Files
pytorch/torch/csrc/xpu/Module.cpp
Yu, Guangye a205e7bf56 [3/4] Intel GPU Runtime Upstreaming for Device (#116850)
# Motivation
According to [[1/4] Intel GPU Runtime Upstreaming for Device](https://github.com/pytorch/pytorch/pull/116019), As mentioned in [[RFC] Intel GPU Runtime Upstreaming](https://github.com/pytorch/pytorch/issues/114842), this third PR  covers the changes under `libtorch_python`.

# Design
This PR primarily offers device-related APIs in python frontend, including
- `torch.xpu.is_available`
- `torch.xpu.device_count`
- `torch.xpu.current_device`
- `torch.xpu.set_device`
- `torch.xpu.device`
- `torch.xpu.device_of`
- `torch.xpu.get_device_name`
- `torch.xpu.get_device_capability`
- `torch.xpu.get_device_properties`
- ====================
- `torch.xpu._DeviceGuard`
- `torch.xpu._is_compiled`
- `torch.xpu._get_device`

# Additional Context
We will implement the support of lazy initialization in the next PR.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/116850
Approved by: https://github.com/EikanWang, https://github.com/jgong5, https://github.com/gujinghui, https://github.com/malfet
2024-02-01 12:31:26 +00:00

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6.0 KiB
C++

#include <ATen/ATen.h>
#include <ATen/xpu/XPUContext.h>
#include <c10/util/CallOnce.h>
#include <c10/xpu/XPUFunctions.h>
#include <torch/csrc/Module.h>
#include <torch/csrc/THP.h>
#include <torch/csrc/utils/python_numbers.h>
#include <torch/csrc/utils/python_strings.h>
using namespace torch;
// XPU management methods
PyObject* THXPModule_setDevice_wrap(PyObject* self, PyObject* arg) {
HANDLE_TH_ERRORS
TORCH_CHECK(THPUtils_checkLong(arg), "invalid argument to set_device");
int device = THPUtils_unpackInt(arg);
c10::xpu::set_device(static_cast<c10::DeviceIndex>(device));
Py_RETURN_NONE;
END_HANDLE_TH_ERRORS
}
PyObject* THXPModule_exchangeDevice_wrap(PyObject* self, PyObject* arg) {
HANDLE_TH_ERRORS
TORCH_CHECK(THPUtils_checkLong(arg), "invalid argument to exchange_device");
int device = THPUtils_unpackInt(arg);
if (device < 0) {
return THPUtils_packInt32(-1);
}
int current_device = c10::xpu::exchange_device(device);
return THPUtils_packInt32(current_device);
END_HANDLE_TH_ERRORS
}
PyObject* THXPModule_maybeExchangeDevice_wrap(PyObject* self, PyObject* arg) {
HANDLE_TH_ERRORS
TORCH_CHECK(
THPUtils_checkLong(arg), "invalid argument to maybe_exchange_device");
int device = THPUtils_unpackInt(arg);
if (device < 0) {
return THPUtils_packInt32(-1);
}
int current_device = c10::xpu::maybe_exchange_device(device);
return THPUtils_packInt32(current_device);
END_HANDLE_TH_ERRORS
}
PyObject* THXPModule_getDevice_wrap(PyObject* self, PyObject* noargs) {
HANDLE_TH_ERRORS
// NOLINTNEXTLINE(bugprone-signed-char-misuse)
auto device = static_cast<int32_t>(c10::xpu::current_device());
return THPUtils_packInt32(device);
END_HANDLE_TH_ERRORS
}
PyObject* THXPModule_getDeviceCount_wrap(PyObject* self, PyObject* noargs) {
HANDLE_TH_ERRORS
return THPUtils_packUInt64(at::xpu::device_count());
END_HANDLE_TH_ERRORS
}
// XPU module initialization
static void registerXpuDeviceProperties(PyObject* module) {
// Add _xpuDevicePropertires class to torch._C
using namespace c10::xpu;
auto get_device_type = [](const DeviceProp& prop) {
std::ostringstream stream;
using namespace sycl::info;
