| # Copyright 2024 ByteDance 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 os | |
| import random | |
| import numpy as np | |
| import torch | |
| def seed_everything(seed, deterministic): | |
| random.seed(seed) | |
| np.random.seed(seed) | |
| torch.random.manual_seed(seed) | |
| torch.cuda.manual_seed_all(seed) | |
| if deterministic: | |
| torch.backends.cudnn.benchmark = False | |
| # torch.backends.cudnn.deterministic=True applies to CUDA convolution operations, and nothing else. | |
| torch.backends.cudnn.deterministic = True | |
| # torch.use_deterministic_algorithms(True) affects all the normally-nondeterministic operations listed here https://pytorch.org/docs/stable/generated/torch.use_deterministic_algorithms.html?highlight=use_deterministic#torch.use_deterministic_algorithms | |
| torch.use_deterministic_algorithms(True) | |
| # https://docs.nvidia.com/cuda/cublas/index.html#cublasApi_reproducibility | |
| os.environ["CUBLAS_WORKSPACE_CONFIG"] = ":4096:8" | |