blob: 519808937bf7ee276351363eba5f88222c076065 [file] [log] [blame]
#include <Python.h>
#include <stdbool.h>
#include <unordered_map>
#include <TH/TH.h>
#include <THC/THCCachingAllocator.h>
#ifdef WITH_NCCL
#include <nccl.h>
#endif
#include "THCP.h"
#include "ModuleSparse.cpp"
THCState *state;
////////////////////////////////////////////////////////////////////////////////
// Class pointer cache
////////////////////////////////////////////////////////////////////////////////
static bool THCPModule_loadClasses(PyObject *torch_module)
{
#define ASSERT_NOT_NULL(ptr) if (!(ptr)) { THPUtils_setError("couldn't load classes"); return false; }
ASSERT_NOT_NULL(THCPDoubleStorageClass = PyObject_GetAttrString(torch_module, (char*)"DoubleStorage"));
ASSERT_NOT_NULL(THCPFloatStorageClass = PyObject_GetAttrString(torch_module, (char*)"FloatStorage"));
ASSERT_NOT_NULL(THCPHalfStorageClass = PyObject_GetAttrString(torch_module, (char*)"HalfStorage"));
ASSERT_NOT_NULL(THCPLongStorageClass = PyObject_GetAttrString(torch_module, (char*)"LongStorage"));
ASSERT_NOT_NULL(THCPIntStorageClass = PyObject_GetAttrString(torch_module, (char*)"IntStorage"));
ASSERT_NOT_NULL(THCPShortStorageClass = PyObject_GetAttrString(torch_module, (char*)"ShortStorage"));
ASSERT_NOT_NULL(THCPCharStorageClass = PyObject_GetAttrString(torch_module, (char*)"CharStorage"));
ASSERT_NOT_NULL(THCPByteStorageClass = PyObject_GetAttrString(torch_module, (char*)"ByteStorage"));
if (!THCPDoubleTensor_postInit(torch_module)) return false;
if (!THCPFloatTensor_postInit(torch_module)) return false;
if (!THCPHalfTensor_postInit(torch_module)) return false;
if (!THCPLongTensor_postInit(torch_module)) return false;
if (!THCPIntTensor_postInit(torch_module)) return false;
if (!THCPShortTensor_postInit(torch_module)) return false;
if (!THCPCharTensor_postInit(torch_module)) return false;
if (!THCPByteTensor_postInit(torch_module)) return false;
return true;
#undef ASSERT_NOT_NULL
}
////////////////////////////////////////////////////////////////////////////////
// Tensor stateless methods
////////////////////////////////////////////////////////////////////////////////
static bool THCPModule_assignStateless()
{
#define INIT_STATELESS(type) INIT_STATELESS_DETAIL(type, TH_CONCAT_2(Cuda, type))
#define INIT_STATELESS_DETAIL(type,ctype) \
stateless = PyObject_Call((PyObject*)&TH_CONCAT_2(ctype, TensorStatelessType), arg, NULL); \
if (!stateless) { \
THPUtils_setError("stateless method initialization error"); \
return false; \
} \
if (PyObject_SetAttrString(TH_CONCAT_3(THCP,type,TensorClass), THP_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_DETAIL(Float, Cuda);
INIT_STATELESS(Half);
INIT_STATELESS(Long);
INIT_STATELESS(Int);
INIT_STATELESS(Short);
INIT_STATELESS(Char);
INIT_STATELESS(Byte);
Py_DECREF(arg);
return true;
#undef INIT_STATELESS_DETAIL
#undef INIT_STATELESS
}
////////////////////////////////////////////////////////////////////////////////
// CUDA management methods
////////////////////////////////////////////////////////////////////////////////
void THCPModule_setDevice(int device)
{
THCudaCheck(cudaSetDevice(device));
}
PyObject * THCPModule_setDevice_wrap(PyObject *self, PyObject *arg)
