Migrate backends/xnnpack to the new namespace

backends/xnnpack/runtime/XNNCompiler.cpp

@@ -16,11 +16,15 @@
 #pragma clang diagnostic ignored "-Wmissing-prototypes"
 #pragma clang diagnostic ignored "-Wglobal-constructors"
 
-namespace torch {
-namespace executor {
+namespace executorch {
+namespace backends {
 namespace xnnpack {
 namespace delegate {
 
+using executorch::runtime::Error;
+using executorch::runtime::MemoryAllocator;
+using executorch::runtime::Result;
+
 /*
  * Provide compile-time allocation.
  */
@@ -1811,5 +1815,5 @@ ET_NODISCARD Error XNNCompiler::compileModel(
 
 } // namespace delegate
 } // namespace xnnpack
-} // namespace executor
-} // namespace torch
+} // namespace backends
+} // namespace executorch

backends/xnnpack/runtime/XNNCompiler.h

@@ -15,8 +15,8 @@
 #include <memory>
 #include <vector>
 
-namespace torch {
-namespace executor {
+namespace executorch {
+namespace backends {
 namespace xnnpack {
 namespace delegate {
 
@@ -25,15 +25,15 @@ class XNNCompiler {
   // Takes Flatbuffer Serialized XNNPACK Model and rebuilds the xnn-subgraph
   // returns an executor object that holds the xnn runtime object which we
   // can then use to set inputs and run inference using the xnn graph.
-  ET_NODISCARD static Error compileModel(
+  ET_NODISCARD static executorch::runtime::Error compileModel(
       const void* buffer_pointer,
       size_t num_bytes,
       XNNExecutor* executor,
-      MemoryAllocator* runtime_allocator,
+      executorch::runtime::MemoryAllocator* runtime_allocator,
       xnn_workspace_t workspace);
 };
 
 } // namespace delegate
 } // namespace xnnpack
-} // namespace executor
-} // namespace torch
+} // namespace backends
+} // namespace executorch

backends/xnnpack/runtime/XNNExecutor.cpp

@@ -8,14 +8,19 @@
 
 #include <executorch/backends/xnnpack/runtime/XNNExecutor.h>
 
-namespace torch {
-namespace executor {
+namespace executorch {
+namespace backends {
 namespace xnnpack {
 namespace delegate {
 
-using Tensor = exec_aten::Tensor;
-using ScalarType = exec_aten::ScalarType;
-using SizesType = exec_aten::SizesType;
+using executorch::aten::ScalarType;
+using executorch::aten::SizesType;
+using executorch::aten::Tensor;
+using executorch::runtime::BackendExecutionContext;
+using executorch::runtime::Error;
+using executorch::runtime::EValue;
+using executorch::runtime::is_contiguous_dim_order;
+using executorch::runtime::kTensorDimensionLimit;
 
 /**
  * Initializes the XNNExecutor with the runtime and given number of
@@ -204,7 +209,7 @@ ET_NODISCARD Error XNNExecutor::resize_outputs(EValue** args) const {
       expected_output_size[d] = static_cast<SizesType>(dims[d]);
     }
 
-    exec_aten::ArrayRef<SizesType> output_size{
+    executorch::aten::ArrayRef<SizesType> output_size{
         expected_output_size, static_cast<size_t>(num_dim)};
 
     ET_LOG(Debug, "Resizing output tensor to a new shape");
@@ -231,5 +236,5 @@ ET_NODISCARD Error XNNExecutor::resize_outputs(EValue** args) const {
 
 } // namespace delegate
 } // namespace xnnpack
-} // namespace executor
-} // namespace torch
+} // namespace backends
+} // namespace executorch

backends/xnnpack/runtime/XNNExecutor.h

@@ -19,8 +19,8 @@
 #include <memory>
 #include <vector>
 
-namespace torch {
-namespace executor {
+namespace executorch {
+namespace backends {
 namespace xnnpack {
 namespace delegate {
 
@@ -51,7 +51,7 @@ class XNNExecutor {
    * The input/output ids are expected to be sorted in order of their
    * flatbuffer id_outs
    */
-  ET_NODISCARD Error initialize(
+  ET_NODISCARD executorch::runtime::Error initialize(
       xnn_runtime_t runtime,
       std::vector<uint32_t>&& input_ids,
       std::vector<uint32_t>&& output_ids);
@@ -62,24 +62,27 @@ class XNNExecutor {
    * input shapes will be propagated through the runtime, and perform
    * any additional memory planning as needed
    */
-  ET_NODISCARD Error prepare_args(EValue** args);
+  ET_NODISCARD executorch::runtime::Error prepare_args(
+      executorch::runtime::EValue** args);
 
