chore: import upstream snapshot with attribution

test/legacy_test/test_async_read_write.py

@@ -0,0 +1,136 @@
+# Copyright (c) 2021 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 is_custom_device
+
+import paddle
+from paddle.base import core
+from paddle.device import cuda
+
+
+class TestAsyncRead(unittest.TestCase):
+    def func_setUp(self):
+        self.empty = paddle.to_tensor(
+            np.array([], dtype="int64"), place=paddle.CPUPlace()
+        )
+        data = np.random.randn(100, 50, 50).astype("float32")
+        self.src = paddle.to_tensor(data, place=paddle.CUDAPinnedPlace())
+        self.dst = paddle.empty(shape=[100, 50, 50], dtype="float32")
+        self.index = paddle.to_tensor(
+            np.array([1, 3, 5, 7, 9], dtype="int64")
+        ).cpu()
+        self.buffer = paddle.empty(
+            shape=[50, 50, 50], dtype="float32"
+        ).pin_memory()
+        self.stream = cuda.Stream()
+
+    def func_test_async_read_empty_offset_and_count(self):
+        with cuda.stream_guard(self.stream):
+            core.eager.async_read(
+                self.src,
+                self.dst,
+                self.index,
+                self.buffer,
+                self.empty,
+                self.empty,
+            )
+        array1 = paddle.gather(self.src, self.index)
+        array2 = self.dst[: len(self.index)]
+
+        np.testing.assert_allclose(array1.numpy(), array2.numpy(), rtol=1e-05)
+
+    def func_test_async_read_success(self):
+        offset = paddle.to_tensor(
+            np.array([10, 20], dtype="int64"), place=paddle.CPUPlace()
+        )
+        count = paddle.to_tensor(
+            np.array([5, 10], dtype="int64"), place=paddle.CPUPlace()
+        )
+        with cuda.stream_guard(self.stream):
+            core.eager.async_read(
+                self.src, self.dst, self.index, self.buffer, offset, count
+            )
+        # index data
+        index_array1 = paddle.gather(self.src, self.index)
+        count_numel = paddle.sum(count).item()
+        index_array2 = self.dst[count_numel : count_numel + len(self.index)]
+        np.testing.assert_allclose(
+            index_array1.numpy(), index_array2.numpy(), rtol=1e-05
+        )
+
+        # offset, count
+        offset_a = paddle.gather(self.src, paddle.to_tensor(np.arange(10, 15)))
+        offset_b = paddle.gather(self.src, paddle.to_tensor(np.arange(20, 30)))
+        offset_array1 = paddle.concat([offset_a, offset_b], axis=0)
+        offset_array2 = self.dst[:count_numel]
+        np.testing.assert_allclose(
+            offset_array1.numpy(), offset_array2.numpy(), rtol=1e-05
+        )
+
+    def func_test_async_read_only_1dim(self):
+        src = paddle.rand([40], dtype="float32").pin_memory()
+        dst = paddle.empty([40], dtype="float32")
+        buffer_ = paddle.empty([20]).pin_memory()
+        with cuda.stream_guard(self.stream):
+            core.eager.async_read(
+                src, dst, self.index, buffer_, self.empty, self.empty
+            )
+        array1 = paddle.gather(src, self.index)
+        array2 = dst[: len(self.index)]
+        np.testing.assert_allclose(array1.numpy(), array2.numpy(), rtol=1e-05)
+
+    def test_main(self):
+        self.func_setUp()
+        self.func_test_async_read_empty_offset_and_count()
+        self.func_setUp()
+        self.func_test_async_read_success()
+        self.func_setUp()
+        self.func_test_async_read_only_1dim()
+
+
+class TestAsyncWrite(unittest.TestCase):
+    def func_setUp(self):
+        self.src = paddle.rand(shape=[100, 50, 50, 5], dtype="float32")
+        self.dst = paddle.empty(
+            shape=[200, 50, 50, 5], dtype="float32"
+        ).pin_memory()
+        self.stream = cuda.Stream()
+
+    def func_test_async_write_success(self):
+        offset = paddle.to_tensor(
+            np.array([0, 60], dtype="int64"), place=paddle.CPUPlace()
+        )
+        count = paddle.to_tensor(
+            np.array([40, 60], dtype="int64"), place=paddle.CPUPlace()
+        )
+        with cuda.stream_guard(self.stream):
+            core.eager.async_write(self.src, self.dst, offset, count)
+
+        offset_a = paddle.gather(self.dst, paddle.to_tensor(np.arange(0, 40)))
+        offset_b = paddle.gather(self.dst, paddle.to_tensor(np.arange(60, 120)))
+        offset_array = paddle.concat([offset_a, offset_b], axis=0)
+        np.testing.assert_allclose(
+            self.src.numpy(), offset_array.numpy(), rtol=1e-05
+        )
+
+    def test_async_write_success(self):
+        self.func_setUp()
+        self.func_test_async_write_success()
+
+
+if __name__ == "__main__":
+    if core.is_compiled_with_cuda() or is_custom_device():
+        unittest.main()