62 lines
2.2 KiB
Python
62 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 is_custom_device
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import paddle
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from paddle.base import core
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paddle.set_device('cpu')
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class TestHostMemoryStats(unittest.TestCase):
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def test_memory_allocated_with_pinned(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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tensor_pinned = tensor.pin_memory()
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alloc_size = 4 * 256 # 256 float32 data, with 4 bytes for each one
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memory_allocated_size = core.host_memory_stat_current_value(
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"Allocated", 0
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)
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self.assertEqual(memory_allocated_size, alloc_size * 2)
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def foo():
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tensor = paddle.zeros(shape=[256])
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tensor_pinned = tensor.pin_memory()
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memory_allocated_size = core.host_memory_stat_current_value(
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"Allocated", 0
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)
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self.assertEqual(memory_allocated_size, alloc_size * 4)
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max_allocated_size = core.host_memory_stat_peak_value(
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"Allocated", 0
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)
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self.assertEqual(memory_allocated_size, alloc_size * 4)
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foo()
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memory_allocated_size = core.host_memory_stat_current_value(
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"Allocated", 0
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)
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self.assertEqual(memory_allocated_size, alloc_size * 2)
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max_allocated_size = core.host_memory_stat_peak_value(
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"Allocated", 0
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)
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self.assertEqual(max_allocated_size, alloc_size * 4)
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if __name__ == "__main__":
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unittest.main()
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