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paddlepaddle--paddle/test/legacy_test/test_cuda_max_memory_allocated.py
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2026-07-13 12:40:42 +08:00

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Python

# 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
from op_test import get_device_place, is_custom_device
import paddle
from paddle.base import core
from paddle.device.cuda import (
device_count,
max_memory_allocated,
memory_allocated,
)
class TestMaxMemoryAllocated(unittest.TestCase):
def func_test_max_memory_allocated(self, device=None):
if (
core.is_compiled_with_cuda() or is_custom_device()
) or is_custom_device():
alloc_time = 100
max_alloc_size = 10000
peak_memory_allocated_size = max_memory_allocated(device)
for i in range(alloc_time):
shape = paddle.randint(max_alloc_size)
tensor = paddle.zeros(shape)
peak_memory_allocated_size = max(
peak_memory_allocated_size, memory_allocated(device)
)
del shape
del tensor
self.assertEqual(
peak_memory_allocated_size, max_memory_allocated(device)
)
def test_max_memory_allocated_for_all_places(self):
if (
core.is_compiled_with_cuda() or is_custom_device()
) or is_custom_device():
gpu_num = device_count()
for i in range(gpu_num):
paddle.device.set_device("gpu:" + str(i))
self.func_test_max_memory_allocated(get_device_place(i))
self.func_test_max_memory_allocated(i)
self.func_test_max_memory_allocated("gpu:" + str(i))
def test_max_memory_allocated_exception(self):
if (
core.is_compiled_with_cuda() or is_custom_device()
) or is_custom_device():
wrong_device = [
core.CPUPlace(),
device_count() + 1,
-2,
0.5,
"gpu1",
]
for device in wrong_device:
with self.assertRaises(BaseException): # noqa: B017
max_memory_allocated(device)
else:
with self.assertRaises(ValueError):
max_memory_allocated()
if __name__ == "__main__":
unittest.main()