Commit Graph

5 Commits

Author SHA1 Message Date
Xuehai Pan
8962610247 [BE][clang-format] make macro PyObject_HEAD_INIT(type) and PyVarObject_HEAD_INIT(type, size) have its own line (#136949)
Pull Request resolved: https://github.com/pytorch/pytorch/pull/136949
Approved by: https://github.com/albanD, https://github.com/eqy
ghstack dependencies: #136945
2024-10-02 18:39:22 +00:00
Yu, Guangye
df5bbc09d1 Make device-specific event inherits from torch.Event (#134845)
# Motivation
This PR intends to make device-specific Event inherit from the generic torch.Event. The benefit is providing a generic abstract class `torch.Event` for different devices, like `torch.Stream`. This make it easier for Dynamo to capture the Event of different devices, like torch.cuda.Event and torch.xpu.Event.
And the next PR would like to remove previous useless base class `_StreamBase` and `_EventBase` to avoid multiple Inheritance.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/134845
Approved by: https://github.com/albanD, https://github.com/EikanWang
2024-10-01 06:28:41 +00:00
cyy
29861779ce [2/N] Change #include <c10/util/Optional.h> to #include <optional> (#130236)
Follows  #128301. The changes were made by grep and sed

Pull Request resolved: https://github.com/pytorch/pytorch/pull/130236
Approved by: https://github.com/ezyang
2024-07-09 03:17:24 +00:00
Yu, Guangye
1aa9099839 [CLANGTIDY] Enable clang-tidy in torch/csrc/xpu (#120616)
# Motivation
refer to [#118504](https://github.com/pytorch/pytorch/pull/118504), enabling clang-tidy in `torch/csrc/xpu`.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/120616
Approved by: https://github.com/albanD
2024-02-28 01:35:25 +00:00
Yu, Guangye
4dc75f9084 Intel GPU Runtime Upstreaming for Event (#117734)
# Motivation
As mentioned in [[RFC] Intel GPU Runtime Upstreaming](https://github.com/pytorch/pytorch/issues/114842), the next runtime component we would like to upstream is `Event` which handles the status of an operation that is being executed. Typically, in some circumstances, we can fine-grain control of the operation execution via `Event`.

# Design
`XPUEvent` is a movable but not a copyable wrapper around sycl event. It should be created lazily on an XPU device when recording an `XPUStream`. Meanwhile, `XPUEvent` can wait for another `XPUEvent` or all the submitted kernels on an `XPUStream` to complete. Align to the other backend, the C++ files related to `Event` will be placed in `aten/src/ATen/xpu` folder. For frontend code, `XPUEvent` runtime API will be bound to Python `torch.xpu.Event`. The corresponding C++ code will be placed in `torch/csrc/xpu/Event.cpp` and Python code will be placed in `torch/xpu/streams.py` respectively.

# Additional Context
It is worth mentioning that the `elapsed_time` method is temporarily not supported by `XPUEvent`. We will be adding support for it soon. Meanwhile `XPUEvent` doesn't support IPC from different processes. For the other parts, we have almost a 1:1 mapping with CUDA.

lack of the below APIs:
- `torch.cuda.Event.ipc_handle`
- `CUDAEvent`'s constructor with `IpcEventHandle`

Pull Request resolved: https://github.com/pytorch/pytorch/pull/117734
Approved by: https://github.com/EikanWang, https://github.com/gujinghui, https://github.com/jgong5, https://github.com/malfet
ghstack dependencies: #117611, #117619
2024-02-16 06:28:26 +00:00