Files
pytorch/torch/csrc/Module.cpp
2016-08-12 07:46:46 -07:00

736 lines
33 KiB
C++

#include <Python.h>
#include <stdbool.h>
#include <unordered_map>
#include <TH/TH.h>
#include "THP.h"
PyObject* module;
PyObject* tensor_classes;
PyObject *THPDoubleStorageClass = NULL;
PyObject *THPFloatStorageClass = NULL;
PyObject *THPLongStorageClass = NULL;
PyObject *THPIntStorageClass = NULL;
PyObject *THPShortStorageClass = NULL;
PyObject *THPCharStorageClass = NULL;
PyObject *THPByteStorageClass = NULL;
PyObject *THPDoubleTensorClass = NULL;
PyObject *THPFloatTensorClass = NULL;
PyObject *THPLongTensorClass = NULL;
PyObject *THPIntTensorClass = NULL;
PyObject *THPShortTensorClass = NULL;
PyObject *THPCharTensorClass = NULL;
PyObject *THPByteTensorClass = NULL;
PyObject *THPDefaultTensorClass = NULL;
PyObject *THPGeneratorClass = NULL;
// Used if no other generator is provided
THPGenerator *THPDefaultGenerator = NULL;
static bool THPModule_loadClasses(PyObject *self)
{
#define ASSERT_NOT_NULL(ptr) if (!(ptr)) { THPUtils_setError("couldn't load classes"); return false; }
PyObject *torch_module = PyImport_ImportModule("torch");
if (!torch_module) {
THPUtils_setError("class loader couldn't access torch module");
return false;
}
PyObject* module_dict = PyModule_GetDict(torch_module);
ASSERT_NOT_NULL(tensor_classes = PyMapping_GetItemString(module_dict, (char*)"_tensor_classes"));
ASSERT_NOT_NULL(THPDoubleStorageClass = PyMapping_GetItemString(module_dict,(char*)"DoubleStorage"));
ASSERT_NOT_NULL(THPFloatStorageClass = PyMapping_GetItemString(module_dict,(char*)"FloatStorage"));
ASSERT_NOT_NULL(THPLongStorageClass = PyMapping_GetItemString(module_dict,(char*)"LongStorage"));
ASSERT_NOT_NULL(THPIntStorageClass = PyMapping_GetItemString(module_dict,(char*)"IntStorage"));
ASSERT_NOT_NULL(THPShortStorageClass = PyMapping_GetItemString(module_dict,(char*)"ShortStorage"));
ASSERT_NOT_NULL(THPCharStorageClass = PyMapping_GetItemString(module_dict,(char*)"CharStorage"));
ASSERT_NOT_NULL(THPByteStorageClass = PyMapping_GetItemString(module_dict,(char*)"ByteStorage"));
ASSERT_NOT_NULL(THPDoubleTensorClass = PyMapping_GetItemString(module_dict,(char*)"DoubleTensor"));
ASSERT_NOT_NULL(THPFloatTensorClass = PyMapping_GetItemString(module_dict,(char*)"FloatTensor"));
ASSERT_NOT_NULL(THPLongTensorClass = PyMapping_GetItemString(module_dict,(char*)"LongTensor"));
ASSERT_NOT_NULL(THPIntTensorClass = PyMapping_GetItemString(module_dict,(char*)"IntTensor"));
ASSERT_NOT_NULL(THPShortTensorClass = PyMapping_GetItemString(module_dict,(char*)"ShortTensor"));
ASSERT_NOT_NULL(THPCharTensorClass = PyMapping_GetItemString(module_dict,(char*)"CharTensor"));
ASSERT_NOT_NULL(THPByteTensorClass = PyMapping_GetItemString(module_dict,(char*)"ByteTensor"));
THPDefaultTensorClass = THPDoubleTensorClass;
return true;
#undef ASSERT_NOT_NULL
}
////////////////////////////////////////////////////////////////////////////////
// Copy handlers
////////////////////////////////////////////////////////////////////////////////
#include "ModuleCopy.h"
std::unordered_map<std::pair<PyObject *, PyObject *>, THPCopyFunction, pair_hasher> tensor_copy_handlers;
std::unordered_map<std::pair<PyObject *, PyObject *>, THPCopyFunction, pair_hasher> storage_copy_handlers;
#define COPY_METHODS(name) TH_CONCAT_2(name,_copy_handlers)
#define IMPLEMENT_COPY_WITH_WRAPPER(name) \
