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bfloat16.cc
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bfloat16.cc
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/* Copyright 2017 The TensorFlow Authors. All Rights Reserved.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
==============================================================================*/
/* Modified by martin.croome@greenwaves-technologies.com - Modifications to allow a standalone build
and remove requirements for pybind11 and other tensorflow dependencies
Add support for scalar operations and python numeric types
*/
#include <iostream>
#include <array>
#include <locale>
#define NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION
// #define DEBUG_CALLS
#include <Python.h>
#include <cinttypes>
#include <patchlevel.h>
#include <vector>
#ifdef DEBUG_CALLS
#include <iostream>
#endif
#include "eigen/Eigen/Core"
#include <fenv.h>
#include "numpy/arrayobject.h"
#include "numpy/ufuncobject.h"
#include <memory>
namespace greenwaves
{
namespace
{
using bfloat16 = Eigen::bfloat16;
using uint8 = std::uint8_t;
using int8 = std::int8_t;
using uint16 = std::uint16_t;
using int16 = std::int16_t;
using uint64 = std::uint64_t;
struct PyDecrefDeleter
{
void operator()(PyObject *p) const { Py_DECREF(p); }
};
// Safe container for an owned PyObject. On destruction, the reference count of
// the contained object will be decremented.
using Safe_PyObjectPtr = std::unique_ptr<PyObject, PyDecrefDeleter>;
Safe_PyObjectPtr make_safe(PyObject *object)
{
return Safe_PyObjectPtr(object);
}
bool PyLong_CheckNoOverflow(PyObject *object)
{
if (!PyLong_Check(object))
{
return false;
}
int overflow = 0;
PyLong_AsLongAndOverflow(object, &overflow);
return (overflow == 0);
}
// Registered numpy type ID. Global variable populated by the registration code.
// Protected by the GIL.
int npy_bfloat16 = NPY_NOTYPE;
// Forward declaration.
extern PyTypeObject bfloat16_type;
extern PyArray_Descr NPyBfloat16_Descr;
// Pointer to the bfloat16 type object we are using. This is either a pointer
// to bfloat16_type, if we choose to register it, or to the bfloat16 type
// registered by another system into NumPy.
PyTypeObject *bfloat16_type_ptr = nullptr;
// Representation of a Python bfloat16 object.
struct PyBfloat16
{
PyObject_HEAD; // Python object header
bfloat16 value;
};
// Returns true if 'object' is a PyBfloat16.
bool PyBfloat16_Check(PyObject *object)
{
return PyObject_IsInstance(object, reinterpret_cast<PyObject *>(&bfloat16_type));
}
// Extracts the value of a PyBfloat16 object.
bfloat16 PyBfloat16_Bfloat16(PyObject *object)
{
return reinterpret_cast<PyBfloat16 *>(object)->value;
}
// Constructs a PyBfloat16 object from a bfloat16.
PyObject *PyBfloat16_FromBfloat16(bfloat16 x)
{
return PyArray_Scalar(&x, &NPyBfloat16_Descr, NULL);
}
// Converts a Python object to a bfloat16 value. Returns true on success,
// returns false and reports a Python error on failure.
