PaddlePaddle
diff --git a/‎paddle/fluid/eager/to_static/run_program_op_node.h
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+30-24Lines changed: 30 additions & 24 deletions b/‎paddle/fluid/eager/to_static/run_program_op_node.h
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+30-24Lines changed: 30 additions & 24 deletions
@@ -91,39 +91,45 @@ static bool IsVariableRefArray(const Tensor &tensor) {
 
 static auto GetNameFromValue(const ::pir::Block *block,
                              const std::vector<::pir::Value> &values,
-                             bool is_input) {
+                             bool allow_input,
+                             bool allow_output) {
+  PADDLE_ENFORCE_EQ(
+      allow_input || allow_output,
+      true,
+      paddle::platform::errors::InvalidArgument(
+          "GetNameFromValue should allow input or output at least one."));
   // we use name here, later value is used directly.
   std::unordered_map<::pir::Value, std::string> value2name;
-  if (is_input) {
+  if (allow_input) {
     for (auto &kwarg : block->kwargs()) {
       value2name[kwarg.second] = kwarg.first;
     }
   }
   for (auto &op : *block) {
     std::string name;
-    if (is_input && op.name() == "pd_op.data") {
+    if (allow_input && op.name() == "pd_op.data") {
       name =
           op.attributes().at("name").dyn_cast<pir::StrAttribute>().AsString();
       value2name[op.results()[0].Value::impl()] = name;
-    } else if (!is_input && op.name() == "builtin.set_parameter") {
+    } else if (allow_output && op.name() == "builtin.set_parameter") {
       name = op.attributes()
                  .at("parameter_name")
                  .dyn_cast<pir::StrAttribute>()
                  .AsString();
       value2name[op.operand(0).source()] = name;
-    } else if (!is_input && op.name() == "builtin.shadow_output") {
+    } else if (allow_output && op.name() == "builtin.shadow_output") {
       name = op.attributes()
                  .at("output_name")
                  .dyn_cast<pir::StrAttribute>()
                  .AsString();
       value2name[op.operand(0).source()] = name;
-    } else if (is_input && op.name() == "builtin.parameter") {
+    } else if (allow_input && op.name() == "builtin.parameter") {
       name = op.attributes()
                  .at("parameter_name")
                  .dyn_cast<pir::StrAttribute>()
                  .AsString();
       value2name[op.result(0).Value::impl()] = name;
-    } else if (is_input && op.name() == "builtin.constant") {
+    } else if (allow_input && op.name() == "builtin.constant") {
       if (op.isa<pir::ConstantTensorOp>()) {
         name = op.dyn_cast<pir::ConstantTensorOp>().tensor_name();
         value2name[op.result(0).Value::impl()] = name;
@@ -248,12 +254,7 @@ static void ShareTensorsIntoScopeByValue(
     const std::vector<Tensor> &tensors,
     const std::vector<::pir::Value> &values,
     paddle::framework::Scope *scope) {
-  auto names = GetNameFromValue(block, values, true);
-  if (VLOG_IS_ON(4)) {
-    for (auto &s : names) {
-      VLOG(4) << "ShareTensorIntoScopeByValue name: " << s;
-    }
-  }
+  auto names = GetNameFromValue(block, values, true, false);
   ShareTensorsIntoScopeWithName(tensors, names, scope);
 }
 
@@ -262,11 +263,16 @@ static void ShareTensorsFromScopeByValue(
     const std::vector<Tensor *> &tensors,
     const std::vector<::pir::Value> &values,
     paddle::framework::Scope *scope) {
-  auto names = GetNameFromValue(block, values, false);
+  // NOTE(SigureMo): If the program has an inplace chain connecting
+  // an input value to an output value, the output value will be
+  // replaced with the input value, so we set the `allow_input` to
+  // `true` in `GetNameFromValue`
+  auto names = GetNameFromValue(block, values, true, true);
   for (size_t i = 0; i < tensors.size(); ++i) {
     auto &name = names[i];
     auto &value = values[i];
-    VLOG(2) << "share " << name << " from scope";
+    VLOG(4) << "Share Tensor From Scope: " << name;
+
     if (value.impl() == nullptr) {
       // skip stop_gradient.
       continue;
@@ -524,20 +530,20 @@ inline void PirRunProgramAPI(
     // *backward_program);
 
     // update interpretercore skip_gc_var
-    auto skip_names =
-        details::GetNameFromValue(forward_global_block, middle_values, false);
+    auto skip_names = details::GetNameFromValue(
+        forward_global_block, middle_values, false, true);
     auto skip_names_set =
         std::set<std::string>(skip_names.begin(), skip_names.end());
     auto no_need_buffer_values = PADDLE_GET_CONST(std::vector<::pir::Value>,
                                                   attrs.at("no_need_buffers"));
     auto no_need_buffer_names = details::GetNameFromValue(
-        forward_global_block, no_need_buffer_values, false);
+        forward_global_block, no_need_buffer_values, false, true);
     for (auto &name : no_need_buffer_names) {
       VLOG(4) << "Find no need buffer vars with name:" << name;
       skip_names_set.erase(name);
     }
-    skip_names =
-        details::GetNameFromValue(forward_global_block, output_values, false);
+    skip_names = details::GetNameFromValue(
+        forward_global_block, output_values, false, true);
     skip_names_set.insert(skip_names.begin(), skip_names.end());
     details::print_collection(skip_names_set);
     interpreter_core->SetSkipGcVars(skip_names_set);
@@ -1127,11 +1133,11 @@ inline void PirRunProgramGradAPI(
 
     // get all eager gc vars
     std::set<std::string> skip_eager_delete_vars;
-    auto skip_names =
-        details::GetNameFromValue(backward_global_block, x_grad_values, false);
+    auto skip_names = details::GetNameFromValue(
+        backward_global_block, x_grad_values, false, true);
     skip_eager_delete_vars.insert(skip_names.begin(), skip_names.end());
-    skip_names =
-        details::GetNameFromValue(backward_global_block, p_grad_values, false);
+    skip_names = details::GetNameFromValue(
+        backward_global_block, p_grad_values, false, true);
     skip_eager_delete_vars.insert(skip_names.begin(), skip_names.end());
     interpreter_core->SetSkipGcVars(skip_eager_delete_vars);
     cache.UpdateSkipEagerDeleteVars(program_id,