bool TH_CONCAT_3(THPModule_,name,Copy)(PyObject *dst, PyObject *src) \
{ \
/* TODO: this won't work for subclasses, but is that a problem? */ \
auto it = COPY_METHODS(name).find(std::make_pair((PyObject*)Py_TYPE(dst), (PyObject*)Py_TYPE(src))); \
if (it == COPY_METHODS(name).end()) { \
THPUtils_setError("Copy function from %s to %s isn't implemented!", Py_TYPE(src)->tp_name, Py_TYPE(dst)->tp_name); \
return false; \
} \
(it->second)(dst, src); \
return true; \
} \
\
static PyObject * TH_CONCAT_3(THPModule_,name,CopyWrapper)(PyObject *unused, PyObject *args)\
{ \
HANDLE_TH_ERRORS \
/* TODO: check args */ \
PyObject *dst = PyTuple_GET_ITEM(args, 0); \
PyObject *src = PyTuple_GET_ITEM(args, 1); \
if (!TH_CONCAT_3(THPModule_,name,Copy)(dst, src)) { \
return NULL; \
} \
/* TODO: return dst? */ \
Py_RETURN_NONE; \
END_HANDLE_TH_ERRORS \
}
IMPLEMENT_COPY_WITH_WRAPPER(tensor)
IMPLEMENT_COPY_WITH_WRAPPER(storage)
#undef COPY_METHODS
#undef IMPLEMENT_COPY_WITH_WRAPPER
#include "ModuleCopy.cpp"
////////////////////////////////////////////////////////////////////////////////
////////////////////////////////////////////////////////////////////////////////
static bool THPModule_assignStateless(PyObject *self)
{
#define INIT_STATELESS(type) \
stateless = PyObject_Call((PyObject*)&TH_CONCAT_2(type, TensorStatelessType), arg, NULL); \
if (!stateless) { \
THPUtils_setError("stateless method initialization error"); \
return false; \
} \
if (PyObject_SetAttrString(TH_CONCAT_3(THP,type,TensorClass), STATELESS_ATTRIBUTE_NAME, stateless) == -1) { \
THPUtils_setError("stateless method initialization error (on assignment)");\
}
PyObject *arg = PyTuple_New(0);
PyObject *stateless;
INIT_STATELESS(Double);
INIT_STATELESS(Float);
INIT_STATELESS(Long);
INIT_STATELESS(Int);
INIT_STATELESS(Short);
INIT_STATELESS(Char);
INIT_STATELESS(Byte);
Py_DECREF(arg);
return true;
#undef INIT_STATELESS
}
// Callback for python part. Used for additional initialization of python classes
static PyObject * THPModule_initExtension(PyObject *self)
{
if (!THPModule_loadClasses(self)) return NULL;
if (!THPModule_assignStateless(self)) return NULL;
if (!THPModule_initCopy(self)) return NULL;
return PyBool_FromLong(true);
}
static PyObject * THPModule_getNumThreads(PyObject *module)
{
#ifdef _OPENMP
return PyLong_FromLong(omp_get_max_threads());
#else
return PyLong_FromLong(1);
#endif
}
static PyObject * THPModule_setNumThreads(PyObject *module, PyObject *arg)
{
if (!THPUtils_checkLong(arg))
return NULL;
// TODO: maybe throw an error to let people know it's a noop? or a warning?
#ifdef _OPENMP
omp_set_num_threads(THPUtils_getLong(arg));
#endif
return 0;
}
static PyObject * THPModule_getRNGState(PyObject *module, PyObject *args)
{
THGenerator *generator = THPDefaultGenerator->cdata;
if (args && PyTuple_Size(args) == 1 && THPGenerator_Check(PyTuple_GET_ITEM(args, 0))) {
generator = ((THPGenerator*)PyTuple_GET_ITEM(args, 0))->cdata;
} else if (args && PyTuple_Size(args) > 0) {
// TODO: better error message
THPUtils_setError("invalid arguments");
return NULL;
}
THByteTensorPtr _t = THByteTensor_new();
THByteTensor_getRNGState(generator, _t.get());
PyObject *_ret = THPByteTensor_newObject(_t);
_t.release();
return _ret;
}
static PyObject * THPModule_setRNGState(PyObject *module, PyObject *args)
{
THGenerator *generator = THPDefaultGenerator->cdata;
