diff --git a/paddleslim/prune/__init__.py b/paddleslim/prune/__init__.py
index c46fd75dd3220abffcaabcadc78b271e48cb5489..42ea0b4c3923cafcebdd2f1acc684defdd9faddb 100644
--- a/paddleslim/prune/__init__.py
+++ b/paddleslim/prune/__init__.py
@@ -25,6 +25,8 @@ from .prune_walker import *
 from ..prune import prune_walker
 from .prune_io import *
 from ..prune import prune_io
+from .group_param import *
+from ..prune import group_param
 
 __all__ = []
 
@@ -34,3 +36,4 @@ __all__ += sensitive_pruner.__all__
 __all__ += sensitive.__all__
 __all__ += prune_walker.__all__
 __all__ += prune_io.__all__
+__all__ += group_param.__all__
diff --git a/paddleslim/prune/group_param.py b/paddleslim/prune/group_param.py
new file mode 100644
index 0000000000000000000000000000000000000000..52075c9a47d34723d0f90b8c69b982a610aeb2f7
--- /dev/null
+++ b/paddleslim/prune/group_param.py
@@ -0,0 +1,79 @@
+"""Define some functions to collect ralated parameters into groups."""
+# Copyright (c) 2020  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.
+
+from ..core import GraphWrapper
+from .prune_walker import conv2d as conv2d_walker
+
+__all__ = ["collect_convs"]
+
+
+def collect_convs(params, graph):
+    """Collect convolution layers of graph into groups. The layers in the same group is relative on pruning operation.
+    A group is a list of tuple with format (param_name, axis) in which `param_name` is the name of parameter and `axis` is the axis to be pruned on.
+
+    .. code-block:: text
+
+       conv1->conv2->conv3->conv4
+
+    As shown above, the demo has 4 convolution layers. And the shape of convolution's parameter is `[out_channel, in_channel, filter_size, filter_size]`. If parameter of `conv1` was pruned on axis 0, then the parameter of `conv2` should be pruned on axis 1. So the `conv1` and `conv2` is a group that can be represented as:
+
+    .. code-block:: python
+
+       [("conv1", 0), ("conv2", 1)]
+
+    If `params` is `["conv1", "conv2"]`, then the returned groups is:
+
+    .. code-block:: python
+
+       [[("conv1", 0), ("conv2", 1)],
+        [("conv2", 0), ("conv3", 1)]]
+
+    Args:
+       params(list): A list of convolution layer's parameter names. It will collect all the groups that contains anyone of these parameters.
+       graph(paddle.fluid.Program | GraphWrapper): The graph used to search the groups.
+
+    Returns:
+       list<list<tuple>>: The groups.
+
+    """
+    if not isinstance(graph, GraphWrapper):
+        graph = GraphWrapper(graph)
+    groups = []
+    for param in params:
+        visited = {}
+        pruned_params = []
+        param = graph.var(param)
+        conv_op = param.outputs()[0]
+        walker = conv2d_walker(
+            conv_op, pruned_params=pruned_params, visited=visited)
+        walker.prune(param, pruned_axis=0, pruned_idx=[])
+        groups.append(pruned_params)
+    visited = set()
+    uniq_groups = []
+    for group in groups:
+        repeat_group = False
+        simple_group = []
+        for param, axis, _ in group:
+            param = param.name()
+            if axis == 0:
+                if param in visited:
+                    repeat_group = True
+                else:
+                    visited.add(param)
+            simple_group.append((param, axis))
+        if not repeat_group:
+            uniq_groups.append(simple_group)
+
+    return uniq_groups
diff --git a/tests/test_group_param.py b/tests/test_group_param.py
new file mode 100644
index 0000000000000000000000000000000000000000..cd699bfd68bf2d28e670a03f9200944be9b1a562
--- /dev/null
+++ b/tests/test_group_param.py
@@ -0,0 +1,51 @@
+# 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 layers import conv_bn_layer
+from paddleslim.prune import collect_convs
+
+
+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-->conv5-->conv6
+        #     |            ^ |                    ^
+        #     |____________| |____________________|
+        #
+        # X: prune output channels
+        # O: prune input channels
+        with fluid.program_guard(main_program, startup_program):
+            input = fluid.data(name="image", shape=[None, 3, 16, 16])
+            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
+            conv5 = conv_bn_layer(sum2, 8, 3, "conv5")
+            conv6 = conv_bn_layer(conv5, 8, 3, "conv6")
+        groups = collect_convs(
+            ["conv1_weights", "conv2_weights", "conv3_weights"], main_program)
+        self.assertTrue(len(groups) == 2)
+        self.assertTrue(len(groups[0]) == 18)
+        self.assertTrue(len(groups[1]) == 6)
+
+
+if __name__ == '__main__':
+    unittest.main()