PaddlePaddle
diff --git a/‎paddle/fluid/framework/ir/coalesce_grad_tensor_pass.cc
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+3-3Lines changed: 3 additions & 3 deletions b/‎paddle/fluid/framework/ir/coalesce_grad_tensor_pass.cc
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+3-3Lines changed: 3 additions & 3 deletions
diff --git a/‎paddle/fluid/framework/ir/fuse_optimizer_ops_pass/fuse_optimizer_op_pass.cc
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+3-3Lines changed: 3 additions & 3 deletions b/‎paddle/fluid/framework/ir/fuse_optimizer_ops_pass/fuse_optimizer_op_pass.cc
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diff --git a/‎paddle/fluid/framework/ir/fuse_optimizer_ops_pass/fuse_optimizer_op_pass.h
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+1-1Lines changed: 1 addition & 1 deletion b/‎paddle/fluid/framework/ir/fuse_optimizer_ops_pass/fuse_optimizer_op_pass.h
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diff --git a/‎paddle/fluid/framework/ir/memory_optimize_pass/eager_deletion_pass.cc
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+5-5Lines changed: 5 additions & 5 deletions b/‎paddle/fluid/framework/ir/memory_optimize_pass/eager_deletion_pass.cc
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+5-5Lines changed: 5 additions & 5 deletions
diff --git a/‎paddle/fluid/framework/ir/pass_test_util.cc
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+17-17Lines changed: 17 additions & 17 deletions b/‎paddle/fluid/framework/ir/pass_test_util.cc
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+17-17Lines changed: 17 additions & 17 deletions
diff --git a/‎paddle/fluid/framework/ir/pass_test_util.h
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+5-5Lines changed: 5 additions & 5 deletions b/‎paddle/fluid/framework/ir/pass_test_util.h
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+5-5Lines changed: 5 additions & 5 deletions
diff --git a/‎paddle/fluid/framework/new_executor/interpreter/data_transfer.cc
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+1-1Lines changed: 1 addition & 1 deletion b/‎paddle/fluid/framework/new_executor/interpreter/data_transfer.cc
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diff --git a/‎paddle/fluid/framework/new_executor/interpreter/interpreter_util.cc
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+2-2Lines changed: 2 additions & 2 deletions b/‎paddle/fluid/framework/new_executor/interpreter/interpreter_util.cc
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diff --git a/‎paddle/fluid/framework/new_executor/pir_interpreter.cc
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+3-3Lines changed: 3 additions & 3 deletions b/‎paddle/fluid/framework/new_executor/pir_interpreter.cc
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+3-3Lines changed: 3 additions & 3 deletions
diff --git a/‎paddle/fluid/framework/new_executor/pir_interpreter.h
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+1-1Lines changed: 1 addition & 1 deletion b/‎paddle/fluid/framework/new_executor/pir_interpreter.h
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+1-1Lines changed: 1 addition & 1 deletion
@@ -94,7 +94,7 @@ class CoalesceGradTensorPass : public ir::Pass {
 
     auto vars_info = GetVarInfo(result);
     for (auto &param_grad : params_grads) {
-      if (IsLoDTensorType(GetTypeOfVar(vars_info, param_grad.second))) {
+      if (IsDenseTensorType(GetTypeOfVar(vars_info, param_grad.second))) {
         p_g_dense_grad.emplace_back(param_grad);
       } else {
         p_g_sparse_grad.emplace_back(param_grad);
@@ -172,7 +172,7 @@ class CoalesceGradTensorPass : public ir::Pass {
         pinned_var_set->insert(it->Var()->Name());
       }
       PADDLE_ENFORCE_EQ(
-          IsLoDTensorType(GetTypeOfVar(vars_info, p_g.second)),
+          IsDenseTensorType(GetTypeOfVar(vars_info, p_g.second)),
           true,
           common::errors::InvalidArgument(
               "Parameter@Grad %s is not phi::DenseTensor.", p_g.second));
@@ -464,7 +464,7 @@ class CoalesceGradTensorPass : public ir::Pass {
   }
 
  private:
-  bool IsLoDTensorType(const proto::VarType::Type &type) const {
+  bool IsDenseTensorType(const proto::VarType::Type &type) const {
     // Current only support DENSE_TENSOR.
     return type == proto::VarType::DENSE_TENSOR;
   }
 