THByteTensor *new_state = NULL;
bool args_ok = false;
if (args && PyTuple_Size(args) > 0) {
PyObject *first_arg = PyTuple_GET_ITEM(args, 0);
if (THPGenerator_Check(first_arg)) {
PyObject *second_arg = PyTuple_GET_ITEM(args, 1);
if (THPByteTensor_IsSubclass(second_arg)) {
new_state = ((THPByteTensor*)second_arg)->cdata;
args_ok = PyTuple_Size(args) == 2;
}
} else if (THPByteTensor_IsSubclass(first_arg)) {
new_state = ((THPByteTensor*)first_arg)->cdata;
args_ok = PyTuple_Size(args) == 1;
}
}
if (!args_ok) {
THPUtils_setError("invalid arguments");
return NULL;
}
THByteTensor_setRNGState(generator, new_state);
Py_RETURN_NONE;
}
static PyObject * THPModule_manualSeed(PyObject *module, PyObject *args)
{
THGenerator *generator = THPDefaultGenerator->cdata;
long new_seed;
bool args_ok = false;
if (args && PyTuple_Size(args) > 0) {
PyObject *first_arg = PyTuple_GET_ITEM(args, 0);
if (THPGenerator_Check(first_arg)) {
PyObject *second_arg = PyTuple_GET_ITEM(args, 1);
if (THPUtils_checkLong(second_arg)) {
THPUtils_getLong(second_arg, &new_seed);
args_ok = PyTuple_Size(args) == 2;
}
} else if (THPUtils_checkLong(first_arg)) {
THPUtils_getLong(first_arg, &new_seed);
args_ok = PyTuple_Size(args) == 1;
}
}
if (!args_ok) {
// TODO: better error message
THPUtils_setError("invalid arguments");
return NULL;
}
THRandom_manualSeed(generator, new_seed);
Py_RETURN_NONE;
}
bool THPModule_isTensor(PyObject *obj)
{
int result = PySet_Contains(tensor_classes, (PyObject*)Py_TYPE(obj));
if (result == -1)
throw std::logic_error("FATAL: tensor_classes isn't a set!");
return result;
}
#define IMPLEMENT_STATELESS(name) \
static PyObject * TH_CONCAT_2(THPModule_, name)(PyObject *_unused, PyObject *args) \
{ \
PyObject *tensor = THPDefaultTensorClass; \
for (int i = 0; i < PyTuple_Size(args); i++) { \
PyObject *item = PyTuple_GET_ITEM(args, i); \
if (THPModule_isTensor(item)) { \
tensor = item; \
break; \
} \
} \
\
PyObject *methods = PyObject_GetAttrString(tensor, STATELESS_ATTRIBUTE_NAME); \
THPUtils_assert(methods, "Type %s doesn't implement statless methods", \
Py_TYPE(tensor)->tp_name); \
PyObject *method = PyObject_GetAttrString(methods, #name); \
THPUtils_assert(method, "Type %s doesn't implement stateless method " #name, \
Py_TYPE(tensor)->tp_name); \
return PyObject_Call(method, args, NULL); \
}
IMPLEMENT_STATELESS(sigmoid)
IMPLEMENT_STATELESS(log)
IMPLEMENT_STATELESS(log1p)
IMPLEMENT_STATELESS(exp)
IMPLEMENT_STATELESS(cos)
IMPLEMENT_STATELESS(acos)
IMPLEMENT_STATELESS(cosh)
IMPLEMENT_STATELESS(sin)
IMPLEMENT_STATELESS(asin)
IMPLEMENT_STATELESS(sinh)
IMPLEMENT_STATELESS(tan)
IMPLEMENT_STATELESS(atan)
IMPLEMENT_STATELESS(tanh)
IMPLEMENT_STATELESS(sqrt)
IMPLEMENT_STATELESS(rsqrt)
IMPLEMENT_STATELESS(ceil)
IMPLEMENT_STATELESS(floor)
IMPLEMENT_STATELESS(round)
IMPLEMENT_STATELESS(abs)
IMPLEMENT_STATELESS(trunc)
IMPLEMENT_STATELESS(frac)
IMPLEMENT_STATELESS(mean)
IMPLEMENT_STATELESS(std)
IMPLEMENT_STATELESS(var)
IMPLEMENT_STATELESS(norm)
IMPLEMENT_STATELESS(cinv)
IMPLEMENT_STATELESS(neg)
IMPLEMENT_STATELESS(add)
IMPLEMENT_STATELESS(csub)
IMPLEMENT_STATELESS(mul)
IMPLEMENT_STATELESS(div)
IMPLEMENT_STATELESS(fmod)
IMPLEMENT_STATELESS(cmul)
IMPLEMENT_STATELESS(cdiv)
IMPLEMENT_STATELESS(cfmod)
IMPLEMENT_STATELESS(min)
IMPLEMENT_STATELESS(max)
IMPLEMENT_STATELESS(cmax)
IMPLEMENT_STATELESS(cmin)
IMPLEMENT_STATELESS(cpow)
IMPLEMENT_STATELESS(dot)
