else
0, /*reserved*/
#endif
0, /*nb_float*/
#if PY_MAJOR_VERSION < 3
0, /*nb_oct*/
#endif
#if PY_MAJOR_VERSION < 3
0, /*nb_hex*/
#endif
0, /*nb_inplace_add*/
0, /*nb_inplace_subtract*/
0, /*nb_inplace_multiply*/
#if PY_MAJOR_VERSION < 3
0, /*nb_inplace_divide*/
#endif
0, /*nb_inplace_remainder*/
0, /*nb_inplace_power*/
0, /*nb_inplace_lshift*/
0, /*nb_inplace_rshift*/
0, /*nb_inplace_and*/
0, /*nb_inplace_xor*/
0, /*nb_inplace_or*/
0, /*nb_floor_divide*/
0, /*nb_true_divide*/
0, /*nb_inplace_floor_divide*/
0, /*nb_inplace_true_divide*/
#if PY_VERSION_HEX >= 0x02050000
0, /*nb_index*/
#endif
};
static PySequenceMethods __pyx_tp_as_sequence_SquaredHinge = {
0, /*sq_length*/
0, /*sq_concat*/
0, /*sq_repeat*/
0, /*sq_item*/
0, /*sq_slice*/
0, /*sq_ass_item*/
0, /*sq_ass_slice*/
0, /*sq_contains*/
0, /*sq_inplace_concat*/
0, /*sq_inplace_repeat*/
};
static PyMappingMethods __pyx_tp_as_mapping_SquaredHinge = {
0, /*mp_length*/
0, /*mp_subscript*/
0, /*mp_ass_subscript*/
};
static PyBufferProcs __pyx_tp_as_buffer_SquaredHinge = {
#if PY_MAJOR_VERSION < 3
0, /*bf_getreadbuffer*/
#endif
#if PY_MAJOR_VERSION < 3
0, /*bf_getwritebuffer*/
#endif
#if PY_MAJOR_VERSION < 3
0, /*bf_getsegcount*/
#endif
#if PY_MAJOR_VERSION < 3
0, /*bf_getcharbuffer*/
#endif
#if PY_VERSION_HEX >= 0x02060000
0, /*bf_getbuffer*/
#endif
#if PY_VERSION_HEX >= 0x02060000
0, /*bf_releasebuffer*/
#endif
};
static PyTypeObject __pyx_type_7sklearn_12linear_model_8sgd_fast_SquaredHinge = {
PyVarObject_HEAD_INIT(0, 0)
__Pyx_NAMESTR("sklearn.linear_model.sgd_fast.SquaredHinge"), /*tp_name*/
sizeof(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_SquaredHinge), /*tp_basicsize*/
0, /*tp_itemsize*/
__pyx_tp_dealloc_7sklearn_12linear_model_8sgd_fast_LossFunction, /*tp_dealloc*/
0, /*tp_print*/
0, /*tp_getattr*/
0, /*tp_setattr*/
#if PY_MAJOR_VERSION < 3
0, /*tp_compare*/
#else
0, /*reserved*/
#endif
0, /*tp_repr*/
&__pyx_tp_as_number_SquaredHinge, /*tp_as_number*/
&__pyx_tp_as_sequence_SquaredHinge, /*tp_as_sequence*/
&__pyx_tp_as_mapping_SquaredHinge, /*tp_as_mapping*/
0, /*tp_hash*/
0, /*tp_call*/
0, /*tp_str*/
0, /*tp_getattro*/
0, /*tp_setattro*/
&__pyx_tp_as_buffer_SquaredHinge, /*tp_as_buffer*/
Py_TPFLAGS_DEFAULT|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE, /*tp_flags*/
__Pyx_DOCSTR("Squared Hinge loss for binary classification tasks with y in {-1,1}\n\n Parameters\n ----------\n\n threshold : float > 0.0\n Margin threshold. When threshold=1.0, one gets the loss used by\n (quadratically penalized) SVM.\n "), /*tp_doc*/
0, /*tp_traverse*/
0, /*tp_clear*/
0, /*tp_richcompare*/
0, /*tp_weaklistoffset*/
0, /*tp_iter*/
0, /*tp_iternext*/
__pyx_methods_7sklearn_12linear_model_8sgd_fast_SquaredHinge, /*tp_methods*/
0, /*tp_members*/
0, /*tp_getset*/
0, /*tp_base*/
0, /*tp_dict*/
0, /*tp_descr_get*/
0, /*tp_descr_set*/
0, /*tp_dictoffset*/
__pyx_pw_7sklearn_12linear_model_8sgd_fast_12SquaredHinge_1__init__, /*tp_init*/
0, /*tp_alloc*/
__pyx_tp_new_7sklearn_12linear_model_8sgd_fast_SquaredHinge, /*tp_new*/
0, /*tp_free*/
0, /*tp_is_gc*/
0, /*tp_bases*/
0, /*tp_mro*/
0, /*tp_cache*/
0, /*tp_subclasses*/
0, /*tp_weaklist*/
0, /*tp_del*/
#if PY_VERSION_HEX >= 0x02060000
0, /*tp_version_tag*/
#endif
};
static struct __pyx_vtabstruct_7sklearn_12linear_model_8sgd_fast_Log __pyx_vtable_7sklearn_12linear_model_8sgd_fast_Log;
static PyObject *__pyx_tp_new_7sklearn_12linear_model_8sgd_fast_Log(PyTypeObject *t, PyObject *a, PyObject *k) {
struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_Log *p;
PyObject *o = __pyx_tp_new_7sklearn_12linear_model_8sgd_fast_LossFunction(t, a, k);
if (!o) return 0;
p = ((struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_Log *)o);
p->__pyx_base.__pyx_base.__pyx_vtab = (struct __pyx_vtabstruct_7sklearn_12linear_model_8sgd_fast_LossFunction*)__pyx_vtabptr_7sklearn_12linear_model_8sgd_fast_Log;
return o;
}
static PyMethodDef __pyx_methods_7sklearn_12linear_model_8sgd_fast_Log[] = {
{__Pyx_NAMESTR("loss"), (PyCFunction)__pyx_pw_7sklearn_12linear_model_8sgd_fast_3Log_1loss, METH_VARARGS|METH_KEYWORDS, __Pyx_DOCSTR(0)},
{__Pyx_NAMESTR("dloss"), (PyCFunction)__pyx_pw_7sklearn_12linear_model_8sgd_fast_3Log_3dloss, METH_VARARGS|METH_KEYWORDS, __Pyx_DOCSTR(0)},
{__Pyx_NAMESTR("__reduce__"), (PyCFunction)__pyx_pw_7sklearn_12linear_model_8sgd_fast_3Log_5__reduce__, METH_NOARGS, __Pyx_DOCSTR(0)},
{0, 0, 0, 0}
};
static PyNumberMethods __pyx_tp_as_number_Log = {
0, /*nb_add*/
0, /*nb_subtract*/
0, /*nb_multiply*/
#if PY_MAJOR_VERSION < 3
0, /*nb_divide*/
#endif
0, /*nb_remainder*/
0, /*nb_divmod*/
0, /*nb_power*/
0, /*nb_negative*/
0, /*nb_positive*/
0, /*nb_absolute*/
0, /*nb_nonzero*/
0, /*nb_invert*/
0, /*nb_lshift*/
0, /*nb_rshift*/
0, /*nb_and*/
0, /*nb_xor*/
0, /*nb_or*/
#if PY_MAJOR_VERSION < 3
0, /*nb_coerce*/
#endif
0, /*nb_int*/
#if PY_MAJOR_VERSION < 3
0, /*nb_long*/
#else
0, /*reserved*/
#endif
0, /*nb_float*/
#if PY_MAJOR_VERSION < 3
0, /*nb_oct*/
#endif
#if PY_MAJOR_VERSION < 3
0, /*nb_hex*/
#endif
0, /*nb_inplace_add*/
0, /*nb_inplace_subtract*/
0, /*nb_inplace_multiply*/
#if PY_MAJOR_VERSION < 3
0, /*nb_inplace_divide*/
#endif
0, /*nb_inplace_remainder*/
0, /*nb_inplace_power*/
0, /*nb_inplace_lshift*/
0, /*nb_inplace_rshift*/
0, /*nb_inplace_and*/
0, /*nb_inplace_xor*/
0, /*nb_inplace_or*/
0, /*nb_floor_divide*/
0, /*nb_true_divide*/
0, /*nb_inplace_floor_divide*/
0, /*nb_inplace_true_divide*/
#if PY_VERSION_HEX >= 0x02050000
0, /*nb_index*/
#endif
};
static PySequenceMethods __pyx_tp_as_sequence_Log = {
0, /*sq_length*/
0, /*sq_concat*/
0, /*sq_repeat*/
0, /*sq_item*/
0, /*sq_slice*/
0, /*sq_ass_item*/
0, /*sq_ass_slice*/
0, /*sq_contains*/
0, /*sq_inplace_concat*/
0, /*sq_inplace_repeat*/
};
static PyMappingMethods __pyx_tp_as_mapping_Log = {
0, /*mp_length*/
0, /*mp_subscript*/
0, /*mp_ass_subscript*/
};
static PyBufferProcs __pyx_tp_as_buffer_Log = {
#if PY_MAJOR_VERSION < 3
0, /*bf_getreadbuffer*/
#endif
#if PY_MAJOR_VERSION < 3
0, /*bf_getwritebuffer*/
#endif
#if PY_MAJOR_VERSION < 3
0, /*bf_getsegcount*/
#endif
#if PY_MAJOR_VERSION < 3
0, /*bf_getcharbuffer*/
#endif
#if PY_VERSION_HEX >= 0x02060000
0, /*bf_getbuffer*/
#endif
#if PY_VERSION_HEX >= 0x02060000
0, /*bf_releasebuffer*/
#endif
};
static PyTypeObject __pyx_type_7sklearn_12linear_model_8sgd_fast_Log = {
PyVarObject_HEAD_INIT(0, 0)
__Pyx_NAMESTR("sklearn.linear_model.sgd_fast.Log"), /*tp_name*/
sizeof(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_Log), /*tp_basicsize*/
0, /*tp_itemsize*/
__pyx_tp_dealloc_7sklearn_12linear_model_8sgd_fast_LossFunction, /*tp_dealloc*/
0, /*tp_print*/
0, /*tp_getattr*/
0, /*tp_setattr*/
#if PY_MAJOR_VERSION < 3
0, /*tp_compare*/
#else
0, /*reserved*/
#endif
0, /*tp_repr*/
&__pyx_tp_as_number_Log, /*tp_as_number*/
&__pyx_tp_as_sequence_Log, /*tp_as_sequence*/
&__pyx_tp_as_mapping_Log, /*tp_as_mapping*/
0, /*tp_hash*/
0, /*tp_call*/
0, /*tp_str*/
0, /*tp_getattro*/
0, /*tp_setattro*/
&__pyx_tp_as_buffer_Log, /*tp_as_buffer*/
Py_TPFLAGS_DEFAULT|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE, /*tp_flags*/
__Pyx_DOCSTR("Logistic regression loss for binary classification with y in {-1, 1}"), /*tp_doc*/
0, /*tp_traverse*/
0, /*tp_clear*/
0, /*tp_richcompare*/
0, /*tp_weaklistoffset*/
0, /*tp_iter*/
0, /*tp_iternext*/
__pyx_methods_7sklearn_12linear_model_8sgd_fast_Log, /*tp_methods*/
0, /*tp_members*/
0, /*tp_getset*/
0, /*tp_base*/
0, /*tp_dict*/
0, /*tp_descr_get*/
0, /*tp_descr_set*/
0, /*tp_dictoffset*/
0, /*tp_init*/
0, /*tp_alloc*/
__pyx_tp_new_7sklearn_12linear_model_8sgd_fast_Log, /*tp_new*/
0, /*tp_free*/
0, /*tp_is_gc*/
0, /*tp_bases*/
0, /*tp_mro*/
0, /*tp_cache*/
0, /*tp_subclasses*/
0, /*tp_weaklist*/
0, /*tp_del*/
#if PY_VERSION_HEX >= 0x02060000
0, /*tp_version_tag*/
#endif
};
static struct __pyx_vtabstruct_7sklearn_12linear_model_8sgd_fast_SquaredLoss __pyx_vtable_7sklearn_12linear_model_8sgd_fast_SquaredLoss;
static PyObject *__pyx_tp_new_7sklearn_12linear_model_8sgd_fast_SquaredLoss(PyTypeObject *t, PyObject *a, PyObject *k) {
struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_SquaredLoss *p;
PyObject *o = __pyx_tp_new_7sklearn_12linear_model_8sgd_fast_LossFunction(t, a, k);
if (!o) return 0;
p = ((struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_SquaredLoss *)o);
p->__pyx_base.__pyx_base.__pyx_vtab = (struct __pyx_vtabstruct_7sklearn_12linear_model_8sgd_fast_LossFunction*)__pyx_vtabptr_7sklearn_12linear_model_8sgd_fast_SquaredLoss;
return o;
}
static PyMethodDef __pyx_methods_7sklearn_12linear_model_8sgd_fast_SquaredLoss[] = {
{__Pyx_NAMESTR("loss"), (PyCFunction)__pyx_pw_7sklearn_12linear_model_8sgd_fast_11SquaredLoss_1loss, METH_VARARGS|METH_KEYWORDS, __Pyx_DOCSTR(0)},
{__Pyx_NAMESTR("dloss"), (PyCFunction)__pyx_pw_7sklearn_12linear_model_8sgd_fast_11SquaredLoss_3dloss, METH_VARARGS|METH_KEYWORDS, __Pyx_DOCSTR(0)},
{__Pyx_NAMESTR("__reduce__"), (PyCFunction)__pyx_pw_7sklearn_12linear_model_8sgd_fast_11SquaredLoss_5__reduce__, METH_NOARGS, __Pyx_DOCSTR(0)},
{0, 0, 0, 0}
};
static PyNumberMethods __pyx_tp_as_number_SquaredLoss = {
0, /*nb_add*/
0, /*nb_subtract*/
0, /*nb_multiply*/
#if PY_MAJOR_VERSION < 3
0, /*nb_divide*/
#endif
0, /*nb_remainder*/
0, /*nb_divmod*/
0, /*nb_power*/
0, /*nb_negative*/
0, /*nb_positive*/
0, /*nb_absolute*/
0, /*nb_nonzero*/
0, /*nb_invert*/
0, /*nb_lshift*/
0, /*nb_rshift*/
0, /*nb_and*/
0, /*nb_xor*/
0, /*nb_or*/
#if PY_MAJOR_VERSION < 3
0, /*nb_coerce*/
#endif
0, /*nb_int*/
#if PY_MAJOR_VERSION < 3
0, /*nb_long*/
#else
0, /*reserved*/
#endif
0, /*nb_float*/
#if PY_MAJOR_VERSION < 3
0, /*nb_oct*/
#endif
#if PY_MAJOR_VERSION < 3
0, /*nb_hex*/
#endif
0, /*nb_inplace_add*/
0, /*nb_inplace_subtract*/
0, /*nb_inplace_multiply*/
#if PY_MAJOR_VERSION < 3
0, /*nb_inplace_divide*/
#endif
0, /*nb_inplace_remainder*/
0, /*nb_inplace_power*/
0, /*nb_inplace_lshift*/
0, /*nb_inplace_rshift*/
0, /*nb_inplace_and*/
0, /*nb_inplace_xor*/
0, /*nb_inplace_or*/
0, /*nb_floor_divide*/
0, /*nb_true_divide*/
0, /*nb_inplace_floor_divide*/
0, /*nb_inplace_true_divide*/
#if PY_VERSION_HEX >= 0x02050000
0, /*nb_index*/
#endif
};
static PySequenceMethods __pyx_tp_as_sequence_SquaredLoss = {
0, /*sq_length*/
0, /*sq_concat*/
0, /*sq_repeat*/
0, /*sq_item*/
0, /*sq_slice*/
0, /*sq_ass_item*/
0, /*sq_ass_slice*/
0, /*sq_contains*/
0, /*sq_inplace_concat*/
0, /*sq_inplace_repeat*/
};
static PyMappingMethods __pyx_tp_as_mapping_SquaredLoss = {
0, /*mp_length*/
0, /*mp_subscript*/
0, /*mp_ass_subscript*/
};
static PyBufferProcs __pyx_tp_as_buffer_SquaredLoss = {
#if PY_MAJOR_VERSION < 3
0, /*bf_getreadbuffer*/
#endif
#if PY_MAJOR_VERSION < 3
0, /*bf_getwritebuffer*/
#endif
#if PY_MAJOR_VERSION < 3
0, /*bf_getsegcount*/
#endif
#if PY_MAJOR_VERSION < 3
0, /*bf_getcharbuffer*/
#endif
#if PY_VERSION_HEX >= 0x02060000
0, /*bf_getbuffer*/
#endif
#if PY_VERSION_HEX >= 0x02060000
0, /*bf_releasebuffer*/
#endif
};
static PyTypeObject __pyx_type_7sklearn_12linear_model_8sgd_fast_SquaredLoss = {
PyVarObject_HEAD_INIT(0, 0)
__Pyx_NAMESTR("sklearn.linear_model.sgd_fast.SquaredLoss"), /*tp_name*/
sizeof(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_SquaredLoss), /*tp_basicsize*/
0, /*tp_itemsize*/
__pyx_tp_dealloc_7sklearn_12linear_model_8sgd_fast_LossFunction, /*tp_dealloc*/
0, /*tp_print*/
0, /*tp_getattr*/
0, /*tp_setattr*/
#if PY_MAJOR_VERSION < 3
0, /*tp_compare*/
#else
0, /*reserved*/
#endif
0, /*tp_repr*/
&__pyx_tp_as_number_SquaredLoss, /*tp_as_number*/
&__pyx_tp_as_sequence_SquaredLoss, /*tp_as_sequence*/
&__pyx_tp_as_mapping_SquaredLoss, /*tp_as_mapping*/
0, /*tp_hash*/
0, /*tp_call*/
0, /*tp_str*/
0, /*tp_getattro*/
0, /*tp_setattro*/
&__pyx_tp_as_buffer_SquaredLoss, /*tp_as_buffer*/
Py_TPFLAGS_DEFAULT|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE, /*tp_flags*/
__Pyx_DOCSTR("Squared loss traditional used in linear regression."), /*tp_doc*/
0, /*tp_traverse*/
0, /*tp_clear*/
0, /*tp_richcompare*/
0, /*tp_weaklistoffset*/
0, /*tp_iter*/
0, /*tp_iternext*/
__pyx_methods_7sklearn_12linear_model_8sgd_fast_SquaredLoss, /*tp_methods*/
0, /*tp_members*/
0, /*tp_getset*/
0, /*tp_base*/
0, /*tp_dict*/
0, /*tp_descr_get*/
0, /*tp_descr_set*/
0, /*tp_dictoffset*/
0, /*tp_init*/
0, /*tp_alloc*/
__pyx_tp_new_7sklearn_12linear_model_8sgd_fast_SquaredLoss, /*tp_new*/
0, /*tp_free*/
0, /*tp_is_gc*/
0, /*tp_bases*/
0, /*tp_mro*/
0, /*tp_cache*/
0, /*tp_subclasses*/
0, /*tp_weaklist*/
0, /*tp_del*/
#if PY_VERSION_HEX >= 0x02060000
0, /*tp_version_tag*/
#endif
};
static struct __pyx_vtabstruct_7sklearn_12linear_model_8sgd_fast_Huber __pyx_vtable_7sklearn_12linear_model_8sgd_fast_Huber;
static PyObject *__pyx_tp_new_7sklearn_12linear_model_8sgd_fast_Huber(PyTypeObject *t, PyObject *a, PyObject *k) {
struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_Huber *p;
PyObject *o = __pyx_tp_new_7sklearn_12linear_model_8sgd_fast_LossFunction(t, a, k);
if (!o) return 0;
p = ((struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_Huber *)o);
p->__pyx_base.__pyx_base.__pyx_vtab = (struct __pyx_vtabstruct_7sklearn_12linear_model_8sgd_fast_LossFunction*)__pyx_vtabptr_7sklearn_12linear_model_8sgd_fast_Huber;
return o;
}
static PyMethodDef __pyx_methods_7sklearn_12linear_model_8sgd_fast_Huber[] = {
{__Pyx_NAMESTR("loss"), (PyCFunction)__pyx_pw_7sklearn_12linear_model_8sgd_fast_5Huber_3loss, METH_VARARGS|METH_KEYWORDS, __Pyx_DOCSTR(0)},
{__Pyx_NAMESTR("dloss"), (PyCFunction)__pyx_pw_7sklearn_12linear_model_8sgd_fast_5Huber_5dloss, METH_VARARGS|METH_KEYWORDS, __Pyx_DOCSTR(0)},
{__Pyx_NAMESTR("__reduce__"), (PyCFunction)__pyx_pw_7sklearn_12linear_model_8sgd_fast_5Huber_7__reduce__, METH_NOARGS, __Pyx_DOCSTR(0)},
{0, 0, 0, 0}
};
static PyNumberMethods __pyx_tp_as_number_Huber = {
0, /*nb_add*/
0, /*nb_subtract*/
0, /*nb_multiply*/
#if PY_MAJOR_VERSION < 3
0, /*nb_divide*/
#endif
0, /*nb_remainder*/
0, /*nb_divmod*/
0, /*nb_power*/
0, /*nb_negative*/
0, /*nb_positive*/
0, /*nb_absolute*/
0, /*nb_nonzero*/
0, /*nb_invert*/
0, /*nb_lshift*/
0, /*nb_rshift*/
0, /*nb_and*/
0, /*nb_xor*/
0, /*nb_or*/
#if PY_MAJOR_VERSION < 3
0, /*nb_coerce*/
#endif
0, /*nb_int*/
#if PY_MAJOR_VERSION < 3
0, /*nb_long*/
#else
0, /*reserved*/
#endif
0, /*nb_float*/
#if PY_MAJOR_VERSION < 3
0, /*nb_oct*/
#endif
#if PY_MAJOR_VERSION < 3
0, /*nb_hex*/
#endif
0, /*nb_inplace_add*/
0, /*nb_inplace_subtract*/
0, /*nb_inplace_multiply*/
#if PY_MAJOR_VERSION < 3
0, /*nb_inplace_divide*/
#endif
0, /*nb_inplace_remainder*/
0, /*nb_inplace_power*/
0, /*nb_inplace_lshift*/
0, /*nb_inplace_rshift*/
0, /*nb_inplace_and*/
0, /*nb_inplace_xor*/
0, /*nb_inplace_or*/
0, /*nb_floor_divide*/
0, /*nb_true_divide*/
0, /*nb_inplace_floor_divide*/
0, /*nb_inplace_true_divide*/
#if PY_VERSION_HEX >= 0x02050000
0, /*nb_index*/
#endif
};
static PySequenceMethods __pyx_tp_as_sequence_Huber = {
0, /*sq_length*/
0, /*sq_concat*/
0, /*sq_repeat*/
0, /*sq_item*/
0, /*sq_slice*/
0, /*sq_ass_item*/
0, /*sq_ass_slice*/
0, /*sq_contains*/
0, /*sq_inplace_concat*/
0, /*sq_inplace_repeat*/
};
static PyMappingMethods __pyx_tp_as_mapping_Huber = {
0, /*mp_length*/
0, /*mp_subscript*/
0, /*mp_ass_subscript*/
};
static PyBufferProcs __pyx_tp_as_buffer_Huber = {
#if PY_MAJOR_VERSION < 3
0, /*bf_getreadbuffer*/
#endif
#if PY_MAJOR_VERSION < 3
0, /*bf_getwritebuffer*/
#endif
#if PY_MAJOR_VERSION < 3
0, /*bf_getsegcount*/
#endif
#if PY_MAJOR_VERSION < 3
0, /*bf_getcharbuffer*/
#endif
#if PY_VERSION_HEX >= 0x02060000
0, /*bf_getbuffer*/
#endif
#if PY_VERSION_HEX >= 0x02060000
0, /*bf_releasebuffer*/
#endif
};
static PyTypeObject __pyx_type_7sklearn_12linear_model_8sgd_fast_Huber = {
PyVarObject_HEAD_INIT(0, 0)
__Pyx_NAMESTR("sklearn.linear_model.sgd_fast.Huber"), /*tp_name*/
sizeof(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_Huber), /*tp_basicsize*/
0, /*tp_itemsize*/
__pyx_tp_dealloc_7sklearn_12linear_model_8sgd_fast_LossFunction, /*tp_dealloc*/
0, /*tp_print*/
0, /*tp_getattr*/
0, /*tp_setattr*/
#if PY_MAJOR_VERSION < 3
0, /*tp_compare*/
#else
0, /*reserved*/
#endif
0, /*tp_repr*/
&__pyx_tp_as_number_Huber, /*tp_as_number*/
&__pyx_tp_as_sequence_Huber, /*tp_as_sequence*/
&__pyx_tp_as_mapping_Huber, /*tp_as_mapping*/
0, /*tp_hash*/
0, /*tp_call*/
0, /*tp_str*/
0, /*tp_getattro*/
0, /*tp_setattro*/
&__pyx_tp_as_buffer_Huber, /*tp_as_buffer*/
Py_TPFLAGS_DEFAULT|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE, /*tp_flags*/
__Pyx_DOCSTR("Huber regression loss\n\n Variant of the SquaredLoss that is robust to outliers (quadratic near zero,\n linear in for large errors).\n\n http://en.wikipedia.org/wiki/Huber_Loss_Function\n "), /*tp_doc*/
0, /*tp_traverse*/
0, /*tp_clear*/
0, /*tp_richcompare*/
0, /*tp_weaklistoffset*/
0, /*tp_iter*/
0, /*tp_iternext*/
__pyx_methods_7sklearn_12linear_model_8sgd_fast_Huber, /*tp_methods*/
0, /*tp_members*/
0, /*tp_getset*/
0, /*tp_base*/
0, /*tp_dict*/
0, /*tp_descr_get*/
0, /*tp_descr_set*/
0, /*tp_dictoffset*/
__pyx_pw_7sklearn_12linear_model_8sgd_fast_5Huber_1__init__, /*tp_init*/
0, /*tp_alloc*/
__pyx_tp_new_7sklearn_12linear_model_8sgd_fast_Huber, /*tp_new*/
0, /*tp_free*/
0, /*tp_is_gc*/
0, /*tp_bases*/
0, /*tp_mro*/
0, /*tp_cache*/
0, /*tp_subclasses*/
0, /*tp_weaklist*/
0, /*tp_del*/
#if PY_VERSION_HEX >= 0x02060000
0, /*tp_version_tag*/
#endif
};
static struct __pyx_vtabstruct_7sklearn_12linear_model_8sgd_fast_EpsilonInsensitive __pyx_vtable_7sklearn_12linear_model_8sgd_fast_EpsilonInsensitive;
static PyObject *__pyx_tp_new_7sklearn_12linear_model_8sgd_fast_EpsilonInsensitive(PyTypeObject *t, PyObject *a, PyObject *k) {
struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_EpsilonInsensitive *p;
PyObject *o = __pyx_tp_new_7sklearn_12linear_model_8sgd_fast_LossFunction(t, a, k);
if (!o) return 0;
p = ((struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_EpsilonInsensitive *)o);
p->__pyx_base.__pyx_base.__pyx_vtab = (struct __pyx_vtabstruct_7sklearn_12linear_model_8sgd_fast_LossFunction*)__pyx_vtabptr_7sklearn_12linear_model_8sgd_fast_EpsilonInsensitive;
return o;
}
static PyMethodDef __pyx_methods_7sklearn_12linear_model_8sgd_fast_EpsilonInsensitive[] = {
{__Pyx_NAMESTR("loss"), (PyCFunction)__pyx_pw_7sklearn_12linear_model_8sgd_fast_18EpsilonInsensitive_3loss, METH_VARARGS|METH_KEYWORDS, __Pyx_DOCSTR(0)},
{__Pyx_NAMESTR("dloss"), (PyCFunction)__pyx_pw_7sklearn_12linear_model_8sgd_fast_18EpsilonInsensitive_5dloss, METH_VARARGS|METH_KEYWORDS, __Pyx_DOCSTR(0)},
