chore: import upstream snapshot with attribution

test/dygraph_to_static/test_circular_reference.py

@@ -0,0 +1,85 @@
+# Copyright (c) 2024 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 sys
+import unittest
+
+from dygraph_to_static_utils import Dy2StTestBase
+
+import paddle
+from paddle import nn
+
+
+class MyConv2D(nn.Layer):
+    def __init__(self, in_channels, out_channels, kernel_size, stride, padding):
+        super().__init__()
+        self.inner_conv = nn.Conv2D(
+            in_channels=in_channels,
+            out_channels=out_channels,
+            kernel_size=kernel_size,
+            stride=stride,
+            padding=padding,
+        )
+
+    def forward(self, x):
+        return self.inner_conv(x)
+
+
+class ExampleCNN(nn.Layer):
+    def __init__(self):
+        super().__init__()
+        self.conv1 = MyConv2D(
+            in_channels=3, out_channels=64, kernel_size=3, stride=1, padding=1
+        )
+        self.pool = nn.MaxPool2D(kernel_size=2, stride=2, padding=0)
+        self.conv2 = nn.Conv2D(
+            in_channels=64, out_channels=128, kernel_size=3, stride=1, padding=1
+        )
+        self.conv3 = nn.Conv2D(
+            in_channels=128,
+            out_channels=256,
+            kernel_size=3,
+            stride=1,
+            padding=1,
+        )
+        self.fc1 = nn.Linear(256 * 28 * 28, 10)
+        self.relu = nn.ReLU()
+
+    def forward(self, x):
+        x = self.pool(self.relu(self.conv1(x)))
+        x = self.pool(self.relu(self.conv2(x)))
+        x = self.pool(self.relu(self.conv3(x)))
+        x = paddle.flatten(x, start_axis=1)
+        x = self.fc1(x)
+        return x
+
+
+class TestCircularReference(Dy2StTestBase):
+    def test_circular_reference(self):
+        model = ExampleCNN()
+        model_ref_before_to_static = sys.getrefcount(model)
+        inner_model_ref_before_to_static = sys.getrefcount(model.conv1)
+        paddle.jit.to_static(model)
+        model_ref_after_to_static = sys.getrefcount(model)
+        inner_model_ref_after_to_static = sys.getrefcount(model.conv1)
+        # NOTE(SigureMo): The reference count of `model` must be the same before and after `to_static`.
+        # Otherwise, it may cause memory leak.
+        self.assertEqual(model_ref_before_to_static, model_ref_after_to_static)
+        self.assertEqual(
+            inner_model_ref_before_to_static, inner_model_ref_after_to_static
+        )
+
+
+if __name__ == '__main__':
+    unittest.main()