move sth from device_info to backends/mlu

lite/api/cxx_api_impl.cc

@@ -36,12 +36,12 @@ void CxxPaddleApiImpl::Init(const lite_api::CxxConfig &config) {
 #endif
 #ifdef LITE_WITH_MLU
   Env<TARGET(kMLU)>::Init();
-  lite::DeviceInfo::Global().SetMLURunMode(config.mlu_core_version(),
-                                           config.mlu_core_number(),
-                                           config.mlu_use_first_conv(),
-                                           config.mlu_first_conv_mean(),
-                                           config.mlu_first_conv_std(),
-                                           config.mlu_input_layout());
+  lite::TargetWrapperMlu::SetMLURunMode(config.mlu_core_version(),
+                                        config.mlu_core_number(),
+                                        config.mlu_use_first_conv(),
+                                        config.mlu_first_conv_mean(),
+                                        config.mlu_first_conv_std(),
+                                        config.mlu_input_layout());
 #endif  // LITE_WITH_MLU
   auto places = config.valid_places();
   std::vector<std::string> passes{};

lite/backends/mlu/target_wrapper.cc

@@ -36,6 +36,13 @@ void cnrtMemcpyDtoH(void* dst, const void* src, size_t size) {
 
 }  // namespace mlu
 
+thread_local cnmlCoreVersion_t TargetWrapperMlu::mlu_core_version_{CNML_MLU270};
+thread_local int TargetWrapperMlu::mlu_core_number_{1};
+thread_local bool TargetWrapperMlu::use_first_conv_{false};
+thread_local std::vector<float> TargetWrapperMlu::mean_vec_;
+thread_local std::vector<float> TargetWrapperMlu::std_vec_;
+thread_local DataLayoutType TargetWrapperMlu::input_layout_{DATALAYOUT(kNCHW)};
+
 size_t TargetWrapperMlu::num_devices() {
   uint32_t dev_count = 0;
   CNRT_CALL(cnrtGetDeviceCount(&dev_count)) << " cnrt get device count failed";
@@ -77,6 +84,47 @@ void TargetWrapperMlu::MemcpySync(void* dst,
       LOG(FATAL) << "Unsupported IoDirection" << static_cast<int>(dir);
   }
 }
+void TargetWrapperMlu::SetMLURunMode(lite_api::MLUCoreVersion core_version,
+                                     int core_number,
+                                     bool use_first_conv,
+                                     const std::vector<float>& mean_vec,
+                                     const std::vector<float>& std_vec,
+                                     DataLayoutType input_layout) {
+  switch (core_version) {
+    case (lite_api::MLUCoreVersion::MLU_220):
+      mlu_core_version_ = CNML_MLU220;
+      break;
+    case (lite_api::MLUCoreVersion::MLU_270):
+      mlu_core_version_ = CNML_MLU270;
+      break;
+    default:
+      mlu_core_version_ = CNML_MLU270;
+      break;
+  }
+  mlu_core_number_ = core_number;
+  use_first_conv_ = use_first_conv;
+  mean_vec_ = mean_vec;
+  std_vec_ = std_vec;
+  input_layout_ = input_layout;
+}
+
+cnmlCoreVersion_t TargetWrapperMlu::MLUCoreVersion() {
+  return mlu_core_version_;
+}
+
+int TargetWrapperMlu::MLUCoreNumber() { return mlu_core_number_; }
+
+bool TargetWrapperMlu::UseFirstConv() { return use_first_conv_; }
+
+// const std::vector<float>& TargetWrapperMlu::MeanVec() const { return
+// mean_vec_; }
+const std::vector<float>& TargetWrapperMlu::MeanVec() { return mean_vec_; }
+
+// const std::vector<float>& TargetWrapperMlu::StdVec() const { return std_vec_;
+// }
+const std::vector<float>& TargetWrapperMlu::StdVec() { return std_vec_; }
+
+DataLayoutType TargetWrapperMlu::InputLayout() { return input_layout_; }
 
 // void TargetWrapperMlu::MemcpyAsync(void* dst,
 //                                    const void* src,

lite/backends/mlu/target_wrapper.h

@@ -13,6 +13,7 @@
 // limitations under the License.
 
