# Description
Fixes#114850, we will port dynamo tests to Intel GPU
We could enable Intel GPU with following methods and try the best to keep the original code styles:
# Changes
1. Get device type from accelerator method.
2. Replace the requires cuda statement with requires_gpu.
3. Add HAS_XPU_AND_TRITON into the scope.
4. Add several wrapper methods in cuda module into the accelerator.
# Notify
Pull Request resolved: https://github.com/pytorch/pytorch/pull/160953
Approved by: https://github.com/EikanWang, https://github.com/guangyey, https://github.com/jansel
Co-authored-by: Yu, Guangye <106960996+guangyey@users.noreply.github.com>
These hooks are used by internal stuck job detection to associate compilation events with the compile lease. Previously, we only had events for Dynamo and Inductor compilation. And recently, the callback handler was updated to ignore nested events. So the Inductor event was only really used by lazy backward.
Here, I remove the inductor event, and add an explicit lazy backward one. Additionally, I add other runtime compilation events: autotuning and cudagraphs. I also expose the CompileId as a string to avoid imports, this will let internal UIs track each graph's contribution to the timeout.
```python
class CallbackTrigger(enum.Enum):
# most common case, dynamo attempts to trace a new frame
DYNAMO = 1
# backward compilation can be deferred to runtime
LAZY_BACKWARD = 2
# some backends autotune at runtime
TRITON_AUTOTUNING = 3
# cudagraphs record at runtime
CUDAGRAPH_RECORDING = 4
```
Differential Revision: [D75092426](https://our.internmc.facebook.com/intern/diff/D75092426)
Pull Request resolved: https://github.com/pytorch/pytorch/pull/153596
Approved by: https://github.com/masnesral