{__Pyx_NAMESTR("__reduce__"), (PyCFunction)__pyx_pw_7sklearn_12linear_model_8sgd_fast_18EpsilonInsensitive_7__reduce__, METH_NOARGS, __Pyx_DOCSTR(0)},
{0, 0, 0, 0}
};
static PyNumberMethods __pyx_tp_as_number_EpsilonInsensitive = {
0, /*nb_add*/
0, /*nb_subtract*/
0, /*nb_multiply*/
#if PY_MAJOR_VERSION < 3
0, /*nb_divide*/
#endif
0, /*nb_remainder*/
0, /*nb_divmod*/
0, /*nb_power*/
0, /*nb_negative*/
0, /*nb_positive*/
0, /*nb_absolute*/
0, /*nb_nonzero*/
0, /*nb_invert*/
0, /*nb_lshift*/
0, /*nb_rshift*/
0, /*nb_and*/
0, /*nb_xor*/
0, /*nb_or*/
#if PY_MAJOR_VERSION < 3
0, /*nb_coerce*/
#endif
0, /*nb_int*/
#if PY_MAJOR_VERSION < 3
0, /*nb_long*/
#else
0, /*reserved*/
#endif
0, /*nb_float*/
#if PY_MAJOR_VERSION < 3
0, /*nb_oct*/
#endif
#if PY_MAJOR_VERSION < 3
0, /*nb_hex*/
#endif
0, /*nb_inplace_add*/
0, /*nb_inplace_subtract*/
0, /*nb_inplace_multiply*/
#if PY_MAJOR_VERSION < 3
0, /*nb_inplace_divide*/
#endif
0, /*nb_inplace_remainder*/
0, /*nb_inplace_power*/
0, /*nb_inplace_lshift*/
0, /*nb_inplace_rshift*/
0, /*nb_inplace_and*/
0, /*nb_inplace_xor*/
0, /*nb_inplace_or*/
0, /*nb_floor_divide*/
0, /*nb_true_divide*/
0, /*nb_inplace_floor_divide*/
0, /*nb_inplace_true_divide*/
#if PY_VERSION_HEX >= 0x02050000
0, /*nb_index*/
#endif
};
static PySequenceMethods __pyx_tp_as_sequence_EpsilonInsensitive = {
0, /*sq_length*/
0, /*sq_concat*/
0, /*sq_repeat*/
0, /*sq_item*/
0, /*sq_slice*/
0, /*sq_ass_item*/
0, /*sq_ass_slice*/
0, /*sq_contains*/
0, /*sq_inplace_concat*/
0, /*sq_inplace_repeat*/
};
static PyMappingMethods __pyx_tp_as_mapping_EpsilonInsensitive = {
0, /*mp_length*/
0, /*mp_subscript*/
0, /*mp_ass_subscript*/
};
static PyBufferProcs __pyx_tp_as_buffer_EpsilonInsensitive = {
#if PY_MAJOR_VERSION < 3
0, /*bf_getreadbuffer*/
#endif
#if PY_MAJOR_VERSION < 3
0, /*bf_getwritebuffer*/
#endif
#if PY_MAJOR_VERSION < 3
0, /*bf_getsegcount*/
#endif
#if PY_MAJOR_VERSION < 3
0, /*bf_getcharbuffer*/
#endif
#if PY_VERSION_HEX >= 0x02060000
0, /*bf_getbuffer*/
#endif
#if PY_VERSION_HEX >= 0x02060000
0, /*bf_releasebuffer*/
#endif
};
static PyTypeObject __pyx_type_7sklearn_12linear_model_8sgd_fast_EpsilonInsensitive = {
PyVarObject_HEAD_INIT(0, 0)
__Pyx_NAMESTR("sklearn.linear_model.sgd_fast.EpsilonInsensitive"), /*tp_name*/
sizeof(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_EpsilonInsensitive), /*tp_basicsize*/
0, /*tp_itemsize*/
__pyx_tp_dealloc_7sklearn_12linear_model_8sgd_fast_LossFunction, /*tp_dealloc*/
0, /*tp_print*/
0, /*tp_getattr*/
0, /*tp_setattr*/
#if PY_MAJOR_VERSION < 3
0, /*tp_compare*/
#else
0, /*reserved*/
#endif
0, /*tp_repr*/
&__pyx_tp_as_number_EpsilonInsensitive, /*tp_as_number*/
&__pyx_tp_as_sequence_EpsilonInsensitive, /*tp_as_sequence*/
&__pyx_tp_as_mapping_EpsilonInsensitive, /*tp_as_mapping*/
0, /*tp_hash*/
0, /*tp_call*/
0, /*tp_str*/
0, /*tp_getattro*/
0, /*tp_setattro*/
&__pyx_tp_as_buffer_EpsilonInsensitive, /*tp_as_buffer*/
Py_TPFLAGS_DEFAULT|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE, /*tp_flags*/
__Pyx_DOCSTR("Epsilon-Insensitive loss (used by SVR).\n\n loss = max(0, |y - p| - epsilon)\n "), /*tp_doc*/
0, /*tp_traverse*/
0, /*tp_clear*/
0, /*tp_richcompare*/
0, /*tp_weaklistoffset*/
0, /*tp_iter*/
0, /*tp_iternext*/
__pyx_methods_7sklearn_12linear_model_8sgd_fast_EpsilonInsensitive, /*tp_methods*/
0, /*tp_members*/
0, /*tp_getset*/
0, /*tp_base*/
0, /*tp_dict*/
0, /*tp_descr_get*/
0, /*tp_descr_set*/
0, /*tp_dictoffset*/
__pyx_pw_7sklearn_12linear_model_8sgd_fast_18EpsilonInsensitive_1__init__, /*tp_init*/
0, /*tp_alloc*/
__pyx_tp_new_7sklearn_12linear_model_8sgd_fast_EpsilonInsensitive, /*tp_new*/
0, /*tp_free*/
0, /*tp_is_gc*/
0, /*tp_bases*/
0, /*tp_mro*/
0, /*tp_cache*/
0, /*tp_subclasses*/
0, /*tp_weaklist*/
0, /*tp_del*/
#if PY_VERSION_HEX >= 0x02060000
0, /*tp_version_tag*/
#endif
};
static struct __pyx_vtabstruct_7sklearn_12linear_model_8sgd_fast_SquaredEpsilonInsensitive __pyx_vtable_7sklearn_12linear_model_8sgd_fast_SquaredEpsilonInsensitive;
static PyObject *__pyx_tp_new_7sklearn_12linear_model_8sgd_fast_SquaredEpsilonInsensitive(PyTypeObject *t, PyObject *a, PyObject *k) {
struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_SquaredEpsilonInsensitive *p;
PyObject *o = __pyx_tp_new_7sklearn_12linear_model_8sgd_fast_LossFunction(t, a, k);
if (!o) return 0;
p = ((struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_SquaredEpsilonInsensitive *)o);
p->__pyx_base.__pyx_base.__pyx_vtab = (struct __pyx_vtabstruct_7sklearn_12linear_model_8sgd_fast_LossFunction*)__pyx_vtabptr_7sklearn_12linear_model_8sgd_fast_SquaredEpsilonInsensitive;
return o;
}
static PyMethodDef __pyx_methods_7sklearn_12linear_model_8sgd_fast_SquaredEpsilonInsensitive[] = {
{__Pyx_NAMESTR("loss"), (PyCFunction)__pyx_pw_7sklearn_12linear_model_8sgd_fast_25SquaredEpsilonInsensitive_3loss, METH_VARARGS|METH_KEYWORDS, __Pyx_DOCSTR(0)},
{__Pyx_NAMESTR("dloss"), (PyCFunction)__pyx_pw_7sklearn_12linear_model_8sgd_fast_25SquaredEpsilonInsensitive_5dloss, METH_VARARGS|METH_KEYWORDS, __Pyx_DOCSTR(0)},
{__Pyx_NAMESTR("__reduce__"), (PyCFunction)__pyx_pw_7sklearn_12linear_model_8sgd_fast_25SquaredEpsilonInsensitive_7__reduce__, METH_NOARGS, __Pyx_DOCSTR(0)},
{0, 0, 0, 0}
};
static PyNumberMethods __pyx_tp_as_number_SquaredEpsilonInsensitive = {
0, /*nb_add*/
0, /*nb_subtract*/
0, /*nb_multiply*/
#if PY_MAJOR_VERSION < 3
0, /*nb_divide*/
#endif
0, /*nb_remainder*/
0, /*nb_divmod*/
0, /*nb_power*/
0, /*nb_negative*/
0, /*nb_positive*/
0, /*nb_absolute*/
0, /*nb_nonzero*/
0, /*nb_invert*/
0, /*nb_lshift*/
0, /*nb_rshift*/
0, /*nb_and*/
0, /*nb_xor*/
0, /*nb_or*/
#if PY_MAJOR_VERSION < 3
0, /*nb_coerce*/
#endif
0, /*nb_int*/
#if PY_MAJOR_VERSION < 3
0, /*nb_long*/
#else
0, /*reserved*/
#endif
0, /*nb_float*/
#if PY_MAJOR_VERSION < 3
0, /*nb_oct*/
#endif
#if PY_MAJOR_VERSION < 3
0, /*nb_hex*/
#endif
0, /*nb_inplace_add*/
0, /*nb_inplace_subtract*/
0, /*nb_inplace_multiply*/
#if PY_MAJOR_VERSION < 3
0, /*nb_inplace_divide*/
#endif
0, /*nb_inplace_remainder*/
0, /*nb_inplace_power*/
0, /*nb_inplace_lshift*/
0, /*nb_inplace_rshift*/
0, /*nb_inplace_and*/
0, /*nb_inplace_xor*/
0, /*nb_inplace_or*/
0, /*nb_floor_divide*/
0, /*nb_true_divide*/
0, /*nb_inplace_floor_divide*/
0, /*nb_inplace_true_divide*/
#if PY_VERSION_HEX >= 0x02050000
0, /*nb_index*/
#endif
};
static PySequenceMethods __pyx_tp_as_sequence_SquaredEpsilonInsensitive = {
0, /*sq_length*/
0, /*sq_concat*/
0, /*sq_repeat*/
0, /*sq_item*/
0, /*sq_slice*/
0, /*sq_ass_item*/
0, /*sq_ass_slice*/
0, /*sq_contains*/
0, /*sq_inplace_concat*/
0, /*sq_inplace_repeat*/
};
static PyMappingMethods __pyx_tp_as_mapping_SquaredEpsilonInsensitive = {
0, /*mp_length*/
0, /*mp_subscript*/
0, /*mp_ass_subscript*/
};
static PyBufferProcs __pyx_tp_as_buffer_SquaredEpsilonInsensitive = {
#if PY_MAJOR_VERSION < 3
0, /*bf_getreadbuffer*/
#endif
#if PY_MAJOR_VERSION < 3
0, /*bf_getwritebuffer*/
#endif
#if PY_MAJOR_VERSION < 3
0, /*bf_getsegcount*/
#endif
#if PY_MAJOR_VERSION < 3
0, /*bf_getcharbuffer*/
#endif
#if PY_VERSION_HEX >= 0x02060000
0, /*bf_getbuffer*/
#endif
#if PY_VERSION_HEX >= 0x02060000
0, /*bf_releasebuffer*/
#endif
};
static PyTypeObject __pyx_type_7sklearn_12linear_model_8sgd_fast_SquaredEpsilonInsensitive = {
PyVarObject_HEAD_INIT(0, 0)
__Pyx_NAMESTR("sklearn.linear_model.sgd_fast.SquaredEpsilonInsensitive"), /*tp_name*/
sizeof(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_SquaredEpsilonInsensitive), /*tp_basicsize*/
0, /*tp_itemsize*/
__pyx_tp_dealloc_7sklearn_12linear_model_8sgd_fast_LossFunction, /*tp_dealloc*/
0, /*tp_print*/
0, /*tp_getattr*/
0, /*tp_setattr*/
#if PY_MAJOR_VERSION < 3
0, /*tp_compare*/
#else
0, /*reserved*/
#endif
0, /*tp_repr*/
&__pyx_tp_as_number_SquaredEpsilonInsensitive, /*tp_as_number*/
&__pyx_tp_as_sequence_SquaredEpsilonInsensitive, /*tp_as_sequence*/
&__pyx_tp_as_mapping_SquaredEpsilonInsensitive, /*tp_as_mapping*/
0, /*tp_hash*/
0, /*tp_call*/
0, /*tp_str*/
0, /*tp_getattro*/
0, /*tp_setattro*/
&__pyx_tp_as_buffer_SquaredEpsilonInsensitive, /*tp_as_buffer*/
Py_TPFLAGS_DEFAULT|Py_TPFLAGS_CHECKTYPES|Py_TPFLAGS_HAVE_NEWBUFFER|Py_TPFLAGS_BASETYPE, /*tp_flags*/
__Pyx_DOCSTR("Epsilon-Insensitive loss.\n\n loss = max(0, |y - p| - epsilon)^2\n "), /*tp_doc*/
0, /*tp_traverse*/
0, /*tp_clear*/
0, /*tp_richcompare*/
0, /*tp_weaklistoffset*/
0, /*tp_iter*/
0, /*tp_iternext*/
__pyx_methods_7sklearn_12linear_model_8sgd_fast_SquaredEpsilonInsensitive, /*tp_methods*/
0, /*tp_members*/
0, /*tp_getset*/
0, /*tp_base*/
0, /*tp_dict*/
0, /*tp_descr_get*/
0, /*tp_descr_set*/
0, /*tp_dictoffset*/
__pyx_pw_7sklearn_12linear_model_8sgd_fast_25SquaredEpsilonInsensitive_1__init__, /*tp_init*/
0, /*tp_alloc*/
__pyx_tp_new_7sklearn_12linear_model_8sgd_fast_SquaredEpsilonInsensitive, /*tp_new*/
0, /*tp_free*/
0, /*tp_is_gc*/
0, /*tp_bases*/
0, /*tp_mro*/
0, /*tp_cache*/
0, /*tp_subclasses*/
0, /*tp_weaklist*/
0, /*tp_del*/
#if PY_VERSION_HEX >= 0x02060000
0, /*tp_version_tag*/
#endif
};
static PyMethodDef __pyx_methods[] = {
{0, 0, 0, 0}
};
#if PY_MAJOR_VERSION >= 3
static struct PyModuleDef __pyx_moduledef = {
PyModuleDef_HEAD_INIT,
__Pyx_NAMESTR("sgd_fast"),
0, /* m_doc */
-1, /* m_size */
__pyx_methods /* m_methods */,
NULL, /* m_reload */
NULL, /* m_traverse */
NULL, /* m_clear */
NULL /* m_free */
};
#endif
static __Pyx_StringTabEntry __pyx_string_tab[] = {
{&__pyx_kp_s_1, __pyx_k_1, sizeof(__pyx_k_1), 0, 0, 1, 0},
{&__pyx_kp_u_10, __pyx_k_10, sizeof(__pyx_k_10), 0, 1, 0, 0},
{&__pyx_kp_u_12, __pyx_k_12, sizeof(__pyx_k_12), 0, 1, 0, 0},
{&__pyx_kp_u_13, __pyx_k_13, sizeof(__pyx_k_13), 0, 1, 0, 0},
{&__pyx_kp_u_16, __pyx_k_16, sizeof(__pyx_k_16), 0, 1, 0, 0},
{&__pyx_kp_s_2, __pyx_k_2, sizeof(__pyx_k_2), 0, 0, 1, 0},
{&__pyx_kp_s_20, __pyx_k_20, sizeof(__pyx_k_20), 0, 0, 1, 0},
{&__pyx_n_s_21, __pyx_k_21, sizeof(__pyx_k_21), 0, 0, 1, 1},
{&__pyx_kp_s_3, __pyx_k_3, sizeof(__pyx_k_3), 0, 0, 1, 0},
{&__pyx_kp_s_4, __pyx_k_4, sizeof(__pyx_k_4), 0, 0, 1, 0},
{&__pyx_kp_u_6, __pyx_k_6, sizeof(__pyx_k_6), 0, 1, 0, 0},
{&__pyx_kp_u_8, __pyx_k_8, sizeof(__pyx_k_8), 0, 1, 0, 0},
{&__pyx_n_s__C, __pyx_k__C, sizeof(__pyx_k__C), 0, 0, 1, 1},
{&__pyx_n_s__NotImplementedError, __pyx_k__NotImplementedError, sizeof(__pyx_k__NotImplementedError), 0, 0, 1, 1},
{&__pyx_n_s__RuntimeError, __pyx_k__RuntimeError, sizeof(__pyx_k__RuntimeError), 0, 0, 1, 1},
{&__pyx_n_s__ValueError, __pyx_k__ValueError, sizeof(__pyx_k__ValueError), 0, 0, 1, 1},
{&__pyx_n_s____main__, __pyx_k____main__, sizeof(__pyx_k____main__), 0, 0, 1, 1},
{&__pyx_n_s____test__, __pyx_k____test__, sizeof(__pyx_k____test__), 0, 0, 1, 1},
{&__pyx_n_s__alpha, __pyx_k__alpha, sizeof(__pyx_k__alpha), 0, 0, 1, 1},
{&__pyx_n_s__any, __pyx_k__any, sizeof(__pyx_k__any), 0, 0, 1, 1},
{&__pyx_n_s__c, __pyx_k__c, sizeof(__pyx_k__c), 0, 0, 1, 1},
{&__pyx_n_s__class_weight, __pyx_k__class_weight, sizeof(__pyx_k__class_weight), 0, 0, 1, 1},
{&__pyx_n_s__count, __pyx_k__count, sizeof(__pyx_k__count), 0, 0, 1, 1},
{&__pyx_n_s__dataset, __pyx_k__dataset, sizeof(__pyx_k__dataset), 0, 0, 1, 1},
{&__pyx_n_s__dloss, __pyx_k__dloss, sizeof(__pyx_k__dloss), 0, 0, 1, 1},
{&__pyx_n_s__dtype, __pyx_k__dtype, sizeof(__pyx_k__dtype), 0, 0, 1, 1},
{&__pyx_n_s__epoch, __pyx_k__epoch, sizeof(__pyx_k__epoch), 0, 0, 1, 1},
{&__pyx_n_s__epsilon, __pyx_k__epsilon, sizeof(__pyx_k__epsilon), 0, 0, 1, 1},
{&__pyx_n_s__eta, __pyx_k__eta, sizeof(__pyx_k__eta), 0, 0, 1, 1},
{&__pyx_n_s__eta0, __pyx_k__eta0, sizeof(__pyx_k__eta0), 0, 0, 1, 1},
{&__pyx_n_s__fit_intercept, __pyx_k__fit_intercept, sizeof(__pyx_k__fit_intercept), 0, 0, 1, 1},
{&__pyx_n_s__float64, __pyx_k__float64, sizeof(__pyx_k__float64), 0, 0, 1, 1},
{&__pyx_n_s__i, __pyx_k__i, sizeof(__pyx_k__i), 0, 0, 1, 1},
{&__pyx_n_s__intercept, __pyx_k__intercept, sizeof(__pyx_k__intercept), 0, 0, 1, 1},
{&__pyx_n_s__intercept_decay, __pyx_k__intercept_decay, sizeof(__pyx_k__intercept_decay), 0, 0, 1, 1},
{&__pyx_n_s__is_hinge, __pyx_k__is_hinge, sizeof(__pyx_k__is_hinge), 0, 0, 1, 1},
{&__pyx_n_s__isinf, __pyx_k__isinf, sizeof(__pyx_k__isinf), 0, 0, 1, 1},
{&__pyx_n_s__isnan, __pyx_k__isnan, sizeof(__pyx_k__isnan), 0, 0, 1, 1},
{&__pyx_n_s__learning_rate, __pyx_k__learning_rate, sizeof(__pyx_k__learning_rate), 0, 0, 1, 1},
{&__pyx_n_s__loss, __pyx_k__loss, sizeof(__pyx_k__loss), 0, 0, 1, 1},
{&__pyx_n_s__n_features, __pyx_k__n_features, sizeof(__pyx_k__n_features), 0, 0, 1, 1},
{&__pyx_n_s__n_iter, __pyx_k__n_iter, sizeof(__pyx_k__n_iter), 0, 0, 1, 1},
{&__pyx_n_s__n_samples, __pyx_k__n_samples, sizeof(__pyx_k__n_samples), 0, 0, 1, 1},
{&__pyx_n_s__nonzero, __pyx_k__nonzero, sizeof(__pyx_k__nonzero), 0, 0, 1, 1},
{&__pyx_n_s__np, __pyx_k__np, sizeof(__pyx_k__np), 0, 0, 1, 1},
{&__pyx_n_s__numpy, __pyx_k__numpy, sizeof(__pyx_k__numpy), 0, 0, 1, 1},
{&__pyx_n_s__order, __pyx_k__order, sizeof(__pyx_k__order), 0, 0, 1, 1},
{&__pyx_n_s__p, __pyx_k__p, sizeof(__pyx_k__p), 0, 0, 1, 1},
{&__pyx_n_s__penalty_type, __pyx_k__penalty_type, sizeof(__pyx_k__penalty_type), 0, 0, 1, 1},
{&__pyx_n_s__plain_sgd, __pyx_k__plain_sgd, sizeof(__pyx_k__plain_sgd), 0, 0, 1, 1},
{&__pyx_n_s__power_t, __pyx_k__power_t, sizeof(__pyx_k__power_t), 0, 0, 1, 1},
{&__pyx_n_s__q, __pyx_k__q, sizeof(__pyx_k__q), 0, 0, 1, 1},
{&__pyx_n_s__q_data_ptr, __pyx_k__q_data_ptr, sizeof(__pyx_k__q_data_ptr), 0, 0, 1, 1},
{&__pyx_n_s__range, __pyx_k__range, sizeof(__pyx_k__range), 0, 0, 1, 1},
{&__pyx_n_s__rho, __pyx_k__rho, sizeof(__pyx_k__rho), 0, 0, 1, 1},
{&__pyx_n_s__sample_weight, __pyx_k__sample_weight, sizeof(__pyx_k__sample_weight), 0, 0, 1, 1},
{&__pyx_n_s__seed, __pyx_k__seed, sizeof(__pyx_k__seed), 0, 0, 1, 1},
{&__pyx_n_s__shape, __pyx_k__shape, sizeof(__pyx_k__shape), 0, 0, 1, 1},
{&__pyx_n_s__shuffle, __pyx_k__shuffle, sizeof(__pyx_k__shuffle), 0, 0, 1, 1},
{&__pyx_n_s__sumloss, __pyx_k__sumloss, sizeof(__pyx_k__sumloss), 0, 0, 1, 1},
{&__pyx_n_s__sys, __pyx_k__sys, sizeof(__pyx_k__sys), 0, 0, 1, 1},
{&__pyx_n_s__t, __pyx_k__t, sizeof(__pyx_k__t), 0, 0, 1, 1},
{&__pyx_n_s__t_start, __pyx_k__t_start, sizeof(__pyx_k__t_start), 0, 0, 1, 1},
{&__pyx_n_s__threshold, __pyx_k__threshold, sizeof(__pyx_k__threshold), 0, 0, 1, 1},
{&__pyx_n_s__time, __pyx_k__time, sizeof(__pyx_k__time), 0, 0, 1, 1},
{&__pyx_n_s__u, __pyx_k__u, sizeof(__pyx_k__u), 0, 0, 1, 1},
{&__pyx_n_s__update, __pyx_k__update, sizeof(__pyx_k__update), 0, 0, 1, 1},
{&__pyx_n_s__verbose, __pyx_k__verbose, sizeof(__pyx_k__verbose), 0, 0, 1, 1},
{&__pyx_n_s__w, __pyx_k__w, sizeof(__pyx_k__w), 0, 0, 1, 1},
{&__pyx_n_s__weight_neg, __pyx_k__weight_neg, sizeof(__pyx_k__weight_neg), 0, 0, 1, 1},
{&__pyx_n_s__weight_pos, __pyx_k__weight_pos, sizeof(__pyx_k__weight_pos), 0, 0, 1, 1},
{&__pyx_n_s__weights, __pyx_k__weights, sizeof(__pyx_k__weights), 0, 0, 1, 1},
{&__pyx_n_s__x_data_ptr, __pyx_k__x_data_ptr, sizeof(__pyx_k__x_data_ptr), 0, 0, 1, 1},
{&__pyx_n_s__x_ind_ptr, __pyx_k__x_ind_ptr, sizeof(__pyx_k__x_ind_ptr), 0, 0, 1, 1},
{&__pyx_n_s__xnnz, __pyx_k__xnnz, sizeof(__pyx_k__xnnz), 0, 0, 1, 1},
{&__pyx_n_s__y, __pyx_k__y, sizeof(__pyx_k__y), 0, 0, 1, 1},
{&__pyx_n_s__zeros, __pyx_k__zeros, sizeof(__pyx_k__zeros), 0, 0, 1, 1},
{0, 0, 0, 0, 0, 0, 0}
};
static int __Pyx_InitCachedBuiltins(void) {
__pyx_builtin_NotImplementedError = __Pyx_GetName(__pyx_b, __pyx_n_s__NotImplementedError); if (!__pyx_builtin_NotImplementedError) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 64; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__pyx_builtin_range = __Pyx_GetName(__pyx_b, __pyx_n_s__range); if (!__pyx_builtin_range) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 438; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__pyx_builtin_ValueError = __Pyx_GetName(__pyx_b, __pyx_n_s__ValueError); if (!__pyx_builtin_ValueError) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 508; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__pyx_builtin_RuntimeError = __Pyx_GetName(__pyx_b, __pyx_n_s__RuntimeError); if (!__pyx_builtin_RuntimeError) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 799; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
return 0;
__pyx_L1_error:;
return -1;
}
static int __Pyx_InitCachedConstants(void) {
__Pyx_RefNannyDeclarations
__Pyx_RefNannySetupContext("__Pyx_InitCachedConstants", 0);
/* "sklearn/linear_model/sgd_fast.pyx":508
* if np.any(np.isinf(weights)) or np.any(np.isnan(weights)) \
* or np.isnan(intercept) or np.isinf(intercept):
* raise ValueError("floating-point under-/overflow occured.") # <<<<<<<<<<<<<<
*
* w.reset_wscale()
*/
__pyx_k_tuple_5 = PyTuple_New(1); if (unlikely(!__pyx_k_tuple_5)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 508; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_k_tuple_5);
__Pyx_INCREF(((PyObject *)__pyx_kp_s_4));
PyTuple_SET_ITEM(__pyx_k_tuple_5, 0, ((PyObject *)__pyx_kp_s_4));
__Pyx_GIVEREF(((PyObject *)__pyx_kp_s_4));
__Pyx_GIVEREF(((PyObject *)__pyx_k_tuple_5));
/* "numpy.pxd":215
* if ((flags & pybuf.PyBUF_C_CONTIGUOUS == pybuf.PyBUF_C_CONTIGUOUS)
* and not PyArray_CHKFLAGS(self, NPY_C_CONTIGUOUS)):
* raise ValueError(u"ndarray is not C contiguous") # <<<<<<<<<<<<<<
*
* if ((flags & pybuf.PyBUF_F_CONTIGUOUS == pybuf.PyBUF_F_CONTIGUOUS)
*/
__pyx_k_tuple_7 = PyTuple_New(1); if (unlikely(!__pyx_k_tuple_7)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 215; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_k_tuple_7);
__Pyx_INCREF(((PyObject *)__pyx_kp_u_6));
PyTuple_SET_ITEM(__pyx_k_tuple_7, 0, ((PyObject *)__pyx_kp_u_6));
__Pyx_GIVEREF(((PyObject *)__pyx_kp_u_6));
__Pyx_GIVEREF(((PyObject *)__pyx_k_tuple_7));
/* "numpy.pxd":219
* if ((flags & pybuf.PyBUF_F_CONTIGUOUS == pybuf.PyBUF_F_CONTIGUOUS)
* and not PyArray_CHKFLAGS(self, NPY_F_CONTIGUOUS)):
* raise ValueError(u"ndarray is not Fortran contiguous") # <<<<<<<<<<<<<<
*
* info.buf = PyArray_DATA(self)
*/
__pyx_k_tuple_9 = PyTuple_New(1); if (unlikely(!__pyx_k_tuple_9)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 219; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_k_tuple_9);
__Pyx_INCREF(((PyObject *)__pyx_kp_u_8));
PyTuple_SET_ITEM(__pyx_k_tuple_9, 0, ((PyObject *)__pyx_kp_u_8));
__Pyx_GIVEREF(((PyObject *)__pyx_kp_u_8));
__Pyx_GIVEREF(((PyObject *)__pyx_k_tuple_9));
/* "numpy.pxd":257
* if ((descr.byteorder == c'>' and little_endian) or
* (descr.byteorder == c'<' and not little_endian)):
* raise ValueError(u"Non-native byte order not supported") # <<<<<<<<<<<<<<