bool CastToBfloat16(PyObject *arg, bfloat16 *output)
{
if (PyBfloat16_Check(arg))
{
*output = PyBfloat16_Bfloat16(arg);
return true;
}
if (PyFloat_Check(arg))
{
double d = PyFloat_AsDouble(arg);
if (PyErr_Occurred())
{
return false;
}
// TODO(phawkins): check for overflow
*output = bfloat16(d);
return true;
}
if (PyLong_CheckNoOverflow(arg))
{
long l = PyLong_AsLong(arg); // NOLINT
if (PyErr_Occurred())
{
return false;
}
// TODO(phawkins): check for overflow
*output = bfloat16(static_cast<float>(l));
return true;
}
if (PyArray_IsScalar(arg, Half))
{
Eigen::half f;
PyArray_ScalarAsCtype(arg, &f);
*output = bfloat16(f);
return true;
}
if (PyArray_IsScalar(arg, Float))
{
float f;
PyArray_ScalarAsCtype(arg, &f);
*output = bfloat16(f);
return true;
}
if (PyArray_IsScalar(arg, Double))
{
double f;
PyArray_ScalarAsCtype(arg, &f);
*output = bfloat16(f);
return true;
}
if (PyArray_IsZeroDim(arg))
{
Safe_PyObjectPtr ref;
PyArrayObject *arr = reinterpret_cast<PyArrayObject *>(arg);
if (PyArray_TYPE(arr) != npy_bfloat16)
{
ref = make_safe(PyArray_Cast(arr, npy_bfloat16));
if (PyErr_Occurred())
{
return false;
}
arg = ref.get();
arr = reinterpret_cast<PyArrayObject *>(arg);
}
*output = *reinterpret_cast<bfloat16 *>(PyArray_DATA(arr));
return true;
}
return false;
}
// Constructs a new PyBfloat16.
PyObject *PyBfloat16_New(PyTypeObject *type, PyObject *args, PyObject *kwds)
{
if (kwds && PyDict_Size(kwds))
{
PyErr_SetString(PyExc_TypeError, "constructor takes no keyword arguments");
return nullptr;
}
Py_ssize_t size = PyTuple_Size(args);
if (size != 1)
{
PyErr_SetString(PyExc_TypeError,
"expected number as argument to bfloat16 constructor");
return nullptr;
}
PyObject *arg = PyTuple_GetItem(args, 0);
bfloat16 value;
if (PyBfloat16_Check(arg))
{
Py_INCREF(arg);
return arg;
}
else if (CastToBfloat16(arg, &value))
{
return PyBfloat16_FromBfloat16(value);
}
else if (PyArray_Check(arg))
{
PyArrayObject *arr = reinterpret_cast<PyArrayObject *>(arg);
if (PyArray_TYPE(arr) != npy_bfloat16)
{
return PyArray_Cast(arr, npy_bfloat16);
}
else
{
Py_INCREF(arg);
return arg;
}
}
PyErr_Format(PyExc_TypeError, "expected number, got %s",
arg->ob_type->tp_name);
return nullptr;
}
// Comparisons on PyBfloat16s.
PyObject *PyBfloat16_RichCompare(PyObject *self, PyObject *other, int cmp_op)
{
PyObject *arr, *ret;
arr = PyArray_FromScalar(self, NULL);
if (arr == NULL)
{
return NULL;
}
if (PyBfloat16_Check(other))
{
PyObject *arr_other;
arr_other = PyArray_FromScalar(other, NULL);
ret = Py_TYPE(arr)->tp_richcompare(arr, arr_other, cmp_op);
Py_DECREF(arr_other);
} else {
ret = Py_TYPE(arr)->tp_richcompare(arr, other, cmp_op);
}
Py_DECREF(arr);
return ret;
}
// Implementation of repr() for PyBfloat16.
PyObject *PyBfloat16_Repr(PyObject *self)
{
bfloat16 x = reinterpret_cast<PyBfloat16 *>(self)->value;
std::string v = std::to_string(static_cast<float>(x));
return PyUnicode_FromString(v.c_str());
}
// Implementation of str() for PyBfloat16.
PyObject *PyBfloat16_Str(PyObject *self)
{
bfloat16 x = reinterpret_cast<PyBfloat16 *>(self)->value;
std::string v = std::to_string(static_cast<float>(x));
return PyUnicode_FromString(v.c_str());
}
// Hash function for PyBfloat16. We use the identity function, which is a weak
// hash function.
Py_hash_t PyBfloat16_Hash(PyObject *self)
{
bfloat16 x = reinterpret_cast<PyBfloat16 *>(self)->value;
return x.value;
}
// Converts a PyBfloat16 into a PyFloat.
