Yet Another Session for Training Artificial Intelligence
This is a framework for easy development of new AI Research Projects.
- Anaconda Envirment.
- AI project structure.
- Tensorflow, Keras and Scikit-learn.
- HPC jobs manager.
- Pip Package.
- Weight and Bias easy setup.
- Notebooks.
- Nose unit tests.
- Singularity container.
- Easy experiment reproducibility.
This is a guide to understand the zen of this repository.
There are 5 folder for develop you new project:
AI
folder is your AI project package, for more details check AI/README.md
If you want to rename the IA
folder with your project name, you must also edit theses files:
setup.py
: replaceia_name
variable in line 7.__version__.py
insideAI
folder.- Maybe you want to edit the conda envirment file
yastai.yml
. - Replace
from AI import *
in every script intrain/
. - Replace
from AI import *
in every nootebook innotebooks/
. - Replace
from AI import *
in every nootebook intests/
. - Replace AI from files in
docs/
. HPC train scripts maybeconda environment maybe
Collections of scripts for setup your data, config preprocessing pipes, and train/evaluate your models.
In these folder you can find also:
experiments/
: Folder with experiments configurations and results. More details and name conventions intrain/experiments/README.md
.debug.py
: Utils functions for check GPU support, profiling keras/tensorflow models and plots models.hpc/
: Script and instructions for run experiments in HPC environments.
More details for train/
folder in train/README.md
.
Contains notebook version of the scripts in \train
. More details in notebooks/README.md
.
Handy for Google Colab
.
Collections of user defined unit tests with nose
.
Here a tutorial for nose oython testing.
More details in tests/README.md
.
Different options for consume a trained model.
More details in api/README.md
.
TODO
Check anaconda documentation here.
environment.yml
conda env create -f environment.yml --prefix ./.env
TODO
Manually add packages to enviroment.yml
and Pipfile
.
TODO
TODO