wehub-resource-sync
137 lines
5.0 KiB
Python
137 lines
5.0 KiB
Python
# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import unittest
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import numpy as np
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from op_test import is_custom_device
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import paddle
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from paddle.base import core
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from paddle.device import cuda
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class TestAsyncRead(unittest.TestCase):
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def func_setUp(self):
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self.empty = paddle.to_tensor(
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np.array([], dtype="int64"), place=paddle.CPUPlace()
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)
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data = np.random.randn(100, 50, 50).astype("float32")
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self.src = paddle.to_tensor(data, place=paddle.CUDAPinnedPlace())
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self.dst = paddle.empty(shape=[100, 50, 50], dtype="float32")
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self.index = paddle.to_tensor(
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np.array([1, 3, 5, 7, 9], dtype="int64")
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).cpu()
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self.buffer = paddle.empty(
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shape=[50, 50, 50], dtype="float32"
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).pin_memory()
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self.stream = cuda.Stream()
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def func_test_async_read_empty_offset_and_count(self):
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with cuda.stream_guard(self.stream):
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core.eager.async_read(
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self.src,
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self.dst,
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self.index,
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self.buffer,
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self.empty,
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self.empty,
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)
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array1 = paddle.gather(self.src, self.index)
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array2 = self.dst[: len(self.index)]
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np.testing.assert_allclose(array1.numpy(), array2.numpy(), rtol=1e-05)
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def func_test_async_read_success(self):
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offset = paddle.to_tensor(
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np.array([10, 20], dtype="int64"), place=paddle.CPUPlace()
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)
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count = paddle.to_tensor(
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np.array([5, 10], dtype="int64"), place=paddle.CPUPlace()
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)
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with cuda.stream_guard(self.stream):
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core.eager.async_read(
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self.src, self.dst, self.index, self.buffer, offset, count
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)
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# index data
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index_array1 = paddle.gather(self.src, self.index)
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count_numel = paddle.sum(count).item()
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index_array2 = self.dst[count_numel : count_numel + len(self.index)]
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np.testing.assert_allclose(
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index_array1.numpy(), index_array2.numpy(), rtol=1e-05
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)
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# offset, count
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offset_a = paddle.gather(self.src, paddle.to_tensor(np.arange(10, 15)))
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offset_b = paddle.gather(self.src, paddle.to_tensor(np.arange(20, 30)))
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offset_array1 = paddle.concat([offset_a, offset_b], axis=0)
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offset_array2 = self.dst[:count_numel]
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np.testing.assert_allclose(
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offset_array1.numpy(), offset_array2.numpy(), rtol=1e-05
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)
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def func_test_async_read_only_1dim(self):
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src = paddle.rand([40], dtype="float32").pin_memory()
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dst = paddle.empty([40], dtype="float32")
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buffer_ = paddle.empty([20]).pin_memory()
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with cuda.stream_guard(self.stream):
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core.eager.async_read(
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src, dst, self.index, buffer_, self.empty, self.empty
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)
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array1 = paddle.gather(src, self.index)
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array2 = dst[: len(self.index)]
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np.testing.assert_allclose(array1.numpy(), array2.numpy(), rtol=1e-05)
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def test_main(self):
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self.func_setUp()
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self.func_test_async_read_empty_offset_and_count()
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self.func_setUp()
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self.func_test_async_read_success()
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self.func_setUp()
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self.func_test_async_read_only_1dim()
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class TestAsyncWrite(unittest.TestCase):
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def func_setUp(self):
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self.src = paddle.rand(shape=[100, 50, 50, 5], dtype="float32")
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self.dst = paddle.empty(
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shape=[200, 50, 50, 5], dtype="float32"
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).pin_memory()
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self.stream = cuda.Stream()
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def func_test_async_write_success(self):
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offset = paddle.to_tensor(
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np.array([0, 60], dtype="int64"), place=paddle.CPUPlace()
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)
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count = paddle.to_tensor(
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np.array([40, 60], dtype="int64"), place=paddle.CPUPlace()
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)
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with cuda.stream_guard(self.stream):
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core.eager.async_write(self.src, self.dst, offset, count)
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offset_a = paddle.gather(self.dst, paddle.to_tensor(np.arange(0, 40)))
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offset_b = paddle.gather(self.dst, paddle.to_tensor(np.arange(60, 120)))
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offset_array = paddle.concat([offset_a, offset_b], axis=0)
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np.testing.assert_allclose(
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self.src.numpy(), offset_array.numpy(), rtol=1e-05
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)
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def test_async_write_success(self):
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self.func_setUp()
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self.func_test_async_write_success()
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if __name__ == "__main__":
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if core.is_compiled_with_cuda() or is_custom_device():
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unittest.main()
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