s/exec_aten::/executorch::aten::/ for extension/**/*.h (#6032)

Summary:
Pull Request resolved: #6032

Migrate all extension headers to use the new aten namespace, so that they act as good examples for users. The .cpp code can migrate later.

Reviewed By: lucylq

Differential Revision: D64079593

fbshipit-source-id: 62164cd6ec3238e21e896813f185d0c1446ef527
(cherry picked from commit 69c2c76)

Author: dbort

extension/android/jni/jni_layer_constants.h

@@ -37,7 +37,7 @@ constexpr static int kTensorDTypeBits4x2 = 20;
 constexpr static int kTensorDTypeBits8 = 21;
 constexpr static int kTensorDTypeBits16 = 22;
 
-using exec_aten::ScalarType;
+using executorch::aten::ScalarType;
 
 const std::unordered_map<ScalarType, int> scalar_type_to_java_dtype = {
     {ScalarType::Byte, kTensorDTypeUInt8},

extension/kernel_util/make_boxed_from_unboxed_functor.h

@@ -66,12 +66,12 @@ struct decay_if_not_tensor final {
   using type = std::decay_t<T>;
 };
 template <>
-struct decay_if_not_tensor<exec_aten::Tensor&> final {
-  using type = exec_aten::Tensor&;
+struct decay_if_not_tensor<executorch::aten::Tensor&> final {
+  using type = executorch::aten::Tensor&;
 };
 template <>
-struct decay_if_not_tensor<const exec_aten::Tensor&> final {
-  using type = const exec_aten::Tensor&;
+struct decay_if_not_tensor<const executorch::aten::Tensor&> final {
+  using type = const executorch::aten::Tensor&;
 };
 
 template <class T>
@@ -82,29 +82,30 @@ struct evalue_to_arg final {
 };
 
 template <>
-struct evalue_to_arg<exec_aten::Tensor&> final {
-  static exec_aten::Tensor& call(executorch::runtime::EValue& v) {
+struct evalue_to_arg<executorch::aten::Tensor&> final {
+  static executorch::aten::Tensor& call(executorch::runtime::EValue& v) {
     return v.toTensor();
   }
 };
 
 template <>
-struct evalue_to_arg<const exec_aten::Tensor&> final {
-  static const exec_aten::Tensor& call(executorch::runtime::EValue& v) {
+struct evalue_to_arg<const executorch::aten::Tensor&> final {
+  static const executorch::aten::Tensor& call(executorch::runtime::EValue& v) {
     return v.toTensor();
   }
 };
 
 template <class T>
-struct evalue_to_arg<exec_aten::optional<T>> final {
-  static exec_aten::optional<T> call(executorch::runtime::EValue& v) {
+struct evalue_to_arg<executorch::aten::optional<T>> final {
+  static executorch::aten::optional<T> call(executorch::runtime::EValue& v) {
     return v.toOptional<T>();
   }
 };
 
 template <class T>
-struct evalue_to_arg<exec_aten::ArrayRef<exec_aten::optional<T>>> final {
-  static exec_aten::ArrayRef<exec_aten::optional<T>> call(
+struct evalue_to_arg<executorch::aten::ArrayRef<executorch::aten::optional<T>>>
+    final {
+  static executorch::aten::ArrayRef<executorch::aten::optional<T>> call(
       executorch::runtime::EValue& v) {
     return v.toListOptionalTensor();
   }

extension/llm/runner/image_prefiller.h

@@ -30,7 +30,7 @@ class ImagePrefiller {
    * It's passed as reference and will be updated inside this function.
    * @return The next token of the LLM Module after prefill.
    */
-  virtual ::executorch::runtime::Result<exec_aten::Tensor> prefill(
+  virtual ::executorch::runtime::Result<executorch::aten::Tensor> prefill(
       Image& image,
       int64_t& start_pos) = 0;
 

extension/llm/runner/text_decoder_runner.h

@@ -37,7 +37,7 @@ class TextDecoderRunner {
    * Module.
    * @return The output of the LLM Module. This will be a tensor of logits.
    */
-  virtual ::executorch::runtime::Result<exec_aten::Tensor> step(
+  virtual ::executorch::runtime::Result<executorch::aten::Tensor> step(
       TensorPtr& input,
       TensorPtr& start_pos);
 
@@ -66,7 +66,8 @@ class TextDecoderRunner {
    * @param logits_tensor The logits tensor.
    * @return The next token.
    */
-  inline int32_t logits_to_token(const exec_aten::Tensor& logits_tensor) {
+  inline int32_t logits_to_token(
+      const executorch::aten::Tensor& logits_tensor) {
     int32_t result = 0;
     ET_SWITCH_THREE_TYPES(
         Float,

extension/llm/runner/text_token_generator.h

@@ -53,7 +53,7 @@ class TextTokenGenerator {
     int64_t pos = start_pos; // position in the sequence
 
     std::vector<uint64_t> token_data; // allocate space for the tokens
-    std::vector<exec_aten::SizesType> token_shape;
+    std::vector<executorch::aten::SizesType> token_shape;
 
     // Token after prefill
     uint64_t cur_token = tokens.back();
@@ -70,8 +70,10 @@ class TextTokenGenerator {
     }
 
     // initialize tensor wrappers
-    auto tokens_managed =
-        from_blob(token_data.data(), token_shape, exec_aten::ScalarType::Long);
+    auto tokens_managed = from_blob(
+        token_data.data(), token_shape, executorch::aten::ScalarType::Long);
+    auto start_pos_managed =
+        from_blob(&pos, {1}, executorch::aten::ScalarType::Long);
 
     auto start_pos_managed = from_blob(&pos, {1}, exec_aten::ScalarType::Long);
 
@@ -82,7 +84,7 @@ class TextTokenGenerator {
           text_decoder_runner_->step(tokens_managed, start_pos_managed);
 
       ET_CHECK_OK_OR_RETURN_ERROR(logits_res.error());
-      exec_aten::Tensor& logits_tensor = logits_res.get();
+      executorch::aten::Tensor& logits_tensor = logits_res.get();
 
       prev_token = cur_token;