@@ -44,7 +44,7 @@ void FuseOptimizerOpPass::ApplyImpl(ir::Graph *graph) const {
               "The %s operator has multiple gradient input. Expected "
               "it to only have one gradient input.",
               fuse_op_type));
-      if (IsLoDTensorType(GetTypeOfVar(vars_info, grad_name[0]))) {
+      if (IsDenseTensorType(GetTypeOfVar(vars_info, grad_name[0]))) {
         opt_nodes.emplace_back(node);
       }
       ++opt_ops_num;
@@ -398,7 +398,7 @@ void FuseOptimizerOpPass::FuseGradientsToContinuousSpace(
         iter->second.front()->Var(),
         common::errors::InvalidArgument("The gradient var(%s) node is null.",
                                         grad_var_name));
-    PADDLE_ENFORCE_EQ(IsLoDTensorType(iter->second.front()->Var()->GetType()),
+    PADDLE_ENFORCE_EQ(IsDenseTensorType(iter->second.front()->Var()->GetType()),
                       true,
                       common::errors::InvalidArgument(
                           "Currently the gradient(%s) type only should be "
@@ -432,7 +432,7 @@ FuseOptimizerOpPass::GetVarInfo(const Graph &result) const {
   return vars;
 }
 
-bool FuseOptimizerOpPass::IsLoDTensorType(
+bool FuseOptimizerOpPass::IsDenseTensorType(
     const proto::VarType::Type &type) const {
   // Current only support DENSE_TENSOR.
   return type == proto::VarType::DENSE_TENSOR;
 
@@ -122,7 +122,7 @@ class FuseOptimizerOpPass : public ir::Pass {
                        std::unordered_map<std::string, std::vector<std::string>>
                            *aux_var_set) const;
 
-  bool IsLoDTensorType(const proto::VarType::Type &type) const;
+  bool IsDenseTensorType(const proto::VarType::Type &type) const;
 
   bool HasVarDepsBetweenOps(const std::vector<Node *> &topo_nodes,
                             const std::vector<Node *> &opt_nodes) const;
 
@@ -46,7 +46,7 @@ static std::map<size_t, std::unordered_set<std::string>> VarsGroupByScopeIdx(
 }
 
 // Check whether the variable is phi::DenseTensor based on static VarDesc info
-static bool IsLoDTensor(VarDesc *var) {
+static bool IsDenseTensor(VarDesc *var) {
   return var->Proto()->type().type() == proto::VarType::DENSE_TENSOR;
 }
 
@@ -59,7 +59,7 @@ static int64_t GetMemorySize(
   PADDLE_ENFORCE_NOT_NULL(
       var_desc,
       common::errors::NotFound("Var(%s) can not find VarDesc.", var_name));
-  PADDLE_ENFORCE_EQ(IsLoDTensor(var_desc),
+  PADDLE_ENFORCE_EQ(IsDenseTensor(var_desc),
                     true,
                     common::errors::InvalidArgument(
                         "Var(%s) must be phi::DenseTensor.", var_name));
@@ -76,7 +76,7 @@ static int64_t GetMemorySize(
 // Non-phi::DenseTensor (e.g. SelectedRows, phi::TensorArray) Since partial GC
 // is based on static analysis of memory size of each variable So we should skip
 // SelectedRows and phi::TensorArray here
-static void SplitIntoLoDTensorAndNonLoDTensorVars(
+static void SplitIntoDenseTensorAndNonDenseTensorVars(
     const OpToVarNameSetMap &m,
     const details::GraphVars &vars,
     OpToVarNameSetMap *lod_tensors,
@@ -88,7 +88,7 @@ static void SplitIntoLoDTensorAndNonLoDTensorVars(
     for (auto var_name : op_vars_pair.second) {
       auto *var_desc = TryGetLatestVarDesc(
           vars[op_vars_pair.first->GetScopeIdx()].at(var_name));
-      if (IsLoDTensor(var_desc)) {
+      if (IsDenseTensor(var_desc)) {
         (*lod_tensors)[op_vars_pair.first].insert(var_name);
       } else {
         (*other_vars)[op_vars_pair.first].insert(var_name);
@@ -130,7 +130,7 @@ static OpToVarNameSetMap ShrinkGCVars(const OpToVarNameSetMap &m,
    * We can only calculate memory size of DenseTensors
    */
   OpToVarNameSetMap lod_tensors, other_vars;
-  SplitIntoLoDTensorAndNonLoDTensorVars(m, vars, &lod_tensors, &other_vars);
+  SplitIntoDenseTensorAndNonDenseTensorVars(m, vars, &lod_tensors, &other_vars);
 
