diff --git a/paddle/fluid/framework/operator.cc b/paddle/fluid/framework/operator.cc
index d70f26026c28867e592a9f8e37cc53e6c1d6d85e..30f784598a897518a8ce3b7a9c65d3330bb93f37 100644
--- a/paddle/fluid/framework/operator.cc
+++ b/paddle/fluid/framework/operator.cc
@@ -466,6 +466,7 @@ class RuntimeInferShapeContext : public InferShapeContext {
  protected:
   DDim GetDim(const std::string& name) const override {
     Variable* var = scope_.FindVar(name);
+    PADDLE_ENFORCE_NOT_NULL(var);
     if (var->IsType<LoDTensor>()) {
       return var->Get<LoDTensor>().dims();
     } else if (var->IsType<SelectedRows>()) {
diff --git a/python/paddle/fluid/layers/nn.py b/python/paddle/fluid/layers/nn.py
index 3f04dcccd6aa29ec8d5cd445320356cfa3d5db2d..ec95efd699b12d6226fe3add35da7f94756649f9 100644
--- a/python/paddle/fluid/layers/nn.py
+++ b/python/paddle/fluid/layers/nn.py
@@ -3996,13 +3996,19 @@ def random_crop(input, shape, seed=1):
     out = helper.create_tmp_variable(dtype)
     if isinstance(seed, int):
         seed_value = seed
-        seed = helper.create_global_variable(
-            persistable=True, shape=[1], dtype="int32")
-        helper.set_variable_initializer(
-            var=seed, initializer=Constant(value=seed_value))
+        seed = helper.create_tmp_variable(dtype="int64")
+        helper.append_op(
+            type="fill_constant",
+            inputs={},
+            outputs={"Out": seed},
+            attrs={
+                "dtype": seed.dtype,
+                "shape": [1],
+                "value": float(seed_value)
+            })
     elif not isinstance(seed, Variable):
         raise ValueError("'seed' must be a Variable or an int.")
-    seed_out = helper.create_tmp_variable(dtype="int32")
+    seed_out = helper.create_tmp_variable(dtype="int64")
     helper.append_op(
         type="random_crop",
         inputs={"X": input,