{
HANDLE_TH_ERRORS
THPUtils_assert(THPUtils_checkLong(arg), "invalid argument to setDevice");
long device = THPUtils_unpackLong(arg);
THCPModule_setDevice(device);
Py_RETURN_NONE;
END_HANDLE_TH_ERRORS
}
PyObject * THCPModule_getDevice_wrap(PyObject *self)
{
HANDLE_TH_ERRORS
int device;
THCudaCheck(cudaGetDevice(&device));
return PyLong_FromLong(device);
END_HANDLE_TH_ERRORS
}
PyObject * THCPModule_getDeviceCount_wrap(PyObject *self)
{
HANDLE_TH_ERRORS
int ndevice;
THCudaCheck(cudaGetDeviceCount(&ndevice));
return PyLong_FromLong(ndevice);
END_HANDLE_TH_ERRORS
}
PyObject * THCPModule_getCurrentStream_wrap(PyObject *self)
{
HANDLE_TH_ERRORS
THCStream* stream = THCState_getStream(state);
return PyLong_FromVoidPtr(stream);
END_HANDLE_TH_ERRORS
}
PyObject * THCPModule_setStream_wrap(PyObject *self, PyObject *obj)
{
HANDLE_TH_ERRORS
THPUtils_assert(PyLong_Check(obj), "invalid stream");
THCStream* stream = (THCStream *)PyLong_AsVoidPtr(obj);
THCState_setStream(state, stream);
Py_RETURN_NONE;
END_HANDLE_TH_ERRORS
}
PyObject * THCPModule_isDriverSufficient(PyObject *self)
{
int count;
cudaError_t err = cudaGetDeviceCount(&count);
if (err == cudaErrorInsufficientDriver) {
return PyBool_FromLong(0);
}
return PyBool_FromLong(1);
}
PyObject * THCPModule_getDriverVersion(PyObject *self)
{
int driverVersion = -1;
cudaError_t err = cudaDriverGetVersion(&driverVersion);
if (err != cudaSuccess) {
PyErr_Format(PyExc_RuntimeError,
"Error calling cudaDriverGetVersion: %d %s",
err, cudaGetErrorString(err));
return NULL;
}
return PyLong_FromLong((long) driverVersion);
}
PyObject * THCPModule_getRNGState(PyObject *_unused)
{
HANDLE_TH_ERRORS
THPByteTensorPtr res = (THPByteTensor *)THPByteTensor_NewEmpty();
if (!res) return NULL;
THCRandom_getRNGState(state, res->cdata);
return (PyObject *)res.release();
END_HANDLE_TH_ERRORS
}
PyObject * THCPModule_setRNGState(PyObject *_unused, PyObject *_new_rng_state)
{
HANDLE_TH_ERRORS
THPUtils_assert(THPByteTensor_Check(_new_rng_state), "set_rng_state expects a "
"torch.ByteTensor, but got %s", THPUtils_typename(_new_rng_state));
THByteTensor *new_rng_state = ((THPByteTensor*)_new_rng_state)->cdata;
THCRandom_setRNGState(state, new_rng_state);
Py_RETURN_NONE;
END_HANDLE_TH_ERRORS
}
PyObject * THCPModule_manualSeed(PyObject *_unused, PyObject *seed)
{
HANDLE_TH_ERRORS
THPUtils_assert(THPUtils_checkLong(seed), "manual_seed expected a long, "
"but got %s", THPUtils_typename(seed));
THCRandom_manualSeed(state, THPUtils_unpackLong(seed));
Py_RETURN_NONE;
END_HANDLE_TH_ERRORS
}
PyObject * THCPModule_manualSeedAll(PyObject *_unused, PyObject *seed)
{
HANDLE_TH_ERRORS
THPUtils_assert(THPUtils_checkLong(seed), "manual_seed expected a long, "
"but got %s", THPUtils_typename(seed));
THCRandom_manualSeedAll(state, THPUtils_unpackLong(seed));
Py_RETURN_NONE;
END_HANDLE_TH_ERRORS
}
PyObject * THCPModule_seed(PyObject *_unused)
{
HANDLE_TH_ERRORS
return PyLong_FromUnsignedLong(THCRandom_seed(state));
END_HANDLE_TH_ERRORS
}
PyObject * THCPModule_seedAll(PyObject *_unused)
{
HANDLE_TH_ERRORS
return PyLong_FromUnsignedLong(THCRandom_seedAll(state));
END_HANDLE_TH_ERRORS
}
PyObject * THCPModule_initialSeed(PyObject *_unused)
{
HANDLE_TH_ERRORS
