chore: import upstream snapshot with attribution

test/legacy_test/test_multi_scale_pool_allocator.py

@@ -0,0 +1,76 @@
+# 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
+
+
+@unittest.skipIf(
+    (not paddle.is_compiled_with_cuda()) or paddle.is_compiled_with_rocm(),
+    'should compile with cuda.',
+)
+class TestMultiScaleAllocator(unittest.TestCase):
+    def setUp(self):
+        paddle.set_flags({'FLAGS_use_virtual_memory_auto_growth': True})
+        self.GB = 1000**3
+        self.MB = 1000**2
+        self.cmds = [
+            ["Alloc", 1 * self.GB, "0x100000000"],
+            ["Alloc", 2 * self.GB, "0x100000001"],
+            ["Alloc", 1 * self.GB, "0x100000002"],
+            ["Alloc", 2 * self.GB, "0x100000003"],
+            ["Free", 1 * self.GB, "0x100000000"],
+            ["Free", 2 * self.GB, "0x100000003"],
+        ]
+
+    def allocate_cmds(self, cmds):
+        params = {}
+        for op, size, ptr in self.cmds:
+            paddle.device.synchronize()
+            paddle_reserved1 = paddle.device.cuda.memory_reserved() // self.MB
+
+            if op == "Alloc":
+                params[ptr] = paddle.randn(
+                    [int(int(size) / 4)], dtype='float32'
+                )
+            if op == "Free" and ptr in params:
+                del params[ptr]
+
+            paddle.device.synchronize()
+            paddle_reserved2 = paddle.device.cuda.memory_reserved() // self.MB
+            paddle_allocated2 = paddle.device.cuda.memory_allocated() // self.MB
+            paddle_max_reserved = (
+                paddle.device.cuda.max_memory_reserved() // self.MB
+            )
+            paddle_max_allocated = (
+                paddle.device.cuda.max_memory_allocated() // self.MB
+            )
+
+            print(
+                f"reserved = {paddle_reserved2} allocated = {paddle_allocated2} auto growth = {paddle_reserved2 - paddle_reserved1} max_allocated = {paddle_max_allocated} max_reserved = {paddle_max_reserved}"
+            )
+        # for multi stream
+        stream = paddle.device.cuda.Stream()
+        with paddle.device.cuda.stream_guard(stream):
+            x = paddle.empty([int(1 * 1024 * 1024 * 1024)], dtype=paddle.uint8)
+            del x
+        return params
+
+    def test_multi_scale_alloc_free(self):
+        params = self.allocate_cmds(self.cmds)
+
+
+if __name__ == '__main__':
+    unittest.main()