add test for CustomAllreduce

Author: zhink

test/distributed/test_custom_all_reduce.py

@@ -0,0 +1,70 @@
+"""
+# Copyright (c) 2025 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 unittest
+
+import numpy as np
+import paddle
+import paddle.distributed as dist
+from paddle.distributed import fleet
+
+from fastdeploy.distributed.custom_all_reduce import CustomAllreduce
+
+class Test(unittest.TestCase):
+    def setUp(self):
+        """
+        Initialize the test environment,
+        including setting random seeds.
+        """
+        paddle.seed(2025)
+        strategy = fleet.DistributedStrategy()
+        strategy.hybrid_configs = {
+                        "dp_degree": 1,
+                        "mp_degree": 2,
+                        "pp_degree": 1,
+                        "sharding_degree": 1,
+                    }
+
+        fleet.init(is_collective=True, strategy=strategy)
+
+    def test_case(self):
+        """
+        Check if the CustomAllreduce function works properly.
+        """
+
+        mns = [[1, 2048], [2, 4096], [20, 4096], [128, 4096], [256, 4096], [256, 8192]]
+
+        hcg = fleet.get_hybrid_communicate_group()
+        model_parallel_group = hcg.get_model_parallel_group()
+        fa = CustomAllreduce(model_parallel_group)
+
+        for (m, n) in mns:
+            data_ar = paddle.rand([m, n],dtype='bfloat16')
+            data_paddle = data_ar.clone()
+            if fa.should_custom_ar(data_ar):
+                fa.custom_all_reduce(data_ar)
+            dist.all_reduce(data_paddle)
+            if dist.get_rank() == 0:
+                np.testing.assert_allclose(
+                    data_ar.numpy(),
+                    data_paddle.numpy(),
+                    rtol=1e-04,
+                    atol=1e-04,
+                )
+
+
+if __name__ == "__main__":
+    unittest.main()