   /**
    * Executes the graph using the args prepared at prepare_args().
    */
-  ET_NODISCARD Error forward(BackendExecutionContext& context);
+  ET_NODISCARD executorch::runtime::Error forward(
+      executorch::runtime::BackendExecutionContext& context);
 
   /**
    * Prepares the outputs to be returned by the delegate
    *
    * Performs any post processing of outputs like tensor resizing
    */
-  ET_NODISCARD Error resize_outputs(EValue** args) const;
+  ET_NODISCARD executorch::runtime::Error resize_outputs(
+      executorch::runtime::EValue** args) const;
 
   friend class XNNCompiler;
 };
 
 } // namespace delegate
 } // namespace xnnpack
-} // namespace executor
-} // namespace torch
+} // namespace backends
+} // namespace executorch

backends/xnnpack/runtime/XNNHeader.cpp

@@ -15,11 +15,14 @@
 
 #pragma clang diagnostic ignored "-Wdeprecated"
 
-namespace torch {
-namespace executor {
+namespace executorch {
+namespace backends {
 namespace xnnpack {
 namespace delegate {
 
+using executorch::runtime::Error;
+using executorch::runtime::Result;
+
 namespace {
 /// Interprets the 8 bytes at `data` as a little-endian uint64_t.
 uint64_t GetUInt64LE(const uint8_t* data) {
@@ -73,5 +76,5 @@ constexpr char XNNHeader::kMagic[kMagicSize];
 
 } // namespace delegate
 } // namespace xnnpack
-} // namespace executor
-} // namespace torch
+} // namespace backends
+} // namespace executorch

backends/xnnpack/runtime/XNNHeader.h

@@ -10,8 +10,8 @@
 
 #include <executorch/runtime/core/result.h>
 
-namespace torch {
-namespace executor {
+namespace executorch {
+namespace backends {
 namespace xnnpack {
 namespace delegate {
 
@@ -98,7 +98,9 @@ struct XNNHeader {
    *     error if size was too short, if the header was not found, or if the
    *     header appeared to be corrupt.
    */
-  static Result<XNNHeader> Parse(const void* data, size_t size);
+  static executorch::runtime::Result<XNNHeader> Parse(
+      const void* data,
+      size_t size);
 
   /**
    * The offset in bytes to the beginning of the flatbuffer data.
@@ -121,5 +123,5 @@ struct XNNHeader {
 
 } // namespace delegate
 } // namespace xnnpack
-} // namespace executor
-} // namespace torch
+} // namespace backends
+} // namespace executorch

backends/xnnpack/runtime/XNNPACKBackend.cpp

@@ -17,8 +17,19 @@
 
 #pragma clang diagnostic ignored "-Wglobal-constructors"
 
-namespace torch {
-namespace executor {
+namespace executorch {
+namespace backends {
+
+using executorch::runtime::ArrayRef;
+using executorch::runtime::Backend;
+using executorch::runtime::BackendExecutionContext;
+using executorch::runtime::BackendInitContext;
+using executorch::runtime::CompileSpec;
+using executorch::runtime::DelegateHandle;
+using executorch::runtime::Error;
+using executorch::runtime::EValue;
+using executorch::runtime::FreeableBuffer;
+using executorch::runtime::Result;
 
 class XnnpackBackend final : public ::executorch::runtime::BackendInterface {
  public:
@@ -145,5 +156,5 @@ Backend backend{"XnnpackBackend", &cls};
 static auto success_with_compiler = register_backend(backend);
 } // namespace
 
-} // namespace executor
-} // namespace torch
+} // namespace backends
+} // namespace executorch

backends/xnnpack/runtime/XNNStatus.h

@@ -11,8 +11,8 @@
 #include <assert.h>
 #include <xnnpack.h>
 
-namespace torch {
-namespace executor {
+namespace executorch {
+namespace backends {
 namespace xnnpack {
 namespace delegate {
 
@@ -34,5 +34,5 @@ inline const char* xnn_status_to_string(enum xnn_status type) {
 
 } // namespace delegate
 } // namespace xnnpack
-} // namespace executor
-} // namespace torch
+} // namespace backends
+} // namespace executorch

backends/xnnpack/runtime/profiling/XNNProfiler.cpp

@@ -22,9 +22,13 @@
 #include <unordered_map>
 // NOLINTEND
 
-namespace torch::executor::xnnpack::delegate::profiling {
+namespace executorch::backends::xnnpack::delegate::profiling {
+
+using executorch::runtime::Error;
+using executorch::runtime::EventTracer;
 