* if t == NPY_BYTE: f = "b"
* elif t == NPY_UBYTE: f = "B"
*/
__pyx_k_tuple_11 = PyTuple_New(1); if (unlikely(!__pyx_k_tuple_11)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 257; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_k_tuple_11);
__Pyx_INCREF(((PyObject *)__pyx_kp_u_10));
PyTuple_SET_ITEM(__pyx_k_tuple_11, 0, ((PyObject *)__pyx_kp_u_10));
__Pyx_GIVEREF(((PyObject *)__pyx_kp_u_10));
__Pyx_GIVEREF(((PyObject *)__pyx_k_tuple_11));
/* "numpy.pxd":799
*
* if (end - f) - (new_offset - offset[0]) < 15:
* raise RuntimeError(u"Format string allocated too short, see comment in numpy.pxd") # <<<<<<<<<<<<<<
*
* if ((child.byteorder == c'>' and little_endian) or
*/
__pyx_k_tuple_14 = PyTuple_New(1); if (unlikely(!__pyx_k_tuple_14)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 799; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_k_tuple_14);
__Pyx_INCREF(((PyObject *)__pyx_kp_u_13));
PyTuple_SET_ITEM(__pyx_k_tuple_14, 0, ((PyObject *)__pyx_kp_u_13));
__Pyx_GIVEREF(((PyObject *)__pyx_kp_u_13));
__Pyx_GIVEREF(((PyObject *)__pyx_k_tuple_14));
/* "numpy.pxd":803
* if ((child.byteorder == c'>' and little_endian) or
* (child.byteorder == c'<' and not little_endian)):
* raise ValueError(u"Non-native byte order not supported") # <<<<<<<<<<<<<<
* # One could encode it in the format string and have Cython
* # complain instead, BUT: < and > in format strings also imply
*/
__pyx_k_tuple_15 = PyTuple_New(1); if (unlikely(!__pyx_k_tuple_15)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 803; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_k_tuple_15);
__Pyx_INCREF(((PyObject *)__pyx_kp_u_10));
PyTuple_SET_ITEM(__pyx_k_tuple_15, 0, ((PyObject *)__pyx_kp_u_10));
__Pyx_GIVEREF(((PyObject *)__pyx_kp_u_10));
__Pyx_GIVEREF(((PyObject *)__pyx_k_tuple_15));
/* "numpy.pxd":823
* t = child.type_num
* if end - f < 5:
* raise RuntimeError(u"Format string allocated too short.") # <<<<<<<<<<<<<<
*
* # Until ticket #99 is fixed, use integers to avoid warnings
*/
__pyx_k_tuple_17 = PyTuple_New(1); if (unlikely(!__pyx_k_tuple_17)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 823; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_k_tuple_17);
__Pyx_INCREF(((PyObject *)__pyx_kp_u_16));
PyTuple_SET_ITEM(__pyx_k_tuple_17, 0, ((PyObject *)__pyx_kp_u_16));
__Pyx_GIVEREF(((PyObject *)__pyx_kp_u_16));
__Pyx_GIVEREF(((PyObject *)__pyx_k_tuple_17));
/* "sklearn/linear_model/sgd_fast.pyx":327
*
*
* def plain_sgd(np.ndarray[DOUBLE, ndim=1, mode='c'] weights, # <<<<<<<<<<<<<<
* double intercept,
* LossFunction loss,
*/
__pyx_k_tuple_18 = PyTuple_New(41); if (unlikely(!__pyx_k_tuple_18)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 327; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_k_tuple_18);
__Pyx_INCREF(((PyObject *)__pyx_n_s__weights));
PyTuple_SET_ITEM(__pyx_k_tuple_18, 0, ((PyObject *)__pyx_n_s__weights));
__Pyx_GIVEREF(((PyObject *)__pyx_n_s__weights));
__Pyx_INCREF(((PyObject *)__pyx_n_s__intercept));
PyTuple_SET_ITEM(__pyx_k_tuple_18, 1, ((PyObject *)__pyx_n_s__intercept));
__Pyx_GIVEREF(((PyObject *)__pyx_n_s__intercept));
__Pyx_INCREF(((PyObject *)__pyx_n_s__loss));
PyTuple_SET_ITEM(__pyx_k_tuple_18, 2, ((PyObject *)__pyx_n_s__loss));
__Pyx_GIVEREF(((PyObject *)__pyx_n_s__loss));
__Pyx_INCREF(((PyObject *)__pyx_n_s__penalty_type));
PyTuple_SET_ITEM(__pyx_k_tuple_18, 3, ((PyObject *)__pyx_n_s__penalty_type));
__Pyx_GIVEREF(((PyObject *)__pyx_n_s__penalty_type));
__Pyx_INCREF(((PyObject *)__pyx_n_s__alpha));
PyTuple_SET_ITEM(__pyx_k_tuple_18, 4, ((PyObject *)__pyx_n_s__alpha));
__Pyx_GIVEREF(((PyObject *)__pyx_n_s__alpha));
__Pyx_INCREF(((PyObject *)__pyx_n_s__C));
PyTuple_SET_ITEM(__pyx_k_tuple_18, 5, ((PyObject *)__pyx_n_s__C));
__Pyx_GIVEREF(((PyObject *)__pyx_n_s__C));
__Pyx_INCREF(((PyObject *)__pyx_n_s__rho));
PyTuple_SET_ITEM(__pyx_k_tuple_18, 6, ((PyObject *)__pyx_n_s__rho));
__Pyx_GIVEREF(((PyObject *)__pyx_n_s__rho));
__Pyx_INCREF(((PyObject *)__pyx_n_s__dataset));
PyTuple_SET_ITEM(__pyx_k_tuple_18, 7, ((PyObject *)__pyx_n_s__dataset));
__Pyx_GIVEREF(((PyObject *)__pyx_n_s__dataset));
__Pyx_INCREF(((PyObject *)__pyx_n_s__n_iter));
PyTuple_SET_ITEM(__pyx_k_tuple_18, 8, ((PyObject *)__pyx_n_s__n_iter));
__Pyx_GIVEREF(((PyObject *)__pyx_n_s__n_iter));
__Pyx_INCREF(((PyObject *)__pyx_n_s__fit_intercept));
PyTuple_SET_ITEM(__pyx_k_tuple_18, 9, ((PyObject *)__pyx_n_s__fit_intercept));
__Pyx_GIVEREF(((PyObject *)__pyx_n_s__fit_intercept));
__Pyx_INCREF(((PyObject *)__pyx_n_s__verbose));
PyTuple_SET_ITEM(__pyx_k_tuple_18, 10, ((PyObject *)__pyx_n_s__verbose));
__Pyx_GIVEREF(((PyObject *)__pyx_n_s__verbose));
__Pyx_INCREF(((PyObject *)__pyx_n_s__shuffle));
PyTuple_SET_ITEM(__pyx_k_tuple_18, 11, ((PyObject *)__pyx_n_s__shuffle));
__Pyx_GIVEREF(((PyObject *)__pyx_n_s__shuffle));
__Pyx_INCREF(((PyObject *)__pyx_n_s__seed));
PyTuple_SET_ITEM(__pyx_k_tuple_18, 12, ((PyObject *)__pyx_n_s__seed));
__Pyx_GIVEREF(((PyObject *)__pyx_n_s__seed));
__Pyx_INCREF(((PyObject *)__pyx_n_s__weight_pos));
PyTuple_SET_ITEM(__pyx_k_tuple_18, 13, ((PyObject *)__pyx_n_s__weight_pos));
__Pyx_GIVEREF(((PyObject *)__pyx_n_s__weight_pos));
__Pyx_INCREF(((PyObject *)__pyx_n_s__weight_neg));
PyTuple_SET_ITEM(__pyx_k_tuple_18, 14, ((PyObject *)__pyx_n_s__weight_neg));
__Pyx_GIVEREF(((PyObject *)__pyx_n_s__weight_neg));
__Pyx_INCREF(((PyObject *)__pyx_n_s__learning_rate));
PyTuple_SET_ITEM(__pyx_k_tuple_18, 15, ((PyObject *)__pyx_n_s__learning_rate));
__Pyx_GIVEREF(((PyObject *)__pyx_n_s__learning_rate));
__Pyx_INCREF(((PyObject *)__pyx_n_s__eta0));
PyTuple_SET_ITEM(__pyx_k_tuple_18, 16, ((PyObject *)__pyx_n_s__eta0));
__Pyx_GIVEREF(((PyObject *)__pyx_n_s__eta0));
__Pyx_INCREF(((PyObject *)__pyx_n_s__power_t));
PyTuple_SET_ITEM(__pyx_k_tuple_18, 17, ((PyObject *)__pyx_n_s__power_t));
__Pyx_GIVEREF(((PyObject *)__pyx_n_s__power_t));
__Pyx_INCREF(((PyObject *)__pyx_n_s__t));
PyTuple_SET_ITEM(__pyx_k_tuple_18, 18, ((PyObject *)__pyx_n_s__t));
__Pyx_GIVEREF(((PyObject *)__pyx_n_s__t));
__Pyx_INCREF(((PyObject *)__pyx_n_s__intercept_decay));
PyTuple_SET_ITEM(__pyx_k_tuple_18, 19, ((PyObject *)__pyx_n_s__intercept_decay));
__Pyx_GIVEREF(((PyObject *)__pyx_n_s__intercept_decay));
__Pyx_INCREF(((PyObject *)__pyx_n_s__n_samples));
PyTuple_SET_ITEM(__pyx_k_tuple_18, 20, ((PyObject *)__pyx_n_s__n_samples));
__Pyx_GIVEREF(((PyObject *)__pyx_n_s__n_samples));
__Pyx_INCREF(((PyObject *)__pyx_n_s__n_features));
PyTuple_SET_ITEM(__pyx_k_tuple_18, 21, ((PyObject *)__pyx_n_s__n_features));
__Pyx_GIVEREF(((PyObject *)__pyx_n_s__n_features));
__Pyx_INCREF(((PyObject *)__pyx_n_s__w));
PyTuple_SET_ITEM(__pyx_k_tuple_18, 22, ((PyObject *)__pyx_n_s__w));
__Pyx_GIVEREF(((PyObject *)__pyx_n_s__w));
__Pyx_INCREF(((PyObject *)__pyx_n_s__x_data_ptr));
PyTuple_SET_ITEM(__pyx_k_tuple_18, 23, ((PyObject *)__pyx_n_s__x_data_ptr));
__Pyx_GIVEREF(((PyObject *)__pyx_n_s__x_data_ptr));
__Pyx_INCREF(((PyObject *)__pyx_n_s__x_ind_ptr));
PyTuple_SET_ITEM(__pyx_k_tuple_18, 24, ((PyObject *)__pyx_n_s__x_ind_ptr));
__Pyx_GIVEREF(((PyObject *)__pyx_n_s__x_ind_ptr));
__Pyx_INCREF(((PyObject *)__pyx_n_s__xnnz));
PyTuple_SET_ITEM(__pyx_k_tuple_18, 25, ((PyObject *)__pyx_n_s__xnnz));
__Pyx_GIVEREF(((PyObject *)__pyx_n_s__xnnz));
__Pyx_INCREF(((PyObject *)__pyx_n_s__eta));
PyTuple_SET_ITEM(__pyx_k_tuple_18, 26, ((PyObject *)__pyx_n_s__eta));
__Pyx_GIVEREF(((PyObject *)__pyx_n_s__eta));
__Pyx_INCREF(((PyObject *)__pyx_n_s__p));
PyTuple_SET_ITEM(__pyx_k_tuple_18, 27, ((PyObject *)__pyx_n_s__p));
__Pyx_GIVEREF(((PyObject *)__pyx_n_s__p));
__Pyx_INCREF(((PyObject *)__pyx_n_s__update));
PyTuple_SET_ITEM(__pyx_k_tuple_18, 28, ((PyObject *)__pyx_n_s__update));
__Pyx_GIVEREF(((PyObject *)__pyx_n_s__update));
__Pyx_INCREF(((PyObject *)__pyx_n_s__sumloss));
PyTuple_SET_ITEM(__pyx_k_tuple_18, 29, ((PyObject *)__pyx_n_s__sumloss));
__Pyx_GIVEREF(((PyObject *)__pyx_n_s__sumloss));
__Pyx_INCREF(((PyObject *)__pyx_n_s__y));
PyTuple_SET_ITEM(__pyx_k_tuple_18, 30, ((PyObject *)__pyx_n_s__y));
__Pyx_GIVEREF(((PyObject *)__pyx_n_s__y));
__Pyx_INCREF(((PyObject *)__pyx_n_s__sample_weight));
PyTuple_SET_ITEM(__pyx_k_tuple_18, 31, ((PyObject *)__pyx_n_s__sample_weight));
__Pyx_GIVEREF(((PyObject *)__pyx_n_s__sample_weight));
__Pyx_INCREF(((PyObject *)__pyx_n_s__class_weight));
PyTuple_SET_ITEM(__pyx_k_tuple_18, 32, ((PyObject *)__pyx_n_s__class_weight));
__Pyx_GIVEREF(((PyObject *)__pyx_n_s__class_weight));
__Pyx_INCREF(((PyObject *)__pyx_n_s__count));
PyTuple_SET_ITEM(__pyx_k_tuple_18, 33, ((PyObject *)__pyx_n_s__count));
__Pyx_GIVEREF(((PyObject *)__pyx_n_s__count));
__Pyx_INCREF(((PyObject *)__pyx_n_s__epoch));
PyTuple_SET_ITEM(__pyx_k_tuple_18, 34, ((PyObject *)__pyx_n_s__epoch));
__Pyx_GIVEREF(((PyObject *)__pyx_n_s__epoch));
__Pyx_INCREF(((PyObject *)__pyx_n_s__i));
PyTuple_SET_ITEM(__pyx_k_tuple_18, 35, ((PyObject *)__pyx_n_s__i));
__Pyx_GIVEREF(((PyObject *)__pyx_n_s__i));
__Pyx_INCREF(((PyObject *)__pyx_n_s__is_hinge));
PyTuple_SET_ITEM(__pyx_k_tuple_18, 36, ((PyObject *)__pyx_n_s__is_hinge));
__Pyx_GIVEREF(((PyObject *)__pyx_n_s__is_hinge));
__Pyx_INCREF(((PyObject *)__pyx_n_s__q));
PyTuple_SET_ITEM(__pyx_k_tuple_18, 37, ((PyObject *)__pyx_n_s__q));
__Pyx_GIVEREF(((PyObject *)__pyx_n_s__q));
__Pyx_INCREF(((PyObject *)__pyx_n_s__q_data_ptr));
PyTuple_SET_ITEM(__pyx_k_tuple_18, 38, ((PyObject *)__pyx_n_s__q_data_ptr));
__Pyx_GIVEREF(((PyObject *)__pyx_n_s__q_data_ptr));
__Pyx_INCREF(((PyObject *)__pyx_n_s__u));
PyTuple_SET_ITEM(__pyx_k_tuple_18, 39, ((PyObject *)__pyx_n_s__u));
__Pyx_GIVEREF(((PyObject *)__pyx_n_s__u));
__Pyx_INCREF(((PyObject *)__pyx_n_s__t_start));
PyTuple_SET_ITEM(__pyx_k_tuple_18, 40, ((PyObject *)__pyx_n_s__t_start));
__Pyx_GIVEREF(((PyObject *)__pyx_n_s__t_start));
__Pyx_GIVEREF(((PyObject *)__pyx_k_tuple_18));
__pyx_k_codeobj_19 = (PyObject*)__Pyx_PyCode_New(20, 0, 41, 0, 0, __pyx_empty_bytes, __pyx_empty_tuple, __pyx_empty_tuple, __pyx_k_tuple_18, __pyx_empty_tuple, __pyx_empty_tuple, __pyx_kp_s_20, __pyx_n_s__plain_sgd, 327, __pyx_empty_bytes); if (unlikely(!__pyx_k_codeobj_19)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 327; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_RefNannyFinishContext();
return 0;
__pyx_L1_error:;
__Pyx_RefNannyFinishContext();
return -1;
}
static int __Pyx_InitGlobals(void) {
if (__Pyx_InitStrings(__pyx_string_tab) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;};
__pyx_int_15 = PyInt_FromLong(15); if (unlikely(!__pyx_int_15)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;};
return 0;
__pyx_L1_error:;
return -1;
}
#if PY_MAJOR_VERSION < 3
PyMODINIT_FUNC initsgd_fast(void); /*proto*/
PyMODINIT_FUNC initsgd_fast(void)
#else
PyMODINIT_FUNC PyInit_sgd_fast(void); /*proto*/
PyMODINIT_FUNC PyInit_sgd_fast(void)
#endif
{
PyObject *__pyx_t_1 = NULL;
PyObject *__pyx_t_2 = NULL;
__Pyx_RefNannyDeclarations
#if CYTHON_REFNANNY
__Pyx_RefNanny = __Pyx_RefNannyImportAPI("refnanny");
if (!__Pyx_RefNanny) {
PyErr_Clear();
__Pyx_RefNanny = __Pyx_RefNannyImportAPI("Cython.Runtime.refnanny");
if (!__Pyx_RefNanny)
Py_FatalError("failed to import 'refnanny' module");
}
#endif
__Pyx_RefNannySetupContext("PyMODINIT_FUNC PyInit_sgd_fast(void)", 0);
if ( __Pyx_check_binary_version() < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__pyx_empty_tuple = PyTuple_New(0); if (unlikely(!__pyx_empty_tuple)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__pyx_empty_bytes = PyBytes_FromStringAndSize("", 0); if (unlikely(!__pyx_empty_bytes)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
#ifdef __Pyx_CyFunction_USED
if (__Pyx_CyFunction_init() < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
#endif
#ifdef __Pyx_FusedFunction_USED
if (__pyx_FusedFunction_init() < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
#endif
#ifdef __Pyx_Generator_USED
if (__pyx_Generator_init() < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
#endif
/*--- Library function declarations ---*/
/*--- Threads initialization code ---*/
#if defined(__PYX_FORCE_INIT_THREADS) && __PYX_FORCE_INIT_THREADS
#ifdef WITH_THREAD /* Python build with threading support? */
PyEval_InitThreads();
#endif
#endif
/*--- Module creation code ---*/
#if PY_MAJOR_VERSION < 3
__pyx_m = Py_InitModule4(__Pyx_NAMESTR("sgd_fast"), __pyx_methods, 0, 0, PYTHON_API_VERSION); Py_XINCREF(__pyx_m);
#else
__pyx_m = PyModule_Create(&__pyx_moduledef);
#endif
if (unlikely(!__pyx_m)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
#if PY_MAJOR_VERSION >= 3
{
PyObject *modules = PyImport_GetModuleDict(); if (unlikely(!modules)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
if (!PyDict_GetItemString(modules, "sklearn.linear_model.sgd_fast")) {
if (unlikely(PyDict_SetItemString(modules, "sklearn.linear_model.sgd_fast", __pyx_m) < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
}
}
#endif
__pyx_b = PyImport_AddModule(__Pyx_NAMESTR(__Pyx_BUILTIN_MODULE_NAME)); if (unlikely(!__pyx_b)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
#if CYTHON_COMPILING_IN_PYPY
Py_INCREF(__pyx_b);
#endif
if (__Pyx_SetAttrString(__pyx_m, "__builtins__", __pyx_b) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;};
/*--- Initialize various global constants etc. ---*/
if (unlikely(__Pyx_InitGlobals() < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
if (__pyx_module_is_main_sklearn__linear_model__sgd_fast) {
if (__Pyx_SetAttrString(__pyx_m, "__name__", __pyx_n_s____main__) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;};
}
/*--- Builtin init code ---*/
if (unlikely(__Pyx_InitCachedBuiltins() < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
/*--- Constants init code ---*/
if (unlikely(__Pyx_InitCachedConstants() < 0)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
/*--- Global init code ---*/
/*--- Variable export code ---*/
/*--- Function export code ---*/
/*--- Type init code ---*/
__pyx_vtabptr_7sklearn_12linear_model_8sgd_fast_LossFunction = &__pyx_vtable_7sklearn_12linear_model_8sgd_fast_LossFunction;
__pyx_vtable_7sklearn_12linear_model_8sgd_fast_LossFunction.loss = (double (*)(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_LossFunction *, double, double, int __pyx_skip_dispatch))__pyx_f_7sklearn_12linear_model_8sgd_fast_12LossFunction_loss;
__pyx_vtable_7sklearn_12linear_model_8sgd_fast_LossFunction.dloss = (double (*)(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_LossFunction *, double, double, int __pyx_skip_dispatch))__pyx_f_7sklearn_12linear_model_8sgd_fast_12LossFunction_dloss;
if (PyType_Ready(&__pyx_type_7sklearn_12linear_model_8sgd_fast_LossFunction) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 46; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
if (__Pyx_SetVtable(__pyx_type_7sklearn_12linear_model_8sgd_fast_LossFunction.tp_dict, __pyx_vtabptr_7sklearn_12linear_model_8sgd_fast_LossFunction) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 46; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
if (__Pyx_SetAttrString(__pyx_m, "LossFunction", (PyObject *)&__pyx_type_7sklearn_12linear_model_8sgd_fast_LossFunction) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 46; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__pyx_ptype_7sklearn_12linear_model_8sgd_fast_LossFunction = &__pyx_type_7sklearn_12linear_model_8sgd_fast_LossFunction;
__pyx_vtabptr_7sklearn_12linear_model_8sgd_fast_Regression = &__pyx_vtable_7sklearn_12linear_model_8sgd_fast_Regression;
__pyx_vtable_7sklearn_12linear_model_8sgd_fast_Regression.__pyx_base = *__pyx_vtabptr_7sklearn_12linear_model_8sgd_fast_LossFunction;
__pyx_vtable_7sklearn_12linear_model_8sgd_fast_Regression.__pyx_base.loss = (double (*)(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_LossFunction *, double, double, int __pyx_skip_dispatch))__pyx_f_7sklearn_12linear_model_8sgd_fast_10Regression_loss;
__pyx_vtable_7sklearn_12linear_model_8sgd_fast_Regression.__pyx_base.dloss = (double (*)(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_LossFunction *, double, double, int __pyx_skip_dispatch))__pyx_f_7sklearn_12linear_model_8sgd_fast_10Regression_dloss;
__pyx_type_7sklearn_12linear_model_8sgd_fast_Regression.tp_base = __pyx_ptype_7sklearn_12linear_model_8sgd_fast_LossFunction;
if (PyType_Ready(&__pyx_type_7sklearn_12linear_model_8sgd_fast_Regression) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 84; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
if (__Pyx_SetVtable(__pyx_type_7sklearn_12linear_model_8sgd_fast_Regression.tp_dict, __pyx_vtabptr_7sklearn_12linear_model_8sgd_fast_Regression) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 84; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
if (__Pyx_SetAttrString(__pyx_m, "Regression", (PyObject *)&__pyx_type_7sklearn_12linear_model_8sgd_fast_Regression) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 84; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__pyx_ptype_7sklearn_12linear_model_8sgd_fast_Regression = &__pyx_type_7sklearn_12linear_model_8sgd_fast_Regression;
__pyx_vtabptr_7sklearn_12linear_model_8sgd_fast_Classification = &__pyx_vtable_7sklearn_12linear_model_8sgd_fast_Classification;
__pyx_vtable_7sklearn_12linear_model_8sgd_fast_Classification.__pyx_base = *__pyx_vtabptr_7sklearn_12linear_model_8sgd_fast_LossFunction;
__pyx_vtable_7sklearn_12linear_model_8sgd_fast_Classification.__pyx_base.loss = (double (*)(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_LossFunction *, double, double, int __pyx_skip_dispatch))__pyx_f_7sklearn_12linear_model_8sgd_fast_14Classification_loss;
__pyx_vtable_7sklearn_12linear_model_8sgd_fast_Classification.__pyx_base.dloss = (double (*)(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_LossFunction *, double, double, int __pyx_skip_dispatch))__pyx_f_7sklearn_12linear_model_8sgd_fast_14Classification_dloss;
__pyx_type_7sklearn_12linear_model_8sgd_fast_Classification.tp_base = __pyx_ptype_7sklearn_12linear_model_8sgd_fast_LossFunction;
if (PyType_Ready(&__pyx_type_7sklearn_12linear_model_8sgd_fast_Classification) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 94; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
if (__Pyx_SetVtable(__pyx_type_7sklearn_12linear_model_8sgd_fast_Classification.tp_dict, __pyx_vtabptr_7sklearn_12linear_model_8sgd_fast_Classification) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 94; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