PyObject* PyBfloat16_Float(PyObject* self) {
bfloat16 x = PyBfloat16_Bfloat16(self);
return PyFloat_FromDouble(static_cast<double>(x));
}
// Converts a PyBfloat16 into a PyInt.
PyObject* PyBfloat16_Int(PyObject* self) {
bfloat16 x = PyBfloat16_Bfloat16(self);
long y = static_cast<long>(x); // NOLINT
return PyLong_FromLong(y);
}
PyNumberMethods PyBfloat16_AsNumber = {
nullptr, // nb_add
nullptr, // nb_subtract
nullptr, // nb_multiply
nullptr, // nb_remainder
nullptr, // nb_divmod
nullptr, // nb_power
nullptr, // nb_negative
nullptr, // nb_positive
nullptr, // nb_absolute
nullptr, // nb_nonzero
nullptr, // nb_invert
nullptr, // nb_lshift
nullptr, // nb_rshift
nullptr, // nb_and
nullptr, // nb_xor
nullptr, // nb_or
PyBfloat16_Int, // nb_int
nullptr, // reserved
PyBfloat16_Float, // nb_float
nullptr, // nb_inplace_add
nullptr, // nb_inplace_subtract
nullptr, // nb_inplace_multiply
nullptr, // nb_inplace_remainder
nullptr, // nb_inplace_power
nullptr, // nb_inplace_lshift
nullptr, // nb_inplace_rshift
nullptr, // nb_inplace_and
nullptr, // nb_inplace_xor
nullptr, // nb_inplace_or
nullptr, // nb_floor_divide
nullptr, // nb_true_divide
nullptr, // nb_inplace_floor_divide
nullptr, // nb_inplace_true_divide
nullptr, // nb_index
};
// format bfloat16. Convert to a float and call format on that
PyObject *PyBfloat16_Format(PyObject *self, PyObject *format)
{
bfloat16 x = reinterpret_cast<PyBfloat16 *>(self)->value;
PyObject * f_obj = PyFloat_FromDouble(static_cast<double>(x));
PyObject * __format__str = PyUnicode_FromString("__format__");
PyObject * f_str = PyObject_CallMethodObjArgs(f_obj, __format__str, format, NULL);
Py_DECREF(__format__str);
Py_XDECREF(f_obj);
return f_str;
}
static PyMethodDef PyBfloat16_methods[] = {
{
"__format__",
(PyCFunction) PyBfloat16_Format,
METH_O,
"__format__ method for bfloat16"
},
{NULL} /* Sentinel */
};
#ifdef IMPLEMENT_BUFFER
int PyBfloat16_getbuffer(PyObject *exporter, Py_buffer *view, int flags) {
view->obj = exporter;
Py_INCREF(exporter);
view->buf = &(reinterpret_cast<PyBfloat16 *>(exporter)->value);
view->len = 1;
view->itemsize = sizeof(bfloat16);
view->readonly = 0;
view->format = NULL;
if ((flags & PyBUF_FORMAT) == PyBUF_FORMAT)
view->format = (char *)"BB";
view->ndim = 1;
view->shape = NULL;
if ((flags & PyBUF_ND) == PyBUF_ND)
view->shape = &(view->len);
view->strides = NULL;
if ((flags & PyBUF_STRIDES) == PyBUF_STRIDES)
view->strides = &(view->itemsize);
view->suboffsets = NULL;
view->internal = NULL;
return 0;
}
static PyBufferProcs PyBfloat16_buffer_procs = {
&PyBfloat16_getbuffer,
NULL
};
#endif
// Python type for PyBfloat16 objects.
