# Welcome to fastai v2
> NB: This is still in early development. Use v1 unless you want to contribute to the next version of fastai
## Installing
You can get all the necessary dependencies by simply installing fastai v1: `conda install -c fastai -c pytorch fastai`. Or alternatively you can automatically install the dependencies into a new environment:
```bash
git clone https://github.com/fastai/fastai2
cd fastai2
conda env create -f environment.yml
source activate fastai2
```
Then, you can install fastai v2 with pip: `pip install fastai2`.
Or you can use an editable install (which is probably the best approach at the moment, since fastai v2 is under heavy development):
```
git clone https://github.com/fastai/fastai2
cd fastai2
pip install -e ".[dev]"
```
You should also use an editable install of [`fastcore`](https://github.com/fastai/fastcore) to go with it.
If you want to browse the notebooks and build the library from them you will need nbdev:
```
pip install nbdev
```
To use `fastai2.medical.imaging` you'll also need to:
```bash
conda install pyarrow
pip install pydicom kornia opencv-python scikit-image
```
## Tests
To run the tests in parallel, launch:
```bash
nbdev_test_nbs
```
or
```bash
make test
```
## Contributing
After you clone this repository, please run `nbdev_install_git_hooks` in your terminal. This sets up git hooks, which clean up the notebooks to remove the extraneous stuff stored in the notebooks (e.g. which cells you ran) which causes unnecessary merge conflicts.
Before submitting a PR, check that the local library and notebooks match. The script `nbdev_diff_nbs` can let you know if there is a difference between the local library and the notebooks.
* If you made a change to the notebooks in one of the exported cells, you can export it to the library with `nbdev_build_lib` or `make fastai2`.
* If you made a change to the library, you can export it back to the notebooks with `nbdev_update_lib`.
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fastai2-0.0.8.tar.gz (91个子文件)
fastai2-0.0.8
MANIFEST.in 210B
PKG-INFO 3KB
settings.ini 758B
LICENSE 11KB
fastai2
vision
models
__init__.py 349B
all.py 42B
xresnet.py 7KB
unet.py 4KB
learner.py 12KB
gan.py 14KB
core.py 9KB
utils.py 2KB
augment.py 34KB
__init__.py 1B
all.py 207B
widgets.py 4KB
data.py 9KB
test_utils.py 1KB
collab.py 5KB
learner.py 27KB
text
models
qrnn.py 8KB
core.py 7KB
forget_mult_cuda.cpp 1KB
awdlstm.py 8KB
bwd_forget_mult_cuda_kernel.cu 5KB
__init__.py 42B
forget_mult_cuda_kernel.cu 5KB
bwd_forget_mult_cuda.cpp 1KB
learner.py 9KB
core.py 15KB
__init__.py 1B
all.py 137B
data.py 11KB
imports.py 3KB
torch_imports.py 411B
data
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core.py 14KB
__init__.py 1B
all.py 140B
load.py 6KB
block.py 8KB
checks.txt 6KB
external.py 9KB
metrics.py 14KB
medical
imaging.py 10KB
text.py 144B
__init__.py 0B
basics.py 119B
notebook
core.py 1KB
showdoc.py 10KB
test.py 4KB
export2html.py 14KB
__init__.py 0B
export.py 18KB
tabular
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core.py 12KB
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fp16_utils.py 7KB
__init__.py 23B
torch_core.py 26KB
_nbdev.py 38KB
layers.py 26KB
interpret.py 4KB
torch_basics.py 134B
callback
hook.py 9KB
tensorboard.py 3KB
tracker.py 5KB
wandb.py 5KB
schedule.py 8KB
rnn.py 1KB
__init__.py 1B
progress.py 4KB
mixup.py 2KB
fp16.py 6KB
all.py 170B
data.py 1KB
optimizer.py 14KB
distributed.py 4KB
fastai2.egg-info
PKG-INFO 3KB
requires.txt 148B
not-zip-safe 1B
SOURCES.txt 2KB
top_level.txt 8B
dependency_links.txt 1B
setup.cfg 38B
setup.py 2KB
README.md 2KB
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