IMPLEMENT_STATELESS(sum)
IMPLEMENT_STATELESS(prod)
IMPLEMENT_STATELESS(remainder)
IMPLEMENT_STATELESS(cremainder)
IMPLEMENT_STATELESS(cumsum)
IMPLEMENT_STATELESS(cumprod)
IMPLEMENT_STATELESS(clamp)
IMPLEMENT_STATELESS(equal)
IMPLEMENT_STATELESS(eye)
IMPLEMENT_STATELESS(fill)
IMPLEMENT_STATELESS(diag)
IMPLEMENT_STATELESS(numel)
IMPLEMENT_STATELESS(sign)
IMPLEMENT_STATELESS(trace)
IMPLEMENT_STATELESS(tril)
IMPLEMENT_STATELESS(triu)
IMPLEMENT_STATELESS(zero)
IMPLEMENT_STATELESS(kthvalue)
IMPLEMENT_STATELESS(mode)
IMPLEMENT_STATELESS(median)
IMPLEMENT_STATELESS(cross)
IMPLEMENT_STATELESS(sort)
IMPLEMENT_STATELESS(topk)
IMPLEMENT_STATELESS(t)
IMPLEMENT_STATELESS(transpose)
IMPLEMENT_STATELESS(squeeze)
IMPLEMENT_STATELESS(renorm)
IMPLEMENT_STATELESS(dist)
IMPLEMENT_STATELESS(linspace)
IMPLEMENT_STATELESS(logspace)
IMPLEMENT_STATELESS(histc)
IMPLEMENT_STATELESS(atan2)
IMPLEMENT_STATELESS(pow)
IMPLEMENT_STATELESS(lerp)
IMPLEMENT_STATELESS(reshape)
IMPLEMENT_STATELESS(zeros)
IMPLEMENT_STATELESS(ones)
IMPLEMENT_STATELESS(indexSelect)
IMPLEMENT_STATELESS(indexCopy)
IMPLEMENT_STATELESS(indexAdd)
IMPLEMENT_STATELESS(indexFill)
IMPLEMENT_STATELESS(narrow)
IMPLEMENT_STATELESS(addmm)
IMPLEMENT_STATELESS(addmv)
IMPLEMENT_STATELESS(addr)
IMPLEMENT_STATELESS(ger)
IMPLEMENT_STATELESS(mv)
IMPLEMENT_STATELESS(addbmm)
IMPLEMENT_STATELESS(baddbmm)
IMPLEMENT_STATELESS(addcmul)
IMPLEMENT_STATELESS(addcdiv)
IMPLEMENT_STATELESS(mm)
IMPLEMENT_STATELESS(bmm)
// TODO: this doesn't implement options that return numbers!
IMPLEMENT_STATELESS(multinomial)
IMPLEMENT_STATELESS(uniform)
IMPLEMENT_STATELESS(normal)
IMPLEMENT_STATELESS(cauchy)
IMPLEMENT_STATELESS(logNormal)
IMPLEMENT_STATELESS(exponential)
IMPLEMENT_STATELESS(random)
IMPLEMENT_STATELESS(geometric)
IMPLEMENT_STATELESS(bernoulli)
IMPLEMENT_STATELESS(randperm)
IMPLEMENT_STATELESS(unfold)
IMPLEMENT_STATELESS(range)
IMPLEMENT_STATELESS(gather)
IMPLEMENT_STATELESS(scatter)
IMPLEMENT_STATELESS(rand)
IMPLEMENT_STATELESS(randn)
IMPLEMENT_STATELESS(all)
IMPLEMENT_STATELESS(any)
IMPLEMENT_STATELESS(maskedSelect)
#undef IMPLEMENT_STATELESS
// For logical functions a reverse type search is required (if the first argument
// is a ByteTensor (result), it shouldn't pick it's version).
#define IMPLEMENT_STATELESS_REVERSED(name) \
static PyObject * TH_CONCAT_2(THPModule_, name)(PyObject *_unused, PyObject *args) \
{ \
PyObject *tensor = THPDefaultTensorClass; \
for (int i = PyTuple_Size(args)-1; i >= 0; i--) { \
PyObject *item = PyTuple_GET_ITEM(args, i); \
if (THPModule_isTensor(item)) { \
tensor = item; \
break; \
} \
} \
\
PyObject *methods = PyObject_GetAttrString(tensor, STATELESS_ATTRIBUTE_NAME); \
THPUtils_assert(methods, "Type %s doesn't implement statless methods", \
Py_TYPE(tensor)->tp_name); \
PyObject *method = PyObject_GetAttrString(methods, #name); \
THPUtils_assert(method, "Type %s doesn't implement stateless method " #name, \
Py_TYPE(tensor)->tp_name); \
return PyObject_Call(method, args, NULL); \
}
IMPLEMENT_STATELESS_REVERSED(gt)
IMPLEMENT_STATELESS_REVERSED(lt)
IMPLEMENT_STATELESS_REVERSED(ge)
IMPLEMENT_STATELESS_REVERSED(le)
IMPLEMENT_STATELESS_REVERSED(eq)
IMPLEMENT_STATELESS_REVERSED(ne)
#undef IMPLEMENT_STATELESS
// In nonzero, the first argument might be a LongTensor that will be used
// for indices output, so we should pick a function based on second
// tensor's type.