PyTypeObject bfloat16_type = {
PyVarObject_HEAD_INIT(nullptr, 0) "bfloat16", // tp_name
sizeof(PyBfloat16), // tp_basicsize
0, // tp_itemsize
nullptr, // tp_dealloc
#if PY_VERSION_HEX < 0x03080000
nullptr, // tp_print
#else
0, // tp_vectorcall_offset
#endif
nullptr, // tp_getattr
nullptr, // tp_setattr
nullptr, // tp_compare / tp_reserved
PyBfloat16_Repr, // tp_repr
&PyBfloat16_AsNumber, // tp_as_number
nullptr, // tp_as_sequence
nullptr, // tp_as_mapping
PyBfloat16_Hash, // tp_hash
nullptr, // tp_call
PyBfloat16_Str, // tp_str
nullptr, // tp_getattro
nullptr, // tp_setattro
#ifdef IMPLEMENT_BUFFER
&PyBfloat16_buffer_procs, // tp_as_buffer
#else
nullptr,
#endif
// tp_flags
Py_TPFLAGS_DEFAULT | Py_TPFLAGS_BASETYPE,
"bfloat16 floating-point values", // tp_doc
nullptr, // tp_traverse
nullptr, // tp_clear
PyBfloat16_RichCompare, // tp_richcompare
0, // tp_weaklistoffset
nullptr, // tp_iter
nullptr, // tp_iternext
PyBfloat16_methods, // tp_methods
nullptr, // tp_members
nullptr, // tp_getset
nullptr, // tp_base
nullptr, // tp_dict
nullptr, // tp_descr_get
nullptr, // tp_descr_set
0, // tp_dictoffset
nullptr, // tp_init
nullptr, // tp_alloc
PyBfloat16_New, // tp_new
nullptr, // tp_free
nullptr, // tp_is_gc
nullptr, // tp_bases
nullptr, // tp_mro
nullptr, // tp_cache
nullptr, // tp_subclasses
nullptr, // tp_weaklist
nullptr, // tp_del
0, // tp_version_tag
};
// Numpy support
PyArray_ArrFuncs NPyBfloat16_ArrFuncs;
PyArray_Descr NPyBfloat16_Descr = {
PyObject_HEAD_INIT(nullptr) //
/*typeobj=*/
(&bfloat16_type),
// We must register bfloat16 with a kind other than "f", because numpy
// considers two types with the same kind and size to be equal, but
// float16 != bfloat16.
// The downside of this is that NumPy scalar promotion does not work with
// bfloat16 values.
/*kind=*/'g',
// TODO(phawkins): there doesn't seem to be a way of guaranteeing a type
// character is unique.
/*type=*/'E',
/*byteorder=*/'=',
/*flags=*/NPY_NEEDS_PYAPI, // | NPY_USE_GETITEM | NPY_USE_SETITEM,
/*type_num=*/0,
/*elsize=*/sizeof(bfloat16),
/*alignment=*/alignof(bfloat16),
/*subarray=*/nullptr,
/*fields=*/nullptr,
/*names=*/nullptr,
/*f=*/&NPyBfloat16_ArrFuncs,
/*metadata=*/nullptr,
/*c_metadata=*/nullptr,
/*hash=*/-1, // -1 means "not computed yet".
};
// Implementations of NumPy array methods.
