chore: import upstream snapshot with attribution

test/legacy_test/test_function_hook.py

@@ -0,0 +1,55 @@
+#   Copyright (c) 2021 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 numpy as np
+
+import paddle
+from paddle import _C_ops
+
+
+class TestCapture:
+    def __init__(self):
+        self.list = []
+
+
+test_cap = TestCapture()
+
+
+def grad_hook(grad):
+    test_cap.list.append(2)
+
+    return grad
+
+
+class TestBackwardFunctionHookError(unittest.TestCase):
+    def test_hook(self):
+        input_data = np.ones([4, 4]).astype('float32')
+
+        x = paddle.to_tensor(input_data.astype(np.float32), stop_gradient=False)
+        z = paddle.to_tensor(input_data.astype(np.float32), stop_gradient=False)
+
+        y = _C_ops.sigmoid(x)
+        out = _C_ops.matmul(y, z, False, False)
+
+        y.register_hook(grad_hook)
+
+        out.backward()
+
+        assert test_cap.list == [2]
+
+
+if __name__ == "__main__":
+    unittest.main()