static PyObject * THPModule_nonzero(PyObject *_unused, PyObject *args)
{
PyObject *tensor = THPDefaultTensorClass;
if (PyTuple_Size(args) == 1)
tensor = PyTuple_GET_ITEM(args, 0);
else if (PyTuple_Size(args) == 2)
tensor = PyTuple_GET_ITEM(args, 1);
PyObject *methods = PyObject_GetAttrString(tensor, STATELESS_ATTRIBUTE_NAME);
THPUtils_assert(methods, "Type %s doesn't implement statless methods",
Py_TYPE(tensor)->tp_name);
PyObject *method = PyObject_GetAttrString(methods, "nonzero");
THPUtils_assert(method, "Type %s doesn't implement stateless method nonzero",
Py_TYPE(tensor)->tp_name);
return PyObject_Call(method, args, NULL);
}
// In nonzero, the first argument might be a LongTensor that will be used
// for indices output, so we should pick a function based on second
// tensor's type.
static PyObject * THPModule_cat(PyObject *_unused, PyObject *args)
{
PyObject *tensor = THPDefaultTensorClass;
THPObjectPtr iterator;
THPObjectPtr item;
if (args && PyTuple_Size(args) > 0) {
if (THPModule_isTensor(PyTuple_GET_ITEM(args, 0))) {
tensor = PyTuple_GET_ITEM(args, 0);
} else if ((iterator = PyObject_GetIter(PyTuple_GET_ITEM(args, 0)))) {
item = PyIter_Next(iterator);
if (item && THPModule_isTensor(item)) {
tensor = item;
}
}
PyErr_Clear();
}
PyObject *methods = PyObject_GetAttrString(tensor, STATELESS_ATTRIBUTE_NAME);
THPUtils_assert(methods, "Type %s doesn't implement statless methods",
Py_TYPE(tensor)->tp_name);
PyObject *method = PyObject_GetAttrString(methods, "cat");
THPUtils_assert(method, "Type %s doesn't implement stateless method nonzero",
Py_TYPE(tensor)->tp_name);
return PyObject_Call(method, args, NULL);
}
#ifdef WITH_CUDA
extern PyObject * THCPModule_initExtension(PyObject *self);
extern PyObject * THCPModule_setDevice_wrap(PyObject *self, PyObject *arg);
extern PyObject * THCPModule_getDevice_wrap(PyObject *self);
extern PyObject * THCPModule_getDeviceCount_wrap(PyObject *self);
#endif
static PyMethodDef TorchMethods[] = {
{"_initExtension", (PyCFunction)THPModule_initExtension, METH_NOARGS, NULL},
#ifdef WITH_CUDA
{"_cuda_init", (PyCFunction)THCPModule_initExtension, METH_NOARGS, NULL},
{"_cuda_setDevice", (PyCFunction)THCPModule_setDevice_wrap, METH_O, NULL},
{"_cuda_getDevice", (PyCFunction)THCPModule_getDevice_wrap, METH_NOARGS, NULL},
{"_cuda_getDeviceCount", (PyCFunction)THCPModule_getDeviceCount_wrap, METH_NOARGS, NULL},
#endif
{"_tensorCopy", (PyCFunction)THPModule_tensorCopyWrapper, METH_VARARGS, NULL},
{"_storageCopy", (PyCFunction)THPModule_storageCopyWrapper, METH_VARARGS, NULL},
{"getNumThreads", (PyCFunction)THPModule_getNumThreads, METH_NOARGS, NULL},
{"setNumThreads", (PyCFunction)THPModule_setNumThreads, METH_O, NULL},
{"getRNGState", (PyCFunction)THPModule_getRNGState, METH_VARARGS, NULL},
{"setRNGState", (PyCFunction)THPModule_setRNGState, METH_VARARGS, NULL},
{"manualSeed", (PyCFunction)THPModule_manualSeed, METH_VARARGS, NULL},
{"sigmoid", (PyCFunction)THPModule_sigmoid, METH_VARARGS, NULL},
{"log", (PyCFunction)THPModule_log, METH_VARARGS, NULL},
{"log1p", (PyCFunction)THPModule_log1p, METH_VARARGS, NULL},
{"exp", (PyCFunction)THPModule_exp, METH_VARARGS, NULL},
{"cos", (PyCFunction)THPModule_cos, METH_VARARGS, NULL},
{"acos", (PyCFunction)THPModule_acos, METH_VARARGS, NULL},
{"cosh", (PyCFunction)THPModule_cosh, METH_VARARGS, NULL},
{"sin", (PyCFunction)THPModule_sin, METH_VARARGS, NULL},
{"asin", (PyCFunction)THPModule_asin, METH_VARARGS, NULL},
{"sinh", (PyCFunction)THPModule_sinh, METH_VARARGS, NULL},
