diff --git a/python/paddle/fluid/dygraph/io.py b/python/paddle/fluid/dygraph/io.py
index 3fd690cab058ae19cb26117c7665876284a925c8..9ffdea969be5d4691e3fbf271f17d08db6667647 100644
--- a/python/paddle/fluid/dygraph/io.py
+++ b/python/paddle/fluid/dygraph/io.py
@@ -1077,8 +1077,13 @@ def append_var_from_block_desc_static(block,
             else:
                 lod_level = None
 
+            if var_desc.persistable():
+                current_block = block.program.global_block()
+            else:
+                current_block = block
+
             vars_append.append(
-                block.create_var(
+                current_block.create_var(
                     name=var_desc.name(),
                     dtype=data_type,
                     type=var_type,
diff --git a/python/paddle/fluid/dygraph/layers.py b/python/paddle/fluid/dygraph/layers.py
index df2a00978aa6751877a3b9d940e32db6da79afda..1985a4ebb9256f47c6c46681c392cd9e398b12d0 100644
--- a/python/paddle/fluid/dygraph/layers.py
+++ b/python/paddle/fluid/dygraph/layers.py
@@ -31,7 +31,7 @@ from .. import unique_name
 from paddle.fluid import core
 from .layer_object_helper import LayerObjectHelper
 from .layer_hooks import record_program_ops_pre_hook, set_op_customized_attrs_post_hook, LayerOpsRecoder
-from .base import program_desc_tracing_guard, param_guard, in_declarative_mode
+from .base import program_desc_tracing_guard, param_guard, in_declarative_mode, _convert_into_variable
 from paddle.fluid import framework
 from ..param_attr import ParamAttr
 from paddle.fluid.executor import Executor, global_scope
@@ -914,16 +914,7 @@ class Layer(object):
         return outputs
 
     def __call__(self, *inputs, **kwargs):
-        # NOTE(Aurelius84): Why we still need param_guard here?
-        # In case of ControlFlow, true_fn and false_fn will contain
-        # parameters that may not trigger logic of `Operator` to create
-        # them. we add this to make sure all parameters is available.
-
-        if in_declarative_mode() and not framework.in_dygraph_mode():
-            with param_guard(self._parameters), param_guard(self._buffers):
-                return self._dygraph_call_func(*inputs, **kwargs)
-        else:
-            return self._dygraph_call_func(*inputs, **kwargs)
+        return self._dygraph_call_func(*inputs, **kwargs)
 
     def forward(self, *inputs, **kwargs):
         """
@@ -1103,6 +1094,8 @@ class Layer(object):
         if '_parameters' in self.__dict__:
             _parameters = self.__dict__['_parameters']
             if name in self._parameters:
+                if in_declarative_mode() and not framework.in_dygraph_mode():
+                    return _convert_into_variable(self._parameters[name])
                 return self._parameters[name]
         if '_sub_layers' in self.__dict__:
             _sub_layers = self.__dict__['_sub_layers']
@@ -1111,6 +1104,8 @@ class Layer(object):
         if '_buffers' in self.__dict__:
             _buffers = self.__dict__['_buffers']
             if name in _buffers:
+                if in_declarative_mode() and not framework.in_dygraph_mode():
+                    return _convert_into_variable(_buffers[name])
                 return _buffers[name]
         return object.__getattribute__(self, name)
 
diff --git a/python/paddle/fluid/tests/unittests/dygraph_to_static/test_declarative.py b/python/paddle/fluid/tests/unittests/dygraph_to_static/test_declarative.py
index 91086c31a396a66c02815b943df3f20811b54d06..1c2ac34e1b501d65bba35a1ec4daa67f1d6ea618 100644
--- a/python/paddle/fluid/tests/unittests/dygraph_to_static/test_declarative.py
+++ b/python/paddle/fluid/tests/unittests/dygraph_to_static/test_declarative.py
@@ -379,5 +379,34 @@ class TestErrorWithInitFromStaticMode(unittest.TestCase):
             net.forward.outputs
 
 
+class CallNonForwardFuncNet(paddle.nn.Layer):
+    def __init__(self):
+        super(CallNonForwardFuncNet, self).__init__()
+        self.sub = CallNonForwardFuncSubNet()
+
+    @paddle.jit.to_static
+    def forward(self):
+        return self.sub.func()
+
+
+class CallNonForwardFuncSubNet(paddle.nn.Layer):
+    def __init__(self):
+        super(CallNonForwardFuncSubNet, self).__init__()
+        self.a = paddle.to_tensor([1, 2])
+
+    def func(self):
+        x = self.a * 2
+        return x
+
+
+class TestCallNonForwardFunc(unittest.TestCase):
+    def test_call_non_forward(self):
+        paddle.disable_static()
+        net = CallNonForwardFuncNet()
+        out = net()
+        self.assertEqual(out.numpy().tolist(), [2, 4])
+        paddle.enable_static()
+
+
 if __name__ == '__main__':
     unittest.main()