Installation¶
Environment setting (optional)¶
For using BRIE2, we recommend creating a separated conda environment for easier and cleaner management of dependent packages, particularly TensorFlow and TensorFlow-probability, which are under active development.
The following command line in terminal (Linux or MacOS) will create a conda
environment with name TFProb
, probably in the path ~/.conda/envs/TFProb
:
conda create -n TFProb python=3.7
Alternatively, you can create the environment in another path by replacing
-n TFProb
with -p ANY_PATH/TFProb
to specify the path for conda
environment. Then you can check your environment by conda env list
and
activate the environment by conda activate TFProb
or the full path, before
start installing brie and other packages.
Easy install¶
BRIE2 is available on PYPI. To install, type the following command
line, and add -U
for upgrading:
pip install -U brie
Alternatively, you can install from this GitHub repository for the latest (often development) version by the following command line
pip install -U git+https://github.com/huangyh09/brie
In either case, if you don’t have write permission for your current Python
environment, add --user
, but check the previous section above for creating
your own conda environment.
GPU usage¶
One of the key benefits of using TensorFlow backend is its direct support of GPU for substantial speedups (generally >10x). Here is one way to set up GPU configurations with NVIDIA GPU on Ubuntu:
pip install -U tensorflow-gpu
conda install -c anaconda cudatoolkit
Make sure that you have compatible versions between tensorflow and NVIDIA CUDA. You can check TF’s test here. For more information on GPU configuration, please refer to the Tensorflow documentation or anaconda GPU.
Once successfully configured, you will see log info like the following when
using brie-quant
:
$ brie-quant
I tensorflow/stream_executor/platform/default/dso_loader.cc:53]
Successfully opened dynamic library libcudart.so.11.0
Welcome to brie-quant in BRIE v2.0.5!
Note
At the moment, TensorFlow calls all available GPUs, which is not necessary.
You can specify the card (e.g., card 3) by adding the below variable before
your command line CUDA_VISIBLE_DEVICES=3 brie-quant -i my_count.h5ad
Test¶
In order to test the installation, you could type brie-quant
. If successful,
you will see the following output.
Welcome to brie-quant in BRIE v2.0.2!
use -h or --help for help on argument.
If you install BRIE successfully, but can’t run it and see the error below,
then check whether its directory is added to PATH
environment.
brie-quant: command not found
Usually, the directory is ~/.local/bin
if you don’t use Anaconda. You could add
the path into PATH
environment variable, by writing the following line into
.profile
or .bashrc
file.
export PATH="~/.local/bin:$PATH"
If you have any issues, please report them to the issue on brie issues.