| # Copyright 2023-present the HuggingFace Inc. team. | |
| # | |
| # 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. | |
| # This is a minimal example of launching PEFT with Accelerate. This used to cause issues because PEFT would eagerly | |
| # import bitsandbytes, which initializes CUDA, resulting in: | |
| # > RuntimeError: Cannot re-initialize CUDA in forked subprocess. To use CUDA with multiprocessing, you must use the | |
| # > 'spawn' start method | |
| # This script exists to ensure that this issue does not reoccur. | |
| import torch | |
| from accelerate import notebook_launcher | |
| import peft | |
| from peft.utils import infer_device | |
| def init(): | |
| class MyModule(torch.nn.Module): | |
| def __init__(self): | |
| super().__init__() | |
| self.linear = torch.nn.Linear(1, 2) | |
| def forward(self, x): | |
| return self.linear(x) | |
| device = infer_device() | |
| model = MyModule().to(device) | |
| peft.get_peft_model(model, peft.LoraConfig(target_modules=["linear"])) | |
| def main(): | |
| notebook_launcher(init, (), num_processes=2) | |
| if __name__ == "__main__": | |
| main() | |