Update on "[ExecuTorch][#10375] Add extension.BundledModule to Wrap extension.Module with Bundled Program Logic"

#10375

# Context

This issue is a step of #9638.

In #9638, we want to have `extension.Module` as the single source of implementation in `pybindings`, which means that `pybindings.PyModule` should use `extension.Module` rather than its own `pybindings.Module`.

The issue is that `pybindings.PyModule` is dependent on the `method` getter from `pybindings.Module`, which `extension.Module` do not have. Since we don't want to expose `method` getter in `extension.Module`, we have to protect the getter, wrap the functions that is dependent on it and use the protected getter there, ultimately decouple `pybindings` from a `method` getter.

# Proposal

Now that we have a protected `method` getter, we can introduce a `extension.BundledModule`, a child class inheriting `extension.Module` which wraps up bundled program logic that is dependent on the `method` getter.

Differential Revision: [D73564125](https://our.internmc.facebook.com/intern/diff/D73564125/)

[ghstack-poisoned]

Author: zhenyan-zhang-meta

extension/module/test/resources/gen_bundled_program.py

@@ -1,14 +1,13 @@
-# (c) Meta Platforms, Inc. and affiliates. Confidential and proprietary.
-
 import torch
 
-from executorch.exir import to_edge_transform_and_lower
 from executorch.devtools import BundledProgram
 
 from executorch.devtools.bundled_program.config import MethodTestCase, MethodTestSuite
 from executorch.devtools.bundled_program.serialize import (
     serialize_from_bundled_program_to_flatbuffer,
 )
+
+from executorch.exir import to_edge_transform_and_lower
 from torch.export import export, export_for_training
 
 # Step 1: ExecuTorch Program Export
@@ -17,8 +16,8 @@ class SampleModel(torch.nn.Module):
 
     def __init__(self) -> None:
         super().__init__()
-        self.register_buffer('a', 3 * torch.ones(2, 2, dtype=torch.int32))
-        self.register_buffer('b', 2 * torch.ones(2, 2, dtype=torch.int32))
+        self.register_buffer("a", 3 * torch.ones(2, 2, dtype=torch.int32))
+        self.register_buffer("b", 2 * torch.ones(2, 2, dtype=torch.int32))
 
     def forward(self, x: torch.Tensor, q: torch.Tensor) -> torch.Tensor:
         z = x.clone()
@@ -76,7 +75,7 @@ def main() -> None:
             test_cases=[
                 MethodTestCase(
                     inputs=input,
-                    expected_outputs=(getattr(model, method_name)(*input), ),
+                    expected_outputs=(getattr(model, method_name)(*input),),
                 )
                 for input in inputs
             ],