Move examples/mediatek out from under the torch namespace (#5478)

Summary:
The code under examples/... is a proxy for user code, and users should never declare code under the `torch::` or `executorch::` namespaces.

Move this code under the `example::` namespace to make it more clear that users should use their own namespaces when writing code like this.

Pull Request resolved: #5478

Test Plan: - Built using the instructions at https://github.com/pytorch/executorch/blob/main/examples/mediatek/README.md

Reviewed By: JacobSzwejbka, cccclai

Differential Revision: D62992974

Pulled By: dbort

fbshipit-source-id: b01f1b33d2853a0555ae19d79769a5bb6d0ba853

Author: dbort

examples/mediatek/executor_runner/llama_runner/FileMemMapper.h

@@ -15,7 +15,7 @@
 #include <sys/stat.h>
 #include <unistd.h>
 
-namespace torch::executor {
+namespace example {
 
 class FileMemMapper { // Read-only mmap
  public:
@@ -97,4 +97,4 @@ class FileMemMapper { // Read-only mmap
   size_t mSize = 0;
 };
 
-} // namespace torch::executor
+} // namespace example

examples/mediatek/executor_runner/llama_runner/LlamaConfig.h

@@ -13,7 +13,7 @@
 
 #include "llm_helper/include/llm_types.h"
 
-namespace torch::executor {
+namespace example {
 
 using llm_helper::LLMType;
 
@@ -42,4 +42,4 @@ struct LlamaModelPaths {
   std::vector<std::string> gen_model_paths;
 };
 
-} // namespace torch::executor
+} // namespace example

examples/mediatek/executor_runner/llama_runner/LlamaModelChunk.cpp

@@ -26,7 +26,7 @@
 #include "llm_helper/include/mask_builder.h"
 #include "llm_helper/include/rotary_embedding.h"
 
-namespace torch::executor {
+namespace example {
 
 inline std::vector<size_t> getIndexRange(
     const size_t startIndex,
@@ -343,4 +343,4 @@ void LlamaModelChunk::InitCache() {
   }
 }
 
-} // namespace torch::executor
+} // namespace example

examples/mediatek/executor_runner/llama_runner/LlamaModelChunk.h

@@ -27,12 +27,12 @@
 #include "llm_helper/include/mask_builder.h"
 #include "llm_helper/include/rotary_embedding.h"
 
-namespace torch::executor {
+namespace example {
 
 using llm_helper::MaskBuilder;
 using llm_helper::RotaryEmbeddingMasterLut;
 
-using TensorShape = Span<const int32_t>;
+using TensorShape = executorch::runtime::Span<const int32_t>;
 using ModelIndexMap = std::unordered_map<size_t, size_t>;
 
 // Llama decoder chunk
@@ -135,4 +135,4 @@ class LlamaModelChunk : public ModelChunk {
   size_t mCurrentTokenIndex = 0;
 };
 
-} // namespace torch::executor
+} // namespace example

examples/mediatek/executor_runner/llama_runner/LlamaRuntime.cpp

@@ -18,7 +18,7 @@
 #include "llm_helper/include/rotary_embedding.h"
 #include "llm_helper/include/token_embedding.h"
 
-namespace torch::executor {
+namespace example {
 
 void LlamaRuntime::Initialize(
     const LlamaModelOptions& modelOptions,
@@ -201,4 +201,4 @@ const LlamaModelOptions& LlamaRuntime::GetModelOptions() const {
   return mModelOptions;
 }
 
-} // namespace torch::executor
+} // namespace example

examples/mediatek/executor_runner/llama_runner/LlamaRuntime.h

@@ -20,7 +20,7 @@
 #include "llm_helper/include/rotary_embedding.h"
 #include "llm_helper/include/token_embedding.h"
 
-namespace torch::executor {
+namespace example {
 
 class LlamaRuntime {
  public:
@@ -56,4 +56,4 @@ class LlamaRuntime {
   size_t mTokenIndex = 0;
 };
 
-} // namespace torch::executor
+} // namespace example

examples/mediatek/executor_runner/llama_runner/ModelChunk.cpp

@@ -23,9 +23,21 @@
 #define ENSURE_INIT \
   ET_CHECK_MSG(Initialized(), "Error: Model chunk not initialized.");
 
-namespace torch::executor {
-
-using util::FileDataLoader;
+namespace example {
+
+using executorch::aten::Tensor;
+using executorch::aten::TensorImpl;
+using executorch::extension::FileDataLoader;
+using executorch::runtime::Error;
+using executorch::runtime::HierarchicalAllocator;
+using executorch::runtime::MemoryAllocator;
+using executorch::runtime::MemoryManager;
+using executorch::runtime::Method;
+using executorch::runtime::MethodMeta;
+using executorch::runtime::Program;
+using executorch::runtime::Result;
+using executorch::runtime::Span;
+using executorch::runtime::Tag;
 
 static constexpr size_t kMethodAllocatorPoolSize = 4 * 1024U * 1024U; // 4MB
 
@@ -572,4 +584,4 @@ void ModelChunk::ReleaseModelInstance(void* modelInstance) {
   }
 }
 
-} // namespace torch::executor
+} // namespace example

examples/mediatek/executor_runner/llama_runner/ModelChunk.h

@@ -16,7 +16,7 @@
 
 #include "MultiModelLoader.h"
 
-namespace torch::executor {
+namespace example {
 
 struct BufferInfo {
   void* data = nullptr;
@@ -91,7 +91,7 @@ class ModelChunk : protected MultiTokenSizeModelLoader {
   // Release allocated buffers for model IOs
   void ReleaseIoBuffers();
 
-  Method& GetModelMethod();
+  executorch::runtime::Method& GetModelMethod();
 
  private:
   // Override the virtual functions
@@ -119,4 +119,4 @@ class ModelChunk : protected MultiTokenSizeModelLoader {
   std::unordered_map<size_t, size_t> mModelOutToInIndexLinks;
 };
 
-} // namespace torch::executor
+} // namespace example

examples/mediatek/executor_runner/llama_runner/MultiModelLoader.cpp

@@ -16,7 +16,7 @@
 #include <unordered_map>
 #include <vector>
 
-namespace torch::executor {
+namespace example {
 
 template <typename IdType>
 void MultiModelLoader<IdType>::LoadModels() {
@@ -174,4 +174,4 @@ std::string MultiModelLoader<IdType>::GetIdString(const IdType& id) {
 template class MultiModelLoader<int>;
 template class MultiModelLoader<size_t>;
 
-} // namespace torch::executor
+} // namespace example

examples/mediatek/executor_runner/llama_runner/MultiModelLoader.h

@@ -12,7 +12,7 @@
 #include <unordered_map>
 #include <vector>
 
-namespace torch::executor {
+namespace example {
 
 template <typename IdType = size_t>
 class MultiModelLoader {
@@ -92,4 +92,4 @@ class MultiModelLoader {
   IdType mCurrentModelId = 0;
 };
 
-} // namespace torch::executor
+} // namespace example