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()

test/rpc/test_rpc.py

@@ -0,0 +1,147 @@
+# 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 os
+import unittest
+
+import numpy as np
+from test_rpc_base import RpcLaunchTestBase, RpcTestBase
+
+import paddle
+import paddle.distributed as dist
+
+paddle.device.set_device("cpu")
+
+
+def worker_name(rank):
+    return f"worker{rank}"
+
+
+def paddle_add(a, b):
+    a = paddle.to_tensor(a)
+    b = paddle.to_tensor(b)
+    res = paddle.add(a, b).numpy()
+    return res
+
+
+class TestMultiProcessRpc(RpcTestBase):
+    def test_one_server_sync_paddle_add(self):
+        a = np.random.random((10, 100))
+        b = np.random.random((10, 100))
+        res = np.add(a, b)
+        args = (a, b)
+        queues = self.run_rpc(True, 1, paddle_add, args)
+        out = queues[0].get()
+        np.testing.assert_allclose(out, res, rtol=1e-05)
+
+    def test_one_server_async_paddle_add(self):
+        a = np.random.random((10, 100))
+        b = np.random.random((10, 100))
+        res = np.add(a, b)
+        args = (a, b)
+        queues = self.run_rpc(False, 1, paddle_add, args)
+        out = queues[0].get()
+        np.testing.assert_allclose(out, res, rtol=1e-05)
+
+    def test_two_server_sync_paddle_add(self):
+        a = np.random.random((10, 100))
+        b = np.random.random((10, 100))
+        res = np.add(a, b)
+        args = (a, b)
+        queues = self.run_rpc(True, 2, paddle_add, args)
+        out1 = queues[0].get()
+        out2 = queues[1].get()
+        np.testing.assert_allclose(out1, res, rtol=1e-05)
+        np.testing.assert_allclose(out2, res, rtol=1e-05)
+
+    def test_two_server_async_paddle_add(self):
+        a = np.random.random((10, 100))
+        b = np.random.random((10, 100))
+        res = np.add(a, b)
+        args = (a, b)
+        queues = self.run_rpc(False, 2, paddle_add, args)
+        out1 = queues[0].get()
+        out2 = queues[1].get()
+        np.testing.assert_allclose(out1, res, rtol=1e-05)
+        np.testing.assert_allclose(out2, res, rtol=1e-05)
+
+
+class TestSingleProcessRpc(RpcTestBase):
+    def setUp(self):
+        self._port_set = set()
+        master_endpoint = f"127.0.0.1:{self._find_free_port()}"
+        dist.rpc.init_rpc(worker_name(0), 0, 1, master_endpoint)
+        print("Single Process RPC setUp...")
+
+    def tearDown(self):
+        dist.rpc.shutdown()
+        print("Single Process RPC tearDown...")
+
+    def test_sync_rpc_paddle_add(self):
+        a = np.random.random((10, 100))
+        b = np.random.random((10, 100))
+        res = np.add(a, b)
+        args = (a, b)
+        out = dist.rpc.rpc_sync(worker_name(0), paddle_add, args=args)
+        np.testing.assert_allclose(out, res, rtol=1e-05)
+
+    def test_async_rpc_paddle_add(self):
+        a = np.random.random((10, 100))
+        b = np.random.random((10, 100))
+        res = np.add(a, b)
+        args = (a, b)
+        out = dist.rpc.rpc_async(worker_name(0), paddle_add, args=args).wait()
+        np.testing.assert_allclose(out, res, rtol=1e-05)
+
+    def test_get_worker_info(self):
+        info = dist.rpc.get_worker_info(worker_name(0))
+        self.assertEqual(info.name, worker_name(0))
+        self.assertEqual(info.rank, 0)
+
+    def test_get_all_worker_infos(self):
+        infos = dist.rpc.get_all_worker_infos()
+        info = infos[0]
+        self.assertEqual(info.name, worker_name(0))
+        self.assertEqual(info.rank, 0)
+
+    def test_get_current_worker_info(self):
