PaddlePaddle
diff --git a/‎paddle/fluid/ir/dialect/paddle_dialect/ir/pd_type.cc
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-13Lines changed: 0 additions & 13 deletions b/‎paddle/fluid/ir/dialect/paddle_dialect/ir/pd_type.cc
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-13Lines changed: 0 additions & 13 deletions
diff --git a/‎paddle/fluid/ir/dialect/paddle_dialect/ir/pd_type.h
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+2-21Lines changed: 2 additions & 21 deletions b/‎paddle/fluid/ir/dialect/paddle_dialect/ir/pd_type.h
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+2-21Lines changed: 2 additions & 21 deletions
diff --git a/‎paddle/fluid/ir/dialect/paddle_dialect/ir/pd_type_storage.h
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+2-104Lines changed: 2 additions & 104 deletions b/‎paddle/fluid/ir/dialect/paddle_dialect/ir/pd_type_storage.h
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+2-104Lines changed: 2 additions & 104 deletions
diff --git a/‎paddle/ir/core/CMakeLists.txt
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+1-1Lines changed: 1 addition & 1 deletion b/‎paddle/ir/core/CMakeLists.txt
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+1-1Lines changed: 1 addition & 1 deletion
diff --git a/‎paddle/ir/core/builtin_type.cc
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+16Lines changed: 16 additions & 0 deletions b/‎paddle/ir/core/builtin_type.cc
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+16Lines changed: 16 additions & 0 deletions
diff --git a/‎paddle/ir/core/builtin_type.h
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+19Lines changed: 19 additions & 0 deletions b/‎paddle/ir/core/builtin_type.h
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+19Lines changed: 19 additions & 0 deletions
@@ -16,18 +16,6 @@
 
 namespace paddle {
 namespace dialect {
-const ir::Type& DenseTensorType::dtype() const { return storage()->dtype_; }
-
-const phi::DDim& DenseTensorType::dims() const { return storage()->dims_; }
-
-const phi::DataLayout& DenseTensorType::data_layout() const {
-  return storage()->layout_;
-}
-
-const phi::LoD& DenseTensorType::lod() const { return storage()->lod_; }
-
-const size_t& DenseTensorType::offset() const { return storage()->offset_; }
-
 const ir::Type& SelectedRowsType::dtype() const { return storage()->dtype_; }
 
 const phi::DDim& SelectedRowsType::dims() const { return storage()->dims_; }
@@ -43,5 +31,4 @@ const size_t& SelectedRowsType::offset() const { return storage()->offset_; }
 }  // namespace dialect
 }  // namespace paddle
 
-IR_DEFINE_EXPLICIT_TYPE_ID(paddle::dialect::DenseTensorType)
 IR_DEFINE_EXPLICIT_TYPE_ID(paddle::dialect::SelectedRowsType)
@@ -15,30 +15,12 @@
 #pragma once
 
 #include "paddle/fluid/ir/dialect/paddle_dialect/ir/pd_type_storage.h"
+#include "paddle/ir/core/builtin_type.h"
 #include "paddle/ir/core/type.h"
 
 namespace paddle {
 namespace dialect {
-///
-/// \brief Define built-in parametric types.
-///
-class DenseTensorType : public ir::Type {
- public:
-  using Type::Type;
-
-  DECLARE_TYPE_UTILITY_FUNCTOR(DenseTensorType, DenseTensorTypeStorage);
-
-  const ir::Type &dtype() const;
-
-  const phi::DDim &dims() const;
-
-  const phi::DataLayout &data_layout() const;
-
-  const phi::LoD &lod() const;
-
-  const size_t &offset() const;
-};
-
+using DenseTensorType = ir::DenseTensorType;
 class SelectedRowsType : public ir::Type {
  public:
   using Type::Type;
@@ -59,5 +41,4 @@ class SelectedRowsType : public ir::Type {
 }  // namespace dialect
 }  // namespace paddle
 
-IR_DECLARE_EXPLICIT_TYPE_ID(paddle::dialect::DenseTensorType)
 IR_DECLARE_EXPLICIT_TYPE_ID(paddle::dialect::SelectedRowsType)
@@ -16,117 +16,15 @@
 
