![]() automatic_optimization = False def sample_z ( self, n ) -> Tensor : sample = self. D = Discriminator () # Important: This property activates manual optimization. Import torch from torch import Tensor from pytorch_lightning import LightningModule class SimpleGAN ( LightningModule ): def _init_ ( self ): super (). Here is a minimal example of manual optimization. ![]() Optimizer.step() to update your model parameters Self.manual_backward(loss) instead of loss.backward() Optimizer.zero_grad() to clear the gradients from the previous training step Self.optimizers() to access your optimizers (one or multiple) Use the following functions and call them manually: Set tomatic_optimization=False in your LightningModule’s _init_. The users are left with optimizer.zero_grad(), gradient accumulation, model toggling, etc. Lightning will handle only accelerator, precision and strategy logic. This is only recommended for experts who need ultimate flexibility. Manually manage the optimization process. Lightning offers two modes for managing the optimization process:įor the majority of research cases, automatic optimization will do the right thing for you and it is what mostįor advanced/expert users who want to do esoteric optimization schedules or techniques, use manual optimization.įor advanced research topics like reinforcement learning, sparse coding, or GAN research, it may be desirable to Multi-agent Reinforcement Learning With WarpDrive.Finetune Transformers Models with PyTorch Lightning.PyTorch Lightning CIFAR10 ~94% Baseline Tutorial.GPU and batched data augmentation with Kornia and PyTorch-Lightning.Tutorial 13: Self-Supervised Contrastive Learning with SimCLR.Tutorial 12: Meta-Learning - Learning to Learn.Tutorial 10: Autoregressive Image Modeling.Tutorial 9: Normalizing Flows for Image Modeling.Tutorial 7: Deep Energy-Based Generative Models.Tutorial 6: Basics of Graph Neural Networks.Tutorial 5: Transformers and Multi-Head Attention. ![]()
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |