diff --git a/paddle/fluid/lite/core/kernel.h b/paddle/fluid/lite/core/kernel.h
index 6bba59263ace64884d4737ca490855d8ae964f1a..d3308d016f26cd1fc44926fa126a20cdfd63c1eb 100644
--- a/paddle/fluid/lite/core/kernel.h
+++ b/paddle/fluid/lite/core/kernel.h
@@ -45,9 +45,9 @@ class KernelBase {
     param_.set<T>(param);
   }
 
-  template <typename Param>
-  Param& param() const {
-    return param_.get<Param>();
+  template <typename P>
+  P& Param() const {
+    return param_.get<P>();
   }
 
   void set_op_type(const std::string& type) { op_type_ = type; }
@@ -71,161 +71,6 @@ class KernelBase {
   std::string op_type_;
 };
 
-/*
- * ParamType is used to represent a data type of a parameter for the kernel. It
- * can represent any Variable data type.
- * The element_type_hash is the hash code of the element, it should be
- * registered in the `TypeSystem`.
- */
-struct ParamType {
-  // For unsupported types.
-  size_t element_type_hash{};
-  Place tensor_place{};
-  const Type* type_;
-
-  explicit ParamType() = default;
-  explicit ParamType(size_t element_type_hash)
-      : element_type_hash(element_type_hash) {}
-  ParamType(size_t element_type_hash, const Place& place)
-      : element_type_hash(element_type_hash), tensor_place(place) {}
-  ParamType(const Type* type) : type_(type) { tensor_place = type_->place(); }
-
-  std::string DebugString() const { return tensor_place.DebugString(); }
-};
-
-/*
- * The data types of kernel parameters. It is used to track the type of kernel's
- * inputs and outputs.
- */
-struct ParamTypeRecorder {
-  std::map<std::string, ParamType> inputs;
-  std::map<std::string, ParamType> outputs;
-
-  void RegisterInputType(const std::string& arg_name, const ParamType& type) {
-    Register(&inputs, arg_name, type);
-  }
-
-  void RegisterOutputType(const std::string& arg_name, const ParamType& type) {
-    Register(&outputs, arg_name, type);
-  }
-
- private:
-  void Register(std::map<std::string, ParamType>* ts,
-                const std::string& arg_name, ParamType type) {
-    (*ts)[arg_name] = type;
-  }
-};
-
-/*
- * The ParamTypeRegistry help register the input and output data types for all
- * the kernels. It is made singleton so that all the objects of the same kernel
- * can share the same information.
- *
- * Usage:
- * for register a kernel for FC operator.
- * ParamTypeRegistry::Global().Register(
- *        "fc", {TARGET(kCUDA), PRECISION(kFloat)}, 0,
- *        {typeid(Tensor), {TARGET(kCUDA)}});
- */
-class ParamTypeRegistry {
- public:
-  enum class IO : int { kInput = 0, kOutput };
-
-  template <TargetType target, PrecisionType precision,
-            DataLayoutType layout = DataLayoutType::kNCHW>
-  /*
-   * Helper class for registering a ParamType for a Kernel.
-   * Usage:
-   *
-   * NewInstance<TARGET(kHost), PRECISION(kFloat)>("fc")
-   *   .BindInput(0, {typeid(Tensor).hash_code(), {TARGET(kHost)})
-   *   .BindInput(1, {typeid(Tensor).hash_code(), {TARGET(kHost),
-   *                                               PRECISION(kFloat)});
-   */
-  struct NewInstance {
-    explicit NewInstance(const std::string& kernel_type)
-        : kernel_type_(kernel_type) {}
-