if (__Pyx_SetAttrString(__pyx_m, "Classification", (PyObject *)&__pyx_type_7sklearn_12linear_model_8sgd_fast_Classification) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 94; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__pyx_ptype_7sklearn_12linear_model_8sgd_fast_Classification = &__pyx_type_7sklearn_12linear_model_8sgd_fast_Classification;
__pyx_vtabptr_7sklearn_12linear_model_8sgd_fast_ModifiedHuber = &__pyx_vtable_7sklearn_12linear_model_8sgd_fast_ModifiedHuber;
__pyx_vtable_7sklearn_12linear_model_8sgd_fast_ModifiedHuber.__pyx_base = *__pyx_vtabptr_7sklearn_12linear_model_8sgd_fast_Classification;
__pyx_vtable_7sklearn_12linear_model_8sgd_fast_ModifiedHuber.__pyx_base.__pyx_base.loss = (double (*)(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_LossFunction *, double, double, int __pyx_skip_dispatch))__pyx_f_7sklearn_12linear_model_8sgd_fast_13ModifiedHuber_loss;
__pyx_vtable_7sklearn_12linear_model_8sgd_fast_ModifiedHuber.__pyx_base.__pyx_base.dloss = (double (*)(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_LossFunction *, double, double, int __pyx_skip_dispatch))__pyx_f_7sklearn_12linear_model_8sgd_fast_13ModifiedHuber_dloss;
__pyx_type_7sklearn_12linear_model_8sgd_fast_ModifiedHuber.tp_base = __pyx_ptype_7sklearn_12linear_model_8sgd_fast_Classification;
if (PyType_Ready(&__pyx_type_7sklearn_12linear_model_8sgd_fast_ModifiedHuber) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 104; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
if (__Pyx_SetVtable(__pyx_type_7sklearn_12linear_model_8sgd_fast_ModifiedHuber.tp_dict, __pyx_vtabptr_7sklearn_12linear_model_8sgd_fast_ModifiedHuber) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 104; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
if (__Pyx_SetAttrString(__pyx_m, "ModifiedHuber", (PyObject *)&__pyx_type_7sklearn_12linear_model_8sgd_fast_ModifiedHuber) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 104; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__pyx_ptype_7sklearn_12linear_model_8sgd_fast_ModifiedHuber = &__pyx_type_7sklearn_12linear_model_8sgd_fast_ModifiedHuber;
__pyx_vtabptr_7sklearn_12linear_model_8sgd_fast_Hinge = &__pyx_vtable_7sklearn_12linear_model_8sgd_fast_Hinge;
__pyx_vtable_7sklearn_12linear_model_8sgd_fast_Hinge.__pyx_base = *__pyx_vtabptr_7sklearn_12linear_model_8sgd_fast_Classification;
__pyx_vtable_7sklearn_12linear_model_8sgd_fast_Hinge.__pyx_base.__pyx_base.loss = (double (*)(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_LossFunction *, double, double, int __pyx_skip_dispatch))__pyx_f_7sklearn_12linear_model_8sgd_fast_5Hinge_loss;
__pyx_vtable_7sklearn_12linear_model_8sgd_fast_Hinge.__pyx_base.__pyx_base.dloss = (double (*)(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_LossFunction *, double, double, int __pyx_skip_dispatch))__pyx_f_7sklearn_12linear_model_8sgd_fast_5Hinge_dloss;
__pyx_type_7sklearn_12linear_model_8sgd_fast_Hinge.tp_base = __pyx_ptype_7sklearn_12linear_model_8sgd_fast_Classification;
if (PyType_Ready(&__pyx_type_7sklearn_12linear_model_8sgd_fast_Hinge) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 134; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
if (__Pyx_SetVtable(__pyx_type_7sklearn_12linear_model_8sgd_fast_Hinge.tp_dict, __pyx_vtabptr_7sklearn_12linear_model_8sgd_fast_Hinge) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 134; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
if (__Pyx_SetAttrString(__pyx_m, "Hinge", (PyObject *)&__pyx_type_7sklearn_12linear_model_8sgd_fast_Hinge) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 134; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__pyx_ptype_7sklearn_12linear_model_8sgd_fast_Hinge = &__pyx_type_7sklearn_12linear_model_8sgd_fast_Hinge;
__pyx_vtabptr_7sklearn_12linear_model_8sgd_fast_SquaredHinge = &__pyx_vtable_7sklearn_12linear_model_8sgd_fast_SquaredHinge;
__pyx_vtable_7sklearn_12linear_model_8sgd_fast_SquaredHinge.__pyx_base = *__pyx_vtabptr_7sklearn_12linear_model_8sgd_fast_LossFunction;
__pyx_vtable_7sklearn_12linear_model_8sgd_fast_SquaredHinge.__pyx_base.loss = (double (*)(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_LossFunction *, double, double, int __pyx_skip_dispatch))__pyx_f_7sklearn_12linear_model_8sgd_fast_12SquaredHinge_loss;
__pyx_vtable_7sklearn_12linear_model_8sgd_fast_SquaredHinge.__pyx_base.dloss = (double (*)(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_LossFunction *, double, double, int __pyx_skip_dispatch))__pyx_f_7sklearn_12linear_model_8sgd_fast_12SquaredHinge_dloss;
__pyx_type_7sklearn_12linear_model_8sgd_fast_SquaredHinge.tp_base = __pyx_ptype_7sklearn_12linear_model_8sgd_fast_LossFunction;
if (PyType_Ready(&__pyx_type_7sklearn_12linear_model_8sgd_fast_SquaredHinge) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 166; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
if (__Pyx_SetVtable(__pyx_type_7sklearn_12linear_model_8sgd_fast_SquaredHinge.tp_dict, __pyx_vtabptr_7sklearn_12linear_model_8sgd_fast_SquaredHinge) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 166; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
if (__Pyx_SetAttrString(__pyx_m, "SquaredHinge", (PyObject *)&__pyx_type_7sklearn_12linear_model_8sgd_fast_SquaredHinge) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 166; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__pyx_ptype_7sklearn_12linear_model_8sgd_fast_SquaredHinge = &__pyx_type_7sklearn_12linear_model_8sgd_fast_SquaredHinge;
__pyx_vtabptr_7sklearn_12linear_model_8sgd_fast_Log = &__pyx_vtable_7sklearn_12linear_model_8sgd_fast_Log;
__pyx_vtable_7sklearn_12linear_model_8sgd_fast_Log.__pyx_base = *__pyx_vtabptr_7sklearn_12linear_model_8sgd_fast_Classification;
__pyx_vtable_7sklearn_12linear_model_8sgd_fast_Log.__pyx_base.__pyx_base.loss = (double (*)(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_LossFunction *, double, double, int __pyx_skip_dispatch))__pyx_f_7sklearn_12linear_model_8sgd_fast_3Log_loss;
__pyx_vtable_7sklearn_12linear_model_8sgd_fast_Log.__pyx_base.__pyx_base.dloss = (double (*)(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_LossFunction *, double, double, int __pyx_skip_dispatch))__pyx_f_7sklearn_12linear_model_8sgd_fast_3Log_dloss;
__pyx_type_7sklearn_12linear_model_8sgd_fast_Log.tp_base = __pyx_ptype_7sklearn_12linear_model_8sgd_fast_Classification;
if (PyType_Ready(&__pyx_type_7sklearn_12linear_model_8sgd_fast_Log) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 198; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
if (__Pyx_SetVtable(__pyx_type_7sklearn_12linear_model_8sgd_fast_Log.tp_dict, __pyx_vtabptr_7sklearn_12linear_model_8sgd_fast_Log) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 198; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
if (__Pyx_SetAttrString(__pyx_m, "Log", (PyObject *)&__pyx_type_7sklearn_12linear_model_8sgd_fast_Log) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 198; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__pyx_ptype_7sklearn_12linear_model_8sgd_fast_Log = &__pyx_type_7sklearn_12linear_model_8sgd_fast_Log;
__pyx_vtabptr_7sklearn_12linear_model_8sgd_fast_SquaredLoss = &__pyx_vtable_7sklearn_12linear_model_8sgd_fast_SquaredLoss;
__pyx_vtable_7sklearn_12linear_model_8sgd_fast_SquaredLoss.__pyx_base = *__pyx_vtabptr_7sklearn_12linear_model_8sgd_fast_Regression;
__pyx_vtable_7sklearn_12linear_model_8sgd_fast_SquaredLoss.__pyx_base.__pyx_base.loss = (double (*)(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_LossFunction *, double, double, int __pyx_skip_dispatch))__pyx_f_7sklearn_12linear_model_8sgd_fast_11SquaredLoss_loss;
__pyx_vtable_7sklearn_12linear_model_8sgd_fast_SquaredLoss.__pyx_base.__pyx_base.dloss = (double (*)(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_LossFunction *, double, double, int __pyx_skip_dispatch))__pyx_f_7sklearn_12linear_model_8sgd_fast_11SquaredLoss_dloss;
__pyx_type_7sklearn_12linear_model_8sgd_fast_SquaredLoss.tp_base = __pyx_ptype_7sklearn_12linear_model_8sgd_fast_Regression;
if (PyType_Ready(&__pyx_type_7sklearn_12linear_model_8sgd_fast_SquaredLoss) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 223; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
if (__Pyx_SetVtable(__pyx_type_7sklearn_12linear_model_8sgd_fast_SquaredLoss.tp_dict, __pyx_vtabptr_7sklearn_12linear_model_8sgd_fast_SquaredLoss) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 223; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
if (__Pyx_SetAttrString(__pyx_m, "SquaredLoss", (PyObject *)&__pyx_type_7sklearn_12linear_model_8sgd_fast_SquaredLoss) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 223; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__pyx_ptype_7sklearn_12linear_model_8sgd_fast_SquaredLoss = &__pyx_type_7sklearn_12linear_model_8sgd_fast_SquaredLoss;
__pyx_vtabptr_7sklearn_12linear_model_8sgd_fast_Huber = &__pyx_vtable_7sklearn_12linear_model_8sgd_fast_Huber;
__pyx_vtable_7sklearn_12linear_model_8sgd_fast_Huber.__pyx_base = *__pyx_vtabptr_7sklearn_12linear_model_8sgd_fast_Regression;
__pyx_vtable_7sklearn_12linear_model_8sgd_fast_Huber.__pyx_base.__pyx_base.loss = (double (*)(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_LossFunction *, double, double, int __pyx_skip_dispatch))__pyx_f_7sklearn_12linear_model_8sgd_fast_5Huber_loss;
__pyx_vtable_7sklearn_12linear_model_8sgd_fast_Huber.__pyx_base.__pyx_base.dloss = (double (*)(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_LossFunction *, double, double, int __pyx_skip_dispatch))__pyx_f_7sklearn_12linear_model_8sgd_fast_5Huber_dloss;
__pyx_type_7sklearn_12linear_model_8sgd_fast_Huber.tp_base = __pyx_ptype_7sklearn_12linear_model_8sgd_fast_Regression;
if (PyType_Ready(&__pyx_type_7sklearn_12linear_model_8sgd_fast_Huber) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 235; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
if (__Pyx_SetVtable(__pyx_type_7sklearn_12linear_model_8sgd_fast_Huber.tp_dict, __pyx_vtabptr_7sklearn_12linear_model_8sgd_fast_Huber) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 235; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
if (__Pyx_SetAttrString(__pyx_m, "Huber", (PyObject *)&__pyx_type_7sklearn_12linear_model_8sgd_fast_Huber) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 235; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__pyx_ptype_7sklearn_12linear_model_8sgd_fast_Huber = &__pyx_type_7sklearn_12linear_model_8sgd_fast_Huber;
__pyx_vtabptr_7sklearn_12linear_model_8sgd_fast_EpsilonInsensitive = &__pyx_vtable_7sklearn_12linear_model_8sgd_fast_EpsilonInsensitive;
__pyx_vtable_7sklearn_12linear_model_8sgd_fast_EpsilonInsensitive.__pyx_base = *__pyx_vtabptr_7sklearn_12linear_model_8sgd_fast_Regression;
__pyx_vtable_7sklearn_12linear_model_8sgd_fast_EpsilonInsensitive.__pyx_base.__pyx_base.loss = (double (*)(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_LossFunction *, double, double, int __pyx_skip_dispatch))__pyx_f_7sklearn_12linear_model_8sgd_fast_18EpsilonInsensitive_loss;
__pyx_vtable_7sklearn_12linear_model_8sgd_fast_EpsilonInsensitive.__pyx_base.__pyx_base.dloss = (double (*)(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_LossFunction *, double, double, int __pyx_skip_dispatch))__pyx_f_7sklearn_12linear_model_8sgd_fast_18EpsilonInsensitive_dloss;
__pyx_type_7sklearn_12linear_model_8sgd_fast_EpsilonInsensitive.tp_base = __pyx_ptype_7sklearn_12linear_model_8sgd_fast_Regression;
if (PyType_Ready(&__pyx_type_7sklearn_12linear_model_8sgd_fast_EpsilonInsensitive) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 271; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
if (__Pyx_SetVtable(__pyx_type_7sklearn_12linear_model_8sgd_fast_EpsilonInsensitive.tp_dict, __pyx_vtabptr_7sklearn_12linear_model_8sgd_fast_EpsilonInsensitive) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 271; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
if (__Pyx_SetAttrString(__pyx_m, "EpsilonInsensitive", (PyObject *)&__pyx_type_7sklearn_12linear_model_8sgd_fast_EpsilonInsensitive) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 271; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__pyx_ptype_7sklearn_12linear_model_8sgd_fast_EpsilonInsensitive = &__pyx_type_7sklearn_12linear_model_8sgd_fast_EpsilonInsensitive;
__pyx_vtabptr_7sklearn_12linear_model_8sgd_fast_SquaredEpsilonInsensitive = &__pyx_vtable_7sklearn_12linear_model_8sgd_fast_SquaredEpsilonInsensitive;
__pyx_vtable_7sklearn_12linear_model_8sgd_fast_SquaredEpsilonInsensitive.__pyx_base = *__pyx_vtabptr_7sklearn_12linear_model_8sgd_fast_Regression;
__pyx_vtable_7sklearn_12linear_model_8sgd_fast_SquaredEpsilonInsensitive.__pyx_base.__pyx_base.loss = (double (*)(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_LossFunction *, double, double, int __pyx_skip_dispatch))__pyx_f_7sklearn_12linear_model_8sgd_fast_25SquaredEpsilonInsensitive_loss;
__pyx_vtable_7sklearn_12linear_model_8sgd_fast_SquaredEpsilonInsensitive.__pyx_base.__pyx_base.dloss = (double (*)(struct __pyx_obj_7sklearn_12linear_model_8sgd_fast_LossFunction *, double, double, int __pyx_skip_dispatch))__pyx_f_7sklearn_12linear_model_8sgd_fast_25SquaredEpsilonInsensitive_dloss;
__pyx_type_7sklearn_12linear_model_8sgd_fast_SquaredEpsilonInsensitive.tp_base = __pyx_ptype_7sklearn_12linear_model_8sgd_fast_Regression;
if (PyType_Ready(&__pyx_type_7sklearn_12linear_model_8sgd_fast_SquaredEpsilonInsensitive) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 298; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
if (__Pyx_SetVtable(__pyx_type_7sklearn_12linear_model_8sgd_fast_SquaredEpsilonInsensitive.tp_dict, __pyx_vtabptr_7sklearn_12linear_model_8sgd_fast_SquaredEpsilonInsensitive) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 298; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
if (__Pyx_SetAttrString(__pyx_m, "SquaredEpsilonInsensitive", (PyObject *)&__pyx_type_7sklearn_12linear_model_8sgd_fast_SquaredEpsilonInsensitive) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 298; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__pyx_ptype_7sklearn_12linear_model_8sgd_fast_SquaredEpsilonInsensitive = &__pyx_type_7sklearn_12linear_model_8sgd_fast_SquaredEpsilonInsensitive;
/*--- Type import code ---*/
__pyx_ptype_7cpython_4type_type = __Pyx_ImportType(__Pyx_BUILTIN_MODULE_NAME, "type",
#if CYTHON_COMPILING_IN_PYPY
sizeof(PyTypeObject),
#else
sizeof(PyHeapTypeObject),
#endif
0); if (unlikely(!__pyx_ptype_7cpython_4type_type)) {__pyx_filename = __pyx_f[2]; __pyx_lineno = 9; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__pyx_ptype_5numpy_dtype = __Pyx_ImportType("numpy", "dtype", sizeof(PyArray_Descr), 0); if (unlikely(!__pyx_ptype_5numpy_dtype)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 155; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__pyx_ptype_5numpy_flatiter = __Pyx_ImportType("numpy", "flatiter", sizeof(PyArrayIterObject), 0); if (unlikely(!__pyx_ptype_5numpy_flatiter)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 165; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__pyx_ptype_5numpy_broadcast = __Pyx_ImportType("numpy", "broadcast", sizeof(PyArrayMultiIterObject), 0); if (unlikely(!__pyx_ptype_5numpy_broadcast)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 169; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__pyx_ptype_5numpy_ndarray = __Pyx_ImportType("numpy", "ndarray", sizeof(PyArrayObject), 0); if (unlikely(!__pyx_ptype_5numpy_ndarray)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 178; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__pyx_ptype_5numpy_ufunc = __Pyx_ImportType("numpy", "ufunc", sizeof(PyUFuncObject), 0); if (unlikely(!__pyx_ptype_5numpy_ufunc)) {__pyx_filename = __pyx_f[1]; __pyx_lineno = 861; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__pyx_ptype_7sklearn_5utils_13weight_vector_WeightVector = __Pyx_ImportType("sklearn.utils.weight_vector", "WeightVector", sizeof(struct __pyx_obj_7sklearn_5utils_13weight_vector_WeightVector), 1); if (unlikely(!__pyx_ptype_7sklearn_5utils_13weight_vector_WeightVector)) {__pyx_filename = __pyx_f[3]; __pyx_lineno = 14; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__pyx_vtabptr_7sklearn_5utils_13weight_vector_WeightVector = (struct __pyx_vtabstruct_7sklearn_5utils_13weight_vector_WeightVector*)__Pyx_GetVtable(__pyx_ptype_7sklearn_5utils_13weight_vector_WeightVector->tp_dict); if (unlikely(!__pyx_vtabptr_7sklearn_5utils_13weight_vector_WeightVector)) {__pyx_filename = __pyx_f[3]; __pyx_lineno = 14; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__pyx_ptype_7sklearn_5utils_11seq_dataset_SequentialDataset = __Pyx_ImportType("sklearn.utils.seq_dataset", "SequentialDataset", sizeof(struct __pyx_obj_7sklearn_5utils_11seq_dataset_SequentialDataset), 1); if (unlikely(!__pyx_ptype_7sklearn_5utils_11seq_dataset_SequentialDataset)) {__pyx_filename = __pyx_f[4]; __pyx_lineno = 9; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__pyx_vtabptr_7sklearn_5utils_11seq_dataset_SequentialDataset = (struct __pyx_vtabstruct_7sklearn_5utils_11seq_dataset_SequentialDataset*)__Pyx_GetVtable(__pyx_ptype_7sklearn_5utils_11seq_dataset_SequentialDataset->tp_dict); if (unlikely(!__pyx_vtabptr_7sklearn_5utils_11seq_dataset_SequentialDataset)) {__pyx_filename = __pyx_f[4]; __pyx_lineno = 9; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__pyx_ptype_7sklearn_5utils_11seq_dataset_ArrayDataset = __Pyx_ImportType("sklearn.utils.seq_dataset", "ArrayDataset", sizeof(struct __pyx_obj_7sklearn_5utils_11seq_dataset_ArrayDataset), 1); if (unlikely(!__pyx_ptype_7sklearn_5utils_11seq_dataset_ArrayDataset)) {__pyx_filename = __pyx_f[4]; __pyx_lineno = 17; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__pyx_vtabptr_7sklearn_5utils_11seq_dataset_ArrayDataset = (struct __pyx_vtabstruct_7sklearn_5utils_11seq_dataset_ArrayDataset*)__Pyx_GetVtable(__pyx_ptype_7sklearn_5utils_11seq_dataset_ArrayDataset->tp_dict); if (unlikely(!__pyx_vtabptr_7sklearn_5utils_11seq_dataset_ArrayDataset)) {__pyx_filename = __pyx_f[4]; __pyx_lineno = 17; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__pyx_ptype_7sklearn_5utils_11seq_dataset_CSRDataset = __Pyx_ImportType("sklearn.utils.seq_dataset", "CSRDataset", sizeof(struct __pyx_obj_7sklearn_5utils_11seq_dataset_CSRDataset), 1); if (unlikely(!__pyx_ptype_7sklearn_5utils_11seq_dataset_CSRDataset)) {__pyx_filename = __pyx_f[4]; __pyx_lineno = 34; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__pyx_vtabptr_7sklearn_5utils_11seq_dataset_CSRDataset = (struct __pyx_vtabstruct_7sklearn_5utils_11seq_dataset_CSRDataset*)__Pyx_GetVtable(__pyx_ptype_7sklearn_5utils_11seq_dataset_CSRDataset->tp_dict); if (unlikely(!__pyx_vtabptr_7sklearn_5utils_11seq_dataset_CSRDataset)) {__pyx_filename = __pyx_f[4]; __pyx_lineno = 34; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