   // Perform complete gc when fraction_of_memory_size >= 1
   if (fraction_of_memory_size >= 1.0) {
 
@@ -177,11 +177,11 @@ bool RunPassAndAssert(Graph* graph,
 }
 
 template <typename T>
-void InitLoDTensorHolder(const Scope& scope,
-                         const phi::Place& place,
-                         const std::string& var_name,
-                         const std::vector<int64_t>& dims,
-                         const T* data) {
+void InitDenseTensorHolder(const Scope& scope,
+                           const phi::Place& place,
+                           const std::string& var_name,
+                           const std::vector<int64_t>& dims,
+                           const T* data) {
   auto var = scope.FindLocalVar(var_name);
   auto tensor = var->GetMutable<phi::DenseTensor>();
   auto* tensor_mem_ptr =
@@ -194,21 +194,21 @@ void InitLoDTensorHolder(const Scope& scope,
 }
 
 // Instantiate for below data types.
-template void InitLoDTensorHolder<float>(const Scope&,
+template void InitDenseTensorHolder<float>(const Scope&,
+                                           const phi::Place&,
+                                           const std::string&,
+                                           const std::vector<int64_t>&,
+                                           const float*);
+template void InitDenseTensorHolder<int>(const Scope&,
                                          const phi::Place&,
                                          const std::string&,
                                          const std::vector<int64_t>&,
-                                         const float*);
-template void InitLoDTensorHolder<int>(const Scope&,
-                                       const phi::Place&,
-                                       const std::string&,
-                                       const std::vector<int64_t>&,
-                                       const int*);
-template void InitLoDTensorHolder<double>(const Scope&,
-                                          const phi::Place&,
-                                          const std::string&,
-                                          const std::vector<int64_t>&,
-                                          const double*);
+                                         const int*);
+template void InitDenseTensorHolder<double>(const Scope&,
+                                            const phi::Place&,
+                                            const std::string&,
+                                            const std::vector<int64_t>&,
+                                            const double*);
 
 OpDesc* GetOp(const ProgramDesc& prog,
               const std::string& op_type,
 
@@ -132,11 +132,11 @@ bool RunPassAndAssert(Graph* graph,
 /// @tparam     T         phi::DenseTensor data type.
 ///
 template <typename T>
-void InitLoDTensorHolder(const Scope& scope,
-                         const phi::Place& place,
-                         const std::string& var_name,
-                         const std::vector<int64_t>& dims,
-                         const T* data = nullptr);
+void InitDenseTensorHolder(const Scope& scope,
+                           const phi::Place& place,
+                           const std::string& var_name,
+                           const std::vector<int64_t>& dims,
+                           const T* data = nullptr);
 
 ///
 /// @brief      Retrieve operator descriptor from program.
 
@@ -775,7 +775,7 @@ void HandleComplexGradToRealGrad(const OpFuncNode& op_func_node,
         continue;
       }
       auto* grad_tensor =
-          framework::GetMutableLoDTensorOrSelectedRowsValueFromVar(grad_var);
+          framework::GetMutableDenseTensorOrSelectedRowsValueFromVar(grad_var);
       // skip nullptr tensor
       if (grad_tensor == nullptr || !grad_tensor->IsInitialized()) {
         VLOG(3) << "skip with grad_tensor not IsInitialized";
 
@@ -951,10 +951,10 @@ void BuildOpFuncList(const phi::Place& place,
           // operator.cc
           for (auto& p : m) {
             auto* transformed_tensor =
-                GetMutableLoDTensorOrSelectedRowsValueFromVar(
+                GetMutableDenseTensorOrSelectedRowsValueFromVar(
                     local_scope->FindVar(var_scope->GetNameById(p.first)));
             auto* original_tensor =
-                GetMutableLoDTensorOrSelectedRowsValueFromVar(
+                GetMutableDenseTensorOrSelectedRowsValueFromVar(
                     local_scope->FindVar(var_scope->GetNameById(p.second)));
 
