[Reland][2/N]Port several test files under test/distributed to Intel GPU (#159473)

For https://github.com/pytorch/pytorch/issues/114850, we will port distributed tests to Intel GPU. This PR will work on some test files under test/distributed. We could enable Intel GPU with following methods and try the best to keep the original code styles:

- instantiate_device_type_tests()
- use "torch.accelerator.current_accelerator()" to determine the accelerator backend
- use requires_accelerator_dist_backend to allow both nccl and xccl test
- enabled XPU for some test path
- Change the hardcoded world_size according to device_count.
- Unify some common code under torch/testing/_internal for multiple backend, for example:
  Added xpu for Backend.backend_capability and dist.Backend.register_backend()

Pull Request resolved: https://github.com/pytorch/pytorch/pull/159473
Approved by: https://github.com/guangyey, https://github.com/d4l3k

torch/distributed/distributed_c10d.py

@@ -337,10 +337,12 @@ class Backend(str):  # noqa: SLOT000
             # assume default devices "cpu" and "cuda", but warn
             warnings.warn(
                 f"Device capability of {name} unspecified, assuming `cpu` and "
-                "`cuda`. Please specify it via the `devices` argument of "
+                "`cuda` or `xpu`. Please specify it via the `devices` argument of "
                 "`register_backend`."
             )
-            Backend.backend_capability[name.lower()] = ["cpu", "cuda"]
+            Backend.backend_capability[name.lower()] = (
+                ["cpu", "cuda", "xpu"] if torch.xpu.is_available() else ["cpu", "cuda"]
+            )
         elif isinstance(devices, str):
             # Single device string specified. Simply convert to list.
             Backend.backend_capability[name.lower()] = [devices]