chore: import upstream snapshot with attribution

test/auto_parallel/semi_auto_parallel_set_value.py

@@ -0,0 +1,49 @@
+# Copyright (c) 2023 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 os
+
+import numpy as np
+
+import paddle
+import paddle.distributed as dist
+
+
+class TestSemiAutoParallelSetValue:
+    def __init__(self):
+        self._backend = os.getenv("backend")
+        self._seed = eval(os.getenv("seed"))
+        self._mesh = dist.ProcessMesh([0, 1], dim_names=["x"])
+
+    def test_set_value_from_numpy(self):
+        p = paddle.rand(shape=[10, 10])
+        p = dist.shard_tensor(p, self._mesh, [dist.Shard(0)])
+        q = np.arange(0, 100).reshape(10, 10).astype("float32")
+        p.set_value(q)
+        np.testing.assert_equal(p.numpy(), q)
+
+    def test_set_value_from_tensor(self):
+        p = paddle.rand(shape=[10, 10])
+        p = dist.shard_tensor(p, self._mesh, [dist.Shard(0)])
+        q = paddle.arange(0, 100, dtype="float32").reshape(shape=[10, 10])
+        p.set_value(q)
+        np.testing.assert_equal(p.numpy(), q.numpy())
+
+    def run_test_case(self):
+        self.test_set_value_from_tensor()
+        self.test_set_value_from_numpy()
+
+
+if __name__ == '__main__':
+    TestSemiAutoParallelSetValue().run_test_case()