chore: import upstream snapshot with attribution

test/auto_parallel/clear_param_storage_api.py

@@ -0,0 +1,59 @@
+# 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 paddle
+from paddle.distributed import fleet
+from paddle.distributed.fleet.meta_optimizers.dygraph_optimizer.dygraph_sharding_optimizer import (
+    DygraphShardingOptimizerV2,
+)
+
+
+class TestClearParamStorage(unittest.TestCase):
+    def test_clear_param_storage(self):
+        class TestLayer(paddle.nn.Layer):
+            def __init__(self, dtype):
+                super().__init__()
+                self._w = self.create_parameter([2, 3], dtype=dtype)
+                self._b = self.create_parameter([2, 3], dtype=dtype)
+                self._w.color = {"color": "_w"}
+                self._b.color = {"color": "_b"}
+
+            @paddle.amp.debugging.check_layer_numerics
+            def forward(self, x):
+                return x * self._w + self._b
+
+        strategy = fleet.DistributedStrategy()
+        strategy.hybrid_configs = {
+            "dp_degree": 1,
+            "mp_degree": 1,
+            "pp_degree": 1,
+            "sharding_degree": 2,
+        }
+        fleet.init(is_collective=True, strategy=strategy)
+        hcg = fleet.get_hybrid_communicate_group()
+        dtype = 'float32'
+        model = TestLayer(dtype)
+
+        optimizer = paddle.optimizer.AdamW(parameters=model.parameters())
+        optimizer = DygraphShardingOptimizerV2(optimizer, hcg)
+        optimizer.clear_param_storage("_w")
+        optimizer.clear_param_storage("_b")
+        optimizer.clear_param_storage(None)
+        optimizer.reset_param_storage()
+
+
+if __name__ == '__main__':
+    unittest.main()