 #if defined(ET_EVENT_TRACER_ENABLED) || defined(ENABLE_XNNPACK_PROFILING)
+
 XNNProfiler::XNNProfiler()
     : state_(XNNProfilerState::Uninitialized), run_count_(0) {}
 
@@ -210,10 +214,10 @@ void XNNProfiler::submit_trace() {
 
     auto end_time = time + interval_ticks;
 
-    torch::executor::event_tracer_log_profiling_delegate(
+    executorch::runtime::event_tracer_log_profiling_delegate(
         event_tracer_,
         name_formatted.c_str(),
-        /*delegate_debug_id=*/static_cast<torch::executor::DebugHandle>(-1),
+        /*delegate_debug_id=*/static_cast<executorch::runtime::DebugHandle>(-1),
         time,
         end_time);
 
@@ -246,4 +250,4 @@ Error XNNProfiler::end() {
 
 #endif
 
-} // namespace torch::executor::xnnpack::delegate::profiling
+} // namespace executorch::backends::xnnpack::delegate::profiling

backends/xnnpack/runtime/profiling/XNNProfiler.h

@@ -14,8 +14,8 @@
 #include <xnnpack.h>
 #include <vector>
 
-namespace torch {
-namespace executor {
+namespace executorch {
+namespace backends {
 namespace xnnpack {
 namespace delegate {
 namespace profiling {
@@ -30,24 +30,25 @@ class XNNProfiler {
    * Initialize the profiler. This must be called after model is
    * compiled and before calling begin_execution.
    */
-  Error initialize(xnn_runtime_t runtime);
+  executorch::runtime::Error initialize(xnn_runtime_t runtime);
 
   /**
    * Start a new profiling session. This is typically invoked
    * immediately before invoking the XNNPACK runtime as part
    * of a forward pass.
    */
-  Error start(EventTracer* event_tracer);
+  executorch::runtime::Error start(
+      executorch::runtime::EventTracer* event_tracer);
 
   /**
    * End a profiling session. This is typically invoked immediately
    * after the XNNPACK runtime invocation completes.
    */
-  Error end();
+  executorch::runtime::Error end();
 
  private:
 #if defined(ET_EVENT_TRACER_ENABLED) || defined(ENABLE_XNNPACK_PROFILING)
-  EventTracer* event_tracer_;
+  executorch::runtime::EventTracer* event_tracer_;
   xnn_runtime_t runtime_;
   XNNProfilerState state_;
 
@@ -64,9 +65,9 @@ class XNNProfiler {
   std::vector<uint64_t> op_timings_sum_;
 #endif
 
-  Error get_runtime_operator_names();
-  Error get_runtime_num_operators();
-  Error get_runtime_operator_timings();
+  executorch::runtime::Error get_runtime_operator_names();
+  executorch::runtime::Error get_runtime_num_operators();
+  executorch::runtime::Error get_runtime_operator_timings();
 
   void log_operator_timings();
 
@@ -80,5 +81,5 @@ class XNNProfiler {
 } // namespace profiling
 } // namespace delegate
 } // namespace xnnpack
-} // namespace executor
-} // namespace torch
+} // namespace backends
+} // namespace executorch

backends/xnnpack/runtime/utils/utils.cpp

@@ -10,12 +10,14 @@
 #include <executorch/runtime/platform/assert.h>
 #include <cinttypes>
 
-namespace torch {
-namespace executor {
-namespace qnnpack_utils {
+namespace executorch {
+namespace backends {
+namespace xnnpack {
+namespace utils {
 
-using Tensor = exec_aten::Tensor;
-using ScalarType = exec_aten::ScalarType;
+using executorch::aten::ScalarType;
+using executorch::aten::Tensor;
+using executorch::runtime::Error;
 
 constexpr float SMALL_SCALE_THRESHOLD = 6.1e-5f;
 
@@ -222,6 +224,8 @@ void quantize_tensor_arm64_q8_wrapper<int8_t>(
   quantize_tensor_arm64_q8<int8_t, int8x8_t>(in, out, N, scale, zero_point);
 }
 #endif
-} // namespace qnnpack_utils
-} // namespace executor
-} // namespace torch
+
+} // namespace utils
+} // namespace xnnpack
+} // namespace backends
+} // namespace executorch