chore: import upstream snapshot with attribution

test/sot/test_segment_linear.py

@@ -0,0 +1,73 @@
+# Copyright (c) 2023 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
+
+from test_case_base import TestCaseBase
+
+import paddle
+from paddle import nn
+from paddle.jit import sot
+from paddle.jit.sot.utils import strict_mode_guard
+
+
+class Head(nn.Layer):
+    def __init__(self):
+        super().__init__()
+        self.head = nn.Linear(10, 150)
+
+    def forward(self, x, patch_embed_size):
+        masks = self.head(x)
+        # [b, (h w), c] -> [b, c, h, w]
+        h, w = patch_embed_size[0], patch_embed_size[1]
+        masks = masks.reshape((1, h, w, paddle.shape(masks)[-1]))
+        masks = masks.transpose((0, 3, 1, 2))
+        return masks
+
+
+class SimpleNet(nn.Layer):
+    def __init__(self):
+        super().__init__()
+        self.tmp = nn.Linear(1, 1024 * 10)
+        self.tmp2 = nn.Linear(1, 1 * 10 * 32 * 32)
+        self.head = Head()
+
+    def getshape(self, x):
+        x = self.tmp2(x.mean().reshape([1])).reshape([1, 10, 32, 32])
+        x = paddle.shape(x)
+        return x
+
+    def forward(self, x):
+        sot.psdb.fallback()
+        shape = self.getshape(x)
+        feat = self.tmp(x.mean().reshape([1])).reshape([1, 1024, 10])
+        logits = self.head(feat, shape[2:])
+        return logits
+
+
+class TestSegmentLinear(TestCaseBase):
+    @strict_mode_guard(False)
+    def test_simple(self):
+        x = paddle.randn((1, 8, 8))
+        net = SimpleNet()
+        net = paddle.jit.to_static(
+            net, full_graph=False
+        )  # dont make effect. we need fetch sot PR in paddle.
+        loss = net(x)
+        loss = loss.sum()
+        loss.backward()
+
+
+if __name__ == "__main__":
+    unittest.main()