PyObject *NPyBfloat16_GetItem(void *data, void *arr)
{
bfloat16 x;
NPyBfloat16_Descr.f->copyswap(&x, data, !PyArray_ISNOTSWAPPED(reinterpret_cast<PyArrayObject *>(arr)), NULL);
return PyBfloat16_FromBfloat16(x);
}
int NPyBfloat16_SetItem(PyObject *item, void *data, void *arr)
{
bfloat16 x;
if (!CastToBfloat16(item, &x))
{
PyErr_Format(PyExc_TypeError, "expected number, got %s",
item->ob_type->tp_name);
return -1;
}
memcpy(data, &x, sizeof(bfloat16));
return 0;
}
void ByteSwap16(void *value)
{
char *p = reinterpret_cast<char *>(value);
std::swap(p[0], p[1]);
}
void NPyBfloat16_CopySwapN(void *dstv, npy_intp dstride, void *srcv,
npy_intp sstride, npy_intp n, int swap, void *arr)
{
char *dst = reinterpret_cast<char *>(dstv);
char *src = reinterpret_cast<char *>(srcv);
if (!src)
{
return;
}
if (swap)
{
for (npy_intp i = 0; i < n; i++)
{
char *r = dst + dstride * i;
memcpy(r, src + sstride * i, sizeof(uint16_t));
ByteSwap16(r);
}
}
else if (dstride == sizeof(uint16_t) && sstride == sizeof(uint16_t))
{
memcpy(dst, src, n * sizeof(uint16_t));
}
else
{
for (npy_intp i = 0; i < n; i++)
{
memcpy(dst + dstride * i, src + sstride * i, sizeof(uint16_t));
}
}
}
void NPyBfloat16_CopySwap(void *dst, void *src, int swap, void *arr)
{
if (!src)
{
return;
}
memcpy(dst, src, sizeof(uint16_t));
if (swap)
{
ByteSwap16(dst);
}
}
npy_bool NPyBfloat16_NonZero(void *data, void *arr)
{
bfloat16 x;
memcpy(&x, data, sizeof(x));
return x != static_cast<bfloat16>(0);
}
int NPyBfloat16_Fill(void *buffer_raw, npy_intp length, void *ignored)
{
bfloat16 *const buffer = reinterpret_cast<bfloat16 *>(buffer_raw);
const float start(buffer[0]);
const float delta = static_cast<float>(buffer[1]) - start;
for (npy_intp i = 2; i < length; ++i)
{
buffer[i] = static_cast<bfloat16>(start + i * delta);
}
return 0;
}
void NPyBfloat16_DotFunc(void *ip1, npy_intp is1, void *ip2, npy_intp is2,
void *op, npy_intp n, void *arr)
{
char *c1 = reinterpret_cast<char *>(ip1);
char *c2 = reinterpret_cast<char *>(ip2);
float acc = 0.0f;
for (npy_intp i = 0; i < n; ++i)
{
bfloat16 *const b1 = reinterpret_cast<bfloat16 *>(c1);
bfloat16 *const b2 = reinterpret_cast<bfloat16 *>(c2);
acc += static_cast<float>(*b1) * static_cast<float>(*b2);
c1 += is1;
c2 += is2;
}
bfloat16 *out = reinterpret_cast<bfloat16 *>(op);
*out = static_cast<bfloat16>(acc);
}
int NPyBfloat16_CompareFunc(const void *v1, const void *v2, void *arr)
{
#ifdef DEBUG_CALLS
std::cout << "NPyBfloat16_CompareFunc\n";
#endif
bfloat16 b1 = *reinterpret_cast<const bfloat16 *>(v1);
bfloat16 b2 = *reinterpret_cast<const bfloat16 *>(v2);
if (b1 < b2)
{
return -1;
}
if (b1 > b2)
{
return 1;
}
if (!Eigen::numext::isnan(b1) && Eigen::numext::isnan(b2))
{
return 1;
}
if (Eigen::numext::isnan(b2) && !Eigen::numext::isnan(b1))
{
return -1;
}
return 0;
}
int NPyBfloat16_ArgMaxFunc(void *data, npy_intp n, npy_intp *max_ind,
void *arr)
{
const bfloat16 *bdata = reinterpret_cast<const bfloat16 *>(data);
float max_val = -std::numeric_limits<float>::infinity();
for (npy_intp i = 0; i < n; ++i)
{
if (static_cast<float>(bdata[i]) > max_val)
{
max_val = static_cast<float>(bdata[i]);
*max_ind = i;
}
}
return 0;
}
int NPyBfloat16_ArgMinFunc(void *data, npy_intp n, npy_intp *min_ind,
void *arr)
{
const bfloat16 *bdata = reinterpret_cast<const bfloat16 *>(data);
float min_val = std::numeric_limits<float>::infinity();
for (npy_intp i = 0; i < n; ++i)
{
if (static_cast<float>(bdata[i]) < min_val)
{
min_val = static_cast<float>(bdata[i]);
*min_ind = i;
}
}
return 0;
}
// NumPy casts
template <typename T, typename Enable = void>
struct TypeDescriptor
{
// typedef ... T; // Representation type in memory for NumPy values of type
// static int Dtype() { return NPY_...; } // Numpy type number for T.
