Metadata-Version: 2.1
Name: fastai
Version: 1.0.2
Summary: fastai makes deep learning with PyTorch faster, more accurate, and easier
Home-page: https://github.com/fastai/fastai
Author: Jeremy Howard
Author-email: info@fast.ai
License: Apache Software License 2.0
Keywords: fastai
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Requires-Python: >=3.6
Description-Content-Type: text/markdown
Requires-Dist: fastprogress
Requires-Dist: ipython
Requires-Dist: matplotlib
Requires-Dist: numpy (>=1.12)
Requires-Dist: pandas
Requires-Dist: Pillow
Requires-Dist: requests
Requires-Dist: scipy
Requires-Dist: spacy
Requires-Dist: torchvision (>=0.2.1)
Requires-Dist: typing
Requires-Dist: dataclasses

# fastai

The fastai deep learning library. See the [fastai website](http://docs.fast.ai) to get started.

### Conda Install

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.

### 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](https://pytorch.org/get-started/locally/). 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 `torch_nightly`.

```
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](https://github.com/fastai/fastai/issues/):

```
pip install fastai
```

 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
```

### 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](http://codumentary.blogspot.com/2014/11/python-tip-of-year-pip-install-editable.html):

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

Please refer to [CONTRIBUTING.md](https://github.com/fastai/fastai/blob/master/CONTRIBUTING.md) and [the developers guide](http://docs.fast.ai/developers.html) for more details.

### Copyright

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.


# History

1.0.0 (2018-10-01)
------------------

* Released on Conda and Pypi

1.0.0.beta1 (2018-09-22)
------------------

* First release on PyPI.


