Ignite Your Networks!¶
ignite
is a high-level library to help with training and evaluating neural networks in PyTorch flexibly and transparently.
Click on the image to see complete code
Features¶
Less code than pure PyTorch while ensuring maximum control and simplicity
Library approach and no program’s control inversion - Use ignite where and when you need
Extensible API for metrics, experiment managers, and other components
Installation¶
From pip:
pip install pytorch-ignite
From conda:
conda install ignite -c pytorch
From source:
pip install git+https://github.com/pytorch/ignite
Nightly releases¶
From pip:
pip install --pre pytorch-ignite
From conda (this suggests to install pytorch nightly release instead of stable version as dependency):
conda install ignite -c pytorch-nightly
Docker Images¶
Using pre-built images¶
Pull a pre-built docker image from our Docker Hub and run it with docker v19.03+.
docker run --gpus all -it -v $PWD:/workspace/project --network=host --shm-size 16G pytorchignite/base:latest
Available pre-built images are :
pytorchignite/base:latest | pytorchignite/hvd-base:latest | pytorchignite/msdp-apex-base:latest
pytorchignite/apex:latest | pytorchignite/hvd-apex:latest
pytorchignite/vision:latest | pytorchignite/hvd-vision:latest | pytorchignite/msdp-apex-vision:latest
pytorchignite/apex-vision:latest | pytorchignite/hvd-apex-vision:latest
pytorchignite/nlp:latest | pytorchignite/hvd-nlp:latest | pytorchignite/msdp-apex-nlp:latest
pytorchignite/apex-nlp:latest | pytorchignite/hvd-apex-nlp:latest
For more details, see here.
Documentation¶
To get started, please, read Quick start and Concepts.
Library structure¶
ignite
: Core of the library, contains an engine for training and evaluating, most of the classic machine learning metrics and a variety of handlers to ease the pain of training and validation of neural networks.ignite.contrib
: The contrib directory contains additional modules that can require extra dependencies. Modules vary from TBPTT engine, various optimisation parameter schedulers, experiment tracking system handlers and a metrics module containing many regression metrics.