.
├── data
│ ├── processed <- processed data
│ └── raw <- original unmodified/raw data
├── models <- folder for ML models
├── notebooks <- Jupyter Notebooks (ingored by Git)
├── reports <- folder for experiment reports
├── model-a <- Model A sub-directory (DVC repo)
├── model-b <- Model B sub-directory (DVC repo)
├── model-c <- Model C sub-directory (DVC repo)
└── README.md
- models A and B outputs are used by Model C as inputs
Create virtual environment named .venv
(you may use other name)
python3 -m venv .venv
echo "export PYTHONPATH=$PWD" >> .venv/bin/activate
source .venv/bin/activate
pip install --upgrade pip setuptools wheel
pip install -r requirements.txt
# Navigate to `model_a` dir: cd model_a
dvc init
git add .dvc/config .dvc/.gitignore && git commit -m "Initialize DVC project"
# Navigate to `model_a` dir: cd model_a
dvc init --subdir
git add .dvc/config .dvc/.gitignore && git commit -m "Initialize DVC project A"
# Navigate to `model_b` dir: cd model_b
dvc init --subdir
git add .dvc/config .dvc/.gitignore && git commit -m "Initialize DVC project B"
# Navigate to `model_c` dir: cd model_c
dvc init --subdir
git add .dvc/config .dvc/.gitignore && git commit -m "Initialize DVC project C"
dvc exp run