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fastai makes deep learning with PyTorch faster, more accurate, and easier

Project description

fastai

The fastai deep learning library.

Copyright 2017 onwards, fast.ai, Inc. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. A copy of the License is provided in the LICENSE file in this repository.

Current Status

This is a ground-up rewrite of fastai. Everything should work, although docs are still in progress. If you're interested in contributing, join the discussion at: http://forums.fast.ai/c/fastai-dev.

Install

To use the notebooks or the beta version of the fastai modules you will need:

  • to use python 3.7 or python 3.6 with dataclasses: pip install dataclasses
  • to use the pytorch-nightly conda package, or the master branch of pytorch master
  • to install fastprogress: pip install fastprogress

PyPI Install

First install the nightly pytorch build, e.g. for CUDA 9.2:

pip install torch_nightly -f https://download.pytorch.org/whl/nightly/cu92/torch_nightly.html

If you have a different CUDA version find the right build here. Choose Preview/Linux/Pip/python3.6|python3.7 and Your CUDA version and it will give you the correct install instruction.

Now you can install fastai. Note, that this is a beta test version at the moment, please report any issues:

pip install --index-url https://test.pypi.org/simple/ --extra-index-url  https://pypi.org/simple/ fastai==1.0.0b6

Sometimes, the last pip command still tries to get torch-0.4.1. If that happens to you, do:

pip uninstall torchvision fastai
pip install --no-deps torchvision
pip install --index-url https://test.pypi.org/simple/ --extra-index-url  https://pypi.org/simple/ fastai==1.0.0b6

Conda Install

To install fastai with CUDA 9.2 simply run (read the paragraph after this for other GPU and CPU options):

conda install -c pytorch -c fastai/label/test fastai cuda92

If your setup doesn't have CUDA support remove the cuda92 above.

For different versions of the CUDA toolkit, you'll need to install the appropriate CUDA conda package based on what you've got installed on your system (i.e. instead of cuda92 in the above, pick the appropriate option for whichever toolkit version you have installed; to see a list of options type: conda search "cuda*" -c pytorch).

Note, that this is a beta test version at the moment, please report any issues. We are currently using a re-packaged torchvision in order to support pytorch-nightly, which is required for using fastai.

Developer Install

First, follow the instructions above for either PyPi or Conda. Then remove the fastai package (pip uninstall fastai or conda uninstall fastai) and replace it with a pip editable install:

git clone https://github.com/fastai/fastai_pytorch
cd fastai_pytorch
pip install -e .
tools/run-after-git-clone

Please refer to CONTRIBUTING.md and the developers guide for more details.

History

1.0.0.beta1 (2018-09-22)

  • First release on PyPI.

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