diff --git a/paddle/fluid/framework/operator.cc b/paddle/fluid/framework/operator.cc
index 96339412e6b6d8c08fd771793018599fcbdf6b92..019ad295cc455634265154ed9d8510b30c80b46c 100644
--- a/paddle/fluid/framework/operator.cc
+++ b/paddle/fluid/framework/operator.cc
@@ -414,34 +414,12 @@ Tensor* GetMutableLoDTensorOrSelectedRowsValueFromVar(Variable* var) {
 }
 
 bool ExecutionContext::HasInput(const std::string& name) const {
-  if (!op_.HasInputs(name)) {
-    return false;
-  }
-  auto& ins = Inputs(name);
-  size_t length = ins.size();
-  if (length == 0) {
-    return false;
-  }
-  PADDLE_ENFORCE_EQ(length, 1UL,
-                    "Input %s should not have more than one inputs", name);
-  auto arg = ins[0];
-  auto* var = arg == kEmptyVarName ? nullptr : scope_.FindVar(arg);
+  auto* var = InputVar(name);
   return var != nullptr;
 }
 
 bool ExecutionContext::HasOutput(const std::string& name) const {
-  if (!op_.HasOutputs(name)) {
-    return false;
-  }
-  auto& outs = Outputs(name);
-  size_t length = outs.size();
-  if (length == 0) {
-    return false;
-  }
-  PADDLE_ENFORCE_EQ(length, 1UL,
-                    "Output %s should not have more than one inputs", name);
-  auto arg = outs[0];
-  auto* var = arg == kEmptyVarName ? nullptr : scope_.FindVar(arg);
+  auto* var = OutputVar(name);
   return var != nullptr;
 }
 
diff --git a/python/paddle/fluid/layers/nn.py b/python/paddle/fluid/layers/nn.py
index f696353b5d816945c179095de838c689f322d20f..385297fc1dea6691800d4d7f42643493be4adf2e 100755
--- a/python/paddle/fluid/layers/nn.py
+++ b/python/paddle/fluid/layers/nn.py
@@ -9011,8 +9011,8 @@ def reshape(x, shape, actual_shape=None, act=None, inplace=False, name=None):
                 actual_shape.stop_gradient = True
                 inputs["Shape"] = actual_shape
 
-    out = x if inplace else helper.create_variable_for_type_inference(
-        dtype=x.dtype)
+    out = x if inplace and not in_dygraph_mode(
+    ) else helper.create_variable_for_type_inference(dtype=x.dtype)
     x_shape = helper.create_variable_for_type_inference(dtype=x.dtype)
     helper.append_op(
         type="reshape2",