This repo is dedicated to the updated version of the algorithm presented in the MLST.
The current projects include
data
- Scripts for generating training and testing datatrain
- Pytorch (lightning) code for training neural-networksdeploy
- Triton wapper (hermes) code to deploy trained neural-networks
The repo includes implementation of both gwak1
and gwak2
, where the configs for gwak1
live in the corresponding folder and in the Snakefile
the corresponding rules have _gwak1
.
The project uses poetry
, Conda
and Snakemake
to run the code. Follow installation instructions below to prepare your environment.
If you do not have Miniconda
installed on your machine, follow first those steps
- use the
quickstart
repo to setupMiniconda
and installpoetry
$ git clone git@github.com:ml4gw/quickstart.git
$ cd quickstart
$ make
If you see this error, it is already known in issue#7
Verifying checksum... Done.
Preparing to install helm into /you/path/miniconda3-tmp/bin/
helm installed into /you/path/miniconda3-tmp/bin//helm
helm not found. Is /you/path/miniconda3-tmp/bin/ on your $PATH?
Failed to install helm
For support, go to https://github.com/helm/helm.
make: *** [Makefile:65: install-helm] Error 1
do the following commands:
$ source ~/.bashrc
$ make install-poetry install-kubectl install-s3cmd
If everything was installed successfully, continue to the steps below.
If you do have Miniconda
already installed on your machine, follow those steps
- checkout this repo and clone submodules (such as
ml4gw
)
$ git clone git@github.com:ML4GW/gwak.git
$ cd gwak
$ git submodule update --init --recursive
- create a new
Conda
environment
$ conda env create -n gwak --file environment.yaml
$ conda activate gwak
- install
gwak
project in the editing mode
$ pip install -e .
Now you are ready to gwak! As a first step, you can run the training by doing
$ cd gwak
$ snakemake -c1 train_all
- if you want to modify any of the submodules, first do the changes localy and then re-install
gwak
to pick up the changes:
$ pip install -e .
$ pip install -U 'jsonargparse[signatures]>=4.27.7'
- Installation for deployment
Run the following command at base enviroment.
(base)$ pip install snakemake==7.32.4 pulp==2.6.0
(base)$ cd gwak/gwak/deploy
(base)$ poetry install
Use poetry add <package>
to add new packages to the deploy application.