Examples

We provide several examples ported from pytorch/examples using ignite to display how it helps to write compact and full-featured training loops in a few lines of code:

MNIST example

Basic neural network training on MNIST dataset with/without ignite.contrib module:

• MNIST with ignite.contrib TQDM/Tensorboard/Visdom loggers

• MNIST with native TQDM/Tensorboard/Visdom logging

Distributed CIFAR10 example

Training a small variant of ResNet on CIFAR10 in various configurations: 1) single gpu, 2) single node multiple gpus, 3) multiple nodes and multilple gpus.

• CIFAR10

Other examples

• DCGAN

• Reinforcement Learning

• Fast Neural Style

Notebooks

• Text Classification using Convolutional Neural Networks

• Variational Auto Encoders

• Training Cycle-GAN on Horses to Zebras

• Finetuning EfficientNet-B0 on CIFAR100

• Convolutional Neural Networks for Classifying Fashion-MNIST Dataset

• Hyperparameters tuning with Ax

Reproducible trainings

Inspired by torchvision/references, we provide several reproducible baselines for vision tasks:

• ImageNet

• Pascal VOC2012

Features:

• Distributed training with mixed precision by nvidia/apex

• Experiments tracking with MLflow or Polyaxon