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Towards Efficient Continual Learning: Strategies on Utilizing Knowledge Distillation Loss

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How To Use

Clone this github repository:

git clone https://github.com/rkdrn79/EKD.git
cd EKD
Optionally, create an environment to run the code (click to expand).

Using a requirements file

The library requirements of the code are detailed in requirements.txt. You can install them using pip with:

python3 -m pip install -r requirements.txt

Using a conda environment

Development environment based on Conda distribution. All dependencies are in environment.yml file.

Create env

To create a new environment check out the repository and type:

conda env create --file environment.yml --name EKD

Notice: set the appropriate version of your CUDA driver for cudatoolkit in environment.yml.

Environment activation/deactivation

conda activate EKD
conda deactivate

To run the basic code:

python3 -u src/main_incremental.py

More options are explained in the src, including GridSearch usage. Also, more specific options on approaches, loggers, datasets and networks.

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  • Python 98.6%
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