diff --git a/paddle/fluid/pybind/imperative.cc b/paddle/fluid/pybind/imperative.cc
index af7f03dc1971665fc7e9b539413cd5f0d7522fd9..619301e3b45d3116a545dd16ef1d5dc165a4f210 100644
--- a/paddle/fluid/pybind/imperative.cc
+++ b/paddle/fluid/pybind/imperative.cc
@@ -146,21 +146,33 @@ static const platform::Place PyObjectToPlace(const py::object &place_obj) {
   }
 }
 
-static void InitTensorForVarBase(imperative::VarBase *self,
-                                 const py::array &array,
-                                 const platform::Place place,
-                                 bool persistable = false,
-                                 bool zero_copy = false, std::string name = "",
-                                 int stop_gradient = -1) {
-  if (name == "") {
-    name =
-        imperative::GetCurrentTracer()->GenerateUniqueName("generated_tensor");
-  }
-  VLOG(5) << "Init Tensor as: / name: " << name
-          << " / persistable: " << persistable << " / zero_copy: " << zero_copy
+// only initialize varbase, but not its tensor.
+static void InitVarBaseOnly(imperative::VarBase *self, const std::string &name,
+                            bool persistable = false, int stop_gradient = -1) {
+  auto name_ = name == ""
+                   ? imperative::GetCurrentTracer()->GenerateUniqueName(
+                         "generated_tensor")
+                   : name;
+
+  VLOG(5) << "Init Tensor as: / name: " << name_
+          << " / persistable: " << persistable
           << " / stop_gradient: " << stop_gradient;
-  new (self) imperative::VarBase(name);
+  new (self) imperative::VarBase(name_);
+  if (stop_gradient != -1) {
+    self->SetOverridedStopGradient(stop_gradient);
+  }
+  self->SetPersistable(persistable);
+  self->SetType(framework::proto::VarType::LOD_TENSOR);
+}
+
+// initialize varbase and its tensor.
+static void InitVarBaseAndTensor(
+    imperative::VarBase *self, const py::array &array,
+    const platform::Place &place, const std::string &name,
+    bool persistable = false, bool zero_copy = false, int stop_gradient = -1) {
+  InitVarBaseOnly(self, name, persistable, stop_gradient);
   auto *tensor = self->MutableVar()->GetMutable<framework::LoDTensor>();
+  VLOG(4) << "zero_copy: " << zero_copy;
   if (platform::is_cpu_place(place)) {
     SetTensorFromPyArray<platform::CPUPlace>(
         tensor, array, BOOST_GET_CONST(platform::CPUPlace, place), zero_copy);
@@ -182,26 +194,15 @@ static void InitTensorForVarBase(imperative::VarBase *self,
         "Place should be one of "
         "CPUPlace/XPUPlace/CUDAPlace/CUDAPinnedPlace/NPUPlace"));
   }
-  if (stop_gradient != -1) {
-    self->SetOverridedStopGradient(stop_gradient);
-  }
-  self->SetPersistable(persistable);
-  self->SetType(framework::proto::VarType::LOD_TENSOR);
   self->SetDataType(tensor->type());
 }
 
 static void InitVarBaseFromNumpyWithKwargs(imperative::VarBase *self,
                                            const py::kwargs &kwargs) {
   VLOG(4) << "Init VarBase from kwargs: ";
-  PADDLE_ENFORCE_EQ(
-      kwargs.contains("value"), true,
-      platform::errors::NotFound(
-          "The kwargs used to create Varbase misses argument: value"));
   auto persistable = kwargs.contains("persistable")
                          ? kwargs["persistable"].cast<bool>()
                          : false;
-  auto array = kwargs.contains("value") ? kwargs["value"].cast<py::array>()
-                                        : py::array();
   auto zero_copy =
       kwargs.contains("zero_copy") ? kwargs["zero_copy"].cast<bool>() : false;
   auto name = kwargs.contains("name") ? kwargs["name"].cast<std::string>() : "";
@@ -209,10 +210,18 @@ static void InitVarBaseFromNumpyWithKwargs(imperative::VarBase *self,
                            ? kwargs["stop_gradient"].cast<int>()
                            : -1;
   auto default_place = imperative::GetCurrentTracer()->ExpectedPlace();
-  auto place = kwargs.contains("place") ? PyObjectToPlace(kwargs["place"])
-                                        : default_place;
-  InitTensorForVarBase(self, array, place, persistable, zero_copy, name,
-                       stop_gradient);
+
+  if (kwargs.contains("value")) {
+    auto array = kwargs["value"].cast<py::array>();
+    // place is only used when array is given, otherwise, it is meaningless and
+    // ignored
+    auto place = kwargs.contains("place") ? PyObjectToPlace(kwargs["place"])
+                                          : default_place;
+    InitVarBaseAndTensor(self, array, place, name, persistable, zero_copy,
+                         stop_gradient);
+  } else {
+    InitVarBaseOnly(self, name, persistable, stop_gradient);
+  }
 }
 
 template <typename P>
@@ -247,7 +256,7 @@ static void InitVarBaseFromNumpyWithArgDefault(imperative::VarBase *self,
                                                const py::array &array) {
   auto place = imperative::GetCurrentTracer()->ExpectedPlace();
   VLOG(4) << "Init VarBase from numpy at " << place;
-  InitTensorForVarBase(self, array, place);
+  InitVarBaseAndTensor(self, array, place, "");
 }
 
 static void InitVarBaseFromTensorWithArgDefault(