/*--- Variable import code ---*/
/*--- Function import code ---*/
/*--- Execution code ---*/
/* "sklearn/linear_model/sgd_fast.pyx":11
*
*
* import numpy as np # <<<<<<<<<<<<<<
* import sys
* from time import time
*/
__pyx_t_1 = __Pyx_Import(((PyObject *)__pyx_n_s__numpy), 0, -1); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 11; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_1);
if (PyObject_SetAttr(__pyx_m, __pyx_n_s__np, __pyx_t_1) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 11; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0;
/* "sklearn/linear_model/sgd_fast.pyx":12
*
* import numpy as np
* import sys # <<<<<<<<<<<<<<
* from time import time
*
*/
__pyx_t_1 = __Pyx_Import(((PyObject *)__pyx_n_s__sys), 0, -1); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 12; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_1);
if (PyObject_SetAttr(__pyx_m, __pyx_n_s__sys, __pyx_t_1) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 12; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0;
/* "sklearn/linear_model/sgd_fast.pyx":13
* import numpy as np
* import sys
* from time import time # <<<<<<<<<<<<<<
*
* from libc.math cimport exp, log, sqrt, pow, fabs
*/
__pyx_t_1 = PyList_New(1); if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 13; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_1);
__Pyx_INCREF(((PyObject *)__pyx_n_s__time));
PyList_SET_ITEM(__pyx_t_1, 0, ((PyObject *)__pyx_n_s__time));
__Pyx_GIVEREF(((PyObject *)__pyx_n_s__time));
__pyx_t_2 = __Pyx_Import(((PyObject *)__pyx_n_s__time), ((PyObject *)__pyx_t_1), -1); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 13; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_2);
__Pyx_DECREF(((PyObject *)__pyx_t_1)); __pyx_t_1 = 0;
__pyx_t_1 = PyObject_GetAttr(__pyx_t_2, __pyx_n_s__time);
if (__pyx_t_1 == NULL) {
if (PyErr_ExceptionMatches(PyExc_AttributeError)) __Pyx_RaiseImportError(__pyx_n_s__time);
if (unlikely(!__pyx_t_1)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 13; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
}
__Pyx_GOTREF(__pyx_t_1);
if (PyObject_SetAttr(__pyx_m, __pyx_n_s__time, __pyx_t_1) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 13; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_DECREF(__pyx_t_1); __pyx_t_1 = 0;
__Pyx_DECREF(__pyx_t_2); __pyx_t_2 = 0;
/* "sklearn/linear_model/sgd_fast.pyx":22
* from sklearn.utils.seq_dataset cimport SequentialDataset
*
* np.import_array() # <<<<<<<<<<<<<<
*
*
*/
import_array();
/* "sklearn/linear_model/sgd_fast.pyx":327
*
*
* def plain_sgd(np.ndarray[DOUBLE, ndim=1, mode='c'] weights, # <<<<<<<<<<<<<<
* double intercept,
* LossFunction loss,
*/
__pyx_t_2 = PyCFunction_NewEx(&__pyx_mdef_7sklearn_12linear_model_8sgd_fast_1plain_sgd, NULL, __pyx_n_s_21); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 327; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(__pyx_t_2);
if (PyObject_SetAttr(__pyx_m, __pyx_n_s__plain_sgd, __pyx_t_2) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 327; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_DECREF(__pyx_t_2); __pyx_t_2 = 0;
/* "sklearn/linear_model/sgd_fast.pyx":1
* # encoding: utf-8 # <<<<<<<<<<<<<<
* # cython: cdivision=True
* # cython: boundscheck=False
*/
__pyx_t_2 = PyDict_New(); if (unlikely(!__pyx_t_2)) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_GOTREF(((PyObject *)__pyx_t_2));
if (PyObject_SetAttr(__pyx_m, __pyx_n_s____test__, ((PyObject *)__pyx_t_2)) < 0) {__pyx_filename = __pyx_f[0]; __pyx_lineno = 1; __pyx_clineno = __LINE__; goto __pyx_L1_error;}
__Pyx_DECREF(((PyObject *)__pyx_t_2)); __pyx_t_2 = 0;
/* "numpy.pxd":975
* arr.base = baseptr
*
* cdef inline object get_array_base(ndarray arr): # <<<<<<<<<<<<<<
* if arr.base is NULL:
* return None
*/
goto __pyx_L0;
__pyx_L1_error:;
__Pyx_XDECREF(__pyx_t_1);
__Pyx_XDECREF(__pyx_t_2);
if (__pyx_m) {
__Pyx_AddTraceback("init sklearn.linear_model.sgd_fast", __pyx_clineno, __pyx_lineno, __pyx_filename);
Py_DECREF(__pyx_m); __pyx_m = 0;
} else if (!PyErr_Occurred()) {
PyErr_SetString(PyExc_ImportError, "init sklearn.linear_model.sgd_fast");
}
__pyx_L0:;
__Pyx_RefNannyFinishContext();
#if PY_MAJOR_VERSION < 3
return;
#else
return __pyx_m;
#endif
}
/* Runtime support code */
#if CYTHON_REFNANNY
static __Pyx_RefNannyAPIStruct *__Pyx_RefNannyImportAPI(const char *modname) {
PyObject *m = NULL, *p = NULL;
void *r = NULL;
m = PyImport_ImportModule((char *)modname);
if (!m) goto end;
p = PyObject_GetAttrString(m, (char *)"RefNannyAPI");
if (!p) goto end;
r = PyLong_AsVoidPtr(p);
end:
Py_XDECREF(p);
Py_XDECREF(m);
return (__Pyx_RefNannyAPIStruct *)r;
}
#endif /* CYTHON_REFNANNY */
static PyObject *__Pyx_GetName(PyObject *dict, PyObject *name) {
PyObject *result;
result = PyObject_GetAttr(dict, name);
if (!result) {
if (dict != __pyx_b) {
PyErr_Clear();
result = PyObject_GetAttr(__pyx_b, name);
}
if (!result) {
PyErr_SetObject(PyExc_NameError, name);
}
}
return result;
}
static CYTHON_INLINE void __Pyx_ErrRestore(PyObject *type, PyObject *value, PyObject *tb) {
#if CYTHON_COMPILING_IN_CPYTHON
PyObject *tmp_type, *tmp_value, *tmp_tb;
PyThreadState *tstate = PyThreadState_GET();
tmp_type = tstate->curexc_type;
tmp_value = tstate->curexc_value;
tmp_tb = tstate->curexc_traceback;
tstate->curexc_type = type;
tstate->curexc_value = value;
tstate->curexc_traceback = tb;
Py_XDECREF(tmp_type);
Py_XDECREF(tmp_value);
Py_XDECREF(tmp_tb);
#else
PyErr_Restore(type, value, tb);
#endif
}
static CYTHON_INLINE void __Pyx_ErrFetch(PyObject **type, PyObject **value, PyObject **tb) {
#if CYTHON_COMPILING_IN_CPYTHON
PyThreadState *tstate = PyThreadState_GET();
*type = tstate->curexc_type;
*value = tstate->curexc_value;
*tb = tstate->curexc_traceback;
tstate->curexc_type = 0;
tstate->curexc_value = 0;
tstate->curexc_traceback = 0;
#else
PyErr_Fetch(type, value, tb);
#endif
}
#if PY_MAJOR_VERSION < 3
static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb,
CYTHON_UNUSED PyObject *cause) {
Py_XINCREF(type);
if (!value || value == Py_None)
value = NULL;
else
Py_INCREF(value);
if (!tb || tb == Py_None)
tb = NULL;
else {
Py_INCREF(tb);
if (!PyTraceBack_Check(tb)) {
PyErr_SetString(PyExc_TypeError,
"raise: arg 3 must be a traceback or None");
goto raise_error;
}
}
#if PY_VERSION_HEX < 0x02050000
if (PyClass_Check(type)) {
#else
if (PyType_Check(type)) {
#endif
#if CYTHON_COMPILING_IN_PYPY
if (!value) {
Py_INCREF(Py_None);
value = Py_None;
}
#endif
PyErr_NormalizeException(&type, &value, &tb);
} else {
if (value) {
PyErr_SetString(PyExc_TypeError,
"instance exception may not have a separate value");
goto raise_error;
}
value = type;
#if PY_VERSION_HEX < 0x02050000
if (PyInstance_Check(type)) {
type = (PyObject*) ((PyInstanceObject*)type)->in_class;
Py_INCREF(type);
}
else {
type = 0;
PyErr_SetString(PyExc_TypeError,
"raise: exception must be an old-style class or instance");
goto raise_error;
}
#else
type = (PyObject*) Py_TYPE(type);
Py_INCREF(type);
if (!PyType_IsSubtype((PyTypeObject *)type, (PyTypeObject *)PyExc_BaseException)) {
PyErr_SetString(PyExc_TypeError,
"raise: exception class must be a subclass of BaseException");
goto raise_error;
}
#endif
}
__Pyx_ErrRestore(type, value, tb);
return;
raise_error:
Py_XDECREF(value);
Py_XDECREF(type);
Py_XDECREF(tb);
return;
}
#else /* Python 3+ */
static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, PyObject *cause) {
PyObject* owned_instance = NULL;
if (tb == Py_None) {
tb = 0;
} else if (tb && !PyTraceBack_Check(tb)) {
PyErr_SetString(PyExc_TypeError,
"raise: arg 3 must be a traceback or None");
goto bad;
}
if (value == Py_None)
value = 0;
if (PyExceptionInstance_Check(type)) {
if (value) {
PyErr_SetString(PyExc_TypeError,
"instance exception may not have a separate value");
goto bad;
}
value = type;
type = (PyObject*) Py_TYPE(value);
} else if (PyExceptionClass_Check(type)) {
PyObject *args;
if (!value)
args = PyTuple_New(0);
else if (PyTuple_Check(value)) {
Py_INCREF(value);
args = value;
}
else
args = PyTuple_Pack(1, value);
if (!args)
goto bad;
owned_instance = PyEval_CallObject(type, args);
Py_DECREF(args);
if (!owned_instance)
goto bad;
value = owned_instance;
if (!PyExceptionInstance_Check(value)) {
PyErr_Format(PyExc_TypeError,
"calling %R should have returned an instance of "
"BaseException, not %R",
type, Py_TYPE(value));
goto bad;
}
} else {
PyErr_SetString(PyExc_TypeError,
"raise: exception class must be a subclass of BaseException");
goto bad;
}
if (cause && cause != Py_None) {
PyObject *fixed_cause;
if (PyExceptionClass_Check(cause)) {
fixed_cause = PyObject_CallObject(cause, NULL);
if (fixed_cause == NULL)
goto bad;
}
else if (PyExceptionInstance_Check(cause)) {
fixed_cause = cause;
Py_INCREF(fixed_cause);
}
else {
PyErr_SetString(PyExc_TypeError,
"exception causes must derive from "
"BaseException");
goto bad;
}
PyException_SetCause(value, fixed_cause);
}
PyErr_SetObject(type, value);
if (tb) {
PyThreadState *tstate = PyThreadState_GET();
PyObject* tmp_tb = tstate->curexc_traceback;
if (tb != tmp_tb) {
Py_INCREF(tb);
tstate->curexc_traceback = tb;
Py_XDECREF(tmp_tb);
}
}
bad:
Py_XDECREF(owned_instance);
return;
}
#endif
static void __Pyx_RaiseArgtupleInvalid(
const char* func_name,
int exact,
Py_ssize_t num_min,
Py_ssize_t num_max,
Py_ssize_t num_found)
{
Py_ssize_t num_expected;
const char *more_or_less;
if (num_found < num_min) {
num_expected = num_min;
more_or_less = "at least";
} else {
num_expected = num_max;
more_or_less = "at most";
}
if (exact) {
more_or_less = "exactly";
}
PyErr_Format(PyExc_TypeError,
"%s() takes %s %" CYTHON_FORMAT_SSIZE_T "d positional argument%s (%" CYTHON_FORMAT_SSIZE_T "d given)",
func_name, more_or_less, num_expected,
(num_expected == 1) ? "" : "s", num_found);
}
static void __Pyx_RaiseDoubleKeywordsError(
const char* func_name,
PyObject* kw_name)
{
PyErr_Format(PyExc_TypeError,
#if PY_MAJOR_VERSION >= 3
"%s() got multiple values for keyword argument '%U'", func_name, kw_name);
#else
"%s() got multiple values for keyword argument '%s'", func_name,
PyString_AsString(kw_name));
#endif
}
static int __Pyx_ParseOptionalKeywords(
PyObject *kwds,
PyObject **argnames[],
PyObject *kwds2,
PyObject *values[],
Py_ssize_t num_pos_args,
const char* function_name)
{
PyObject *key = 0, *value = 0;
Py_ssize_t pos = 0;
PyObject*** name;
PyObject*** first_kw_arg = argnames + num_pos_args;
while (PyDict_Next(kwds, &pos, &key, &value)) {
name = first_kw_arg;
while (*name && (**name != key)) name++;
if (*name) {
values[name-argnames] = value;
continue;
}
name = first_kw_arg;
#if PY_MAJOR_VERSION < 3
if (likely(PyString_CheckExact(key)) || likely(PyString_Check(key))) {
while (*name) {
if ((CYTHON_COMPILING_IN_PYPY || PyString_GET_SIZE(**name) == PyString_GET_SIZE(key))
&& _PyString_Eq(**name, key)) {
values[name-argnames] = value;
break;
}
name++;
}
if (*name) continue;
else {
PyObject*** argname = argnames;
while (argname != first_kw_arg) {
if ((**argname == key) || (
(CYTHON_COMPILING_IN_PYPY || PyString_GET_SIZE(**argname) == PyString_GET_SIZE(key))
&& _PyString_Eq(**argname, key))) {
goto arg_passed_twice;
}
argname++;
}
}
} else
#endif
if (likely(PyUnicode_Check(key))) {
while (*name) {
int cmp = (**name == key) ? 0 :
#if !CYTHON_COMPILING_IN_PYPY && PY_MAJOR_VERSION >= 3
(PyUnicode_GET_SIZE(**name) != PyUnicode_GET_SIZE(key)) ? 1 :
#endif
PyUnicode_Compare(**name, key);
if (cmp < 0 && unlikely(PyErr_Occurred())) goto bad;
if (cmp == 0) {
values[name-argnames] = value;
break;
}
name++;
}
if (*name) continue;
else {
PyObject*** argname = argnames;
while (argname != first_kw_arg) {
int cmp = (**argname == key) ? 0 :
#if !CYTHON_COMPILING_IN_PYPY && PY_MAJOR_VERSION >= 3
(PyUnicode_GET_SIZE(**argname) != PyUnicode_GET_SIZE(key)) ? 1 :
#endif
PyUnicode_Compare(**argname, key);
if (cmp < 0 && unlikely(PyErr_Occurred())) goto bad;
if (cmp == 0) goto arg_passed_twice;
argname++;
}
}
} else
goto invalid_keyword_type;
if (kwds2) {
if (unlikely(PyDict_SetItem(kwds2, key, value))) goto bad;
} else {
goto invalid_keyword;
}
}
return 0;
arg_passed_twice:
__Pyx_RaiseDoubleKeywordsError(function_name, key);
goto bad;
invalid_keyword_type:
PyErr_Format(PyExc_TypeError,
"%s() keywords must be strings", function_name);
goto bad;
invalid_keyword:
PyErr_Format(PyExc_TypeError,
#if PY_MAJOR_VERSION < 3
"%s() got an unexpected keyword argument '%s'",
function_name, PyString_AsString(key));
#else
"%s() got an unexpected keyword argument '%U'",
function_name, key);
#endif
bad:
return -1;
}
static int __Pyx_ArgTypeTest(PyObject *obj, PyTypeObject *type, int none_allowed,
const char *name, int exact)
{
if (!type) {
PyErr_Format(PyExc_SystemError, "Missing type object");
return 0;
}
if (none_allowed && obj == Py_None) return 1;
else if (exact) {
if (Py_TYPE(obj) == type) return 1;
}
else {
if (PyObject_TypeCheck(obj, type)) return 1;
}
PyErr_Format(PyExc_TypeError,
"Argument '%s' has incorrect type (expected %s, got %s)",
name, type->tp_name, Py_TYPE(obj)->tp_name);
return 0;
}
static CYTHON_INLINE int __Pyx_IsLittleEndian(void) {
unsigned int n = 1;
return *(unsigned char*)(&n) != 0;
}
static void __Pyx_BufFmt_Init(__Pyx_BufFmt_Context* ctx,
__Pyx_BufFmt_StackElem* stack,
__Pyx_TypeInfo* type) {
stack[0].field = &ctx->root;
stack[0].parent_offset = 0;
ctx->root.type = type;
ctx->root.name = "buffer dtype";
ctx->root.offset = 0;
ctx->head = stack;
ctx->head->field = &ctx->root;
ctx->fmt_offset = 0;
ctx->head->parent_offset = 0;
ctx->new_packmode = '@';
ctx->enc_packmode = '@';
ctx->new_count = 1;
ctx->enc_count = 0;
ctx->enc_type = 0;
ctx->is_complex = 0;
ctx->is_valid_array = 0;
ctx->struct_alignment = 0;
while (type->typegroup == 'S') {
++ctx->head;
ctx->head->field = type->fields;
ctx->head->parent_offset = 0;
type = type->fields->type;
}
}
static int __Pyx_BufFmt_ParseNumber(const char** ts) {
int count;
const char* t = *ts;
if (*t < '0' || *t > '9') {
return -1;
} else {
count = *t++ - '0';
while (*t >= '0' && *t < '9') {
count *= 10;
count += *t++ - '0';
}
}
*ts = t;
return count;
}
static int __Pyx_BufFmt_ExpectNumber(const char **ts) {
int number = __Pyx_BufFmt_ParseNumber(ts);
if (number == -1) /* First char was not a digit */
PyErr_Format(PyExc_ValueError,\
"Does not understand character buffer dtype format string ('%c')", **ts);
return number;
}
static void __Pyx_BufFmt_RaiseUnexpectedChar(char ch) {
PyErr_Format(PyExc_ValueError,
"Unexpected format string character: '%c'", ch);
}
static const char* __Pyx_BufFmt_DescribeTypeChar(char ch, int is_complex) {
switch (ch) {
case 'c': return "'char'";
case 'b': return "'signed char'";
case 'B': return "'unsigned char'";
case 'h': return "'short'";
case 'H': return "'unsigned short'";
case 'i': return "'int'";
case 'I': return "'unsigned int'";
case 'l': return "'long'";
case 'L': return "'unsigned long'";
case 'q': return "'long long'";
case 'Q': return "'unsigned long long'";
case 'f': return (is_complex ? "'complex float'" : "'float'");
case 'd': return (is_complex ? "'complex double'" : "'double'");
case 'g': return (is_complex ? "'complex long double'" : "'long double'");
case 'T': return "a struct";
case 'O': return "Python object";
case 'P': return "a pointer";
case 's': case 'p': return "a string";
case 0: return "end";
default: return "unparseable format string";
}
}
static size_t __Pyx_BufFmt_TypeCharToStandardSize(char ch, int is_complex) {
switch (ch) {
case '?': case 'c': case 'b': case 'B': case 's': case 'p': return 1;
case 'h': case 'H': return 2;
case 'i': case 'I': case 'l': case 'L': return 4;
case 'q': case 'Q': return 8;
case 'f': return (is_complex ? 8 : 4);
case 'd': return (is_complex ? 16 : 8);
case 'g': {
PyErr_SetString(PyExc_ValueError, "Python does not define a standard format string size for long double ('g')..");
return 0;
}
case 'O': case 'P': return sizeof(void*);
default:
__Pyx_BufFmt_RaiseUnexpectedChar(ch);
return 0;
}
}
static size_t __Pyx_BufFmt_TypeCharToNativeSize(char ch, int is_complex) {
switch (ch) {
case 'c': case 'b': case 'B': case 's': case 'p': return 1;
case 'h': case 'H': return sizeof(short);
case 'i': case 'I': return sizeof(int);
case 'l': case 'L': return sizeof(long);
#ifdef HAVE_LONG_LONG
case 'q': case 'Q': return sizeof(PY_LONG_LONG);
#endif
case 'f': return sizeof(float) * (is_complex ? 2 : 1);
case 'd': return sizeof(double) * (is_complex ? 2 : 1);
case 'g': return sizeof(long double) * (is_complex ? 2 : 1);
case 'O': case 'P': return sizeof(void*);
default: {
__Pyx_BufFmt_RaiseUnexpectedChar(ch);
return 0;
}
}
}
typedef struct { char c; short x; } __Pyx_st_short;
typedef struct { char c; int x; } __Pyx_st_int;
typedef struct { char c; long x; } __Pyx_st_long;
typedef struct { char c; float x; } __Pyx_st_float;
typedef struct { char c; double x; } __Pyx_st_double;
typedef struct { char c; long double x; } __Pyx_st_longdouble;
typedef struct { char c; void *x; } __Pyx_st_void_p;
#ifdef HAVE_LONG_LONG
typedef struct { char c; PY_LONG_LONG x; } __Pyx_st_longlong;
#endif
static size_t __Pyx_BufFmt_TypeCharToAlignment(char ch, CYTHON_UNUSED int is_complex) {
switch (ch) {
case '?': case 'c': case 'b': case 'B': case 's': case 'p': return 1;
case 'h': case 'H': return sizeof(__Pyx_st_short) - sizeof(short);
case 'i': case 'I': return sizeof(__Pyx_st_int) - sizeof(int);
case 'l': case 'L': return sizeof(__Pyx_st_long) - sizeof(long);
#ifdef HAVE_LONG_LONG
case 'q': case 'Q': return sizeof(__Pyx_st_longlong) - sizeof(PY_LONG_LONG);
#endif
case 'f': return sizeof(__Pyx_st_float) - sizeof(float);
case 'd': return sizeof(__Pyx_st_double) - sizeof(double);
case 'g': return sizeof(__Pyx_st_longdouble) - sizeof(long double);
case 'P': case 'O': return sizeof(__Pyx_st_void_p) - sizeof(void*);
default:
__Pyx_BufFmt_RaiseUnexpectedChar(ch);
return 0;
}
}
/* These are for computing the padding at the end of the struct to align
on the first member of the struct. This will probably the same as above,
but we don't have any guarantees.