+        info = dist.rpc.get_current_worker_info()
+        self.assertEqual(info.name, worker_name(0))
+        self.assertEqual(info.rank, 0)
+
+
+class RpcLaunchTest(RpcLaunchTestBase):
+    def test_sync_rpc_paddle_add1(self):
+        nnodes = 2
+        nproc_per_node = 1
+        pwd, _ = os.path.split(os.path.realpath(__file__))
+        model_file = os.path.join(pwd, "rpc_launch_sync_add.py")
+        a, b = self.create_data(nnodes, nproc_per_node)
+        res = np.add(a, b)
+        out = self.launch_rpc(nnodes, nproc_per_node, model_file)
+        np.testing.assert_allclose(out, res, rtol=1e-05)
+
+    def test_sync_rpc_paddle_add2(self):
+        nnodes = 2
+        nproc_per_node = 2
+        pwd, _ = os.path.split(os.path.realpath(__file__))
+        model_file = os.path.join(pwd, "rpc_launch_sync_add.py")
+        a, b = self.create_data(nnodes, nproc_per_node)
+        res = np.add(a, b)
+        out = self.launch_rpc(nnodes, nproc_per_node, model_file)
+        np.testing.assert_allclose(out, res, rtol=1e-05)
+
+
+if __name__ == "__main__":
+    unittest.main()

test/rpc/test_rpc_base.py

@@ -0,0 +1,258 @@
+# 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 os
+import socket
+import subprocess
+import unittest
+from contextlib import closing
+from multiprocessing import Process, Queue
+
+import numpy as np
+
+import paddle.distributed as dist
+
+
+def worker_name(rank):
+    return f"worker{rank}"
+
+
+def run_rpc_sync(
+    rank,
+    world_size,
+    master_endpoint,
+    queue,
+    fn,
+    args=None,
+    kwargs=None,
+):
+    dist.rpc.init_rpc(
+        worker_name(rank),
+        rank,
+        world_size,
+        master_endpoint,
+    )
+    res = dist.rpc.rpc_sync(worker_name(0), fn, args=args, kwargs=kwargs)
+    queue.put(res)
+    dist.rpc.shutdown()
+
+
+def run_rpc_sync_master_working(
+    rank,
+    world_size,
+    master_endpoint,
+    queue,
+    fn,
+    args=None,
+    kwargs=None,
+):
+    dist.rpc.init_rpc(
+        worker_name(rank),
+        rank,
+        world_size,
+        master_endpoint,
+    )
+    if dist.get_rank() == 0:
+        for i in range(1, dist.get_rank()):
+            res = dist.rpc.rpc_sync(
+                worker_name(i), fn, args=args, kwargs=kwargs
+            )
+            queue.put(res)
+    dist.rpc.shutdown()
+
+
+def run_rpc_async(
+    rank,
+    world_size,
+    master_endpoint,
+    queue,
+    fn,
+    args=None,
+    kwargs=None,
+):
+    dist.rpc.init_rpc(
+        worker_name(rank),
+        rank,
+        world_size,
+        master_endpoint,
+    )
+    res = dist.rpc.rpc_async(worker_name(0), fn, args=args, kwargs=kwargs)
+    queue.put(res.wait())
+    dist.rpc.shutdown()
+
+
+def run_rpc_async_master_working(
+    rank,
+    world_size,
+    master_endpoint,
+    queue,
+    fn,
+    args=None,
+    kwargs=None,
+):
+    dist.rpc.init_rpc(
+        worker_name(rank),
+        rank,
+        world_size,
+        master_endpoint,
+    )
+    if dist.get_rank() == 0:
+        for i in range(1, dist.get_rank()):
+            res = dist.rpc.rpc_async(
+                worker_name(i), fn, args=args, kwargs=kwargs
+            )
+            queue.put(res.wait())
+    dist.rpc.shutdown()
+
+
+class RpcTestBase(unittest.TestCase):
+    def setUp(self):
+        self._port_set = set()
+        print("RPC setUp...")
+
+    def tearDown(self):
+        if len(self.processes) != 0:
+            [p.join() for p in self.processes]
+        print("RPC tearDown...")
