Add a demo backend with compiler (#52603)

Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/52603

This PR introduced a backend with minimum compilation capability to the to_<backend> flow. The targets are:

- Demonstrate the end-to-end flow with adding a backend -> compilation -> runtime
- How the backend compilation errors be surfaced to the user, with the original model's source code information. (C++ only in this PR. Python APIs will be demonstrated in a following PR.)

Changes:

- Compilation

1. A backend with minimum compilation features, "backend_with_compiler_demo" is added.
2. The compilation happens AOT in the ```pre_process``` function registered to this backend.
3. Compiled results are stored in a string blob for each method. They are serialized to the lowered module with ```__get_state__``` function.
4. Error message with model source code is thrown, for features not handled by the backend compiler.

- Runtime

1. The compiled blob is loaded in ```__set_state__``` method.
2. The ```compile``` function of the backend pass through the AOT compiled blob. (TODO: parsing the blob to the format that the backend can understand can happen here.)
3. The ```execute``` function of the backend executes the specified method (handle).

Test Plan:
- ```BackendTest.TestCompiler```: the C++ end-to-end demonstration on a supported model. After compilation and running, the lowered model produces the same result as the original torchscript model.
- ```BackendTest.TestCompilerNotSupport```: Demonstrate the error message from the AOT compilation for a feature not supported from the input module. The error message looks like:

```
"The node of aten::mul is not supported in this compiler. Source code:   File "<string>", line 3

    def forward(self, x, h):
        return x * h
               ~~~~~ <--- HERE
```

Reviewed By: raziel

Differential Revision: D26593968

Pulled By: iseeyuan

fbshipit-source-id: 8f264f60a0470e9f07e36fdeccbf17da6c1d7cd7

test/cpp/jit/test_backend_lib.cpp

@@ -61,15 +61,15 @@ class TestBackend : public PyTorchBackendInterface {
   }
 };
 
+namespace {
 c10::IValue preprocess(
     const Module& mod,
     const c10::Dict<IValue, IValue>& method_compile_spec) {
   return mod._ivalue();
 }
 
-namespace {
 static auto cls = torch::jit::backend<TestBackend>("test_backend", preprocess);
-}
+} // namespace
 
 } // namespace jit
 } // namespace torch