};
template <>
struct TypeDescriptor<bfloat16>
{
typedef bfloat16 T;
static int Dtype() { return npy_bfloat16; }
};
template <>
struct TypeDescriptor<uint8>
{
typedef uint8 T;
static int Dtype() { return NPY_UINT8; }
};
template <>
struct TypeDescriptor<uint16>
{
typedef uint16 T;
static int Dtype() { return NPY_UINT16; }
};
// We register "int", "long", and "long long" types for portability across
// Linux, where "int" and "long" are the same type, and Windows, where "long"
// and "longlong" are the same type.
template <>
struct TypeDescriptor<unsigned int>
{
typedef unsigned int T;
static int Dtype() { return NPY_UINT; }
};
template <>
struct TypeDescriptor<unsigned long>
{ // NOLINT
typedef unsigned long T; // NOLINT
static int Dtype() { return NPY_ULONG; }
};
template <>
struct TypeDescriptor<unsigned long long>
{ // NOLINT
typedef unsigned long long T; // NOLINT
static int Dtype() { return NPY_ULONGLONG; }
};
template <>
struct TypeDescriptor<int8>
{
typedef int8 T;
static int Dtype() { return NPY_INT8; }
};
template <>
struct TypeDescriptor<int16>
{
typedef int16 T;
static int Dtype() { return NPY_INT16; }
};
template <>
struct TypeDescriptor<int>
{
typedef int T;
static int Dtype() { return NPY_INT; }
};
template <>
struct TypeDescriptor<long>
{ // NOLINT
typedef long T; // NOLINT
static int Dtype() { return NPY_LONG; }
};
template <>
struct TypeDescriptor<long long>
{ // NOLINT
typedef long long T; // NOLINT
static int Dtype() { return NPY_LONGLONG; }
};
template <>
struct TypeDescriptor<bool>
{
typedef int8 T;
static int Dtype() { return NPY_BOOL; }
};
template <>
struct TypeDescriptor<Eigen::half>
{
typedef Eigen::half T;
static int Dtype() { return NPY_HALF; }
};
template <>
struct TypeDescriptor<float>
{
typedef float T;
static int Dtype() { return NPY_FLOAT; }
};
template <>
struct TypeDescriptor<double>
{
typedef double T;
static int Dtype() { return NPY_DOUBLE; }
};
template <>
struct TypeDescriptor<std::complex<float>>
{
typedef std::complex<float> T;
static int Dtype() { return NPY_COMPLEX64; }
};
template <>
struct TypeDescriptor<std::complex<double>>
{
typedef std::complex<double> T;
static int Dtype() { return NPY_COMPLEX128; }
};
template <>
struct TypeDescriptor<PyObject *>
{
typedef void * T;
static int Dtype() { return NPY_OBJECT; }
};
// Performs a NumPy array cast from type 'From' to 'To'.
template <typename From, typename To>
void NPyCast(void *from_void, void *to_void, npy_intp n, void *fromarr,
void *toarr)
{
const auto *from =
reinterpret_cast<typename TypeDescriptor<From>::T *>(from_void);
auto *to = reinterpret_cast<typename TypeDescriptor<To>::T *>(to_void);
for (npy_intp i = 0; i < n; ++i)
{
to[i] =
static_cast<typename TypeDescriptor<To>::T>(static_cast<To>(from[i]));
}
}
// Registers a cast between bfloat16 and type 'T'. 'numpy_type' is the NumPy
// type corresponding to 'T'. If 'cast_is_safe', registers that bfloat16 can be
// safely coerced to T.