 #include <type_traits>
 
+#include "paddle/ir/core/builtin_type_storage.h"
 #include "paddle/ir/core/type.h"
 #include "paddle/ir/core/type_base.h"
 #include "paddle/ir/core/utils.h"
 #include "paddle/phi/core/tensor_meta.h"
 
-namespace std {
-///
-/// \brief Enable hashing std::vector<T> instances.
-///
-template <typename T>
-struct hash<std::vector<T>> {
-  std::size_t operator()(const std::vector<T>& dim) const {
-    std::size_t seed = 0;
-    for (size_t i = 0; i < dim.size(); ++i) {
-      seed ^= std::hash<T>()(dim[i]) + 0x9e3779b9 + (seed << 6) + (seed >> 2);
-    }
-    return seed;
-  }
-};
-
-}  // namespace std
-
 namespace paddle {
 namespace dialect {
-///
-/// \brief Define Parametric TypeStorage for DenseTensorType.
-///
-/// NOTE(zhangbo9674): The derived TypeStorage class needs to implement the
-/// following methods: (1)declare ParamKey, (2)define Construction method,
-/// (3)define HashValue method, (4)overload operator==.
-///
-struct DenseTensorTypeStorage : public ir::TypeStorage {
-  using DataLayout = phi::DataLayout;
-  using Dim = phi::DDim;
-  using LoD = std::vector<std::vector<size_t>>;
-  ///
-  /// \brief Declare ParamKey according to parameter type.
-  ///
-  using ParamKey =
-      std::tuple<ir::Type, phi::DDim, phi::DataLayout, phi::LoD, size_t>;
-
-  DenseTensorTypeStorage(const ir::Type& dtype,
-                         const phi::DDim& dims,
-                         const phi::DataLayout& layout,
-                         const phi::LoD& lod,
-                         size_t offset)
-      : dtype_(dtype),
-        dims_(dims),
-        layout_(layout),
-        lod_(lod),
-        offset_(offset) {}
-
-  ///
-  /// \brief Each derived TypeStorage must define a Construct method, which
-  /// StorageManager uses to construct a derived TypeStorage.
-  ///
-  static DenseTensorTypeStorage* Construct(const ParamKey& key) {
-    return new DenseTensorTypeStorage(std::get<0>(key),
-                                      std::get<1>(key),
-                                      std::get<2>(key),
-                                      std::get<3>(key),
-                                      std::get<4>(key));
-  }
-
-  ///
-  /// \brief Each derived TypeStorage must provide a HashValue method.
-  ///
-  static std::size_t HashValue(const ParamKey& key) {
-    std::size_t hash_value = 0;
-    // hash dtype
-    hash_value =
-        ir::hash_combine(hash_value, std::hash<ir::Type>()(std::get<0>(key)));
-    // hash dims
-    hash_value =
-        ir::hash_combine(hash_value, std::hash<phi::DDim>()(std::get<1>(key)));
-    // hash layout
-    hash_value = ir::hash_combine(
-        hash_value,
-        std::hash<std::underlying_type<phi::DataLayout>::type>()(
-            static_cast<std::underlying_type<phi::DataLayout>::type>(
-                std::get<2>(key))));
-    // hash lod
-    hash_value =
-        ir::hash_combine(hash_value, std::hash<phi::LoD>()(std::get<3>(key)));
-    // hash offset
-    hash_value =
-        ir::hash_combine(hash_value, std::hash<size_t>()(std::get<4>(key)));
-    return hash_value;
-  }
-
-  ///
-  /// \brief Each derived TypeStorage needs to overload operator==.
-  ///
-  bool operator==(const ParamKey& key) const {
-    return ParamKey(dtype_, dims_, layout_, lod_, offset_) == key;
-  }
-
-  ParamKey GetAsKey() const {
-    return ParamKey(dtype_, dims_, layout_, lod_, offset_);
-  }
-
-  ///
-  /// \brief DenseTensorTypeStorage include five parameters: dims, dtype,
-  /// layout, lod, offset.
-  ///
-  ir::Type dtype_;
-  phi::DDim dims_;
-  phi::DataLayout layout_;
-  phi::LoD lod_;
-  size_t offset_;
-};
+using DenseTensorTypeStorage = ir::DenseTensorTypeStorage;
 
 struct SelectedRowsTypeStorage : public ir::TypeStorage {
   using DataLayout = phi::DataLayout;
 
