diff --git a/python/paddle/distributed/fleet/meta_parallel/parallel_layers/pp_layers.py b/python/paddle/distributed/fleet/meta_parallel/parallel_layers/pp_layers.py
index 2f5c42a69e362fdcbf063aa336257a10bc0af1ab..f3be9894a9cfeb48983b1317bf035296b0e59f50 100755
--- a/python/paddle/distributed/fleet/meta_parallel/parallel_layers/pp_layers.py
+++ b/python/paddle/distributed/fleet/meta_parallel/parallel_layers/pp_layers.py
@@ -109,7 +109,37 @@ class SegmentLayers:
         ), "layer number should be greater than number of segments"
 
     def do_segment(self):
-        if self.method == "uniform":
+
+        if isinstance(self.method, list):
+            seg_method = self.method[:]
+            source_num_parts = len(seg_method) - 1
+
+            def check_sanity():
+                assert seg_method[0] == 0, "seg_method[0] should be 0"
+                for part in seg_method:
+                    assert isinstance(part, int), "part should be int"
+                    assert part >= 0, f"part[{part}] should be greater than 0"
+                    assert (
+                        part <= self.num_items
+                    ), "part[{}] should be less than num_items[{}]".format(
+                        part, self.num_items
+                    )
+
+            check_sanity()
+
+            if self.num_parts == source_num_parts + 1:
+                seg_method.append(self.num_items)
+                return seg_method
+            elif self.num_parts == source_num_parts:
+                return seg_method
+            else:
+                raise ValueError(
+                    "We set seg_method as {}, this length is {}, but the number of stages is {}".format(
+                        seg_method, len(seg_method), self.num_parts
+                    )
+                )
+
+        elif self.method == "uniform":
             return self.uniform(self.num_items, self.num_parts)
 
         elif self.method.startswith('layer:'):
@@ -144,6 +174,8 @@ class SegmentLayers:
                     memory_counter = 0
             result[actual_num_parts] = len(weights)
             return result
+        else:
+            raise ValueError(f"method {self.method} is not supported")
 
     def _gen_layer_weight(self, layername):
         weight_idxs = []
diff --git a/python/paddle/fluid/tests/unittests/hybrid_parallel_pp_layer.py b/python/paddle/fluid/tests/unittests/hybrid_parallel_pp_layer.py
index 5d15e79d64b755b32afd61fea4c202d0731ddb7a..cf4c20e550ab388aaf36856e09bad2ad6b40b4c2 100644
--- a/python/paddle/fluid/tests/unittests/hybrid_parallel_pp_layer.py
+++ b/python/paddle/fluid/tests/unittests/hybrid_parallel_pp_layer.py
@@ -136,6 +136,20 @@ class TestPipeLayerAPI(unittest.TestCase):
                 np.testing.assert_array_equal(param_a.name, param_b.name)
                 np.testing.assert_allclose(param_a.numpy(), param_b.numpy())
 
+    def test_pipelayer_segment_method(self):
+        init_net = AlexNetPipe()
+        pipe_model = PipelineLayer(
+            layers=init_net.to_layers(),
+            num_stages=self.pipeline_parallel_size,
+            seg_method=[0, 4],
+            loss_fn=nn.CrossEntropyLoss(),
+        )
+        stage_id = self.hcg.get_stage_id()
+        if stage_id == 0:
+            np.testing.assert_array_equal(len(pipe_model.parameters()), 4)
+        elif stage_id == 1:
+            np.testing.assert_array_equal(len(pipe_model.parameters()), 8)
+
 
 if __name__ == '__main__':
     unittest.main()