template <typename T>
bool RegisterBfloat16Cast(int numpy_type, bool cast_is_safe)
{
if (PyArray_RegisterCastFunc(PyArray_DescrFromType(numpy_type), npy_bfloat16, NPyCast<T, bfloat16>) < 0)
{
return false;
}
if (PyArray_RegisterCastFunc(&NPyBfloat16_Descr, numpy_type, NPyCast<bfloat16, T>) < 0)
{
return false;
}
if (cast_is_safe && PyArray_RegisterCanCast(&NPyBfloat16_Descr, numpy_type, NPY_NOSCALAR) < 0)
{
return false;
}
return true;
}
template <typename InType, typename OutType, typename Functor>
struct UnaryUFunc
{
static std::vector<int> Types()
{
return {TypeDescriptor<InType>::Dtype(), TypeDescriptor<OutType>::Dtype()};
}
static void Call(char **args, const npy_intp *dimensions,
const npy_intp *steps, void *data)
{
const char *i0 = args[0];
char *o = args[1];
for (npy_intp k = 0; k < *dimensions; k++)
{
auto x = *reinterpret_cast<const typename TypeDescriptor<InType>::T *>(i0);
*reinterpret_cast<typename TypeDescriptor<OutType>::T *>(o) = Functor()(x);
i0 += steps[0];
o += steps[1];
}
}
};
template <typename InType, typename OutType, typename OutType2,
typename Functor>
struct UnaryUFunc2
{
static std::vector<int> Types()
{
return {TypeDescriptor<InType>::Dtype(), TypeDescriptor<OutType>::Dtype(),
TypeDescriptor<OutType2>::Dtype()};
}
static void Call(char **args, const npy_intp *dimensions,
const npy_intp *steps, void *data)
{
const char *i0 = args[0];
char *o0 = args[1];
char *o1 = args[2];
for (npy_intp k = 0; k < *dimensions; k++)
{
auto x = *reinterpret_cast<const typename TypeDescriptor<InType>::T *>(i0);
std::tie(*reinterpret_cast<typename TypeDescriptor<OutType>::T *>(o0),
*reinterpret_cast<typename TypeDescriptor<OutType2>::T *>(o1)) =
Functor()(x);
i0 += steps[0];
o0 += steps[1];
o1 += steps[2];
}
}
};
template <typename InType, typename OutType, typename Functor>
struct BinaryUFunc
{
static std::vector<int> Types()
{
return {TypeDescriptor<InType>::Dtype(), TypeDescriptor<InType>::Dtype(),
TypeDescriptor<OutType>::Dtype()};
}
static void Call(char **args, const npy_intp *dimensions,
const npy_intp *steps, void *data)
{
#ifdef DEBUG_CALLS
std::cout << "BinaryUFunc->Call\n";
#endif
const char *i0 = args[0];
const char *i1 = args[1];
char *o = args[2];
fenv_t fenv;
feholdexcept(&fenv);
for (npy_intp k = 0; k < *dimensions; k++)
{
auto x = *reinterpret_cast<const typename TypeDescriptor<InType>::T *>(i0);
auto y = *reinterpret_cast<const typename TypeDescriptor<InType>::T *>(i1);
*reinterpret_cast<typename TypeDescriptor<OutType>::T *>(o) =
Functor()(x, y);
i0 += steps[0];
i1 += steps[1];
o += steps[2];
}
if (fetestexcept(FE_INVALID | FE_DIVBYZERO | FE_OVERFLOW | FE_UNDERFLOW)) {
if (fetestexcept(FE_INVALID)) {
PyErr_SetString(PyExc_ArithmeticError, "bfloat16 invalid");
} else if (fetestexcept(FE_DIVBYZERO)) {
PyErr_SetString(PyExc_ArithmeticError, "bfloat16 divide by zero");
} else if (fetestexcept(FE_OVERFLOW)) {
PyErr_SetString(PyExc_ArithmeticError, "bfloat16 overflow");
} else if (fetestexcept(FE_UNDERFLOW)) {
PyErr_SetString(PyExc_ArithmeticError, "bfloat16 underflow");
}
}
fesetenv(&fenv);
}
};
template <typename InType, typename InType2, typename OutType, typename Functor>
struct BinaryUFunc2
{
static std::vector<int> Types()
{
return {TypeDescriptor<InType>::Dtype(), TypeDescriptor<InType2>::Dtype(),
TypeDescriptor<OutType>::Dtype()};
}
static void Call(char **args, const npy_intp *dimensions,
const npy_intp *steps, void *data)
{
#ifdef DEBUG_CALLS
std::cout << "BinaryUFunc2->Call\n";
#endif
const char *i0 = args[0];
const char *i1 = args[1];
char *o = args[2];
fenv_t fenv;
feholdexcept(&fenv);
for (npy_intp k = 0; k < *dimensions; k++)
{
auto x = *reinterpret_cast<const typename TypeDescriptor<InType>::T *>(i0);
auto y =
*reinterpret_cast<const typename TypeDescriptor<InType2>::T *>(i1);
*reinterpret_cast<typename TypeDescriptor<OutType>::T *>(o) =
Functor()(x, y);
i0 += steps[0];
i1 += steps[1];
o += steps[2];
}
if (fetestexcept(FE_INVALID | FE_DIVBYZERO | FE_OVERFLOW | FE_UNDERFLOW)) {
if (fetestexcept(FE_INVALID)) {
PyErr_SetString(PyExc_ArithmeticError, "bfloat16 invalid");
} else if (fetestexcept(FE_DIVBYZERO)) {
PyErr_SetString(PyExc_ArithmeticError, "bfloat16 divide by zero");
} else if (fetestexcept(FE_OVERFLOW)) {
PyErr_SetString(PyExc_ArithmeticError, "bfloat16 overflow");
} else if (fetestexcept(FE_UNDERFLOW)) {
PyErr_SetString(PyExc_ArithmeticError, "bfloat16 underflow");
}
}
fesetenv(&fenv);
}
};
// template <typename InType, typename OutType, typename Functor>
// struct BinaryUFuncObj
// {
// static std::vector<int> Types()
// {
// return {TypeDescriptor<InType>::Dtype(), NPY_OBJECT,
// TypeDescriptor<OutType>::Dtype()};
// }
// static void Call(char **args, const npy_intp *dimensions,
// const npy_intp *steps, void *data)
// {
// const char *i0 = args[0];
// char *i1 = args[1];
// char *o = args[2];
// for (npy_intp k = 0; k < *dimensions; k++)
// {
// auto x = *reinterpret_cast<const typename TypeDescriptor<InType>::T *>(i0);
// bfloat16 y = *reinterpret_cast<bfloat16 *>(i1);
// *reinterpret_cast<typename TypeDescriptor<OutType>::T *>(o) =
// Functor()(x, y);
// i0 += steps[0];
// i1 += steps[1];
// o += steps[2];
// }
// }
// };
template <typename UFunc>
bool RegisterUFunc(PyObject *numpy, const char *name)
{
std::vector<int> types = UFunc::Types();
PyUFuncGenericFunction fn =
reinterpret_cast<PyUFuncGenericFunction>(UFunc::Call);
Safe_PyObjectPtr ufunc_obj = make_safe(PyObject_GetAttrString(numpy, name));
if (!ufunc_obj)
{
return false;
}
PyUFuncObject *ufunc = reinterpret_cast<PyUFuncObject *>(ufunc_obj.get());
if (static_cast<int>(types.size()) != ufunc->nargs)
{
PyErr_Format(PyExc_AssertionError,
"ufunc %s takes %d arguments, loop takes %lu", name,
ufunc->nargs, types.size());
return false;
}
if (PyUFunc_RegisterLoopForType(ufunc, npy_bfloat16, fn,