return PyLong_FromUnsignedLong(THCRandom_initialSeed(state));
END_HANDLE_TH_ERRORS
}
PyObject * THCPModule_cudaHostAllocator(PyObject *_unused)
{
HANDLE_TH_ERRORS
THAllocator* allocator = THCState_getCudaHostAllocator(state);
return PyLong_FromVoidPtr(allocator);
END_HANDLE_TH_ERRORS
}
PyObject * THCPModule_cudaSynchronize(PyObject *_unused)
{
HANDLE_TH_ERRORS
THCudaCheck(cudaDeviceSynchronize());
Py_RETURN_NONE;
END_HANDLE_TH_ERRORS
}
PyObject * THCPModule_cudaSleep(PyObject *_unused, PyObject *cycles)
{
HANDLE_TH_ERRORS
THPUtils_assert(THPUtils_checkLong(cycles), "torch.cuda._sleep(): expected 'int'");
THC_sleep(LIBRARY_STATE THPUtils_unpackLong(cycles));
Py_RETURN_NONE;
END_HANDLE_TH_ERRORS
}
PyObject * THCPModule_cudaLockMutex(PyObject *module)
{
auto mutex = THCCachingAllocator_getCudaFreeMutex();
mutex->lock();
Py_RETURN_NONE;
}
PyObject * THCPModule_cudaUnlockMutex(PyObject *module)
{
auto mutex = THCCachingAllocator_getCudaFreeMutex();
mutex->unlock();
Py_RETURN_NONE;
}
PyObject * THCPModule_getLibPath(PyObject *_unused)
{
#define _STR(x) #x
#define STR(x) _STR(x)
#if PY_MAJOR_VERSION == 2
return PyString_FromString(STR(CUDA_LIB_PATH));
#else
return PyUnicode_FromString(STR(CUDA_LIB_PATH));
#endif
#undef STR
#undef _STR
}
////////////////////////////////////////////////////////////////////////////////
// Cuda module initialization
////////////////////////////////////////////////////////////////////////////////
bool THCPModule_initCuda(PyObject *torch_module) {
HANDLE_TH_ERRORS
#define ASSERT_TRUE(cond) if (!(cond)) { return false; }
state = THCState_alloc();
THCState_setDeviceAllocator(state, THCCachingAllocator_get());
state->cudaHostAllocator = &THCCachingHostAllocator;
THCudaInit(state);
#ifdef USE_MAGMA
THCMagma_init(state);
ASSERT_TRUE(PyObject_SetAttrString(torch_module, "has_magma", PyBool_FromLong(true)) != -1);
#else
ASSERT_TRUE(PyObject_SetAttrString(torch_module, "has_magma", PyBool_FromLong(false)) != -1);
#endif
#ifdef CUDA_HALF_TENSOR
ASSERT_TRUE(PyObject_SetAttrString(torch_module, "has_half", PyBool_FromLong(true)) != -1);
#else
ASSERT_TRUE(PyObject_SetAttrString(torch_module, "has_half", PyBool_FromLong(false)) != -1);
#endif
ASSERT_TRUE(THCPModule_loadClasses(torch_module));
ASSERT_TRUE(THCPModule_assignStateless());
ASSERT_TRUE(PyObject_SetAttrString(torch_module, "_state_cdata", PyLong_FromVoidPtr(state)) != -1);
// TODO: register THCudaShutdown handler at exit
return true;
#undef ASSERT_TRUE
END_HANDLE_TH_ERRORS
}
// Callback for python part. Used for additional initialization of python classes
PyObject * THCPModule_initExtension(PyObject *self)
{
PyObject *torch_module = PyImport_ImportModule("torch.cuda");
if (!torch_module) {
THPUtils_setError("class loader couldn't access torch module");
return NULL;
}
return PyBool_FromLong(THCPModule_initCuda(torch_module));
}
#ifdef WITH_NCCL
void THCPModule_useNccl()
{
// Use NCCL to ensure that the symbols are loaded
ncclUniqueId uniqueId;
ncclGetUniqueId(&uniqueId);
}
#endif
PyObject * THCPModule_getCurrentBlasHandle_wrap(PyObject *self)
{
HANDLE_TH_ERRORS
cublasHandle_t handle = THCState_getCurrentBlasHandle(state);
return PyLong_FromVoidPtr(handle);
END_HANDLE_TH_ERRORS
}