# 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, memory_allocated class TestMemoryAllocated(unittest.TestCase): def test_memory_allocated(self, device=None): if core.is_compiled_with_cuda() or is_custom_device(): tensor = paddle.zeros(shape=[256]) alloc_size = 4 * 256 # 256 float32 data, with 4 bytes for each one memory_allocated_size = memory_allocated(device) self.assertEqual(memory_allocated_size, alloc_size) def test_memory_allocated_for_all_places(self): if core.is_compiled_with_cuda() or is_custom_device(): gpu_num = device_count() for i in range(gpu_num): paddle.device.set_device("gpu:" + str(i)) self.test_memory_allocated(get_device_place(i)) self.test_memory_allocated(i) self.test_memory_allocated("gpu:" + str(i)) def test_memory_allocated_exception(self): if core.is_compiled_with_cuda() 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 memory_allocated(device) else: with self.assertRaises(ValueError): memory_allocated() if __name__ == "__main__": unittest.main()