-    NewInstance& BindInput(const std::string& arg_name,
-                           const ParamType& ptype) {
-      ParamTypeRegistry::Global().Register<IO::kInput>(
-          kernel_type_, Place{target, precision, layout}, arg_name, ptype);
-      return *this;
-    }
-    NewInstance& BindOutput(const std::string& arg_name,
-                            const ParamType& ptype) {
-      ParamTypeRegistry::Global().Register<IO::kOutput>(
-          kernel_type_, Place{target, precision, layout}, arg_name, ptype);
-      return *this;
-    }
-
-    bool Finalize() { return true; }
-
-   private:
-    std::string kernel_type_;
-  };
-
-  template <IO io>
-  void Register(const std::string& kernel_type, const Place& place,
-                const std::string& arg_name, ParamType data_type) {
-    KernelIdTy key{kernel_type, place, io, arg_name};
-    types_[key] = data_type;
-    CHECK(types_.count(key));
-  }
-
-  template <IO io>
-  const ParamType* Retrieve(const Place& place, const std::string& op_type,
-                            const std::string& arg_name) {
-    KernelIdTy key{op_type, place, io, arg_name};
-    auto it = types_.find(key);
-    if (it == types_.end()) return nullptr;
-    return &it->second;
-  }
-
-  static ParamTypeRegistry& Global() {
-    static ParamTypeRegistry x;
-    return x;
-  }
-
-  friend std::ostream& operator<<(std::ostream& os,
-                                  const ParamTypeRegistry& other) {
-    for (auto& item : other.types_) {
-      os << item.first << " " << item.second.DebugString() << "\n";
-    }
-    return os;
-  }
-
- private:
-  ParamTypeRegistry() = default;
-
- public:
-  // Identification for a Kernel.
-  struct KernelIdTy {
-    std::string kernel_type;
-    Place place;
-    IO io;
-    std::string arg_name;
-
-    size_t hash() const {
-      std::hash<std::string> h;
-      size_t hash = h(kernel_type);
-      hash = hash_combine(hash, place.hash());
-      hash = hash_combine(hash, std::hash<int>()(static_cast<int>(io)));
-      hash = hash_combine(hash, std::hash<std::string>()(arg_name));
-      return hash;
-    }
-    friend std::ostream& operator<<(std::ostream& os, const KernelIdTy& other);
-  };
-
-  using key_t = KernelIdTy;
-  struct KeyCmp {
-    bool operator()(const key_t& a, const key_t& b) const;
-  };
-
- private:
-  std::map<key_t, ParamType, ParamTypeRegistry::KeyCmp> types_;
-};
-
 // Light-weight kernel implementation.
 // The OpKernel is designed to implement the specific algorithm on a target
 // device.
diff --git a/paddle/fluid/lite/core/kernel_test.cc b/paddle/fluid/lite/core/kernel_test.cc
index 7be5f8714c4af5066e27619b8ac8e8e742539c64..bf23990c8f369b9ac658ad31c26c083b49239c0e 100644
--- a/paddle/fluid/lite/core/kernel_test.cc
+++ b/paddle/fluid/lite/core/kernel_test.cc
@@ -25,8 +25,8 @@ class SomeKernel : public OpKernel<TARGET(kHost), PRECISION(kFloat)> {
  public:
   void Run() override {
     LOG(INFO) << "SomeKernel executed";
-    LOG(INFO) << param<operators::FcParam>().in_num_col_dims;
-    test_code = param<operators::FcParam>().in_num_col_dims;
+    LOG(INFO) << Param<operators::FcParam>().in_num_col_dims;
+    test_code = Param<operators::FcParam>().in_num_col_dims;
   }
 