+
+    def _find_free_port(self):
+        def __free_port():
+            with closing(
+                socket.socket(socket.AF_INET, socket.SOCK_STREAM)
+            ) as s:
+                s.bind(("", 0))
+                return s.getsockname()[1]
+
+        while True:
+            port = __free_port()
+            if port not in self._port_set:
+                self._port_set.add(port)
+                return port
+
+    def run_rpc(self, sync, world_size, fn, fn_args=None, fn_kwargs=None):
+        self.processes = []
+        queues = []
+        master_endpoint = f"127.0.0.1:{self._find_free_port()}"
+        for rank in range(world_size):
+            q = Queue()
+            queues.append(q)
+            if sync:
+                self.processes.append(
+                    Process(
+                        target=run_rpc_sync,
+                        args=(
+                            rank,
+                            world_size,
+                            master_endpoint,
+                            q,
+                            fn,
+                            fn_args,
+                            fn_kwargs,
+                        ),
+                    )
+                )
+            else:
+                self.processes.append(
+                    Process(
+                        target=run_rpc_async,
+                        args=(
+                            rank,
+                            world_size,
+                            master_endpoint,
+                            q,
+                            fn,
+                            fn_args,
+                            fn_kwargs,
+                        ),
+                    )
+                )
+        [p.start() for p in self.processes]
+        return queues
+
+
+class RpcLaunchTestBase(unittest.TestCase):
+    def setUp(self):
+        self._port_set = set()
+        print("Launch RPC setUp...")
+
+    def tearDown(self):
+        self.remove_data()
+        print("Launch RPC tearDown...")
+
+    def _find_free_port(self):
+        def __free_port():
+            with closing(
+                socket.socket(socket.AF_INET, socket.SOCK_STREAM)
+            ) as s:
+                s.bind(("", 0))
+                return s.getsockname()[1]
+
+        while True:
+            port = __free_port()
+            if port not in self._port_set:
+                self._port_set.add(port)
+                return port
+
+    def create_data(self, nnodes, nproc_per_node):
+        mmap_data1 = np.memmap(
+            "rpc_launch_data1.npy",
+            dtype=np.float32,
+            mode="w+",
+            shape=(10 * nnodes * nproc_per_node, 100),
+        )
+        mmap_data2 = np.memmap(
+            "rpc_launch_data2.npy",
+            dtype=np.float32,
+            mode="w+",
+            shape=(10 * nnodes * nproc_per_node, 100),
+        )
+        for i in range(nnodes * nproc_per_node):
+            a = np.random.random((10, 100)).astype(np.float32)
+            b = np.random.random((10, 100)).astype(np.float32)
+            mmap_data1[i * 10 : (i + 1) * 10, :] = a
+            mmap_data2[i * 10 : (i + 1) * 10, :] = b
+        return mmap_data1, mmap_data2
+
+    def remove_data(self):
+        os.remove("rpc_launch_data1.npy")
+        os.remove("rpc_launch_data2.npy")
+
+    def launch_rpc(self, nnodes, nproc_per_node, model_file):
+        master_endpoint = f"127.0.0.1:{self._find_free_port()}"
+        log_dir = "log"
+        tr_cmd = "python -m paddle.distributed.launch --master {} --rank {} --nnodes {} --nproc_per_node {} --run_mode rpc {} --log_dir {}"
+        cmds = [
+            tr_cmd.format(
+                master_endpoint,
+                rank,
+                nnodes,
+                nproc_per_node,
+                model_file,
+                log_dir,
+            )
+            for rank in range(nnodes)
+        ]
+        processes = [subprocess.Popen(cmd.strip().split()) for cmd in cmds]
+        [proc.communicate() for proc in processes]
+        out = np.memmap(
+            "rpc_launch_result.npy",
+            dtype=np.float32,
+            mode="r",
+            shape=(10 * nnodes * nproc_per_node, 100),
+        )
+        os.remove("rpc_launch_result.npy")
+        import shutil
+
+        shutil.rmtree(log_dir)
+        return out