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| # // Copyright (c) 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 random | |
| from typing import Optional | |
| import numpy as np | |
| import torch | |
| from common.distributed import get_global_rank | |
| def set_seed(seed: Optional[int], same_across_ranks: bool = False): | |
| """Function that sets the seed for pseudo-random number generators.""" | |
| if seed is not None: | |
| seed += get_global_rank() if not same_across_ranks else 0 | |
| random.seed(seed) | |
| np.random.seed(seed) | |
| torch.manual_seed(seed) | |