[NVFUSER] refactor nvfuser build (#89621)

This PR is the first step towards refactors the build for nvfuser in order to have the coegen being a standalone library.

Contents inside this PR:
1. nvfuser code base has been moved to `./nvfuser`, from `./torch/csrc/jit/codegen/cuda/`, except for registration code for integration (interface.h/interface.cpp)
2. splits the build system so nvfuser is generating its own `.so` files. Currently there are:
    - `libnvfuser_codegen.so`, which contains the integration, codegen and runtime system of nvfuser
    - `nvfuser.so`, which is nvfuser's python API via pybind. Python frontend is now exposed via `nvfuser._C.XXX` instead of `torch._C._nvfuser`
3. nvfuser cpp tests is currently being compiled into `nvfuser_tests`
4. cmake is refactored so that:
    - nvfuser now has its own `CMakeLists.txt`, which is under `torch/csrc/jit/codegen/cuda/`.
    - nvfuser backend code is not compiled inside `libtorch_cuda_xxx` any more
    - nvfuser is added as a subdirectory under `./CMakeLists.txt` at the very end after torch is built.
    - since nvfuser has dependency on torch, the registration of nvfuser at runtime is done via dlopen (`at::DynamicLibrary`). This avoids circular dependency in cmake, which will be a nightmare to handle. For details, look at `torch/csrc/jit/codegen/cuda/interface.cpp::LoadingNvfuserLibrary`

Future work that's scoped in following PR:
- Currently since nvfuser codegen has dependency on torch, we need to refactor that out so we can move nvfuser into a submodule and not rely on dlopen to load the library. @malfet
- Since we moved nvfuser into a cmake build, we effectively disabled bazel build for nvfuser. This could impact internal workload at Meta, so we need to put support back. cc'ing @vors

Pull Request resolved: https://github.com/pytorch/pytorch/pull/89621
Approved by: https://github.com/davidberard98

test/test_prims.py

@@ -145,7 +145,7 @@ class TestPrims(TestCase):
         # This test is to ensure that when the nvfuser implementation exists it is used
         # Assuming one-to-one mapping between prims and nvfuser implementations
         # This test is not intended to test the correctness of the nvfuser implementation
-        from torch._C._nvfuser import FusionDefinition as fd
+        from nvfuser._C import FusionDefinition as fd
 
         prim_nvfuser_ops = set(torch._prims.__all__).intersection(dir(fd.ops))
         ops_without_nvfuser_impl = {