             // avoid overwriting valid data
 
@@ -478,7 +478,7 @@ void PirInterpreter::CheckCUDAGraphBeforeRun(
 #endif
 }
 
-void PirInterpreter::ClearLoDTensorArrayInLocalScope() {
+void PirInterpreter::ClearDenseTensorArrayInLocalScope() {
   auto vars = local_scope_->LocalVars();
   for (auto var : vars) {
     if (var->IsType<phi::TensorArray>()) {
@@ -1544,7 +1544,7 @@ paddle::framework::FetchList PirInterpreter::Run(
   }
 
   if (HasLocalScope()) {
-    ClearLoDTensorArrayInLocalScope();
+    ClearDenseTensorArrayInLocalScope();
   }
 
   // return Fetch Tensors
@@ -1623,7 +1623,7 @@ FetchList PirInterpreter::Run(const std::vector<std::string>& feed_names,
   }
 
   if (HasLocalScope()) {
-    ClearLoDTensorArrayInLocalScope();
+    ClearDenseTensorArrayInLocalScope();
   }
 
   framework::FetchList fetch_res;
 
@@ -138,7 +138,7 @@ class PirInterpreter : public InterpreterBaseImpl {
   void CalculateLastLiveOps();
 
   // gc
-  void ClearLoDTensorArrayInLocalScope();
+  void ClearDenseTensorArrayInLocalScope();
 
   // cuda graph
   void CheckCUDAGraphBeforeRun(const std::vector<std::string>& feed_names);
Original file line number	Diff line number	Diff line change
`@@ -775,7 +775,7 @@ void HandleComplexGradToRealGrad(const OpFuncNode& op_func_node,`
`775`	`775`	`continue;`
`776`	`776`	`}`
`777`	`777`	`auto* grad_tensor =`
`778`		`- framework::GetMutableLoDTensorOrSelectedRowsValueFromVar(grad_var);`
	`778`	`+ framework::GetMutableDenseTensorOrSelectedRowsValueFromVar(grad_var);`
`779`	`779`	`// skip nullptr tensor`
`780`	`780`	`if (grad_tensor == nullptr \|\| !grad_tensor->IsInitialized()) {`
`781`	`781`	`VLOG(3) << "skip with grad_tensor not IsInitialized";`
Original file line number	Diff line number	Diff line change
`@@ -478,7 +478,7 @@ void PirInterpreter::CheckCUDAGraphBeforeRun(`
`478`	`478`	`#endif`
`479`	`479`	`}`
`480`	`480`
`481`		`-void PirInterpreter::ClearLoDTensorArrayInLocalScope() {`
	`481`	`+void PirInterpreter::ClearDenseTensorArrayInLocalScope() {`
`482`	`482`	`auto vars = local_scope_->LocalVars();`
`483`	`483`	`for (auto var : vars) {`
`484`	`484`	`if (var->IsType<phi::TensorArray>()) {`
`@@ -1544,7 +1544,7 @@ paddle::framework::FetchList PirInterpreter::Run(`
`1544`	`1544`	`}`
`1545`	`1545`
`1546`	`1546`	`if (HasLocalScope()) {`
`1547`		`- ClearLoDTensorArrayInLocalScope();`
	`1547`	`+ ClearDenseTensorArrayInLocalScope();`
`1548`	`1548`	`}`
`1549`	`1549`
`1550`	`1550`	`// return Fetch Tensors`
`@@ -1623,7 +1623,7 @@ FetchList PirInterpreter::Run(const std::vector<std::string>& feed_names,`
`1623`	`1623`	`}`
`1624`	`1624`
`1625`	`1625`	`if (HasLocalScope()) {`
`1626`		`- ClearLoDTensorArrayInLocalScope();`
	`1626`	`+ ClearDenseTensorArrayInLocalScope();`
`1627`	`1627`	`}`
`1628`	`1628`
`1629`	`1629`	`framework::FetchList fetch_res;`