wehub-resource-sync
59 lines
2.2 KiB
Python
59 lines
2.2 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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from op_test import get_device_place, 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.cuda import device_count, memory_allocated
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class TestMemoryAllocated(unittest.TestCase):
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def test_memory_allocated(self, device=None):
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if core.is_compiled_with_cuda() or is_custom_device():
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tensor = paddle.zeros(shape=[256])
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alloc_size = 4 * 256 # 256 float32 data, with 4 bytes for each one
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memory_allocated_size = memory_allocated(device)
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self.assertEqual(memory_allocated_size, alloc_size)
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def test_memory_allocated_for_all_places(self):
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if core.is_compiled_with_cuda() or is_custom_device():
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gpu_num = device_count()
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for i in range(gpu_num):
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paddle.device.set_device("gpu:" + str(i))
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self.test_memory_allocated(get_device_place(i))
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self.test_memory_allocated(i)
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self.test_memory_allocated("gpu:" + str(i))
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def test_memory_allocated_exception(self):
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if core.is_compiled_with_cuda() or is_custom_device():
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wrong_device = [
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core.CPUPlace(),
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device_count() + 1,
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-2,
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0.5,
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"gpu1",
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]
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for device in wrong_device:
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with self.assertRaises(BaseException): # noqa: B017
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memory_allocated(device)
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else:
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with self.assertRaises(ValueError):
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memory_allocated()
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if __name__ == "__main__":
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unittest.main()
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