 #pragma once
+#include <vector>
 #include "lite/backends/mlu/mlu_utils.h"
 #include "lite/core/target_wrapper.h"
 
@@ -43,11 +44,32 @@ class TargetWrapper<TARGET(kMLU)> {
                          const void* src,
                          size_t size,
                          IoDirection dir);
+  static void SetMLURunMode(lite_api::MLUCoreVersion core_version,
+                            int core_number,
+                            bool use_first_conv,
+                            const std::vector<float>& mean_vec,
+                            const std::vector<float>& std_vec,
+                            DataLayoutType input_layout);
+  static cnmlCoreVersion_t MLUCoreVersion();
+  static int MLUCoreNumber();
+  static bool UseFirstConv();
+  // static const std::vector<float>& MeanVec() const;
+  // static const std::vector<float>& StdVec() const;
+  static const std::vector<float>& MeanVec();
+  static const std::vector<float>& StdVec();
+  static DataLayoutType InputLayout();
   // static void MemcpyAsync(void* dst,
   //                         const void* src,
   //                         size_t size,
   //                         IoDirection dir,
   //                         const queue_t& queue);
+ private:
+  static thread_local cnmlCoreVersion_t mlu_core_version_;
+  static thread_local int mlu_core_number_;
+  static thread_local bool use_first_conv_;
+  static thread_local std::vector<float> mean_vec_;
+  static thread_local std::vector<float> std_vec_;
+  static thread_local DataLayoutType input_layout_;
 };
 
 }  // namespace lite

lite/core/context.h

@@ -227,10 +227,12 @@ class Context<TargetType::kMLU> {
   void SetIoQueue(cnrtQueue_t queue) { io_queue_ = queue; }
 
   cnmlCoreVersion_t MLUCoreVersion() {
-    return DeviceInfo::Global().MLUCoreVersion();
+    return paddle::lite::TargetWrapperMlu::MLUCoreVersion();
   }
 
-  int MLUCoreNumber() { return DeviceInfo::Global().MLUCoreNumber(); }
+  int MLUCoreNumber() {
+    return paddle::lite::TargetWrapperMlu::MLUCoreNumber();
+  }
 
   u32_t affinity() { return affinity_; }
 

lite/core/device_info.cc

@@ -66,14 +66,14 @@ thread_local std::vector<int> DeviceInfo::active_ids_;
 thread_local TensorLite DeviceInfo::workspace_;
 thread_local int64_t DeviceInfo::count_ = 0;
 
-#ifdef LITE_WITH_MLU
-thread_local cnmlCoreVersion_t DeviceInfo::mlu_core_version_{CNML_MLU270};
-thread_local int DeviceInfo::mlu_core_number_{1};
-thread_local bool DeviceInfo::use_first_conv_{false};
-thread_local std::vector<float> DeviceInfo::mean_vec_;
-thread_local std::vector<float> DeviceInfo::std_vec_;
-thread_local DataLayoutType DeviceInfo::input_layout_{DATALAYOUT(kNCHW)};
-#endif
+// #ifdef LITE_WITH_MLU
+// thread_local cnmlCoreVersion_t DeviceInfo::mlu_core_version_{CNML_MLU270};
+// thread_local int DeviceInfo::mlu_core_number_{1};
+// thread_local bool DeviceInfo::use_first_conv_{false};
+// thread_local std::vector<float> DeviceInfo::mean_vec_;
+// thread_local std::vector<float> DeviceInfo::std_vec_;
+// thread_local DataLayoutType DeviceInfo::input_layout_{DATALAYOUT(kNCHW)};
+// #endif
 
 #ifdef TARGET_IOS
 const int DEFAULT_L1_CACHE_SIZE = 64 * 1024;
@@ -1089,44 +1089,44 @@ int DeviceInfo::Setup() {
   return 0;
 }
 
