pip install -r requirements.txt

python ./download_dataset.py

python main.py --config ./config/AASIST.conf

python main.py --config ./config/AASIST-L.conf

python main.py --config ./config/RawNet2_baseline.conf

python main.py --config ./config/RawGATST_baseline.conf

python main.py --eval --config ./config/AASIST.conf

python main.py --eval --config ./config/AASIST-L.conf

1. Define your model
  - The model should be a class named "Model"
2. Make a configuration by modifying "model_config"
  - architecture: filename of your model.
  - hyper-parameters to be tuned can be also passed using variables in "model_config"
3. run python main.py --config {CUSTOM_CONFIG_NAME}

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