# Copyright 2025 Bytedance Ltd. and/or its affiliates # # 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 pytest from verl.workers.config.optimizer import FSDPOptimizerConfig class TestFSDPOptimizerConfigCPU: def test_default_configuration(self): config = FSDPOptimizerConfig(lr=0.1) assert config.min_lr_ratio is None assert config.lr_scheduler_type == "constant" assert config.num_cycles == 0.5 @pytest.mark.parametrize("lr_scheduler_type", ["constant", "cosine"]) def test_valid_lr_scheduler_types(self, lr_scheduler_type): config = FSDPOptimizerConfig(lr_scheduler_type=lr_scheduler_type, lr=0.1) assert config.lr_scheduler_type == lr_scheduler_type @pytest.mark.parametrize("warmup_style", ["constant", "cosine"]) def test_valid_warmup_style_types(self, warmup_style): config = FSDPOptimizerConfig(warmup_style=warmup_style, lr=0.1) assert config.lr_scheduler_type == warmup_style def test_invalid_lr_scheduler_type(self): with pytest.raises((ValueError, AssertionError)): FSDPOptimizerConfig(lr_scheduler_type="invalid_style", lr=0.1) def test_invalid_warmup_style_type(self): with pytest.raises((ValueError, AssertionError)): FSDPOptimizerConfig(warmup_style="invalid_style", lr=0.1) @pytest.mark.parametrize("num_cycles", [0.1, 1.0, 2.5]) def test_num_cycles_configuration(self, num_cycles): config = FSDPOptimizerConfig(num_cycles=num_cycles, lr=0.1) assert config.num_cycles == num_cycles