# Copyright (c) 2024 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 import numpy as np from op_test import is_custom_device import paddle from paddle.distributed.fleet.utils.timer_helper import get_timers, set_timers class TestGPUEventTimer(unittest.TestCase): def test_main(self): if not (paddle.is_compiled_with_cuda() or is_custom_device()): return if paddle.is_compiled_with_rocm(): return set_timers() key = "matmul" x = paddle.randn([1024, 1024]) timers = get_timers() use_event = True timers(key, use_event=use_event).pre_alloc(5) for _ in range(2): for _ in range(3): timers(key, use_event=use_event).start() paddle.matmul(x, x) timers(key, use_event=use_event).stop() times = timers(key, use_event=use_event).elapsed_list(reset=False) assert isinstance(times, np.ndarray), times times2 = timers(key, use_event=use_event).elapsed_list(reset=False) np.testing.assert_array_equal(times, times2) timers.log(timers.timers.keys()) assert timers(key, use_event=use_event).size() == 0 assert timers(key, use_event=use_event).capacity() > 0 timers(key, use_event=use_event).shrink_to_fit() assert timers(key, use_event=use_event).size() == 0 assert timers(key, use_event=use_event).capacity() == 0 if __name__ == "__main__": unittest.main()