Migrate backends/qualcomm to the new namespace (#6025)

Summary:
Pull Request resolved: #6025

Move the qualcomm backend out of the `torch::` namespace, and update to avoid using the `torch::` or `exec_aten::` namespaces.

Differential Revision: D64073805

Author: dbort

backends/qualcomm/aot/ir/qcir_utils.cpp

@@ -11,8 +11,8 @@
 
 #include <unordered_map>
 
-namespace torch {
-namespace executor {
+namespace executorch {
+namespace backends {
 namespace qnn {
 
 qcir::TensorType ToTensorType(Qnn_TensorType_t type) {
@@ -278,5 +278,5 @@ Qnn_Tensor_t ToTensor(const tensor_type& tensor) {
 }
 
 } // namespace qnn
-} // namespace executor
-} // namespace torch
+} // namespace backends
+} // namespace executorch

backends/qualcomm/aot/ir/qcir_utils.h

@@ -11,8 +11,8 @@
 #include <executorch/backends/qualcomm/aot/ir/qcir_generated.h>
 #include "QnnTypes.h"
 
-namespace torch {
-namespace executor {
+namespace executorch {
+namespace backends {
 namespace qnn {
 
 typedef flatbuffers::Vector<::flatbuffers::Offset<qcir::Tensor>>::return_type
@@ -36,5 +36,5 @@ flatbuffers::Offset<qcir::Tensor> ToTensor(
 Qnn_Tensor_t ToTensor(const tensor_type& tensor);
 
 } // namespace qnn
-} // namespace executor
-} // namespace torch
+} // namespace backends
+} // namespace executorch

backends/qualcomm/aot/python/PyQnnManagerAdaptor.cpp

@@ -9,9 +9,12 @@
 #include <pybind11/pybind11.h>
 
 namespace py = pybind11;
-namespace torch {
-namespace executor {
+namespace executorch {
+namespace backends {
 namespace qnn {
+
+using executorch::runtime::Error;
+
 PYBIND11_MODULE(PyQnnManagerAdaptor, m) {
   // TODO: Add related documents for configurations listed below
   using namespace qnn_delegate;
@@ -39,5 +42,5 @@ PYBIND11_MODULE(PyQnnManagerAdaptor, m) {
       .def("GetSpillFillBufferSize", &PyQnnManager::GetSpillFillBufferSize);
 }
 } // namespace qnn
-} // namespace executor
-} // namespace torch
+} // namespace backends
+} // namespace executorch

backends/qualcomm/aot/python/PyQnnManagerAdaptor.h

@@ -19,8 +19,8 @@
 #include <string_view>
 
 namespace py = pybind11;
-namespace torch {
-namespace executor {
+namespace executorch {
+namespace backends {
 namespace qnn {
 class PyQnnManager {
  public:
@@ -48,7 +48,7 @@ class PyQnnManager {
         qnn_executorch_options, qnn_executorch_context_binary_);
   }
 
-  Error Init() {
+  executorch::runtime::Error Init() {
     return qnn_manager_->Init();
   }
   bool IsNodeSupportedByBackend(
@@ -97,8 +97,8 @@ class PyQnnManager {
             wrapper->SetName(param->GetName());
             set_tensor(wrapper, params);
           } else {
-            Error err = param->PopulateQnnParam();
-            if (err != Error::Ok) {
+            executorch::runtime::Error err = param->PopulateQnnParam();
+            if (err != executorch::runtime::Error::Ok) {
               QNN_EXECUTORCH_LOG_ERROR(
                   "Fail to get scalar parameter in online prepare stage");
               return py::array_t<char>(0);
@@ -131,7 +131,8 @@ class PyQnnManager {
       context_binary.buffer = builder.GetBufferPointer();
       context_binary.nbytes = builder.GetSize();
     } else if (
-        qnn_manager_->Compile(op_wrappers, context_binary) != Error::Ok) {
+        qnn_manager_->Compile(op_wrappers, context_binary) !=
+        executorch::runtime::Error::Ok) {
       return py::array_t<char>(0);
     }
 
@@ -155,7 +156,7 @@ class PyQnnManager {
     return qnn_manager_->IsTensorDump();
   }
 
-  Error AllocateTensor() {
+  executorch::runtime::Error AllocateTensor() {
     return qnn_manager_->AllocateTensor();
   }
 
