Lightning-Sandbox documentation¶ All Tutorial 1: Introduction to PyTorch This tutorial will give a short introduction to PyTorch basics, and get you setup for writing your own neural networks. This notebook is part of a lecture series on Deep... GPU/TPU,UvA-DL-Course Tutorial 2: Activation Functions In this tutorial, we will take a closer look at (popular) activation functions and investigate their effect on optimization properties in neural networks. Activation functions... GPU/TPU,UvA-DL-Course Tutorial 3: Initialization and Optimization In this tutorial, we will review techniques for optimization and initialization of neural networks. When increasing the depth of neural networks, there are various challenges... Image,Initialization,Optimizers,GPU/TPU,UvA-DL-Course Tutorial 4: Inception, ResNet and DenseNet In this tutorial, we will implement and discuss variants of modern CNN architectures. There have been many different architectures been proposed over the past few years. Some... Image,GPU/TPU,UvA-DL-Course Tutorial 5: Transformers and Multi-Head Attention In this tutorial, we will discuss one of the most impactful architectures of the last 2 years: the Transformer model. Since the paper Attention Is All You Need by Vaswani et... Text,GPU/TPU,UvA-DL-Course Tutorial 6: Basics of Graph Neural Networks In this tutorial, we will discuss the application of neural networks on graphs. Graph Neural Networks (GNNs) have recently gained increasing popularity in both applications... Graph,GPU/TPU,UvA-DL-Course Tutorial 7: Deep Energy-Based Generative Models In this tutorial, we will look at energy-based deep learning models, and focus on their application as generative models. Energy models have been a popular tool before the... Image,GPU/TPU,UvA-DL-Course Tutorial 8: Deep Autoencoders In this tutorial, we will take a closer look at autoencoders (AE). Autoencoders are trained on encoding input data such as images into a smaller feature vector, and afterward,... Image,GPU/TPU,UvA-DL-Course Tutorial 9: Normalizing Flows for Image Modeling In this tutorial, we will take a closer look at complex, deep normalizing flows. The most popular, current application of deep normalizing flows is to model datasets of... Image,GPU/TPU,UvA-DL-Course Tutorial 10: Autoregressive Image Modeling In this tutorial, we implement an autoregressive likelihood model for the task of image modeling. Autoregressive models are naturally strong generative models that constitute... Image,GPU/TPU,UvA-DL-Course Tutorial 11: Vision Transformers In this tutorial, we will take a closer look at a recent new trend: Transformers for Computer Vision. Since [Alexey Dosovitskiy et... Image,GPU/TPU,UvA-DL-Course Electricity Price Forecasting with N-BEATS This tutorial covers using Lightning Flash and it's integration with PyTorch Forecasting to train an autoregressive model (N-BEATS) on hourly electricity pricing data. We show... Tabular,Forecasting,Timeseries,GPU/TPU,Kaggle Image Classification on Hymenoptera Dataset In this tutorial, we'll go over the basics of lightning Flash by finetuning/predictin with an ImageClassifier on [Hymenoptera... Image-Classification,Image,GPU/TPU,Kaggle Tabular Classification on Titanic Dataset In this notebook, we'll go over the basics of lightning Flash by training a TabularClassifier on [Titanic Dataset](https://www.kaggle.com/c/titanic). Tabular-Classification,Tabular,GPU/TPU,Kaggle Finetuning a Text Classifier on IMDB Dataset In this notebook, we'll go over the basics of lightning Flash by finetunig a TextClassifier on IMDB Dataset. Text-Classification,Text,GPU/TPU,Kaggle PyTorch Lightning CIFAR10 ~94% Baseline Tutorial Train a Resnet to 94% accuracy on Cifar10! Image,GPU/TPU,Lightning-Examples PyTorch Lightning DataModules This notebook will walk you through how to start using Datamodules. With the release of `pytorch-lightning` version 0.9.0, we have included a new class called... GPU/TPU,Lightning-Examples Fine-Tuning Scheduler This notebook introduces the [Fine-Tuning Scheduler](https://finetuning-scheduler.readthedocs.io/en/stable/index.html) extension and demonstrates the use of it to fine-tune a... Fine-Tuning,GPU/TPU,Lightning-Examples Multi-agent Reinforcement Learning With WarpDrive This notebook introduces multi-agent reinforcement learning (MARL) with WarpDrive (Lan et al. https://arxiv.org/abs/2108.13976). WarpDrive is a flexible, lightweight, and... Reinforcement-Learning,Multi-agent,GPU,GPU/TPU,Lightning-Examples Simple image classification with Lightning Flash This is a template to show simple image classification case if for some reason accelerator is required. Image,GPU/TPU,templates How to write a PyTorch Lightning tutorial This is a template to show how to contribute a tutorial. GPU/TPU,templates Solving Titanic dataset with Lightning Flash This is a template to show how to contribute a tutorial. GPU/TPU,templates Start here 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 Electricity Price Forecasting with N-BEATS Image Classification on Hymenoptera Dataset Finetuning Tabular Classification on Titanic Dataset Training Predicting Finetuning a Text Classifier on IMDB Dataset Finetuning PyTorch Lightning CIFAR10 ~94% Baseline Tutorial PyTorch Lightning DataModules Fine-Tuning Scheduler Multi-agent Reinforcement Learning With WarpDrive Simple image classification with Lightning Flash How to write a PyTorch Lightning tutorial Solving Titanic dataset with Lightning Flash Indices and tables¶ Index Module Index Search Page