Add functions to setup PrivateUse1 as a python backend device. (#157859)

Fixes #156052 and #156444.

This PR setup the privateuseone key in Python to be used as a python backend for pytorch.
Meaning that, after calling `setup_privateuseone_for_python_backend('npy')`, one can use a subclass to with that device to hold arbitrary python data as "device data" and use `torch.library` to register ops that takes that Tensor.

Changes done in this PR:

1. Register an vanilla Device Guard: I extended NoOpDeviceGuard to have allow device index of 0 and to not raise errors when event related functions are accessed. If I don't do those, when calling backward I would get errors. (CPU backend uses NoOpDeviceGuard just fine, although there seems to be special treatment of CPU in the autograd engine.
2. Tensor subclass allows not having `__torch_dispatch__` if the device is not CUDA or CPU. The comment of the check suggests it was to avoid segfault when calling into ops that expects a storage. Here we have a different device so will not call into those ops.
3. python function that invokes the other incantations to setup the privateusekey backend.

This took inspiration of https://github.com/bdhirsh/pytorch_open_registration_example and https://github.com/tinygrad/tinygrad/blob/master/extra/torch_backend/wrapped_tensor.cpp; great thanks to @bdhirsh and @geohot.
Pull Request resolved: https://github.com/pytorch/pytorch/pull/157859
Approved by: https://github.com/albanD

build_variables.bzl

@@ -897,6 +897,7 @@ libtorch_python_core_sources = [
     "torch/csrc/Stream.cpp",
     "torch/csrc/Event.cpp",
     "torch/csrc/TypeInfo.cpp",
+    "torch/csrc/acc/Module.cpp",
     "torch/csrc/api/src/python/init.cpp",
     "torch/csrc/autograd/functions/init.cpp",
     "torch/csrc/autograd/init.cpp",