Update base for 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

docs/source/extension-module.md

@@ -13,7 +13,6 @@ Let's see how we can run the `SimpleConv` model generated from the [Exporting to
 #include <executorch/extension/tensor/tensor.h>
 
 using namespace ::executorch::extension;
-using ::executorch::extension::ET_MODULE_NAMESPACE::Module;
 
 // Create a Module.
 Module module("/path/to/model.pte");
@@ -222,7 +221,6 @@ Use [ExecuTorch Dump](etdump.md) to trace model execution. Create an `ETDumpGen`
 #include <executorch/devtools/etdump/etdump_flatcc.h>
 
 using namespace ::executorch::extension;
-using ::executorch::extension::ET_MODULE_NAMESPACE::Module;
 
 Module module("/path/to/model.pte", Module::LoadMode::MmapUseMlock, std::make_unique<ETDumpGen>());
 

docs/source/extension-tensor.md

@@ -11,7 +11,6 @@ Imagine you’re working with a [`Module`](extension-module.md) interface, and y
 
 using namespace executorch::aten;
 using namespace executorch::extension;
-using ::executorch::extension::ET_MODULE_NAMESPACE::Module;
 
 SizesType sizes[] = {2, 3};
 DimOrderType dim_order[] = {0, 1};
@@ -43,7 +42,6 @@ Here’s how you can use it:
 #include <executorch/extension/tensor/tensor.h>
 
 using namespace executorch::extension;
-using ::executorch::extension::ET_MODULE_NAMESPACE::Module;
 
 auto tensor = make_tensor_ptr(
     {2, 3},                                // sizes

docs/source/getting-started.md

@@ -194,7 +194,6 @@ Loading and running a model using the high-level API can be done as follows:
 #include <executorch/extension/tensor/tensor.h>
 
 using namespace ::executorch::extension;
-using ::executorch::extension::ET_MODULE_NAMESPACE::Module;
 
 // Load the model.
 Module module("/path/to/model.pte");

docs/source/llm/getting-started.md

@@ -209,7 +209,7 @@ Create a file called main.cpp with the following contents:
 using executorch::aten::ScalarType;
 using executorch::aten::Tensor;
 using executorch::extension::from_blob;
-using executorch::extension::ET_MODULE_NAMESPACE::Module;
+using executorch::extension::Module;
 using executorch::runtime::EValue;
 using executorch::runtime::Result;
 ```

docs/source/using-executorch-cpp.md

@@ -13,7 +13,6 @@ In addition the Module class, the tensor extension provides an encapsulated inte
 #include <executorch/extension/tensor/tensor.h>
 
 using namespace ::executorch::extension;
-using ::executorch::extension::ET_MODULE_NAMESPACE::Module;
 
 // Load the model.
 Module module("/path/to/model.pte");

examples/llm_manual/main.cpp

@@ -20,7 +20,7 @@
 using executorch::aten::ScalarType;
 using executorch::aten::Tensor;
 using executorch::extension::from_blob;
-using executorch::extension::ET_MODULE_NAMESPACE::Module;
+using executorch::extension::Module;
 using executorch::runtime::EValue;
 using executorch::runtime::Result;
 

examples/models/llama/runner/runner.cpp

@@ -21,7 +21,7 @@
 
 namespace example {
 
-using ::executorch::extension::ET_MODULE_NAMESPACE::Module;
+using ::executorch::extension::Module;
 using ::executorch::runtime::Error;
 using ::executorch::runtime::Result;
 

examples/models/llama/runner/runner.h

@@ -60,7 +60,7 @@ class ET_EXPERIMENTAL Runner : public executorch::extension::llm::IRunner {
   bool shouldStop_{false};
 
   // model
-  std::unique_ptr<::executorch::extension::ET_MODULE_NAMESPACE::Module> module_;
+  std::unique_ptr<::executorch::extension::Module> module_;
   std::string tokenizer_path_;
   std::unique_ptr<::tokenizers::Tokenizer> tokenizer_;
   std::unordered_map<std::string, int64_t> metadata_;

examples/models/llava/runner/llava_image_prefiller.h

@@ -18,8 +18,7 @@ namespace example {
 class ET_EXPERIMENTAL LlavaImagePrefiller
     : public ::executorch::extension::llm::ImagePrefiller {
  public:
-  explicit LlavaImagePrefiller(
-      ::executorch::extension::ET_MODULE_NAMESPACE::Module* module)
+  explicit LlavaImagePrefiller(::executorch::extension::Module* module)
       : ImagePrefiller(module){};
   /**
    * Prefill an LLM Module with the given image input.

examples/models/llava/runner/llava_text_decoder_runner.h

@@ -17,8 +17,7 @@ namespace example {
 class ET_EXPERIMENTAL LlavaTextDecoderRunner
     : public executorch::extension::llm::TextDecoderRunner {
  public:
-  explicit LlavaTextDecoderRunner(
-      executorch::extension::ET_MODULE_NAMESPACE::Module* module)
+  explicit LlavaTextDecoderRunner(executorch::extension::Module* module)
       : TextDecoderRunner(module, true) {}
 
   inline executorch::runtime::Result<executorch::aten::Tensor> step(