*/
typedef struct { short x; char c; } __Pyx_pad_short;
typedef struct { int x; char c; } __Pyx_pad_int;
typedef struct { long x; char c; } __Pyx_pad_long;
typedef struct { float x; char c; } __Pyx_pad_float;
typedef struct { double x; char c; } __Pyx_pad_double;
typedef struct { long double x; char c; } __Pyx_pad_longdouble;
typedef struct { void *x; char c; } __Pyx_pad_void_p;
#ifdef HAVE_LONG_LONG
typedef struct { PY_LONG_LONG x; char c; } __Pyx_pad_longlong;
#endif
static size_t __Pyx_BufFmt_TypeCharToPadding(char ch, CYTHON_UNUSED int is_complex) {
switch (ch) {
case '?': case 'c': case 'b': case 'B': case 's': case 'p': return 1;
case 'h': case 'H': return sizeof(__Pyx_pad_short) - sizeof(short);
case 'i': case 'I': return sizeof(__Pyx_pad_int) - sizeof(int);
case 'l': case 'L': return sizeof(__Pyx_pad_long) - sizeof(long);
#ifdef HAVE_LONG_LONG
case 'q': case 'Q': return sizeof(__Pyx_pad_longlong) - sizeof(PY_LONG_LONG);
#endif
case 'f': return sizeof(__Pyx_pad_float) - sizeof(float);
case 'd': return sizeof(__Pyx_pad_double) - sizeof(double);
case 'g': return sizeof(__Pyx_pad_longdouble) - sizeof(long double);
case 'P': case 'O': return sizeof(__Pyx_pad_void_p) - sizeof(void*);
default:
__Pyx_BufFmt_RaiseUnexpectedChar(ch);
return 0;
}
}
static char __Pyx_BufFmt_TypeCharToGroup(char ch, int is_complex) {
switch (ch) {
case 'c':
return 'H';
case 'b': case 'h': case 'i':
case 'l': case 'q': case 's': case 'p':
return 'I';
case 'B': case 'H': case 'I': case 'L': case 'Q':
return 'U';
case 'f': case 'd': case 'g':
return (is_complex ? 'C' : 'R');
case 'O':
return 'O';
case 'P':
return 'P';
default: {
__Pyx_BufFmt_RaiseUnexpectedChar(ch);
return 0;
}
}
}
static void __Pyx_BufFmt_RaiseExpected(__Pyx_BufFmt_Context* ctx) {
if (ctx->head == NULL || ctx->head->field == &ctx->root) {
const char* expected;
const char* quote;
if (ctx->head == NULL) {
expected = "end";
quote = "";
} else {
expected = ctx->head->field->type->name;
quote = "'";
}
PyErr_Format(PyExc_ValueError,
"Buffer dtype mismatch, expected %s%s%s but got %s",
quote, expected, quote,
__Pyx_BufFmt_DescribeTypeChar(ctx->enc_type, ctx->is_complex));
} else {
__Pyx_StructField* field = ctx->head->field;
__Pyx_StructField* parent = (ctx->head - 1)->field;
PyErr_Format(PyExc_ValueError,
"Buffer dtype mismatch, expected '%s' but got %s in '%s.%s'",
field->type->name, __Pyx_BufFmt_DescribeTypeChar(ctx->enc_type, ctx->is_complex),
parent->type->name, field->name);
}
}
static int __Pyx_BufFmt_ProcessTypeChunk(__Pyx_BufFmt_Context* ctx) {
char group;
size_t size, offset, arraysize = 1;
if (ctx->enc_type == 0) return 0;
if (ctx->head->field->type->arraysize[0]) {
int i, ndim = 0;
if (ctx->enc_type == 's' || ctx->enc_type == 'p') {
ctx->is_valid_array = ctx->head->field->type->ndim == 1;
ndim = 1;
if (ctx->enc_count != ctx->head->field->type->arraysize[0]) {
PyErr_Format(PyExc_ValueError,
"Expected a dimension of size %zu, got %zu",
ctx->head->field->type->arraysize[0], ctx->enc_count);
return -1;
}
}
if (!ctx->is_valid_array) {
PyErr_Format(PyExc_ValueError, "Expected %d dimensions, got %d",
ctx->head->field->type->ndim, ndim);
return -1;
}
for (i = 0; i < ctx->head->field->type->ndim; i++) {
arraysize *= ctx->head->field->type->arraysize[i];
}
ctx->is_valid_array = 0;
ctx->enc_count = 1;
}
group = __Pyx_BufFmt_TypeCharToGroup(ctx->enc_type, ctx->is_complex);
do {
__Pyx_StructField* field = ctx->head->field;
__Pyx_TypeInfo* type = field->type;
if (ctx->enc_packmode == '@' || ctx->enc_packmode == '^') {
size = __Pyx_BufFmt_TypeCharToNativeSize(ctx->enc_type, ctx->is_complex);
} else {
size = __Pyx_BufFmt_TypeCharToStandardSize(ctx->enc_type, ctx->is_complex);
}
if (ctx->enc_packmode == '@') {
size_t align_at = __Pyx_BufFmt_TypeCharToAlignment(ctx->enc_type, ctx->is_complex);
size_t align_mod_offset;
if (align_at == 0) return -1;
align_mod_offset = ctx->fmt_offset % align_at;
if (align_mod_offset > 0) ctx->fmt_offset += align_at - align_mod_offset;
if (ctx->struct_alignment == 0)
ctx->struct_alignment = __Pyx_BufFmt_TypeCharToPadding(ctx->enc_type,
ctx->is_complex);
}
if (type->size != size || type->typegroup != group) {
if (type->typegroup == 'C' && type->fields != NULL) {
size_t parent_offset = ctx->head->parent_offset + field->offset;
++ctx->head;
ctx->head->field = type->fields;
ctx->head->parent_offset = parent_offset;
continue;
}
if ((type->typegroup == 'H' || group == 'H') && type->size == size) {
} else {
__Pyx_BufFmt_RaiseExpected(ctx);
return -1;
}
}
offset = ctx->head->parent_offset + field->offset;
if (ctx->fmt_offset != offset) {
PyErr_Format(PyExc_ValueError,
"Buffer dtype mismatch; next field is at offset %" CYTHON_FORMAT_SSIZE_T "d but %" CYTHON_FORMAT_SSIZE_T "d expected",
(Py_ssize_t)ctx->fmt_offset, (Py_ssize_t)offset);
return -1;
}
ctx->fmt_offset += size;
if (arraysize)
ctx->fmt_offset += (arraysize - 1) * size;
--ctx->enc_count; /* Consume from buffer string */
while (1) {
if (field == &ctx->root) {
ctx->head = NULL;
if (ctx->enc_count != 0) {
__Pyx_BufFmt_RaiseExpected(ctx);
return -1;
}
break; /* breaks both loops as ctx->enc_count == 0 */
}
ctx->head->field = ++field;
if (field->type == NULL) {
--ctx->head;
field = ctx->head->field;
continue;
} else if (field->type->typegroup == 'S') {
size_t parent_offset = ctx->head->parent_offset + field->offset;
if (field->type->fields->type == NULL) continue; /* empty struct */
field = field->type->fields;
++ctx->head;
ctx->head->field = field;
ctx->head->parent_offset = parent_offset;
break;
} else {
break;
}
}
} while (ctx->enc_count);
ctx->enc_type = 0;
ctx->is_complex = 0;
return 0;
}
static CYTHON_INLINE PyObject *
__pyx_buffmt_parse_array(__Pyx_BufFmt_Context* ctx, const char** tsp)
{
const char *ts = *tsp;
int i = 0, number;
int ndim = ctx->head->field->type->ndim;
;
++ts;
if (ctx->new_count != 1) {
PyErr_SetString(PyExc_ValueError,
"Cannot handle repeated arrays in format string");
return NULL;
}
if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL;
while (*ts && *ts != ')') {
if (isspace(*ts))
continue;
number = __Pyx_BufFmt_ExpectNumber(&ts);
if (number == -1) return NULL;
if (i < ndim && (size_t) number != ctx->head->field->type->arraysize[i])
return PyErr_Format(PyExc_ValueError,
"Expected a dimension of size %zu, got %d",
ctx->head->field->type->arraysize[i], number);
if (*ts != ',' && *ts != ')')
return PyErr_Format(PyExc_ValueError,
"Expected a comma in format string, got '%c'", *ts);
if (*ts == ',') ts++;
i++;
}
if (i != ndim)
return PyErr_Format(PyExc_ValueError, "Expected %d dimension(s), got %d",
ctx->head->field->type->ndim, i);
if (!*ts) {
PyErr_SetString(PyExc_ValueError,
"Unexpected end of format string, expected ')'");
return NULL;
}
ctx->is_valid_array = 1;
ctx->new_count = 1;
*tsp = ++ts;
return Py_None;
}
static const char* __Pyx_BufFmt_CheckString(__Pyx_BufFmt_Context* ctx, const char* ts) {
int got_Z = 0;
while (1) {
switch(*ts) {
case 0:
if (ctx->enc_type != 0 && ctx->head == NULL) {
__Pyx_BufFmt_RaiseExpected(ctx);
return NULL;
}
if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL;
if (ctx->head != NULL) {
__Pyx_BufFmt_RaiseExpected(ctx);
return NULL;
}
return ts;
case ' ':
case 10:
case 13:
++ts;
break;
case '<':
if (!__Pyx_IsLittleEndian()) {
PyErr_SetString(PyExc_ValueError, "Little-endian buffer not supported on big-endian compiler");
return NULL;
}
ctx->new_packmode = '=';
++ts;
break;
case '>':
case '!':
if (__Pyx_IsLittleEndian()) {
PyErr_SetString(PyExc_ValueError, "Big-endian buffer not supported on little-endian compiler");
return NULL;
}
ctx->new_packmode = '=';
++ts;
break;
case '=':
case '@':
case '^':
ctx->new_packmode = *ts++;
break;
case 'T': /* substruct */
{
const char* ts_after_sub;
size_t i, struct_count = ctx->new_count;
size_t struct_alignment = ctx->struct_alignment;
ctx->new_count = 1;
++ts;
if (*ts != '{') {
PyErr_SetString(PyExc_ValueError, "Buffer acquisition: Expected '{' after 'T'");
return NULL;
}
if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL;
ctx->enc_type = 0; /* Erase processed last struct element */
ctx->enc_count = 0;
ctx->struct_alignment = 0;
++ts;
ts_after_sub = ts;
for (i = 0; i != struct_count; ++i) {
ts_after_sub = __Pyx_BufFmt_CheckString(ctx, ts);
if (!ts_after_sub) return NULL;
}
ts = ts_after_sub;
if (struct_alignment) ctx->struct_alignment = struct_alignment;
}
break;
case '}': /* end of substruct; either repeat or move on */
{
size_t alignment = ctx->struct_alignment;
++ts;
if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL;
ctx->enc_type = 0; /* Erase processed last struct element */
if (alignment && ctx->fmt_offset % alignment) {
ctx->fmt_offset += alignment - (ctx->fmt_offset % alignment);
}
}
return ts;
case 'x':
if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL;
ctx->fmt_offset += ctx->new_count;
ctx->new_count = 1;
ctx->enc_count = 0;
ctx->enc_type = 0;
ctx->enc_packmode = ctx->new_packmode;
++ts;
break;
case 'Z':
got_Z = 1;
++ts;
if (*ts != 'f' && *ts != 'd' && *ts != 'g') {
__Pyx_BufFmt_RaiseUnexpectedChar('Z');
return NULL;
} /* fall through */
case 'c': case 'b': case 'B': case 'h': case 'H': case 'i': case 'I':
case 'l': case 'L': case 'q': case 'Q':
case 'f': case 'd': case 'g':
case 'O': case 's': case 'p':
if (ctx->enc_type == *ts && got_Z == ctx->is_complex &&
ctx->enc_packmode == ctx->new_packmode) {
ctx->enc_count += ctx->new_count;
} else {
if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL;
ctx->enc_count = ctx->new_count;
ctx->enc_packmode = ctx->new_packmode;
ctx->enc_type = *ts;
ctx->is_complex = got_Z;
}
++ts;
ctx->new_count = 1;
got_Z = 0;
break;
case ':':
++ts;
while(*ts != ':') ++ts;
++ts;
break;
case '(':
if (!__pyx_buffmt_parse_array(ctx, &ts)) return NULL;
break;
default:
{
int number = __Pyx_BufFmt_ExpectNumber(&ts);
if (number == -1) return NULL;
ctx->new_count = (size_t)number;
}
}
}
}
static CYTHON_INLINE void __Pyx_ZeroBuffer(Py_buffer* buf) {
buf->buf = NULL;
buf->obj = NULL;
buf->strides = __Pyx_zeros;
buf->shape = __Pyx_zeros;
buf->suboffsets = __Pyx_minusones;
}
static CYTHON_INLINE int __Pyx_GetBufferAndValidate(
Py_buffer* buf, PyObject* obj, __Pyx_TypeInfo* dtype, int flags,
int nd, int cast, __Pyx_BufFmt_StackElem* stack)
{
if (obj == Py_None || obj == NULL) {
__Pyx_ZeroBuffer(buf);
return 0;
}
buf->buf = NULL;
if (__Pyx_GetBuffer(obj, buf, flags) == -1) goto fail;
if (buf->ndim != nd) {
PyErr_Format(PyExc_ValueError,
"Buffer has wrong number of dimensions (expected %d, got %d)",
nd, buf->ndim);
goto fail;
}
if (!cast) {
__Pyx_BufFmt_Context ctx;
__Pyx_BufFmt_Init(&ctx, stack, dtype);
if (!__Pyx_BufFmt_CheckString(&ctx, buf->format)) goto fail;
}
if ((unsigned)buf->itemsize != dtype->size) {
PyErr_Format(PyExc_ValueError,
"Item size of buffer (%" CYTHON_FORMAT_SSIZE_T "d byte%s) does not match size of '%s' (%" CYTHON_FORMAT_SSIZE_T "d byte%s)",
buf->itemsize, (buf->itemsize > 1) ? "s" : "",
dtype->name, (Py_ssize_t)dtype->size, (dtype->size > 1) ? "s" : "");
goto fail;
}
if (buf->suboffsets == NULL) buf->suboffsets = __Pyx_minusones;
return 0;
fail:;
__Pyx_ZeroBuffer(buf);
return -1;
}
static CYTHON_INLINE void __Pyx_SafeReleaseBuffer(Py_buffer* info) {
if (info->buf == NULL) return;
if (info->suboffsets == __Pyx_minusones) info->suboffsets = NULL;
__Pyx_ReleaseBuffer(info);
}
static CYTHON_INLINE int __Pyx_TypeTest(PyObject *obj, PyTypeObject *type) {
if (unlikely(!type)) {
PyErr_Format(PyExc_SystemError, "Missing type object");
return 0;
}
if (likely(PyObject_TypeCheck(obj, type)))
return 1;
PyErr_Format(PyExc_TypeError, "Cannot convert %.200s to %.200s",
Py_TYPE(obj)->tp_name, type->tp_name);
return 0;
}
static void __Pyx_RaiseBufferFallbackError(void) {
PyErr_Format(PyExc_ValueError,
"Buffer acquisition failed on assignment; and then reacquiring the old buffer failed too!");
}
static CYTHON_INLINE void __Pyx_RaiseTooManyValuesError(Py_ssize_t expected) {
PyErr_Format(PyExc_ValueError,
"too many values to unpack (expected %" CYTHON_FORMAT_SSIZE_T "d)", expected);
}
static CYTHON_INLINE void __Pyx_RaiseNeedMoreValuesError(Py_ssize_t index) {
PyErr_Format(PyExc_ValueError,
"need more than %" CYTHON_FORMAT_SSIZE_T "d value%s to unpack",
index, (index == 1) ? "" : "s");
}
static CYTHON_INLINE void __Pyx_RaiseNoneNotIterableError(void) {
PyErr_SetString(PyExc_TypeError, "'NoneType' object is not iterable");
}
static CYTHON_INLINE int __Pyx_IterFinish(void) {
#if CYTHON_COMPILING_IN_CPYTHON
PyThreadState *tstate = PyThreadState_GET();
PyObject* exc_type = tstate->curexc_type;
if (unlikely(exc_type)) {
if (likely(exc_type == PyExc_StopIteration) || PyErr_GivenExceptionMatches(exc_type, PyExc_StopIteration)) {
PyObject *exc_value, *exc_tb;
exc_value = tstate->curexc_value;
exc_tb = tstate->curexc_traceback;
tstate->curexc_type = 0;
tstate->curexc_value = 0;
tstate->curexc_traceback = 0;
Py_DECREF(exc_type);
Py_XDECREF(exc_value);
Py_XDECREF(exc_tb);
return 0;
} else {
return -1;
}
}
return 0;
#else
if (unlikely(PyErr_Occurred())) {
if (likely(PyErr_ExceptionMatches(PyExc_StopIteration))) {
PyErr_Clear();
return 0;
} else {
return -1;
}
}
return 0;
#endif
}
static int __Pyx_IternextUnpackEndCheck(PyObject *retval, Py_ssize_t expected) {
if (unlikely(retval)) {
Py_DECREF(retval);
__Pyx_RaiseTooManyValuesError(expected);
return -1;
} else {
return __Pyx_IterFinish();
}
return 0;
}
#if PY_MAJOR_VERSION < 3
static int __Pyx_GetBuffer(PyObject *obj, Py_buffer *view, int flags) {
CYTHON_UNUSED PyObject *getbuffer_cobj;
#if PY_VERSION_HEX >= 0x02060000
if (PyObject_CheckBuffer(obj)) return PyObject_GetBuffer(obj, view, flags);
#endif
if (PyObject_TypeCheck(obj, __pyx_ptype_5numpy_ndarray)) return __pyx_pw_5numpy_7ndarray_1__getbuffer__(obj, view, flags);
#if PY_VERSION_HEX < 0x02060000
if (obj->ob_type->tp_dict &&
(getbuffer_cobj = PyMapping_GetItemString(obj->ob_type->tp_dict,
"__pyx_getbuffer"))) {
getbufferproc func;
#if PY_VERSION_HEX >= 0x02070000 && !(PY_MAJOR_VERSION == 3 && PY_MINOR_VERSION == 0)
func = (getbufferproc) PyCapsule_GetPointer(getbuffer_cobj, "getbuffer(obj, view, flags)");
#else
func = (getbufferproc) PyCObject_AsVoidPtr(getbuffer_cobj);
#endif
Py_DECREF(getbuffer_cobj);
if (!func)
goto fail;
return func(obj, view, flags);
} else {
PyErr_Clear();
}
#endif
PyErr_Format(PyExc_TypeError, "'%100s' does not have the buffer interface", Py_TYPE(obj)->tp_name);
#if PY_VERSION_HEX < 0x02060000
fail:
#endif
return -1;
}
static void __Pyx_ReleaseBuffer(Py_buffer *view) {
PyObject *obj = view->obj;
CYTHON_UNUSED PyObject *releasebuffer_cobj;
if (!obj) return;
#if PY_VERSION_HEX >= 0x02060000
if (PyObject_CheckBuffer(obj)) {
PyBuffer_Release(view);
return;
}
#endif
if (PyObject_TypeCheck(obj, __pyx_ptype_5numpy_ndarray)) { __pyx_pw_5numpy_7ndarray_3__releasebuffer__(obj, view); return; }
#if PY_VERSION_HEX < 0x02060000
if (obj->ob_type->tp_dict &&
(releasebuffer_cobj = PyMapping_GetItemString(obj->ob_type->tp_dict,
"__pyx_releasebuffer"))) {
releasebufferproc func;
#if PY_VERSION_HEX >= 0x02070000 && !(PY_MAJOR_VERSION == 3 && PY_MINOR_VERSION == 0)
func = (releasebufferproc) PyCapsule_GetPointer(releasebuffer_cobj, "releasebuffer(obj, view)");
#else
func = (releasebufferproc) PyCObject_AsVoidPtr(releasebuffer_cobj);
#endif
Py_DECREF(releasebuffer_cobj);
if (!func)
goto fail;
func(obj, view);
return;
} else {
PyErr_Clear();
}
#endif
goto nofail;
#if PY_VERSION_HEX < 0x02060000
fail:
#endif
PyErr_WriteUnraisable(obj);
nofail:
Py_DECREF(obj);
view->obj = NULL;
}
#endif /* PY_MAJOR_VERSION < 3 */
static PyObject *__Pyx_Import(PyObject *name, PyObject *from_list, long level) {
PyObject *py_import = 0;
PyObject *empty_list = 0;
PyObject *module = 0;
PyObject *global_dict = 0;
PyObject *empty_dict = 0;
PyObject *list;
py_import = __Pyx_GetAttrString(__pyx_b, "__import__");
if (!py_import)
goto bad;
if (from_list)
list = from_list;
else {
empty_list = PyList_New(0);
if (!empty_list)
goto bad;
list = empty_list;
}
global_dict = PyModule_GetDict(__pyx_m);
if (!global_dict)
goto bad;
empty_dict = PyDict_New();
if (!empty_dict)
goto bad;