{"tan", (PyCFunction)THPModule_tan, METH_VARARGS, NULL},
{"atan", (PyCFunction)THPModule_atan, METH_VARARGS, NULL},
{"tanh", (PyCFunction)THPModule_tanh, METH_VARARGS, NULL},
{"sqrt", (PyCFunction)THPModule_sqrt, METH_VARARGS, NULL},
{"rsqrt", (PyCFunction)THPModule_rsqrt, METH_VARARGS, NULL},
{"ceil", (PyCFunction)THPModule_ceil, METH_VARARGS, NULL},
{"floor", (PyCFunction)THPModule_floor, METH_VARARGS, NULL},
{"round", (PyCFunction)THPModule_round, METH_VARARGS, NULL},
{"abs", (PyCFunction)THPModule_abs, METH_VARARGS, NULL},
{"trunc", (PyCFunction)THPModule_trunc, METH_VARARGS, NULL},
{"frac", (PyCFunction)THPModule_frac, METH_VARARGS, NULL},
{"mean", (PyCFunction)THPModule_mean, METH_VARARGS, NULL},
{"std", (PyCFunction)THPModule_std, METH_VARARGS, NULL},
{"var", (PyCFunction)THPModule_var, METH_VARARGS, NULL},
{"norm", (PyCFunction)THPModule_norm, METH_VARARGS, NULL},
{"cinv", (PyCFunction)THPModule_cinv, METH_VARARGS, NULL},
{"neg", (PyCFunction)THPModule_neg, METH_VARARGS, NULL},
{"add", (PyCFunction)THPModule_add, METH_VARARGS, NULL},
{"csub", (PyCFunction)THPModule_csub, METH_VARARGS, NULL},
{"mul", (PyCFunction)THPModule_mul, METH_VARARGS, NULL},
{"div", (PyCFunction)THPModule_div, METH_VARARGS, NULL},
{"fmod", (PyCFunction)THPModule_fmod, METH_VARARGS, NULL},
{"mod", (PyCFunction)THPModule_fmod, METH_VARARGS, NULL},
{"cmul", (PyCFunction)THPModule_cmul, METH_VARARGS, NULL},
{"cdiv", (PyCFunction)THPModule_cdiv, METH_VARARGS, NULL},
{"cfmod", (PyCFunction)THPModule_cfmod, METH_VARARGS, NULL},
{"cmod", (PyCFunction)THPModule_cfmod, METH_VARARGS, NULL},
{"min", (PyCFunction)THPModule_min, METH_VARARGS, NULL},
{"max", (PyCFunction)THPModule_max, METH_VARARGS, NULL},
{"cmax", (PyCFunction)THPModule_cmax, METH_VARARGS, NULL},
{"cmin", (PyCFunction)THPModule_cmin, METH_VARARGS, NULL},
{"cpow", (PyCFunction)THPModule_cpow, METH_VARARGS, NULL},
{"dot", (PyCFunction)THPModule_dot, METH_VARARGS, NULL},
{"sum", (PyCFunction)THPModule_sum, METH_VARARGS, NULL},
{"prod", (PyCFunction)THPModule_prod, METH_VARARGS, NULL},
{"remainder", (PyCFunction)THPModule_remainder, METH_VARARGS, NULL},
{"cremainder", (PyCFunction)THPModule_cremainder, METH_VARARGS, NULL},
{"cumsum", (PyCFunction)THPModule_cumsum, METH_VARARGS, NULL},
{"cumprod", (PyCFunction)THPModule_cumprod, METH_VARARGS, NULL},
{"clamp", (PyCFunction)THPModule_clamp, METH_VARARGS, NULL},
{"equal", (PyCFunction)THPModule_equal, METH_VARARGS, NULL},
{"eye", (PyCFunction)THPModule_eye, METH_VARARGS, NULL},
{"fill", (PyCFunction)THPModule_fill, METH_VARARGS, NULL},
{"diag", (PyCFunction)THPModule_diag, METH_VARARGS, NULL},
{"numel", (PyCFunction)THPModule_numel, METH_VARARGS, NULL},
{"sign", (PyCFunction)THPModule_sign, METH_VARARGS, NULL},
{"trace", (PyCFunction)THPModule_trace, METH_VARARGS, NULL},
{"tril", (PyCFunction)THPModule_tril, METH_VARARGS, NULL},
{"triu", (PyCFunction)THPModule_triu, METH_VARARGS, NULL},
{"zero", (PyCFunction)THPModule_zero, METH_VARARGS, NULL},
{"gt", (PyCFunction)THPModule_gt, METH_VARARGS, NULL},
{"lt", (PyCFunction)THPModule_lt, METH_VARARGS, NULL},
{"ge", (PyCFunction)THPModule_ge, METH_VARARGS, NULL},
{"le", (PyCFunction)THPModule_le, METH_VARARGS, NULL},
{"eq", (PyCFunction)THPModule_eq, METH_VARARGS, NULL},
{"ne", (PyCFunction)THPModule_ne, METH_VARARGS, NULL},
{"kthvalue", (PyCFunction)THPModule_kthvalue, METH_VARARGS, NULL},
{"mode", (PyCFunction)THPModule_mode, METH_VARARGS, NULL},
