chore: import upstream snapshot with attribution

test/legacy_test/test_tensor_to_numpy.py

@@ -0,0 +1,61 @@
+# Copyright (c) 2019 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, is_custom_device
+
+from paddle import base
+
+
+class TensorToNumpyTest(unittest.TestCase):
+    def setUp(self):
+        self.shape = [11, 25, 32, 43]
+
+    def test_main(self):
+        dtypes = [
+            'float32',
+            'float64',
+            'int32',
+            'int64',
+            'uint8',
+            'int8',
+            'bool',
+        ]
+
+        places = get_places()
+        if base.core.is_compiled_with_cuda() or is_custom_device():
+            places.append(base.CUDAPinnedPlace())
+
+        for p in places:
+            for dtype in dtypes:
+                np_arr = np.reshape(
+                    np.array(range(np.prod(self.shape))).astype(dtype),
+                    self.shape,
+                )
+
+                t = base.DenseTensor()
+                t.set(np_arr, p)
+
+                ret_np_arr = np.array(t)
+                self.assertEqual(np_arr.shape, ret_np_arr.shape)
+                self.assertEqual(np_arr.dtype, ret_np_arr.dtype)
+
+                all_equal = np.all(np_arr == ret_np_arr)
+                self.assertTrue(all_equal)
+
+
+if __name__ == '__main__':
+    unittest.main()