chore: import upstream snapshot with attribution

test/auto_parallel/test_parallel_api.py

@@ -0,0 +1,70 @@
+#   Copyright (c) 2024 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 paddle
+from paddle.distributed.auto_parallel.intermediate.parallel_base import (
+    ParallelModel,
+)
+
+
+class PP(ParallelModel):
+    def __init__(self, model):
+        super().__init__(model)
+        self.pp_parallelizer = self.pp_init
+
+    def pp_init(self, model):
+        return paddle.nn.Linear(2, 2)
+
+
+class TP(ParallelModel):
+    def __init__(self, model):
+        super().__init__(model)
+        self.tp_parallelizer = self.tp_init
+
+    def tp_init(self, model):
+        return paddle.nn.Linear(3, 3)
+
+
+class SD(ParallelModel):
+    def __init__(self, model):
+        super().__init__(model)
+        self.sharding_parallelizer = self.sd_init
+
+    def sd_init(self, model):
+        return paddle.nn.Linear(4, 4)
+
+
+class TestStrategy:
+    def test_recursive(self):
+        model = paddle.nn.Linear(1, 1)
+        pp = PP(model)
+        data = paddle.rand([1, 2])
+        pp(data)
+        assert pp.model.weight.shape == [2, 2]
+        model = paddle.nn.Linear(1, 1)
+        tp = TP(PP(model))
+        data = paddle.rand([1, 3])
+        tp(data)
+        assert tp.model.weight.shape == [3, 3]
+        model = paddle.nn.Linear(1, 1)
+        sd = SD(TP(PP(model)))
+        data = paddle.rand([1, 4])
+        sd(data)
+        assert sd.model.weight.shape == [4, 4]
+
+
+if __name__ == '__main__':
+    unittest.main()