{"median", (PyCFunction)THPModule_median, METH_VARARGS, NULL},
{"cross", (PyCFunction)THPModule_cross, METH_VARARGS, NULL},
{"sort", (PyCFunction)THPModule_sort, METH_VARARGS, NULL},
{"topk", (PyCFunction)THPModule_topk, METH_VARARGS, NULL},
{"t", (PyCFunction)THPModule_t, METH_VARARGS, NULL},
{"transpose", (PyCFunction)THPModule_transpose, METH_VARARGS, NULL},
{"squeeze", (PyCFunction)THPModule_squeeze, METH_VARARGS, NULL},
{"nonzero", (PyCFunction)THPModule_nonzero, METH_VARARGS, NULL},
{"renorm", (PyCFunction)THPModule_renorm, METH_VARARGS, NULL},
{"dist", (PyCFunction)THPModule_dist, METH_VARARGS, NULL},
{"linspace", (PyCFunction)THPModule_linspace, METH_VARARGS, NULL},
{"logspace", (PyCFunction)THPModule_logspace, METH_VARARGS, NULL},
{"histc", (PyCFunction)THPModule_histc, METH_VARARGS, NULL},
{"atan2", (PyCFunction)THPModule_atan2, METH_VARARGS, NULL},
{"pow", (PyCFunction)THPModule_pow, METH_VARARGS, NULL},
{"lerp", (PyCFunction)THPModule_lerp, METH_VARARGS, NULL},
{"reshape", (PyCFunction)THPModule_reshape, METH_VARARGS, NULL},
{"zeros", (PyCFunction)THPModule_zeros, METH_VARARGS, NULL},
{"ones", (PyCFunction)THPModule_ones, METH_VARARGS, NULL},
{"indexSelect", (PyCFunction)THPModule_indexSelect, METH_VARARGS, NULL},
{"indexCopy", (PyCFunction)THPModule_indexCopy, METH_VARARGS, NULL},
{"indexAdd", (PyCFunction)THPModule_indexAdd, METH_VARARGS, NULL},
{"indexFill", (PyCFunction)THPModule_indexFill, METH_VARARGS, NULL},
{"narrow", (PyCFunction)THPModule_narrow, METH_VARARGS, NULL},
{"addmm", (PyCFunction)THPModule_addmm, METH_VARARGS, NULL},
{"addmv", (PyCFunction)THPModule_addmv, METH_VARARGS, NULL},
{"addr", (PyCFunction)THPModule_addr, METH_VARARGS, NULL},
{"ger", (PyCFunction)THPModule_ger, METH_VARARGS, NULL},
{"mv", (PyCFunction)THPModule_mv, METH_VARARGS, NULL},
{"addbmm", (PyCFunction)THPModule_addbmm, METH_VARARGS, NULL},
{"baddbmm", (PyCFunction)THPModule_baddbmm, METH_VARARGS, NULL},
{"addcmul", (PyCFunction)THPModule_addcmul, METH_VARARGS, NULL},
{"addcdiv", (PyCFunction)THPModule_addcdiv, METH_VARARGS, NULL},
{"mm", (PyCFunction)THPModule_mm, METH_VARARGS, NULL},
{"bmm", (PyCFunction)THPModule_bmm, METH_VARARGS, NULL},
{"multinomial", (PyCFunction)THPModule_multinomial, METH_VARARGS, NULL},
{"uniform", (PyCFunction)THPModule_uniform, METH_VARARGS, NULL},
{"normal", (PyCFunction)THPModule_normal, METH_VARARGS, NULL},
{"cauchy", (PyCFunction)THPModule_cauchy, METH_VARARGS, NULL},
{"logNormal", (PyCFunction)THPModule_logNormal, METH_VARARGS, NULL},
{"exponential", (PyCFunction)THPModule_exponential, METH_VARARGS, NULL},
{"random", (PyCFunction)THPModule_random, METH_VARARGS, NULL},
{"geometric", (PyCFunction)THPModule_geometric, METH_VARARGS, NULL},
{"bernoulli", (PyCFunction)THPModule_bernoulli, METH_VARARGS, NULL},
{"rand", (PyCFunction)THPModule_rand, METH_VARARGS, NULL},
{"randn", (PyCFunction)THPModule_randn, METH_VARARGS, NULL},
{"randperm", (PyCFunction)THPModule_randperm, METH_VARARGS, NULL},
{"unfold", (PyCFunction)THPModule_unfold, METH_VARARGS, NULL},
{"range", (PyCFunction)THPModule_range, METH_VARARGS, NULL},
{"gather", (PyCFunction)THPModule_gather, METH_VARARGS, NULL},
{"scatter", (PyCFunction)THPModule_scatter, METH_VARARGS, NULL},
{"all", (PyCFunction)THPModule_all, METH_VARARGS, NULL},
{"any", (PyCFunction)THPModule_any, METH_VARARGS, NULL},
{"cat", (PyCFunction)THPModule_cat, METH_VARARGS, NULL},
{"maskedSelect", (PyCFunction)THPModule_maskedSelect, METH_VARARGS, NULL},
{NULL, NULL, 0, NULL}
};