@@ -3,4 +3,4 @@ set(NEWIR_BINARY_DIR "${PADDLE_BINARY_DIR}/paddle/ir")
 
 file(GLOB IR_SRCS "*.cc")
 
-ir_library(ir_core SRCS ${IR_SRCS})
+ir_library(ir_core SRCS ${IR_SRCS} DEPS ddim)
@@ -17,6 +17,21 @@
 namespace ir {
 std::vector<Type> VectorType::data() const { return storage()->GetAsKey(); }
 
+const ir::Type& DenseTensorType::dtype() const { return storage()->dtype_; }
+
+const DenseTensorTypeStorage::Dim& DenseTensorType::dims() const {
+  return storage()->dims_;
+}
+
+const DenseTensorTypeStorage::DataLayout& DenseTensorType::data_layout() const {
+  return storage()->layout_;
+}
+
+const DenseTensorTypeStorage::LoD& DenseTensorType::lod() const {
+  return storage()->lod_;
+}
+
+const size_t& DenseTensorType::offset() const { return storage()->offset_; }
 }  // namespace ir
 
 IR_DEFINE_EXPLICIT_TYPE_ID(ir::UInt8Type)
@@ -33,3 +48,4 @@ IR_DEFINE_EXPLICIT_TYPE_ID(ir::IndexType)
 IR_DEFINE_EXPLICIT_TYPE_ID(ir::BoolType)
 IR_DEFINE_EXPLICIT_TYPE_ID(ir::Complex64Type)
 IR_DEFINE_EXPLICIT_TYPE_ID(ir::Complex128Type)
+IR_DEFINE_EXPLICIT_TYPE_ID(ir::DenseTensorType)
@@ -1,3 +1,4 @@
+
 // Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved.
 //
 // Licensed under the Apache License, Version 2.0 (the "License");
@@ -53,6 +54,23 @@ class IR_API VectorType : public Type {
   Type operator[](size_t index) const { return data()[index]; }
 };
 
+class DenseTensorType : public ir::Type {
+ public:
+  using Type::Type;
+
+  DECLARE_TYPE_UTILITY_FUNCTOR(DenseTensorType, DenseTensorTypeStorage);
+
+  const ir::Type &dtype() const;
+
+  const DenseTensorTypeStorage::Dim &dims() const;
+
+  const DenseTensorTypeStorage::DataLayout &data_layout() const;
+
+  const DenseTensorTypeStorage::LoD &lod() const;
+
+  const size_t &offset() const;
+};
+
 #define DECLARE_BUILTIN_TYPE(__name)                   \
   class IR_API __name : public Type {                  \
    public:                                             \
@@ -99,3 +117,4 @@ IR_EXPORT_DECLARE_EXPLICIT_TYPE_ID(ir::BoolType)
 IR_EXPORT_DECLARE_EXPLICIT_TYPE_ID(ir::IndexType)
 IR_EXPORT_DECLARE_EXPLICIT_TYPE_ID(ir::Complex64Type)
 IR_EXPORT_DECLARE_EXPLICIT_TYPE_ID(ir::Complex128Type)
+IR_EXPORT_DECLARE_EXPLICIT_TYPE_ID(ir::DenseTensorType)
Original file line number	Diff line number	Diff line change
`@@ -3,4 +3,4 @@ set(NEWIR_BINARY_DIR "${PADDLE_BINARY_DIR}/paddle/ir")`
`3`	`3`
`4`	`4`	`file(GLOB IR_SRCS "*.cc")`
`5`	`5`
`6`		`-ir_library(ir_core SRCS ${IR_SRCS})`
	`6`	`+ir_library(ir_core SRCS ${IR_SRCS} DEPS ddim)`