chore: import upstream snapshot with attribution

test/dygraph_to_static/test_layer_hook.py

@@ -0,0 +1,99 @@
+# 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 tempfile
+import unittest
+
+import numpy as np
+from dygraph_to_static_utils import (
+    Dy2StTestBase,
+)
+
+import paddle
+
+
+def forward_post_hook1(layer, input, output):
+    return output + output
+
+
+def forward_pre_hook1(layer, input):
+    input_return = (input[0] * 2,)
+    return input_return
+
+
+class SimpleNet(paddle.nn.Layer):
+    def __init__(
+        self,
+    ):
+        super().__init__()
+        self.fc1 = paddle.nn.Linear(10, 10)
+        # sublayer1 register post hook
+        self.fc1.register_forward_post_hook(forward_post_hook1)
+
+        self.fc2 = paddle.nn.Linear(10, 10)
+        # sublayer2 register pre hook
+        self.fc2.register_forward_pre_hook(forward_pre_hook1)
+
+        # register pre/post hook
+        self.register_forward_pre_hook(forward_pre_hook1)
+        self.register_forward_post_hook(forward_post_hook1)
+
+    def forward(self, x):
+        x = self.fc1(x)
+        x = self.fc2(x)
+        out = paddle.mean(x)
+
+        return out
+
+
+class TestNestLayerHook(Dy2StTestBase):
+    def setUp(self):
+        paddle.seed(2022)
+        self.x = paddle.randn([4, 10])
+        self.temp_dir = tempfile.TemporaryDirectory()
+        self.path = os.path.join(self.temp_dir.name, 'net_hook')
+
+    def tearDown(self):
+        self.temp_dir.cleanup()
+
+    def train_net(self, to_static=False):
+        paddle.seed(2022)
+        net = SimpleNet()
+        if to_static:
+            net = paddle.jit.to_static(net)
+        out = net(self.x)
+
+        paddle.jit.save(net, self.path, input_spec=[self.x])
+
+        return float(out)
+
+    def load_train(self):
+        net = paddle.jit.load(self.path)
+        out = net(self.x)
+        return float(out)
+
+    def test_hook(self):
+        dy_out = self.train_net(to_static=False)
+        st_out = self.train_net(to_static=True)
+        np.testing.assert_allclose(
+            st_out,
+            dy_out,
+            rtol=1e-05,
+            err_msg=f'dygraph_res is {dy_out}\nstatic_res is {st_out}',
+        )
+
+
+if __name__ == "__main__":
+    unittest.main()