switch (prop.device_type) {
case device_type::cpu:
stream << "cpu";
break;
case device_type::gpu:
stream << "gpu";
break;
case device_type::accelerator:
stream << "accelerator";
break;
case device_type::host:
stream << "host";
break;
default:
stream << "unknown device type:"
<< static_cast<typename std::underlying_type<device_type>::type>(
prop.device_type);
break;
}
return stream.str();
};
auto gpu_subslice_count = [](const DeviceProp& prop) {
return (prop.gpu_eu_count / prop.gpu_eu_count_per_subslice);
};
auto m = py::handle(module).cast<py::module>();
py::class_<DeviceProp>(m, "_XpuDeviceProperties")
.def_readonly("name", &DeviceProp::name)
.def_readonly("platform_name", &DeviceProp::platform_name)
.def_readonly("total_memory", &DeviceProp::global_mem_size)
.def_readonly("max_compute_units", &DeviceProp::max_compute_units)
.def_readonly("gpu_eu_count", &DeviceProp::gpu_eu_count)
.def_property_readonly("gpu_subslice_count", gpu_subslice_count)
.def_readonly("max_work_group_size", &DeviceProp::max_work_group_size)
.def_readonly("max_num_sub_groups", &DeviceProp::max_num_sub_groups)
.def_readonly("sub_group_sizes", &DeviceProp::sub_group_sizes)
.def_property_readonly("type", get_device_type)
.def(
"__repr__",
[&get_device_type, &gpu_subslice_count](const DeviceProp& prop) {
std::ostringstream stream;
stream << "_XpuDeviceProperties(name='" << prop.name
<< "', platform_name='" << prop.platform_name << "', type='"
<< get_device_type(prop)
<< ", total_memory=" << prop.global_mem_size / (1024 * 1024)
<< "MB, max_compute_units=" << prop.max_compute_units
<< ", gpu_eu_count=" << prop.gpu_eu_count
<< ", gpu_subslice_count=" << gpu_subslice_count(prop)
<< ", max_work_group_size=" << prop.max_work_group_size
<< ", max_num_sub_groups=" << prop.max_num_sub_groups
<< ", sub_group_sizes=[" << prop.sub_group_sizes << "])";
return stream.str();
});
}
static void bindGetDeviceProperties(PyObject* module) {
// Add method to torch.xpu
auto m = py::handle(module).cast<py::module>();
m.def(
"_get_device_properties",
[](int device) -> c10::xpu::DeviceProp* {
return at::xpu::getDeviceProperties(device);
},
py::return_value_policy::reference);
}
// Callback for python part. Used for additional initialization of python
// classes
static PyObject* THXPModule_initExtension(PyObject* self, PyObject* noargs) {
HANDLE_TH_ERRORS
auto m = THPObjectPtr(PyImport_ImportModule("torch.xpu"));
if (!m)
throw python_error();
bindGetDeviceProperties(m);
Py_RETURN_NONE;
END_HANDLE_TH_ERRORS
}
// NOLINTNEXTLINE(modernize-avoid-c-arrays,
// cppcoreguidelines-avoid-non-const-global-variables,
// cppcoreguidelines-avoid-c-arrays)
static struct PyMethodDef _THXPModule_methods[] = {
{"_xpu_init", THXPModule_initExtension, METH_NOARGS, nullptr},
{"_xpu_setDevice", THXPModule_setDevice_wrap, METH_O, nullptr},
{"_xpu_exchangeDevice", THXPModule_exchangeDevice_wrap, METH_O, nullptr},
{"_xpu_maybeExchangeDevice",
THXPModule_maybeExchangeDevice_wrap,
METH_O,
nullptr},
{"_xpu_getDevice", THXPModule_getDevice_wrap, METH_NOARGS, nullptr},
{"_xpu_getDeviceCount",
THXPModule_getDeviceCount_wrap,
METH_NOARGS,
nullptr},
{nullptr}};
PyMethodDef* THXPModule_methods() {
return _THXPModule_methods;
}
namespace torch::xpu {
void initModule(PyObject* module) {
registerXpuDeviceProperties(module);
}
} // namespace torch::xpu