#if PY_VERSION_HEX >= 0x02050000
{
#if PY_MAJOR_VERSION >= 3
if (level == -1) {
if (strchr(__Pyx_MODULE_NAME, '.')) {
/* try package relative import first */
PyObject *py_level = PyInt_FromLong(1);
if (!py_level)
goto bad;
module = PyObject_CallFunctionObjArgs(py_import,
name, global_dict, empty_dict, list, py_level, NULL);
Py_DECREF(py_level);
if (!module) {
if (!PyErr_ExceptionMatches(PyExc_ImportError))
goto bad;
PyErr_Clear();
}
}
level = 0; /* try absolute import on failure */
}
#endif
if (!module) {
PyObject *py_level = PyInt_FromLong(level);
if (!py_level)
goto bad;
module = PyObject_CallFunctionObjArgs(py_import,
name, global_dict, empty_dict, list, py_level, NULL);
Py_DECREF(py_level);
}
}
#else
if (level>0) {
PyErr_SetString(PyExc_RuntimeError, "Relative import is not supported for Python <=2.4.");
goto bad;
}
module = PyObject_CallFunctionObjArgs(py_import,
name, global_dict, empty_dict, list, NULL);
#endif
bad:
Py_XDECREF(empty_list);
Py_XDECREF(py_import);
Py_XDECREF(empty_dict);
return module;
}
static CYTHON_INLINE void __Pyx_RaiseImportError(PyObject *name) {
#if PY_MAJOR_VERSION < 3
PyErr_Format(PyExc_ImportError, "cannot import name %.230s",
PyString_AsString(name));
#else
PyErr_Format(PyExc_ImportError, "cannot import name %S", name);
#endif
}
#if !CYTHON_COMPILING_IN_PYPY && PY_MAJOR_VERSION < 3
static PyObject *__Pyx_GetStdout(void) {
PyObject *f = PySys_GetObject((char *)"stdout");
if (!f) {
PyErr_SetString(PyExc_RuntimeError, "lost sys.stdout");
}
return f;
}
static int __Pyx_Print(PyObject* f, PyObject *arg_tuple, int newline) {
int i;
if (!f) {
if (!(f = __Pyx_GetStdout()))
return -1;
}
Py_INCREF(f);
for (i=0; i < PyTuple_GET_SIZE(arg_tuple); i++) {
PyObject* v;
if (PyFile_SoftSpace(f, 1)) {
if (PyFile_WriteString(" ", f) < 0)
goto error;
}
v = PyTuple_GET_ITEM(arg_tuple, i);
if (PyFile_WriteObject(v, f, Py_PRINT_RAW) < 0)
goto error;
if (PyString_Check(v)) {
char *s = PyString_AsString(v);
Py_ssize_t len = PyString_Size(v);
if (len > 0 &&
isspace(Py_CHARMASK(s[len-1])) &&
s[len-1] != ' ')
PyFile_SoftSpace(f, 0);
}
}
if (newline) {
if (PyFile_WriteString("\n", f) < 0)
goto error;
PyFile_SoftSpace(f, 0);
}
Py_DECREF(f);
return 0;
error:
Py_DECREF(f);
return -1;
}
#else /* Python 3 has a print function */
static int __Pyx_Print(PyObject* stream, PyObject *arg_tuple, int newline) {
PyObject* kwargs = 0;
PyObject* result = 0;
PyObject* end_string;
if (unlikely(!__pyx_print)) {
__pyx_print = __Pyx_GetAttrString(__pyx_b, "print");
if (!__pyx_print)
return -1;
}
if (stream) {
kwargs = PyDict_New();
if (unlikely(!kwargs))
return -1;
if (unlikely(PyDict_SetItemString(kwargs, "file", stream) < 0))
goto bad;
if (!newline) {
end_string = PyUnicode_FromStringAndSize(" ", 1);
if (unlikely(!end_string))
goto bad;
if (PyDict_SetItemString(kwargs, "end", end_string) < 0) {
Py_DECREF(end_string);
goto bad;
}
Py_DECREF(end_string);
}
} else if (!newline) {
if (unlikely(!__pyx_print_kwargs)) {
__pyx_print_kwargs = PyDict_New();
if (unlikely(!__pyx_print_kwargs))
return -1;
end_string = PyUnicode_FromStringAndSize(" ", 1);
if (unlikely(!end_string))
return -1;
if (PyDict_SetItemString(__pyx_print_kwargs, "end", end_string) < 0) {
Py_DECREF(end_string);
return -1;
}
Py_DECREF(end_string);
}
kwargs = __pyx_print_kwargs;
}
result = PyObject_Call(__pyx_print, arg_tuple, kwargs);
if (unlikely(kwargs) && (kwargs != __pyx_print_kwargs))
Py_DECREF(kwargs);
if (!result)
return -1;
Py_DECREF(result);
return 0;
bad:
if (kwargs != __pyx_print_kwargs)
Py_XDECREF(kwargs);
return -1;
}
#endif
#if !CYTHON_COMPILING_IN_PYPY && PY_MAJOR_VERSION < 3
static int __Pyx_PrintOne(PyObject* f, PyObject *o) {
if (!f) {
if (!(f = __Pyx_GetStdout()))
return -1;
}
Py_INCREF(f);
if (PyFile_SoftSpace(f, 0)) {
if (PyFile_WriteString(" ", f) < 0)
goto error;
}
if (PyFile_WriteObject(o, f, Py_PRINT_RAW) < 0)
goto error;
if (PyFile_WriteString("\n", f) < 0)
goto error;
Py_DECREF(f);
return 0;
error:
Py_DECREF(f);
return -1;
/* the line below is just to avoid C compiler
* warnings about unused functions */
return __Pyx_Print(f, NULL, 0);
}
#else /* Python 3 has a print function */
static int __Pyx_PrintOne(PyObject* stream, PyObject *o) {
int res;
PyObject* arg_tuple = PyTuple_Pack(1, o);
if (unlikely(!arg_tuple))
return -1;
res = __Pyx_Print(stream, arg_tuple, 1);
Py_DECREF(arg_tuple);
return res;
}
#endif
#if CYTHON_CCOMPLEX
#ifdef __cplusplus
static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float x, float y) {
return ::std::complex< float >(x, y);
}
#else
static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float x, float y) {
return x + y*(__pyx_t_float_complex)_Complex_I;
}
#endif
#else
static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float x, float y) {
__pyx_t_float_complex z;
z.real = x;
z.imag = y;
return z;
}
#endif
#if CYTHON_CCOMPLEX
#else
static CYTHON_INLINE int __Pyx_c_eqf(__pyx_t_float_complex a, __pyx_t_float_complex b) {
return (a.real == b.real) && (a.imag == b.imag);
}
static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_sumf(__pyx_t_float_complex a, __pyx_t_float_complex b) {
__pyx_t_float_complex z;
z.real = a.real + b.real;
z.imag = a.imag + b.imag;
return z;
}
static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_difff(__pyx_t_float_complex a, __pyx_t_float_complex b) {
__pyx_t_float_complex z;
z.real = a.real - b.real;
z.imag = a.imag - b.imag;
return z;
}
static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_prodf(__pyx_t_float_complex a, __pyx_t_float_complex b) {
__pyx_t_float_complex z;
z.real = a.real * b.real - a.imag * b.imag;
z.imag = a.real * b.imag + a.imag * b.real;
return z;
}
static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_quotf(__pyx_t_float_complex a, __pyx_t_float_complex b) {
__pyx_t_float_complex z;
float denom = b.real * b.real + b.imag * b.imag;
z.real = (a.real * b.real + a.imag * b.imag) / denom;
z.imag = (a.imag * b.real - a.real * b.imag) / denom;
return z;
}
static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_negf(__pyx_t_float_complex a) {
__pyx_t_float_complex z;
z.real = -a.real;
z.imag = -a.imag;
return z;
}
static CYTHON_INLINE int __Pyx_c_is_zerof(__pyx_t_float_complex a) {
return (a.real == 0) && (a.imag == 0);
}
static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_conjf(__pyx_t_float_complex a) {
__pyx_t_float_complex z;
z.real = a.real;
z.imag = -a.imag;
return z;
}
#if 1
static CYTHON_INLINE float __Pyx_c_absf(__pyx_t_float_complex z) {
#if !defined(HAVE_HYPOT) || defined(_MSC_VER)
return sqrtf(z.real*z.real + z.imag*z.imag);
#else
return hypotf(z.real, z.imag);
#endif
}
static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_powf(__pyx_t_float_complex a, __pyx_t_float_complex b) {
__pyx_t_float_complex z;
float r, lnr, theta, z_r, z_theta;
if (b.imag == 0 && b.real == (int)b.real) {
if (b.real < 0) {
float denom = a.real * a.real + a.imag * a.imag;
a.real = a.real / denom;
a.imag = -a.imag / denom;
b.real = -b.real;
}
switch ((int)b.real) {
case 0:
z.real = 1;
z.imag = 0;
return z;
case 1:
return a;
case 2:
z = __Pyx_c_prodf(a, a);
return __Pyx_c_prodf(a, a);
case 3:
z = __Pyx_c_prodf(a, a);
return __Pyx_c_prodf(z, a);
case 4:
z = __Pyx_c_prodf(a, a);
return __Pyx_c_prodf(z, z);
}
}
if (a.imag == 0) {
if (a.real == 0) {
return a;
}
r = a.real;
theta = 0;
} else {
r = __Pyx_c_absf(a);
theta = atan2f(a.imag, a.real);
}
lnr = logf(r);
z_r = expf(lnr * b.real - theta * b.imag);
z_theta = theta * b.real + lnr * b.imag;
z.real = z_r * cosf(z_theta);
z.imag = z_r * sinf(z_theta);
return z;
}
#endif
#endif
#if CYTHON_CCOMPLEX
#ifdef __cplusplus
static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double x, double y) {
return ::std::complex< double >(x, y);
}
#else
static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double x, double y) {
return x + y*(__pyx_t_double_complex)_Complex_I;
}
#endif
#else
static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double x, double y) {
__pyx_t_double_complex z;
z.real = x;
z.imag = y;
return z;
}
#endif
#if CYTHON_CCOMPLEX
#else
static CYTHON_INLINE int __Pyx_c_eq(__pyx_t_double_complex a, __pyx_t_double_complex b) {
return (a.real == b.real) && (a.imag == b.imag);
}
static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_sum(__pyx_t_double_complex a, __pyx_t_double_complex b) {
__pyx_t_double_complex z;
z.real = a.real + b.real;
z.imag = a.imag + b.imag;
return z;
}
static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_diff(__pyx_t_double_complex a, __pyx_t_double_complex b) {
__pyx_t_double_complex z;
z.real = a.real - b.real;
z.imag = a.imag - b.imag;
return z;
}
static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_prod(__pyx_t_double_complex a, __pyx_t_double_complex b) {
__pyx_t_double_complex z;
z.real = a.real * b.real - a.imag * b.imag;
z.imag = a.real * b.imag + a.imag * b.real;
return z;
}
static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_quot(__pyx_t_double_complex a, __pyx_t_double_complex b) {
__pyx_t_double_complex z;
double denom = b.real * b.real + b.imag * b.imag;
z.real = (a.real * b.real + a.imag * b.imag) / denom;
z.imag = (a.imag * b.real - a.real * b.imag) / denom;
return z;
}
static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_neg(__pyx_t_double_complex a) {
__pyx_t_double_complex z;
z.real = -a.real;
z.imag = -a.imag;
return z;
}
static CYTHON_INLINE int __Pyx_c_is_zero(__pyx_t_double_complex a) {
return (a.real == 0) && (a.imag == 0);
}
static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_conj(__pyx_t_double_complex a) {
__pyx_t_double_complex z;
z.real = a.real;
z.imag = -a.imag;
return z;
}
#if 1
static CYTHON_INLINE double __Pyx_c_abs(__pyx_t_double_complex z) {
#if !defined(HAVE_HYPOT) || defined(_MSC_VER)
return sqrt(z.real*z.real + z.imag*z.imag);
#else
return hypot(z.real, z.imag);
#endif
}
static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_pow(__pyx_t_double_complex a, __pyx_t_double_complex b) {
__pyx_t_double_complex z;
double r, lnr, theta, z_r, z_theta;
if (b.imag == 0 && b.real == (int)b.real) {
if (b.real < 0) {
double denom = a.real * a.real + a.imag * a.imag;
a.real = a.real / denom;
a.imag = -a.imag / denom;
b.real = -b.real;
}
switch ((int)b.real) {
case 0:
z.real = 1;
z.imag = 0;
return z;
case 1:
return a;
case 2:
z = __Pyx_c_prod(a, a);
return __Pyx_c_prod(a, a);
case 3:
z = __Pyx_c_prod(a, a);
return __Pyx_c_prod(z, a);
case 4:
z = __Pyx_c_prod(a, a);
return __Pyx_c_prod(z, z);
}
}
if (a.imag == 0) {
if (a.real == 0) {
return a;
}
r = a.real;
theta = 0;
} else {
r = __Pyx_c_abs(a);
theta = atan2(a.imag, a.real);
}
lnr = log(r);
z_r = exp(lnr * b.real - theta * b.imag);
z_theta = theta * b.real + lnr * b.imag;
z.real = z_r * cos(z_theta);
z.imag = z_r * sin(z_theta);
return z;
}
#endif
#endif
static CYTHON_INLINE unsigned char __Pyx_PyInt_AsUnsignedChar(PyObject* x) {
const unsigned char neg_one = (unsigned char)-1, const_zero = 0;
const int is_unsigned = neg_one > const_zero;
if (sizeof(unsigned char) < sizeof(long)) {
long val = __Pyx_PyInt_AsLong(x);
if (unlikely(val != (long)(unsigned char)val)) {
if (!unlikely(val == -1 && PyErr_Occurred())) {
PyErr_SetString(PyExc_OverflowError,
(is_unsigned && unlikely(val < 0)) ?
"can't convert negative value to unsigned char" :
"value too large to convert to unsigned char");
}
return (unsigned char)-1;
}
return (unsigned char)val;
}
return (unsigned char)__Pyx_PyInt_AsUnsignedLong(x);
}
static CYTHON_INLINE unsigned short __Pyx_PyInt_AsUnsignedShort(PyObject* x) {
const unsigned short neg_one = (unsigned short)-1, const_zero = 0;
const int is_unsigned = neg_one > const_zero;
if (sizeof(unsigned short) < sizeof(long)) {
long val = __Pyx_PyInt_AsLong(x);
if (unlikely(val != (long)(unsigned short)val)) {
if (!unlikely(val == -1 && PyErr_Occurred())) {
PyErr_SetString(PyExc_OverflowError,
(is_unsigned && unlikely(val < 0)) ?
"can't convert negative value to unsigned short" :
"value too large to convert to unsigned short");
}
return (unsigned short)-1;
}
return (unsigned short)val;
}
return (unsigned short)__Pyx_PyInt_AsUnsignedLong(x);
}
static CYTHON_INLINE unsigned int __Pyx_PyInt_AsUnsignedInt(PyObject* x) {
const unsigned int neg_one = (unsigned int)-1, const_zero = 0;
const int is_unsigned = neg_one > const_zero;
if (sizeof(unsigned int) < sizeof(long)) {
long val = __Pyx_PyInt_AsLong(x);
if (unlikely(val != (long)(unsigned int)val)) {
if (!unlikely(val == -1 && PyErr_Occurred())) {
PyErr_SetString(PyExc_OverflowError,
(is_unsigned && unlikely(val < 0)) ?
"can't convert negative value to unsigned int" :
"value too large to convert to unsigned int");
}
return (unsigned int)-1;
}
return (unsigned int)val;
}
return (unsigned int)__Pyx_PyInt_AsUnsignedLong(x);
}
static CYTHON_INLINE char __Pyx_PyInt_AsChar(PyObject* x) {
const char neg_one = (char)-1, const_zero = 0;
const int is_unsigned = neg_one > const_zero;
if (sizeof(char) < sizeof(long)) {
long val = __Pyx_PyInt_AsLong(x);
if (unlikely(val != (long)(char)val)) {
if (!unlikely(val == -1 && PyErr_Occurred())) {
PyErr_SetString(PyExc_OverflowError,
(is_unsigned && unlikely(val < 0)) ?
"can't convert negative value to char" :
"value too large to convert to char");
}
return (char)-1;
}
return (char)val;
}
return (char)__Pyx_PyInt_AsLong(x);
}
static CYTHON_INLINE short __Pyx_PyInt_AsShort(PyObject* x) {
const short neg_one = (short)-1, const_zero = 0;
const int is_unsigned = neg_one > const_zero;
if (sizeof(short) < sizeof(long)) {
long val = __Pyx_PyInt_AsLong(x);
if (unlikely(val != (long)(short)val)) {
if (!unlikely(val == -1 && PyErr_Occurred())) {
PyErr_SetString(PyExc_OverflowError,
(is_unsigned && unlikely(val < 0)) ?
"can't convert negative value to short" :
"value too large to convert to short");
}
return (short)-1;
}
return (short)val;
}
return (short)__Pyx_PyInt_AsLong(x);
}
static CYTHON_INLINE int __Pyx_PyInt_AsInt(PyObject* x) {
const int neg_one = (int)-1, const_zero = 0;
const int is_unsigned = neg_one > const_zero;
if (sizeof(int) < sizeof(long)) {
long val = __Pyx_PyInt_AsLong(x);
if (unlikely(val != (long)(int)val)) {
if (!unlikely(val == -1 && PyErr_Occurred())) {
PyErr_SetString(PyExc_OverflowError,
(is_unsigned && unlikely(val < 0)) ?
"can't convert negative value to int" :
"value too large to convert to int");
}
return (int)-1;
}
return (int)val;
}
return (int)__Pyx_PyInt_AsLong(x);
}
static CYTHON_INLINE signed char __Pyx_PyInt_AsSignedChar(PyObject* x) {
const signed char neg_one = (signed char)-1, const_zero = 0;
const int is_unsigned = neg_one > const_zero;
if (sizeof(signed char) < sizeof(long)) {
long val = __Pyx_PyInt_AsLong(x);
if (unlikely(val != (long)(signed char)val)) {
if (!unlikely(val == -1 && PyErr_Occurred())) {
PyErr_SetString(PyExc_OverflowError,
(is_unsigned && unlikely(val < 0)) ?
"can't convert negative value to signed char" :
"value too large to convert to signed char");
}
return (signed char)-1;
}
return (signed char)val;
}
return (signed char)__Pyx_PyInt_AsSignedLong(x);
}
static CYTHON_INLINE signed short __Pyx_PyInt_AsSignedShort(PyObject* x) {
const signed short neg_one = (signed short)-1, const_zero = 0;
const int is_unsigned = neg_one > const_zero;
if (sizeof(signed short) < sizeof(long)) {
long val = __Pyx_PyInt_AsLong(x);
if (unlikely(val != (long)(signed short)val)) {
if (!unlikely(val == -1 && PyErr_Occurred())) {
PyErr_SetString(PyExc_OverflowError,
(is_unsigned && unlikely(val < 0)) ?
"can't convert negative value to signed short" :
"value too large to convert to signed short");
}
return (signed short)-1;
}
return (signed short)val;
}
return (signed short)__Pyx_PyInt_AsSignedLong(x);
}
static CYTHON_INLINE signed int __Pyx_PyInt_AsSignedInt(PyObject* x) {
const signed int neg_one = (signed int)-1, const_zero = 0;
const int is_unsigned = neg_one > const_zero;
if (sizeof(signed int) < sizeof(long)) {
long val = __Pyx_PyInt_AsLong(x);
if (unlikely(val != (long)(signed int)val)) {
if (!unlikely(val == -1 && PyErr_Occurred())) {
PyErr_SetString(PyExc_OverflowError,
(is_unsigned && unlikely(val < 0)) ?
