diff --git a/CMakeLists.txt b/CMakeLists.txt
index f56c5d382af8cdfb5a941ee272a0f8d22ec04d67..920c20d6f813c14df8e02593b1c4a5a13cc11ef0 100644
--- a/CMakeLists.txt
+++ b/CMakeLists.txt
@@ -204,12 +204,11 @@ include(external/snappy)    # download snappy
 include(external/snappystream)
 include(external/threadpool)
 
+set(WITH_ANAKIN OFF CACHE STRING "Disable Anakin first, will add it later." FORCE)
 if(WITH_GPU)
     include(cuda)
     include(tensorrt)
     include(external/anakin)
-else()
-  set(WITH_ANAKIN OFF CACHE STRING "Anakin is valid only when GPU is set." FORCE)
 endif()
 
 include(cudnn)              # set cudnn libraries, must before configure
diff --git a/python/paddle/fluid/tests/unittests/op_test.py b/python/paddle/fluid/tests/unittests/op_test.py
index ada4ad70f0c07dfc25df2ecde82f9c83e5987db8..75373ae2e15fa5b4153ea3072bb2079fed9295ef 100644
--- a/python/paddle/fluid/tests/unittests/op_test.py
+++ b/python/paddle/fluid/tests/unittests/op_test.py
@@ -362,14 +362,10 @@ class OpTest(unittest.TestCase):
 
     def check_output_customized(self, checker):
         places = self._get_places()
-        import sys
-        print('places', places)
         for place in places:
             outs = self.calc_output(place)
             outs = [np.array(out) for out in outs]
-            import sys
-            print('outs', outs)
-            sys.stdout.flush()
+            outs.sort(key=len)
             checker(outs)
 
     def __assert_is_close(self, numeric_grads, analytic_grads, names,
diff --git a/python/paddle/fluid/tests/unittests/test_random_crop_op.py b/python/paddle/fluid/tests/unittests/test_random_crop_op.py
index 1acd377b1f92debd8e919b8bea4d67df88ba7a15..27e5db4991b8dfbc7bbad609004f9b72126245d6 100644
--- a/python/paddle/fluid/tests/unittests/test_random_crop_op.py
+++ b/python/paddle/fluid/tests/unittests/test_random_crop_op.py
@@ -23,9 +23,10 @@ class TestRandomCropOp(OpTest):
         to_crop = np.array([[[1, 2, 3, 4], [5, 6, 7, 8], [9, 10, 11, 12]]] *
                            5).astype(np.int32)
         self.possible_res = [
-            np.array([[1, 2, 3], [5, 6, 7]]), np.array([[2, 3, 4], [6, 7, 8]]),
-            np.array([[5, 6, 7], [9, 10, 11]]),
-            np.array([[6, 7, 8], [10, 11, 12]])
+            np.array([[1, 2, 3], [5, 6, 7]]).astype(np.int32),
+            np.array([[2, 3, 4], [6, 7, 8]]).astype(np.int32),
+            np.array([[5, 6, 7], [9, 10, 11]]).astype(np.int32),
+            np.array([[6, 7, 8], [10, 11, 12]]).astype(np.int32)
         ]
         self.op_type = "random_crop"
         self.inputs = {'X': to_crop, 'Seed': np.array([10])}