chore: import upstream snapshot with attribution

test/sot/test_simulate_initialize.py

@@ -0,0 +1,90 @@
+# 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.sot import symbolic_translate
+from paddle.jit.sot.utils import strict_mode_guard
+
+
+class A:
+    def __init__(self, vals):
+        vals.append(1)
+
+
+def foo(x, y):
+    out = nn.Softmax()(paddle.to_tensor([x, y], dtype="float32"))
+    return out
+
+
+def foo2(x, y):
+    t = nn.Softmax()
+    out1 = t(paddle.to_tensor([x, y], dtype="float32"))
+    out2 = t(paddle.to_tensor([x, y], dtype="float32"))
+    return out1 + out2
+
+
+def error_foo(x):
+    t = nn.Linear(10, 10)
+    return t(x)
+
+
+class NopLayer(paddle.nn.Layer):
+    def __init__(self):
+        super().__init__()
+        self.weight = None
+
+
+def created_layer_reconstruct():
+    x = paddle.to_tensor([1, 2], dtype="float32")
+    weight = NopLayer().weight
+    if weight is not None:
+        x += 1
+    return x
+
+
+def bar(x):
+    a = A(x)
+    t = paddle.to_tensor(x)
+    return t.mean()
+
+
+class TestInit(TestCaseBase):
+    def test_init_paddle_layer(self):
+        self.assert_results(foo, 1, 2)
+        self.assert_results(foo2, 1, 2)
+
+    def test_init_python_object(self):
+        sot_output = symbolic_translate(bar)([1.0, 2.0])
+        dyn_output = bar([1.0, 2.0])
+        self.assert_nest_match(sot_output, dyn_output)
+
+    def test_error(self):
+        def run():
+            inputs = paddle.randn((10, 10))
+            symbolic_translate(error_foo)(inputs)
+
+        self.assertRaises(paddle.jit.sot.utils.exceptions.InnerError, run)
+
+    @strict_mode_guard(False)
+    def test_created_layer_reconstruct(self):
+        self.assert_results(created_layer_reconstruct)
+
+
+if __name__ == "__main__":
+    unittest.main()