-#ifdef LITE_WITH_MLU
-void DeviceInfo::SetMLURunMode(lite_api::MLUCoreVersion core_version,
-                               int core_number,
-                               bool use_first_conv,
-                               const std::vector<float>& mean_vec,
-                               const std::vector<float>& std_vec,
-                               DataLayoutType input_layout) {
-  switch (core_version) {
-    case (lite_api::MLUCoreVersion::MLU_220):
-      mlu_core_version_ = CNML_MLU220;
-      break;
-    case (lite_api::MLUCoreVersion::MLU_270):
-      mlu_core_version_ = CNML_MLU270;
-      break;
-    default:
-      mlu_core_version_ = CNML_MLU270;
-      break;
-  }
-  mlu_core_number_ = core_number;
-  use_first_conv_ = use_first_conv;
-  mean_vec_ = mean_vec;
-  std_vec_ = std_vec;
-  input_layout_ = input_layout;
-}
-
-cnmlCoreVersion_t DeviceInfo::MLUCoreVersion() { return mlu_core_version_; }
-
-int DeviceInfo::MLUCoreNumber() { return mlu_core_number_; }
-
-bool DeviceInfo::UseFirstConv() { return use_first_conv_; }
-
-const std::vector<float>& DeviceInfo::MeanVec() const { return mean_vec_; }
-
-const std::vector<float>& DeviceInfo::StdVec() const { return std_vec_; }
-
-DataLayoutType DeviceInfo::InputLayout() const { return input_layout_; }
-
-#endif  // LITE_WITH_MLU
+// #ifdef LITE_WITH_MLU
+// void DeviceInfo::SetMLURunMode(lite_api::MLUCoreVersion core_version,
+//                                int core_number,
+//                                bool use_first_conv,
+//                                const std::vector<float>& mean_vec,
+//                                const std::vector<float>& std_vec,
+//                                DataLayoutType input_layout) {
+//   switch (core_version) {
+//     case (lite_api::MLUCoreVersion::MLU_220):
+//       mlu_core_version_ = CNML_MLU220;
+//       break;
+//     case (lite_api::MLUCoreVersion::MLU_270):
+//       mlu_core_version_ = CNML_MLU270;
+//       break;
+//     default:
+//       mlu_core_version_ = CNML_MLU270;
+//       break;
+//   }
+//   mlu_core_number_ = core_number;
+//   use_first_conv_ = use_first_conv;
+//   mean_vec_ = mean_vec;
+//   std_vec_ = std_vec;
+//   input_layout_ = input_layout;
+// }
+//
+// cnmlCoreVersion_t DeviceInfo::MLUCoreVersion() { return mlu_core_version_; }
+//
+// int DeviceInfo::MLUCoreNumber() { return mlu_core_number_; }
+//
+// bool DeviceInfo::UseFirstConv() { return use_first_conv_; }
+//
+// const std::vector<float>& DeviceInfo::MeanVec() const { return mean_vec_; }
+//
+// const std::vector<float>& DeviceInfo::StdVec() const { return std_vec_; }
+//
+// DataLayoutType DeviceInfo::InputLayout() const { return input_layout_; }
+//
+// #endif  // LITE_WITH_MLU
 
 void DeviceInfo::SetRunMode(lite_api::PowerMode mode, int thread_num) {
 #ifdef ARM_WITH_OMP

lite/core/device_info.h

@@ -55,20 +55,20 @@ class DeviceInfo {
   int Setup();
 