"can't convert negative value to signed int" :
"value too large to convert to signed int");
}
return (signed int)-1;
}
return (signed int)val;
}
return (signed int)__Pyx_PyInt_AsSignedLong(x);
}
static CYTHON_INLINE int __Pyx_PyInt_AsLongDouble(PyObject* x) {
const int neg_one = (int)-1, const_zero = 0;
const int is_unsigned = neg_one > const_zero;
if (sizeof(int) < sizeof(long)) {
long val = __Pyx_PyInt_AsLong(x);
if (unlikely(val != (long)(int)val)) {
if (!unlikely(val == -1 && PyErr_Occurred())) {
PyErr_SetString(PyExc_OverflowError,
(is_unsigned && unlikely(val < 0)) ?
"can't convert negative value to int" :
"value too large to convert to int");
}
return (int)-1;
}
return (int)val;
}
return (int)__Pyx_PyInt_AsLong(x);
}
static CYTHON_INLINE unsigned long __Pyx_PyInt_AsUnsignedLong(PyObject* x) {
const unsigned long neg_one = (unsigned long)-1, const_zero = 0;
const int is_unsigned = neg_one > const_zero;
#if PY_VERSION_HEX < 0x03000000
if (likely(PyInt_Check(x))) {
long val = PyInt_AS_LONG(x);
if (is_unsigned && unlikely(val < 0)) {
PyErr_SetString(PyExc_OverflowError,
"can't convert negative value to unsigned long");
return (unsigned long)-1;
}
return (unsigned long)val;
} else
#endif
if (likely(PyLong_Check(x))) {
if (is_unsigned) {
if (unlikely(Py_SIZE(x) < 0)) {
PyErr_SetString(PyExc_OverflowError,
"can't convert negative value to unsigned long");
return (unsigned long)-1;
}
return (unsigned long)PyLong_AsUnsignedLong(x);
} else {
return (unsigned long)PyLong_AsLong(x);
}
} else {
unsigned long val;
PyObject *tmp = __Pyx_PyNumber_Int(x);
if (!tmp) return (unsigned long)-1;
val = __Pyx_PyInt_AsUnsignedLong(tmp);
Py_DECREF(tmp);
return val;
}
}
static CYTHON_INLINE unsigned PY_LONG_LONG __Pyx_PyInt_AsUnsignedLongLong(PyObject* x) {
const unsigned PY_LONG_LONG neg_one = (unsigned PY_LONG_LONG)-1, const_zero = 0;
const int is_unsigned = neg_one > const_zero;
#if PY_VERSION_HEX < 0x03000000
if (likely(PyInt_Check(x))) {
long val = PyInt_AS_LONG(x);
if (is_unsigned && unlikely(val < 0)) {
PyErr_SetString(PyExc_OverflowError,
"can't convert negative value to unsigned PY_LONG_LONG");
return (unsigned PY_LONG_LONG)-1;
}
return (unsigned PY_LONG_LONG)val;
} else
#endif
if (likely(PyLong_Check(x))) {
if (is_unsigned) {
if (unlikely(Py_SIZE(x) < 0)) {
PyErr_SetString(PyExc_OverflowError,
"can't convert negative value to unsigned PY_LONG_LONG");
return (unsigned PY_LONG_LONG)-1;
}
return (unsigned PY_LONG_LONG)PyLong_AsUnsignedLongLong(x);
} else {
return (unsigned PY_LONG_LONG)PyLong_AsLongLong(x);
}
} else {
unsigned PY_LONG_LONG val;
PyObject *tmp = __Pyx_PyNumber_Int(x);
if (!tmp) return (unsigned PY_LONG_LONG)-1;
val = __Pyx_PyInt_AsUnsignedLongLong(tmp);
Py_DECREF(tmp);
return val;
}
}
static CYTHON_INLINE long __Pyx_PyInt_AsLong(PyObject* x) {
const long neg_one = (long)-1, const_zero = 0;
const int is_unsigned = neg_one > const_zero;
#if PY_VERSION_HEX < 0x03000000
if (likely(PyInt_Check(x))) {
long val = PyInt_AS_LONG(x);
if (is_unsigned && unlikely(val < 0)) {
PyErr_SetString(PyExc_OverflowError,
"can't convert negative value to long");
return (long)-1;
}
return (long)val;
} else
#endif
if (likely(PyLong_Check(x))) {
if (is_unsigned) {
if (unlikely(Py_SIZE(x) < 0)) {
PyErr_SetString(PyExc_OverflowError,
"can't convert negative value to long");
return (long)-1;
}
return (long)PyLong_AsUnsignedLong(x);
} else {
return (long)PyLong_AsLong(x);
}
} else {
long val;
PyObject *tmp = __Pyx_PyNumber_Int(x);
if (!tmp) return (long)-1;
val = __Pyx_PyInt_AsLong(tmp);
Py_DECREF(tmp);
return val;
}
}
static CYTHON_INLINE PY_LONG_LONG __Pyx_PyInt_AsLongLong(PyObject* x) {
const PY_LONG_LONG neg_one = (PY_LONG_LONG)-1, const_zero = 0;
const int is_unsigned = neg_one > const_zero;
#if PY_VERSION_HEX < 0x03000000
if (likely(PyInt_Check(x))) {
long val = PyInt_AS_LONG(x);
if (is_unsigned && unlikely(val < 0)) {
PyErr_SetString(PyExc_OverflowError,
"can't convert negative value to PY_LONG_LONG");
return (PY_LONG_LONG)-1;
}
return (PY_LONG_LONG)val;
} else
#endif
if (likely(PyLong_Check(x))) {
if (is_unsigned) {
if (unlikely(Py_SIZE(x) < 0)) {
PyErr_SetString(PyExc_OverflowError,
"can't convert negative value to PY_LONG_LONG");
return (PY_LONG_LONG)-1;
}
return (PY_LONG_LONG)PyLong_AsUnsignedLongLong(x);
} else {
return (PY_LONG_LONG)PyLong_AsLongLong(x);
}
} else {
PY_LONG_LONG val;
PyObject *tmp = __Pyx_PyNumber_Int(x);
if (!tmp) return (PY_LONG_LONG)-1;
val = __Pyx_PyInt_AsLongLong(tmp);
Py_DECREF(tmp);
return val;
}
}
static CYTHON_INLINE signed long __Pyx_PyInt_AsSignedLong(PyObject* x) {
const signed long neg_one = (signed long)-1, const_zero = 0;
const int is_unsigned = neg_one > const_zero;
#if PY_VERSION_HEX < 0x03000000
if (likely(PyInt_Check(x))) {
long val = PyInt_AS_LONG(x);
if (is_unsigned && unlikely(val < 0)) {
PyErr_SetString(PyExc_OverflowError,
"can't convert negative value to signed long");
return (signed long)-1;
}
return (signed long)val;
} else
#endif
if (likely(PyLong_Check(x))) {
if (is_unsigned) {
if (unlikely(Py_SIZE(x) < 0)) {
PyErr_SetString(PyExc_OverflowError,
"can't convert negative value to signed long");
return (signed long)-1;
}
return (signed long)PyLong_AsUnsignedLong(x);
} else {
return (signed long)PyLong_AsLong(x);
}
} else {
signed long val;
PyObject *tmp = __Pyx_PyNumber_Int(x);
if (!tmp) return (signed long)-1;
val = __Pyx_PyInt_AsSignedLong(tmp);
Py_DECREF(tmp);
return val;
}
}
static CYTHON_INLINE signed PY_LONG_LONG __Pyx_PyInt_AsSignedLongLong(PyObject* x) {
const signed PY_LONG_LONG neg_one = (signed PY_LONG_LONG)-1, const_zero = 0;
const int is_unsigned = neg_one > const_zero;
#if PY_VERSION_HEX < 0x03000000
if (likely(PyInt_Check(x))) {
long val = PyInt_AS_LONG(x);
if (is_unsigned && unlikely(val < 0)) {
PyErr_SetString(PyExc_OverflowError,
"can't convert negative value to signed PY_LONG_LONG");
return (signed PY_LONG_LONG)-1;
}
return (signed PY_LONG_LONG)val;
} else
#endif
if (likely(PyLong_Check(x))) {
if (is_unsigned) {
if (unlikely(Py_SIZE(x) < 0)) {
PyErr_SetString(PyExc_OverflowError,
"can't convert negative value to signed PY_LONG_LONG");
return (signed PY_LONG_LONG)-1;
}
return (signed PY_LONG_LONG)PyLong_AsUnsignedLongLong(x);
} else {
return (signed PY_LONG_LONG)PyLong_AsLongLong(x);
}
} else {
signed PY_LONG_LONG val;
PyObject *tmp = __Pyx_PyNumber_Int(x);
if (!tmp) return (signed PY_LONG_LONG)-1;
val = __Pyx_PyInt_AsSignedLongLong(tmp);
Py_DECREF(tmp);
return val;
}
}
static void __Pyx_WriteUnraisable(const char *name, CYTHON_UNUSED int clineno,
CYTHON_UNUSED int lineno, CYTHON_UNUSED const char *filename) {
PyObject *old_exc, *old_val, *old_tb;
PyObject *ctx;
__Pyx_ErrFetch(&old_exc, &old_val, &old_tb);
#if PY_MAJOR_VERSION < 3
ctx = PyString_FromString(name);
#else
ctx = PyUnicode_FromString(name);
#endif
__Pyx_ErrRestore(old_exc, old_val, old_tb);
if (!ctx) {
PyErr_WriteUnraisable(Py_None);
} else {
PyErr_WriteUnraisable(ctx);
Py_DECREF(ctx);
}
}
static int __Pyx_check_binary_version(void) {
char ctversion[4], rtversion[4];
PyOS_snprintf(ctversion, 4, "%d.%d", PY_MAJOR_VERSION, PY_MINOR_VERSION);
PyOS_snprintf(rtversion, 4, "%s", Py_GetVersion());
if (ctversion[0] != rtversion[0] || ctversion[2] != rtversion[2]) {
char message[200];
PyOS_snprintf(message, sizeof(message),
"compiletime version %s of module '%.100s' "
"does not match runtime version %s",
ctversion, __Pyx_MODULE_NAME, rtversion);
#if PY_VERSION_HEX < 0x02050000
return PyErr_Warn(NULL, message);
#else
return PyErr_WarnEx(NULL, message, 1);
#endif
}
return 0;
}
static int __Pyx_SetVtable(PyObject *dict, void *vtable) {
#if PY_VERSION_HEX >= 0x02070000 && !(PY_MAJOR_VERSION==3&&PY_MINOR_VERSION==0)
PyObject *ob = PyCapsule_New(vtable, 0, 0);
#else
PyObject *ob = PyCObject_FromVoidPtr(vtable, 0);
#endif
if (!ob)
goto bad;
if (PyDict_SetItemString(dict, "__pyx_vtable__", ob) < 0)
goto bad;
Py_DECREF(ob);
return 0;
bad:
Py_XDECREF(ob);
return -1;
}
#ifndef __PYX_HAVE_RT_ImportModule
#define __PYX_HAVE_RT_ImportModule
static PyObject *__Pyx_ImportModule(const char *name) {
PyObject *py_name = 0;
PyObject *py_module = 0;
py_name = __Pyx_PyIdentifier_FromString(name);
if (!py_name)
goto bad;
py_module = PyImport_Import(py_name);
Py_DECREF(py_name);
return py_module;
bad:
Py_XDECREF(py_name);
return 0;
}
#endif
#ifndef __PYX_HAVE_RT_ImportType
#define __PYX_HAVE_RT_ImportType
static PyTypeObject *__Pyx_ImportType(const char *module_name, const char *class_name,
size_t size, int strict)
{
PyObject *py_module = 0;
PyObject *result = 0;
PyObject *py_name = 0;
char warning[200];
py_module = __Pyx_ImportModule(module_name);
if (!py_module)
goto bad;
py_name = __Pyx_PyIdentifier_FromString(class_name);
if (!py_name)
goto bad;
result = PyObject_GetAttr(py_module, py_name);
Py_DECREF(py_name);
py_name = 0;
Py_DECREF(py_module);
py_module = 0;
if (!result)
goto bad;
if (!PyType_Check(result)) {
PyErr_Format(PyExc_TypeError,
"%s.%s is not a type object",
module_name, class_name);
goto bad;
}
if (!strict && (size_t)((PyTypeObject *)result)->tp_basicsize > size) {
PyOS_snprintf(warning, sizeof(warning),
"%s.%s size changed, may indicate binary incompatibility",
module_name, class_name);
#if PY_VERSION_HEX < 0x02050000
if (PyErr_Warn(NULL, warning) < 0) goto bad;
#else
if (PyErr_WarnEx(NULL, warning, 0) < 0) goto bad;
#endif
}
else if ((size_t)((PyTypeObject *)result)->tp_basicsize != size) {
PyErr_Format(PyExc_ValueError,
"%s.%s has the wrong size, try recompiling",
module_name, class_name);
goto bad;
}
return (PyTypeObject *)result;
bad:
Py_XDECREF(py_module);
Py_XDECREF(result);
return NULL;
}
#endif
static void* __Pyx_GetVtable(PyObject *dict) {
void* ptr;
PyObject *ob = PyMapping_GetItemString(dict, (char *)"__pyx_vtable__");
if (!ob)
goto bad;
#if PY_VERSION_HEX >= 0x02070000 && !(PY_MAJOR_VERSION==3&&PY_MINOR_VERSION==0)
ptr = PyCapsule_GetPointer(ob, 0);
#else
ptr = PyCObject_AsVoidPtr(ob);
#endif
if (!ptr && !PyErr_Occurred())
PyErr_SetString(PyExc_RuntimeError, "invalid vtable found for imported type");
Py_DECREF(ob);
return ptr;
bad:
Py_XDECREF(ob);
return NULL;
}
static int __pyx_bisect_code_objects(__Pyx_CodeObjectCacheEntry* entries, int count, int code_line) {
int start = 0, mid = 0, end = count - 1;
if (end >= 0 && code_line > entries[end].code_line) {
return count;
}
while (start < end) {
mid = (start + end) / 2;
if (code_line < entries[mid].code_line) {
end = mid;
} else if (code_line > entries[mid].code_line) {
start = mid + 1;
} else {
return mid;
}
}
if (code_line <= entries[mid].code_line) {
return mid;
} else {
return mid + 1;
}
}
static PyCodeObject *__pyx_find_code_object(int code_line) {
PyCodeObject* code_object;
int pos;
if (unlikely(!code_line) || unlikely(!__pyx_code_cache.entries)) {
return NULL;
}
pos = __pyx_bisect_code_objects(__pyx_code_cache.entries, __pyx_code_cache.count, code_line);
if (unlikely(pos >= __pyx_code_cache.count) || unlikely(__pyx_code_cache.entries[pos].code_line != code_line)) {
return NULL;
}
code_object = __pyx_code_cache.entries[pos].code_object;
Py_INCREF(code_object);
return code_object;
}
static void __pyx_insert_code_object(int code_line, PyCodeObject* code_object) {
int pos, i;
__Pyx_CodeObjectCacheEntry* entries = __pyx_code_cache.entries;
if (unlikely(!code_line)) {
return;
}
if (unlikely(!entries)) {
entries = (__Pyx_CodeObjectCacheEntry*)PyMem_Malloc(64*sizeof(__Pyx_CodeObjectCacheEntry));
if (likely(entries)) {
__pyx_code_cache.entries = entries;
__pyx_code_cache.max_count = 64;
__pyx_code_cache.count = 1;
entries[0].code_line = code_line;
entries[0].code_object = code_object;
Py_INCREF(code_object);
}
return;
}
pos = __pyx_bisect_code_objects(__pyx_code_cache.entries, __pyx_code_cache.count, code_line);
if ((pos < __pyx_code_cache.count) && unlikely(__pyx_code_cache.entries[pos].code_line == code_line)) {
PyCodeObject* tmp = entries[pos].code_object;
entries[pos].code_object = code_object;
Py_DECREF(tmp);
return;
}
if (__pyx_code_cache.count == __pyx_code_cache.max_count) {
int new_max = __pyx_code_cache.max_count + 64;
entries = (__Pyx_CodeObjectCacheEntry*)PyMem_Realloc(
__pyx_code_cache.entries, new_max*sizeof(__Pyx_CodeObjectCacheEntry));
if (unlikely(!entries)) {
return;
}
__pyx_code_cache.entries = entries;
__pyx_code_cache.max_count = new_max;
}
for (i=__pyx_code_cache.count; i>pos; i--) {
entries[i] = entries[i-1];
}
entries[pos].code_line = code_line;
entries[pos].code_object = code_object;
__pyx_code_cache.count++;
Py_INCREF(code_object);
}
#include "compile.h"
#include "frameobject.h"
#include "traceback.h"
static PyCodeObject* __Pyx_CreateCodeObjectForTraceback(
const char *funcname, int c_line,
int py_line, const char *filename) {
PyCodeObject *py_code = 0;
PyObject *py_srcfile = 0;
PyObject *py_funcname = 0;
#if PY_MAJOR_VERSION < 3
py_srcfile = PyString_FromString(filename);
#else
py_srcfile = PyUnicode_FromString(filename);
#endif
if (!py_srcfile) goto bad;
if (c_line) {
#if PY_MAJOR_VERSION < 3
py_funcname = PyString_FromFormat( "%s (%s:%d)", funcname, __pyx_cfilenm, c_line);
#else
py_funcname = PyUnicode_FromFormat( "%s (%s:%d)", funcname, __pyx_cfilenm, c_line);
#endif
}
else {
#if PY_MAJOR_VERSION < 3
py_funcname = PyString_FromString(funcname);
#else
py_funcname = PyUnicode_FromString(funcname);
#endif
}
if (!py_funcname) goto bad;
py_code = __Pyx_PyCode_New(
0, /*int argcount,*/
0, /*int kwonlyargcount,*/
0, /*int nlocals,*/
0, /*int stacksize,*/
0, /*int flags,*/
__pyx_empty_bytes, /*PyObject *code,*/
__pyx_empty_tuple, /*PyObject *consts,*/
__pyx_empty_tuple, /*PyObject *names,*/
__pyx_empty_tuple, /*PyObject *varnames,*/
__pyx_empty_tuple, /*PyObject *freevars,*/
__pyx_empty_tuple, /*PyObject *cellvars,*/
py_srcfile, /*PyObject *filename,*/
py_funcname, /*PyObject *name,*/
py_line, /*int firstlineno,*/
__pyx_empty_bytes /*PyObject *lnotab*/
);
Py_DECREF(py_srcfile);
Py_DECREF(py_funcname);
return py_code;
bad:
Py_XDECREF(py_srcfile);
Py_XDECREF(py_funcname);
return NULL;
}
static void __Pyx_AddTraceback(const char *funcname, int c_line,
int py_line, const char *filename) {
PyCodeObject *py_code = 0;
PyObject *py_globals = 0;
PyFrameObject *py_frame = 0;
py_code = __pyx_find_code_object(c_line ? c_line : py_line);
if (!py_code) {
py_code = __Pyx_CreateCodeObjectForTraceback(
funcname, c_line, py_line, filename);
if (!py_code) goto bad;
__pyx_insert_code_object(c_line ? c_line : py_line, py_code);
}
py_globals = PyModule_GetDict(__pyx_m);
if (!py_globals) goto bad;
py_frame = PyFrame_New(
PyThreadState_GET(), /*PyThreadState *tstate,*/
py_code, /*PyCodeObject *code,*/
py_globals, /*PyObject *globals,*/
0 /*PyObject *locals*/
);
if (!py_frame) goto bad;
py_frame->f_lineno = py_line;
PyTraceBack_Here(py_frame);
bad:
Py_XDECREF(py_code);
Py_XDECREF(py_frame);
}
static int __Pyx_InitStrings(__Pyx_StringTabEntry *t) {
while (t->p) {
#if PY_MAJOR_VERSION < 3
if (t->is_unicode) {
*t->p = PyUnicode_DecodeUTF8(t->s, t->n - 1, NULL);
} else if (t->intern) {
*t->p = PyString_InternFromString(t->s);
} else {
*t->p = PyString_FromStringAndSize(t->s, t->n - 1);
}
#else /* Python 3+ has unicode identifiers */
if (t->is_unicode | t->is_str) {
if (t->intern) {
*t->p = PyUnicode_InternFromString(t->s);
} else if (t->encoding) {
*t->p = PyUnicode_Decode(t->s, t->n - 1, t->encoding, NULL);
} else {
*t->p = PyUnicode_FromStringAndSize(t->s, t->n - 1);
}
} else {
*t->p = PyBytes_FromStringAndSize(t->s, t->n - 1);
}
#endif
if (!*t->p)
return -1;
++t;
}
return 0;
}
/* Type Conversion Functions */
static CYTHON_INLINE int __Pyx_PyObject_IsTrue(PyObject* x) {
int is_true = x == Py_True;
if (is_true | (x == Py_False) | (x == Py_None)) return is_true;
else return PyObject_IsTrue(x);
}
static CYTHON_INLINE PyObject* __Pyx_PyNumber_Int(PyObject* x) {
PyNumberMethods *m;
const char *name = NULL;
PyObject *res = NULL;
#if PY_VERSION_HEX < 0x03000000
if (PyInt_Check(x) || PyLong_Check(x))
#else
if (PyLong_Check(x))
#endif
return Py_INCREF(x), x;
m = Py_TYPE(x)->tp_as_number;
#if PY_VERSION_HEX < 0x03000000
if (m && m->nb_int) {
name = "int";
res = PyNumber_Int(x);
}
else if (m && m->nb_long) {
name = "long";
res = PyNumber_Long(x);
}
#else
if (m && m->nb_int) {
name = "int";
res = PyNumber_Long(x);
}
#endif
if (res) {
#if PY_VERSION_HEX < 0x03000000
if (!PyInt_Check(res) && !PyLong_Check(res)) {
#else
if (!PyLong_Check(res)) {
#endif
PyErr_Format(PyExc_TypeError,
"__%s__ returned non-%s (type %.200s)",
name, name, Py_TYPE(res)->tp_name);
Py_DECREF(res);
return NULL;
}
}
else if (!PyErr_Occurred()) {
PyErr_SetString(PyExc_TypeError,
"an integer is required");
}
return res;
}
static CYTHON_INLINE Py_ssize_t __Pyx_PyIndex_AsSsize_t(PyObject* b) {
Py_ssize_t ival;
PyObject* x = PyNumber_Index(b);
if (!x) return -1;
ival = PyInt_AsSsize_t(x);
Py_DECREF(x);
return ival;
}
static CYTHON_INLINE PyObject * __Pyx_PyInt_FromSize_t(size_t ival) {
#if PY_VERSION_HEX < 0x02050000
if (ival <= LONG_MAX)
return PyInt_FromLong((long)ival);
else {
unsigned char *bytes = (unsigned char *) &ival;
int one = 1; int little = (int)*(unsigned char*)&one;
return _PyLong_FromByteArray(bytes, sizeof(size_t), little, 0);
}
#else
return PyInt_FromSize_t(ival);
#endif
}
static CYTHON_INLINE size_t __Pyx_PyInt_AsSize_t(PyObject* x) {
unsigned PY_LONG_LONG val = __Pyx_PyInt_AsUnsignedLongLong(x);
if (unlikely(val == (unsigned PY_LONG_LONG)-1 && PyErr_Occurred())) {
return (size_t)-1;
} else if (unlikely(val != (unsigned PY_LONG_LONG)(size_t)val)) {
PyErr_SetString(PyExc_OverflowError,
"value too large to convert to size_t");
return (size_t)-1;
}
return (size_t)val;
}
#endif /* Py_PYTHON_H */