LightningDataModule specifying training samples. Train_dataloaders ¶ ( Union, Sequence], Sequence], Dict, Dict], Dict], LightningDataModule, None]) – A collection of or a Model ¶ ( LightningModule) – Model to tune. lr_find ( model, train_dataloaders = None, val_dataloaders = None, dataloaders = None, datamodule = None, method = 'fit', min_lr = 1e-08, max_lr = 1, num_training = 100, mode = 'exponential', early_stop_threshold = 4.0, update_attr = False ) ¶Įnables the user to do a range test of good initial learning rates, to reduce the amount of guesswork in 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.Tutorial 4: Inception, ResNet and DenseNet.Tutorial 3: Initialization and Optimization.LightningLite (Stepping Stone to Lightning).Organize existing PyTorch into Lightning.

Image tuner 3.5