#if PY_MAJOR_VERSION != 2
static struct PyModuleDef torchmodule = {
PyModuleDef_HEAD_INIT,
"torch._C",
NULL,
-1,
TorchMethods
};
#endif
static void errorHandler(const char *msg, void *data)
{
throw THException(msg);
}
static void errorHandlerArg(int argNumber, const char *msg, void *data)
{
throw THArgException(msg, argNumber);
}
static void updateErrorHandlers()
{
THSetErrorHandler(errorHandler, NULL);
THSetArgErrorHandler(errorHandlerArg, NULL);
}
bool THCPDoubleStorage_init(PyObject *module);
bool THCPFloatStorage_init(PyObject *module);
bool THCPHalfStorage_init(PyObject *module);
bool THCPLongStorage_init(PyObject *module);
bool THCPIntStorage_init(PyObject *module);
bool THCPShortStorage_init(PyObject *module);
bool THCPCharStorage_init(PyObject *module);
bool THCPByteStorage_init(PyObject *module);
bool THCPDoubleTensor_init(PyObject *module);
bool THCPFloatTensor_init(PyObject *module);
bool THCPHalfTensor_init(PyObject *module);
bool THCPLongTensor_init(PyObject *module);
bool THCPIntTensor_init(PyObject *module);
bool THCPShortTensor_init(PyObject *module);
bool THCPCharTensor_init(PyObject *module);
bool THCPByteTensor_init(PyObject *module);
#if PY_MAJOR_VERSION == 2
PyMODINIT_FUNC init_C()
#else
PyMODINIT_FUNC PyInit__C()
#endif
{
#if PY_MAJOR_VERSION == 2
#define ASSERT_TRUE(cmd) if (!(cmd)) {PyErr_SetString(PyExc_ImportError, "initialization error"); return;}
#else
#define ASSERT_TRUE(cmd) if (!(cmd)) return NULL
#endif
#if PY_MAJOR_VERSION == 2
ASSERT_TRUE(module = Py_InitModule("torch._C", TorchMethods));
#else
ASSERT_TRUE(module = PyModule_Create(&torchmodule));
#endif
ASSERT_TRUE(THPGenerator_init(module));
ASSERT_TRUE(THPDoubleStorage_init(module));
ASSERT_TRUE(THPFloatStorage_init(module));
ASSERT_TRUE(THPLongStorage_init(module));
ASSERT_TRUE(THPIntStorage_init(module));
ASSERT_TRUE(THPShortStorage_init(module));
ASSERT_TRUE(THPCharStorage_init(module));
ASSERT_TRUE(THPByteStorage_init(module));
ASSERT_TRUE(THPDoubleTensor_init(module));
ASSERT_TRUE(THPFloatTensor_init(module));
ASSERT_TRUE(THPLongTensor_init(module));
ASSERT_TRUE(THPIntTensor_init(module));
ASSERT_TRUE(THPShortTensor_init(module));
ASSERT_TRUE(THPCharTensor_init(module));
ASSERT_TRUE(THPByteTensor_init(module));
#ifdef WITH_CUDA
// This will only initialise base classes and attach them to library namespace
// They won't be ready for real usage until importing cuda module, that will
// complete the process (but it defines Python classes before calling back into
// C, so these lines have to execute first)..
ASSERT_TRUE(THCPDoubleStorage_init(module));
ASSERT_TRUE(THCPFloatStorage_init(module));
ASSERT_TRUE(THCPHalfStorage_init(module));
ASSERT_TRUE(THCPLongStorage_init(module));
ASSERT_TRUE(THCPIntStorage_init(module));
ASSERT_TRUE(THCPShortStorage_init(module));
ASSERT_TRUE(THCPCharStorage_init(module));
ASSERT_TRUE(THCPByteStorage_init(module));
ASSERT_TRUE(THCPHalfStorage_init(module));
ASSERT_TRUE(THCPDoubleTensor_init(module));
ASSERT_TRUE(THCPFloatTensor_init(module));
ASSERT_TRUE(THCPHalfTensor_init(module));
ASSERT_TRUE(THCPLongTensor_init(module));
ASSERT_TRUE(THCPIntTensor_init(module));
ASSERT_TRUE(THCPShortTensor_init(module));
ASSERT_TRUE(THCPCharTensor_init(module));
ASSERT_TRUE(THCPByteTensor_init(module));
#endif
THPDefaultGenerator = (THPGenerator*)THPGenerator_newObject();
ASSERT_TRUE(THPDefaultGenerator != nullptr);
updateErrorHandlers();
#if PY_MAJOR_VERSION == 2
#else
return module;
#endif
#undef ASSERT_TRUE
}