chore: import upstream snapshot with attribution

test/legacy_test/test_elementwise_tensor_split.py

@@ -0,0 +1,67 @@
+#  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 re
+import unittest
+
+import numpy as np
+from op_test import is_custom_device
+
+import paddle
+from paddle.base import core
+
+
+class TestElementwiseOp(unittest.TestCase):
+    def setUp(self):
+        self.op_type = "elementwise_sub"
+        self.python_api = paddle.subtract
+        self.public_python_api = paddle.subtract
+        self.prim_op_type = "prim"
+
+    def test_float16_sub(self):
+        if not (core.is_compiled_with_cuda() or is_custom_device()):
+            return
+
+        gpu_info = paddle.device.get_device_properties()
+
+        gpu_name = gpu_info.name
+        try:
+            re_result = re.split(r'[ , -]', gpu_name)
+            memory = int(re_result[-1][:-2])
+        except:
+            memory = int(gpu_info.total_memory) // (1000**3)
+        if memory < 37:  # 37GB
+            return
+
+        paddle.disable_static()
+        tensor_a = paddle.rand(shape=[5120, 4, 384, 384], dtype="float16")
+        tensor_b = paddle.rand(shape=[5120, 1, 384, 384], dtype="float16")
+        tensor_z = paddle.subtract(tensor_a, tensor_b)
+
+        in0, in1 = paddle.split(tensor_a, num_or_sections=2, axis=1)
+        (
+            out0,
+            out1,
+        ) = paddle.split(tensor_z, num_or_sections=2, axis=1)
+
+        split_add0 = paddle.subtract(tensor_b, in0)
+        split_add1 = paddle.subtract(tensor_b, in1)
+
+        result1 = paddle.any(paddle.equal(out0, split_add0), [0, 1, 2, 3])
+        result2 = paddle.any(paddle.equal(out1, split_add1), [0, 1, 2, 3])
+        np.testing.assert_equal(result1.numpy(), True)
+        np.testing.assert_equal(result2.numpy(), True)
+
+
+if __name__ == '__main__':
+    unittest.main()