Abstract: This project includes parallel training pipeline with Metaflow based on gender classification problem. The focus is on practicing the tools used, not the problem that model solves.
CelebAHQ dataset was used for training and WIKI dataset was used for validation. Processed images can be downloaded from here then unzip file to src/Data
CelebAHQ: 30000 images
WIKI: 38455 images
All training and hyperparameter tuning parameters can be changed from the train.py file. Descriptions of all parameters are available in the file.
conda create --name meta python==3.7.13
conda activate meta
pip install -r requirements.txt
# For Cuda 11.1
pip install torch==1.10.1+cu111 torchvision==0.11.2+cu111 -f https://download.pytorch.org/whl/torch_stable.html
# For Cuda 10.2
pip install torch==1.10.1+cu102 torchvision==0.11.2+cu102 -f https://download.pytorch.org/whl/torch_stable.html
python train.py run
docker build -t meta .
docker run --runtime=nvidia -it meta train.py run