diff --git a/paddle/fluid/pybind/eager_method.cc b/paddle/fluid/pybind/eager_method.cc
index 5233bbc832935fd5887896d89073e105a42507dd..04820bdb30e7d994a9d99be0f59af50848349125 100644
--- a/paddle/fluid/pybind/eager_method.cc
+++ b/paddle/fluid/pybind/eager_method.cc
@@ -445,6 +445,24 @@ static PyObject* tensor_method_copy_(TensorObject* self,
   EAGER_CATCH_AND_THROW_RETURN_NULL
 }
 
+static PyObject* tensor_method_clone(TensorObject* self,
+                                     PyObject* args,
+                                     PyObject* kwargs) {
+  EAGER_TRY
+
+  PADDLE_ENFORCE_EQ(
+      self->tensor.initialized(),
+      true,
+      paddle::platform::errors::InvalidArgument(
+          "We can only support initialized tensor in clone, however we got "
+          "uninitialized tensor %s, please check your code.",
+          self->tensor.name()));
+
+  auto out = assign_ad_func(self->tensor);
+  return ToPyObject(out);
+  EAGER_CATCH_AND_THROW_RETURN_NULL
+}
+
 static PyObject* tensor_retain_grads(TensorObject* self,
                                      PyObject* args,
                                      PyObject* kwargs) {
@@ -1854,6 +1872,10 @@ PyMethodDef variable_methods[] = {
      (PyCFunction)(void (*)(void))tensor_method_copy_,
      METH_VARARGS | METH_KEYWORDS,
      NULL},
+    {"clone",
+     (PyCFunction)(void (*)(void))tensor_method_clone,
+     METH_VARARGS | METH_KEYWORDS,
+     NULL},
     {"reconstruct_from_",
      (PyCFunction)(void (*)(void))tensor_method_reconstruct_from_,
      METH_VARARGS | METH_KEYWORDS,
diff --git a/python/paddle/fluid/dygraph/varbase_patch_methods.py b/python/paddle/fluid/dygraph/varbase_patch_methods.py
index cb6907d842ca6a9b990064fb8db943fedcda9193..61c856c071207287fafbb0e681dba3b0424b8acb 100644
--- a/python/paddle/fluid/dygraph/varbase_patch_methods.py
+++ b/python/paddle/fluid/dygraph/varbase_patch_methods.py
@@ -815,17 +815,6 @@ def monkey_patch_varbase():
             raise TypeError(
                 "_set_grad_ivar is only supported for Parameter Tensor")
 
-    @framework.dygraph_only
-    def clone(self):
-        if in_dygraph_mode():
-            return _C_ops.assign(self)
-
-        if _in_legacy_dygraph():
-            output = core.VarBase()
-        else:
-            output = core.eager.Tensor()
-        return _legacy_C_ops.assign(self, output)
-
     @framework.dygraph_only
     def value(self):
         return self
@@ -1009,7 +998,6 @@ def monkey_patch_varbase():
     if framework._in_eager_mode_:
         setattr(core.eager.Tensor, "_grad_ivar", _grad_ivar)
         setattr(core.eager.Tensor, "_set_grad_ivar", _set_grad_ivar)
-        setattr(core.eager.Tensor, "clone", clone)
         setattr(core.eager.Tensor, "value", value)
         setattr(core.eager.Tensor, "cpu", cpu)
         setattr(core.eager.Tensor, "cuda", cuda)