@@ -189,5 +190,5 @@ class PyQnnManager {
   std::shared_ptr<QnnManager> qnn_manager_;
 };
 } // namespace qnn
-} // namespace executor
-} // namespace torch
+} // namespace backends
+} // namespace executorch

backends/qualcomm/aot/python/PyQnnWrapperAdaptor.cpp

@@ -15,8 +15,8 @@
 #include <string>
 
 namespace py = pybind11;
-namespace torch {
-namespace executor {
+namespace executorch {
+namespace backends {
 namespace qnn {
 std::unique_ptr<QuantizeParamsWrapper> CreateQuantizationParamWrapper(
     const Qnn_QuantizationEncoding_t& encoding,
@@ -250,5 +250,5 @@ PYBIND11_MODULE(PyQnnWrapperAdaptor, m) {
       .def("GetEncodings", &PyQnnTensorWrapper::GetEncodings);
 }
 } // namespace qnn
-} // namespace executor
-} // namespace torch
+} // namespace backends
+} // namespace executorch

backends/qualcomm/aot/python/PyQnnWrapperAdaptor.h

@@ -14,8 +14,8 @@
 #include <pybind11/pybind11.h>
 #include <pybind11/stl.h>
 namespace py = pybind11;
-namespace torch {
-namespace executor {
+namespace executorch {
+namespace backends {
 namespace qnn {
 class PyQnnOpWrapper {
  public:
@@ -183,5 +183,5 @@ class PyQnnTensorWrapper {
   std::shared_ptr<TensorWrapper> tensor_wrapper_;
 };
 } // namespace qnn
-} // namespace executor
-} // namespace torch
+} // namespace backends
+} // namespace executorch

backends/qualcomm/aot/wrappers/OpWrapper.cpp

@@ -6,8 +6,8 @@
  * LICENSE file in the root directory of this source tree.
  */
 #include <executorch/backends/qualcomm/aot/wrappers/OpWrapper.h>
-namespace torch {
-namespace executor {
+namespace executorch {
+namespace backends {
 namespace qnn {
 Qnn_OpConfig_t OpWrapper::GetOpConfig() {
   param_types_.clear();
@@ -44,5 +44,5 @@ Qnn_OpConfig_t OpWrapper::GetOpConfig() {
   return ret;
 }
 } // namespace qnn
-} // namespace executor
-} // namespace torch
+} // namespace backends
+} // namespace executorch

backends/qualcomm/aot/wrappers/OpWrapper.h

@@ -17,8 +17,8 @@
 #include <memory>
 #include <sstream>
 #include <typeinfo>
-namespace torch {
-namespace executor {
+namespace executorch {
+namespace backends {
 namespace qnn {
 class OpWrapper final {
  public:
@@ -116,5 +116,5 @@ class OpWrapper final {
   std::vector<Qnn_Param_t> param_types_;
 };
 } // namespace qnn
-} // namespace executor
-} // namespace torch
+} // namespace backends
+} // namespace executorch

backends/qualcomm/aot/wrappers/ParamWrapper.h

@@ -13,14 +13,17 @@
 #include <utility>
 
 #include "QnnTypes.h"
-namespace torch {
-namespace executor {
+namespace executorch {
+namespace backends {
 namespace qnn {
+
+using executorch::runtime::Error;
+
 class ParamWrapper {
  public:
   // Populate Qnn_Param_t. Return an error code Error::Ok if succeeded,
   // Error::Internal if failed
-  virtual Error PopulateQnnParam() = 0;
+  virtual executorch::runtime::Error PopulateQnnParam() = 0;
   virtual ~ParamWrapper() = default;
 
   ParamWrapper(const ParamWrapper& rhs) = default;
@@ -50,5 +53,5 @@ class ParamWrapper {
   std::string name_;
 };
 } // namespace qnn
-} // namespace executor
-} // namespace torch
+} // namespace backends
+} // namespace executorch

backends/qualcomm/aot/wrappers/QuantizeParamsWrapper.cpp

@@ -7,8 +7,8 @@
  */
 #include <executorch/backends/qualcomm/aot/wrappers/QuantizeParamsWrapper.h>
 #include <executorch/backends/qualcomm/runtime/Logging.h>
-namespace torch {
-namespace executor {
+namespace executorch {
+namespace backends {
 namespace qnn {
 std::unique_ptr<QuantizeParamsWrapper> CreateQuantizationParamWrapper(
     const Qnn_QuantizeParams_t& quantization) {
@@ -69,5 +69,5 @@ std::unique_ptr<QuantizeParamsWrapper> CreateQuantizationParamWrapper(
   return quantize_param_wrapper;
 }
 } // namespace qnn
-} // namespace executor
-} // namespace torch
+} // namespace backends
+} // namespace executorch