   void SetRunMode(lite_api::PowerMode mode, int thread_num);
-#ifdef LITE_WITH_MLU
-  void SetMLURunMode(lite_api::MLUCoreVersion core_version,
-                     int core_number,
-                     bool use_first_conv,
-                     const std::vector<float>& mean_vec,
-                     const std::vector<float>& std_vec,
-                     DataLayoutType input_layout);
-  cnmlCoreVersion_t MLUCoreVersion();
-  int MLUCoreNumber();
-  bool UseFirstConv();
-  const std::vector<float>& MeanVec() const;
-  const std::vector<float>& StdVec() const;
-  DataLayoutType InputLayout() const;
-#endif
+  // #ifdef LITE_WITH_MLU
+  //   void SetMLURunMode(lite_api::MLUCoreVersion core_version,
+  //                      int core_number,
+  //                      bool use_first_conv,
+  //                      const std::vector<float>& mean_vec,
+  //                      const std::vector<float>& std_vec,
+  //                      DataLayoutType input_layout);
+  //   cnmlCoreVersion_t MLUCoreVersion();
+  //   int MLUCoreNumber();
+  //   bool UseFirstConv();
+  //   const std::vector<float>& MeanVec() const;
+  //   const std::vector<float>& StdVec() const;
+  //   DataLayoutType InputLayout() const;
+  // #endif
   void SetCache(int l1size, int l2size, int l3size);
   void SetArch(ARMArch arch) { arch_ = arch; }
 
@@ -120,14 +120,14 @@ class DeviceInfo {
   static thread_local TensorLite workspace_;
   static thread_local int64_t count_;
 
-#ifdef LITE_WITH_MLU
-  static thread_local cnmlCoreVersion_t mlu_core_version_;
-  static thread_local int mlu_core_number_;
-  static thread_local bool use_first_conv_;
-  static thread_local std::vector<float> mean_vec_;
-  static thread_local std::vector<float> std_vec_;
-  static thread_local DataLayoutType input_layout_;
-#endif
+  // #ifdef LITE_WITH_MLU
+  //   static thread_local cnmlCoreVersion_t mlu_core_version_;
+  //   static thread_local int mlu_core_number_;
+  //   static thread_local bool use_first_conv_;
+  //   static thread_local std::vector<float> mean_vec_;
+  //   static thread_local std::vector<float> std_vec_;
+  //   static thread_local DataLayoutType input_layout_;
+  // #endif
 
   void SetDotInfo(int argc, ...);
   void SetFP16Info(int argc, ...);

lite/core/mir/mlu_postprocess_pass.cc

@@ -569,11 +569,11 @@ void MLUPostprocessPass::Apply(const std::unique_ptr<SSAGraph>& graph) {
   // 1: feed->arg_in->subgraph->... 2: ...->subgraph->arg_out->fetch;
   // arg_in and arg_out are assumed to be NHWC which user should be aware of.
   // Thus here we change these args' layout to NHWC
-  if (lite::DeviceInfo::Global().InputLayout() == DATALAYOUT(kNHWC)) {
+  if (lite::TargetWrapperMlu::InputLayout() == DATALAYOUT(kNHWC)) {
     ModifyLayout(graph.get());
   }
 
-  if (lite::DeviceInfo::Global().UseFirstConv()) {
+  if (lite::TargetWrapperMlu::UseFirstConv()) {
     GatherAndModifyFirstConvNodes(graph.get());
   }
 

lite/kernels/mlu/bridges/conv_op.cc

@@ -164,7 +164,7 @@ int ConvConverter(void* ctx, OpLite* op, KernelBase* kernel) {
   const auto input_scale = op_info->GetAttr<float>("input_scale");
 
   bool use_first_conv = false;
-  if (lite::DeviceInfo::Global().UseFirstConv() && input_dims[1] == 3) {
+  if (lite::TargetWrapperMlu::UseFirstConv() && input_dims[1] == 3) {
     use_first_conv = true;
   }
 
@@ -192,11 +192,11 @@ int ConvConverter(void* ctx, OpLite* op, KernelBase* kernel) {
                                            graph->FPType());
 
     graph->BindConstRawData("first_conv_mean_tensor",
-                            lite::DeviceInfo::Global().MeanVec().data(),
+                            lite::TargetWrapperMlu::MeanVec().data(),
                             3,
                             false);
     graph->BindConstRawData("first_conv_std_tensor",
-                            lite::DeviceInfo::Global().StdVec().data(),
+                            lite::TargetWrapperMlu::StdVec().data(),
                             3,
                             false);