# Copyright (c) 2022 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 paddle.distributed.auto_parallel.static.tuner import trial as tr from paddle.distributed.auto_parallel.static.tuner import tunable_space as ts class TestTiral(unittest.TestCase): def test_trial(self): space = ts.TunableSpace() space.choice("choice", [0, 1, 2, 3], default=2) trial = tr.Trial(space, trial_id="trial-1") trial.recorder.register("latency", direction="min") trial.recorder.update("latency", 0.1, step=0) trial.recorder.update("latency", 0.2, step=1) trial.best_step = 0 self.assertEqual(trial.id, "trial-1") self.assertEqual(trial.space.get_value("choice"), 2) self.assertEqual(trial.best_step, 0) self.assertEqual(trial.status, "RUNNING") def test_serialization(self): space = ts.TunableSpace() space.int_range("int_range", start=1, stop=4, default=2) trial = tr.Trial(space, trial_id="trial-2", status="COMPLETED") trial.recorder.register("latency", direction="min") trial.recorder.update("latency", 0.1, step=0) trial.recorder.update("latency", 0.2, step=1) trial.best_step = 0 new_trial = tr.Trial.from_state(trial.get_state()) self.assertEqual(new_trial.id, "trial-2") self.assertEqual(new_trial.space.get_value("int_range"), 2) self.assertEqual(new_trial.best_step, 0) self.assertEqual(new_trial.status, "COMPLETED") if __name__ == "__main__": unittest.main()