优化器和LR调度器(configure_optimizers())当你使用Lightning时,代码不是抽象的——只是组织起来的。所有不在LightningModule中的其他代码都已由Trainer自动为您执行。net = MyLightningModuleNet() trainer = Trainer() trainer.fit(net)不需要.cuda()或.to(device)
在这个示例中,我们定义了一个简单的MNIST分类模型CustomMNIST,它继承自LightningModule。我们实现了forward方法来定义模型的前向传播逻辑,training_step方法来定义训练步骤中的损失计算逻辑,以及configure_optimizers方法来配置模型优化器。最后,我们使用Trainer类来训练模型。
self.validation_step_outputs.clear() def configure_optimizers(self): optimizer = torch.optim.Adam(self.parameters(), lr=1e-3) return optimizer trainer = L.Trainer( accelerator="cuda", strategy='auto', precision="16-mixed", devices=1, max_epochs=100#, default_root_dir="./log", ) train...
()returnlossdefconfigure_optimizers(self):# note: we are passing in all params, including the one that is not usedreturntorch.optim.SGD(self.parameters(),lr=0.1)train_data=DataLoader(RandomDataset(32,64),batch_size=2)model=BoringModel()trainer=Trainer(default_root_dir=os.getcwd(),max_...
Available add-ons Advanced Security Enterprise-grade security features Copilot for business Enterprise-grade AI features Premium Support Enterprise-grade 24/7 support Pricing Search or jump to... Search code, repositories, users, issues, pull requests... Provide feedback We read every piece...
Pretrain, finetune and deploy AI models on multiple GPUs, TPUs with zero code changes. - pytorch-lightning/src/lightning/pytorch/core/module.py at master · Lightning-AI/pytorch-lightning
But I receive an error: AttributeError: module 'logging' has no attribute 'TensorBoardLogger' To Reproduce ubuntu@ip-172-31-41-72:~$ mkdir pltest ubuntu@ip-172-31-41-72:~$cdpltest/ ubuntu@ip-172-31-41-72:~/pltest$ pipenv --python 3.7 Creating a virtualenvforthis project… Pipfile:...