fastai makes deep learning with PyTorch faster, more accurate, and easier
The fastai deep learning library. See the fastai website to get started.
To install fastai with pytorch-nightly + CUDA 9.2 simply run:
conda install -c pytorch -c fastai fastai pytorch-nightly cuda92
If your setup doesn't have CUDA support remove the
cuda92 above (in which case you'll only be able to train on CPU, not GPU, which will be much slower). 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).
NB: We are currently using a re-packaged torchvision in order to support pytorch-nightly, which is required for using fastai.
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.
Next, install a custom
torchvision build, that is built against
pip install --index-url https://test.pypi.org/simple/ --extra-index-url https://pypi.org/simple/ torchvision==0.2.1.post1
Now you can install
fastai. Note, that this is a beta test version at the moment, please report any issues:
pip install fastai==1.0.0b8
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 fastai==1.0.0b8
First, follow the instructions above for either
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 cd fastai pip install -e . tools/run-after-git-clone
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.
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