chore: import upstream snapshot with attribution

test/legacy_test/test_complex_transpose.py

@@ -0,0 +1,44 @@
+#   Copyright (c) 2020 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
+from op_test import get_places
+
+import paddle
+import paddle.base.dygraph as dg
+
+
+class TestComplexTransposeLayer(unittest.TestCase):
+    def setUp(self):
+        self._dtypes = ["float32", "float64"]
+        self._places = get_places()
+
+    def test_transpose_by_complex_api(self):
+        for dtype in self._dtypes:
+            data = np.random.random((2, 3, 4, 5)).astype(
+                dtype
+            ) + 1j * np.random.random((2, 3, 4, 5)).astype(dtype)
+            perm = [3, 2, 0, 1]
+            np_trans = np.transpose(data, perm)
+            for place in self._places:
+                with dg.guard(place):
+                    var = paddle.to_tensor(data)
+                    trans = paddle.transpose(var, perm=perm)
+                np.testing.assert_allclose(trans.numpy(), np_trans, rtol=1e-05)
+
+
+if __name__ == '__main__':
+    unittest.main()