chore: import upstream snapshot with attribution

test/rpc/rpc_launch_sync_add.py

@@ -0,0 +1,72 @@
+# Copyright (c) 2022 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 numpy as np
+
+import paddle
+import paddle.distributed as dist
+
+paddle.device.set_device("cpu")
+
+
+def add(a, b):
+    a = paddle.to_tensor(a, dtype="float32")
+    b = paddle.to_tensor(b, dtype="float32")
+    res = paddle.add(a, b).numpy()
+    return res
+
+
+def rpc_add(to, args):
+    res = dist.rpc.rpc_sync(to, add, args=args)
+    return res
+
+
+def worker_name(rank):
+    return f"worker{rank}"
+
+
+def main():
+    rank = dist.get_rank()
+    world_size = dist.get_world_size()
+    dist.rpc.init_rpc(worker_name(rank))
+    if rank == 0:
+        mmap_data1 = np.memmap(
+            "rpc_launch_data1.npy",
+            dtype=np.float32,
+            mode="r",
+            shape=(10 * world_size, 100),
+        )
+        mmap_data2 = np.memmap(
+            "rpc_launch_data2.npy",
+            dtype=np.float32,
+            mode="r",
+            shape=(10 * world_size, 100),
+        )
+        mmap_out = np.memmap(
+            "rpc_launch_result.npy",
+            dtype=np.float32,
+            mode="w+",
+            shape=(10 * world_size, 100),
+        )
+        for i in range(world_size):
+            a = mmap_data1[i * 10 : (i + 1) * 10, :]
+            b = mmap_data2[i * 10 : (i + 1) * 10, :]
+            args = (a, b)
+            out = rpc_add(worker_name(i), args)
+            mmap_out[i * 10 : (i + 1) * 10, :] = out[:]
+    dist.rpc.shutdown()
+
+
+if __name__ == "__main__":
+    main()