   TargetType target() const override { return TARGET(kHost); }
diff --git a/paddle/fluid/lite/core/type_system.h b/paddle/fluid/lite/core/type_system.h
index d9107afff8d21714137d12110e302412be7cf42b..05240e2943aa94293515887146d6bddc13a0370e 100644
--- a/paddle/fluid/lite/core/type_system.h
+++ b/paddle/fluid/lite/core/type_system.h
@@ -21,12 +21,14 @@
 // for analysis and runtime.
 
 #include <glog/logging.h>
+#include <map>
 #include <string>
 #include <typeinfo>
 #include <unordered_map>
 #include <unordered_set>
 #include <vector>
 #include "paddle/fluid/lite/core/tensor.h"
+#include "paddle/fluid/lite/utils/all.h"
 
 namespace paddle {
 namespace lite {
@@ -202,5 +204,160 @@ class TypeSystem {
   std::unordered_set<std::string> names_;
 };
 
+/*
+ * ParamType is used to represent a data type of a parameter for the kernel. It
+ * can represent any Variable data type.
+ * The element_type_hash is the hash code of the element, it should be
+ * registered in the `TypeSystem`.
+ */
+struct ParamType {
+  // For unsupported types.
+  size_t element_type_hash{};
+  Place tensor_place{};
+  const Type* type_;
+
+  explicit ParamType() = default;
+  explicit ParamType(size_t element_type_hash)
+      : element_type_hash(element_type_hash) {}
+  ParamType(size_t element_type_hash, const Place& place)
+      : element_type_hash(element_type_hash), tensor_place(place) {}
+  ParamType(const Type* type) : type_(type) { tensor_place = type_->place(); }
+
+  std::string DebugString() const { return tensor_place.DebugString(); }
+};
+
+/*
+ * The data types of kernel parameters. It is used to track the type of kernel's
+ * inputs and outputs.
+ */
+struct ParamTypeRecorder {
+  std::map<std::string, ParamType> inputs;
+  std::map<std::string, ParamType> outputs;
+
+  void RegisterInputType(const std::string& arg_name, const ParamType& type) {
+    Register(&inputs, arg_name, type);
+  }
+
+  void RegisterOutputType(const std::string& arg_name, const ParamType& type) {
+    Register(&outputs, arg_name, type);
+  }
+
+ private:
+  void Register(std::map<std::string, ParamType>* ts,
+                const std::string& arg_name, ParamType type) {
+    (*ts)[arg_name] = type;
+  }
+};
+
+/*
+ * The ParamTypeRegistry help register the input and output data types for all
+ * the kernels. It is made singleton so that all the objects of the same kernel
+ * can share the same information.
+ *
+ * Usage:
+ * for register a kernel for FC operator.
+ * ParamTypeRegistry::Global().Register(
+ *        "fc", {TARGET(kCUDA), PRECISION(kFloat)}, 0,
+ *        {typeid(Tensor), {TARGET(kCUDA)}});
+ */
+class ParamTypeRegistry {
+ public:
+  enum class IO : int { kInput = 0, kOutput };
+
+  template <TargetType target, PrecisionType precision,
+            DataLayoutType layout = DataLayoutType::kNCHW>
+  /*
+   * Helper class for registering a ParamType for a Kernel.
+   * Usage:
+   *
+   * NewInstance<TARGET(kHost), PRECISION(kFloat)>("fc")
+   *   .BindInput(0, {typeid(Tensor).hash_code(), {TARGET(kHost)})
+   *   .BindInput(1, {typeid(Tensor).hash_code(), {TARGET(kHost),
+   *                                               PRECISION(kFloat)});
+   */
+  struct NewInstance {
+    explicit NewInstance(const std::string& kernel_type)
+        : kernel_type_(kernel_type) {}
+
+    NewInstance& BindInput(const std::string& arg_name,
+                           const ParamType& ptype) {
+      ParamTypeRegistry::Global().Register<IO::kInput>(
+          kernel_type_, Place{target, precision, layout}, arg_name, ptype);
+      return *this;
+    }
+    NewInstance& BindOutput(const std::string& arg_name,
+                            const ParamType& ptype) {
+      ParamTypeRegistry::Global().Register<IO::kOutput>(
+          kernel_type_, Place{target, precision, layout}, arg_name, ptype);
+      return *this;
+    }
+
+    bool Finalize() { return true; }
+
+   private:
+    std::string kernel_type_;
+  };
+
+  template <IO io>
+  void Register(const std::string& kernel_type, const Place& place,
+                const std::string& arg_name, ParamType data_type) {
+    KernelIdTy key{kernel_type, place, io, arg_name};
+    types_[key] = data_type;
+    CHECK(types_.count(key));
+  }
+
+  template <IO io>
+  const ParamType* Retrieve(const Place& place, const std::string& op_type,
+                            const std::string& arg_name) {
+    KernelIdTy key{op_type, place, io, arg_name};
+    auto it = types_.find(key);
+    if (it == types_.end()) return nullptr;
+    return &it->second;
+  }
+
+  static ParamTypeRegistry& Global() {
+    static ParamTypeRegistry x;
+    return x;
+  }
+
+  friend std::ostream& operator<<(std::ostream& os,
+                                  const ParamTypeRegistry& other) {
+    for (auto& item : other.types_) {
+      os << item.first << " " << item.second.DebugString() << "\n";
+    }
+    return os;
+  }
+
+ private:
+  ParamTypeRegistry() = default;
+
+ public:
+  // Identification for a Kernel.
+  struct KernelIdTy {
+    std::string kernel_type;
+    Place place;
+    IO io;
+    std::string arg_name;
+
+    size_t hash() const {
+      std::hash<std::string> h;
+      size_t hash = h(kernel_type);
+      hash = hash_combine(hash, place.hash());
+      hash = hash_combine(hash, std::hash<int>()(static_cast<int>(io)));
+      hash = hash_combine(hash, std::hash<std::string>()(arg_name));
+      return hash;
+    }
+    friend std::ostream& operator<<(std::ostream& os, const KernelIdTy& other);
+  };
+
+  using key_t = KernelIdTy;
+  struct KeyCmp {
+    bool operator()(const key_t& a, const key_t& b) const;
+  };
+
+ private:
+  std::map<key_t, ParamType, ParamTypeRegistry::KeyCmp> types_;
+};
+
 }  // namespace lite
 }  // namespace paddle