diff --git a/tests/test_add_ops.py b/tests/test_add_ops.py
new file mode 100644
index 0000000000000000000000000000000000000000..cb671df0ada28272b6b6104e82541fee3dd00d97
--- /dev/null
+++ b/tests/test_add_ops.py
@@ -0,0 +1,82 @@
+# Copyright (c) 2019  PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License"
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+import sys
+sys.path.append("../")
+import unittest
+import paddle.fluid as fluid
+from paddleslim.prune import Pruner
+from paddleslim.core import GraphWrapper
+from paddleslim.prune import conv2d as conv2d_walker
+from layers import conv_bn_layer
+
+
+class TestPrune(unittest.TestCase):
+    def test_prune(self):
+        main_program = fluid.Program()
+        startup_program = fluid.Program()
+        #   X       X              O       X              O
+        # conv1-->conv2-->sum1-->conv3-->conv4-->sum2-->align_out-->conv5
+        #     |            ^ |                    ^   |
+        #     |____________| |____________________|    ->gather_out-->conv6
+        #                                             |
+        #                                              ->lodset_out-->conv7
+        #
+        # X: prune output channels
+        # O: prune input channels
+        with fluid.program_guard(main_program, startup_program):
+            input = fluid.data(name="image", shape=[None, 3, 64, 64])
+            conv1 = conv_bn_layer(input, 8, 3, "conv1")
+            conv2 = conv_bn_layer(conv1, 8, 3, "conv2")
+            sum1 = conv1 + conv2
+            conv3 = conv_bn_layer(sum1, 8, 3, "conv3")
+            conv4 = conv_bn_layer(conv3, 8, 3, "conv4")
+            sum2 = conv4 + sum1
+            #test roi_align
+            rois = fluid.data(
+                name='rois', shape=[None, 4], dtype='float32')
+            align_out = fluid.layers.roi_align(input=sum2,
+                                               rois=rois,
+                                               pooled_height=7,
+                                               pooled_width=7,
+                                               spatial_scale=0.5,
+                                               sampling_ratio=-1)
+            conv5 = conv_bn_layer(align_out, 8, 3, "conv5")
+            #test gather
+            index = fluid.layers.data(name='index', shape=[-1, 1], dtype='int32')
+            gather_out = fluid.layers.gather(sum2, index)
+            conv6 = conv_bn_layer(gather_out, 8, 3, "conv6")
+            #test lod_reset
+            y = fluid.layers.data(name='y', shape=[6], lod_level=2)
+            lodset_out = fluid.layers.lod_reset(x=sum2, y=y)
+            conv7 = conv_bn_layer(lodset_out, 8, 3, "conv7")
+
+        shapes = {}
+        for param in main_program.global_block().all_parameters():
+            shapes[param.name] = param.shape
+
+        place = fluid.CPUPlace()
+        exe = fluid.Executor(place)
+        scope = fluid.Scope()
+        exe.run(startup_program, scope=scope)
+
+        graph = GraphWrapper(main_program)
+
+        conv_op = graph.var("conv4_weights").outputs()[0]
+        walker = conv2d_walker(conv_op, [])
+        walker.prune(graph.var("conv4_weights"), pruned_axis=0, pruned_idx=[])
+        print(walker.pruned_params)
+
+
+if __name__ == '__main__':
+    unittest.main()
\ No newline at end of file