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Table of Contents

1.5.8

Getting started

Lightning in 2 steps
How to organize PyTorch into Lightning
Rapid prototyping templates
LightningLite - Stepping Stone to Lightning

Best practices

Speed up model training
Managing Data
Style guide
Lightning project template
Benchmark with vanilla PyTorch

Lightning API

LightningModule
Trainer

Common Use Cases

Cloud Training
Computing cluster
Child Modules
Debugging
Early stopping
Hyperparameters
Inference in Production
IPU support
Lightning CLI and config files
Learning Rate Finder
Loggers
Multi-GPU training
Model Parallel GPU Training
Mixed Precision Training
Saving and loading weights
Fault-tolerant Training
Custom Checkpointing IO
Optimization
Performance and Bottleneck Profiler
Training Type Plugins Registry
Sequential Data
Single GPU Training
Training Tricks
Pruning and Quantization
Transfer Learning
TPU support
Test set

Optional extensions

Accelerators
Callback
LightningDataModule
Logging
Plugins
Loops

Tutorials

Step-by-step walk-through
PyTorch Lightning 101 class
From PyTorch to PyTorch Lightning [Blog]
From PyTorch to PyTorch Lightning [Video]
Tutorial 1: Introduction to PyTorch
Tutorial 2: Activation Functions
Tutorial 3: Initialization and Optimization
Tutorial 4: Inception, ResNet and DenseNet
Tutorial 5: Transformers and Multi-Head Attention
Tutorial 6: Basics of Graph Neural Networks
Tutorial 7: Deep Energy-Based Generative Models
Tutorial 8: Deep Autoencoders
Tutorial 9: Normalizing Flows for Image Modeling
Tutorial 10: Autoregressive Image Modeling
Tutorial 11: Vision Transformers
Tutorial 12: Meta-Learning - Learning to Learn
Tutorial 13: Self-Supervised Contrastive Learning with SimCLR
GPU and batched data augmentation with Kornia and PyTorch-Lightning
Barlow Twins Tutorial
PyTorch Lightning Basic GAN Tutorial
PyTorch Lightning CIFAR10 ~94% Baseline Tutorial
PyTorch Lightning DataModules
Introduction to Pytorch Lightning
TPU training with PyTorch Lightning
How to train a Deep Q Network
Finetune Transformers Models with PyTorch Lightning

API References

API References

Bolts

Bolts

Examples

Community Examples
PyTorch Ecosystem Examples
Autoencoder
BYOL
DQN
GAN
GPT-2
Image-GPT
SimCLR
VAE

Partner Domain Frameworks

Conversational AI

Community

Contributor Covenant Code of Conduct
Contributing
How to become a core contributor
Lightning Governance
Changelog

Docs >
Callback >
ProgressBar

Shortcuts

ProgressBar¶

class pytorch_lightning.callbacks.ProgressBar(*args, **kwargs)[source]¶: Bases: pytorch_lightning.callbacks.progress.tqdm_progress.TQDMProgressBar

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