mirror of
https://github.com/saymrwulf/pytorch.git
synced 2026-05-14 20:57:59 +00:00
c2b2e57032
# Motivation According to [[RFC] Intel GPU Runtime Upstreaming](https://github.com/pytorch/pytorch/issues/114842), the 5th runtime component we would like to upstream is `Guard`. We will cover device guard and stream guard in this PR. # Design Device guard is used mainly for op dispatcher in PyTorch. Currently, PyTorch already has a device guard abstraction `c10::impl::DeviceGuardImplInterface`. In our design, we will introduce an `XPUGuardImpl` class inherits from `c10::impl::DeviceGuardImplInterface`. Register `XPUGuardImpl` to PyTorch after we implement the device switch management mechanism in `XPUGuardImpl`. Besides, we will introduce `XPUGuard`, `OptionalXPUGuard`, `XPUStreamGuard`, and `OptionalXPUStreamGuard`. They are all following the design of CUDA's counterpart. The corresponding C++ file should be placed in c10/xpu/ folder. # Additional Context It is unnecessary to add `Guard` code to PyTorch frontend. Pull Request resolved: https://github.com/pytorch/pytorch/pull/118523 Approved by: https://github.com/EikanWang, https://github.com/gujinghui, https://github.com/jgong5, https://github.com/malfet ghstack dependencies: #120315
7 lines
143 B
C++
7 lines
143 B
C++
#include <c10/xpu/impl/XPUGuardImpl.h>
|
|
|
|
namespace c10::xpu::impl {
|
|
|
|
C10_REGISTER_GUARD_IMPL(XPU, XPUGuardImpl);
|
|
|
|
} // namespace c10::xpu::impl
|