Smart-Fermenter

Create Environment

conda create -y -n sf

Install Dependencies

conda activate sf
conda install pytorch==1.10.1 torchvision==0.11.2 torchaudio==0.10.1 cudatoolkit=11.3 -c pytorch -c conda-forge
conda install wandb --channel conda-forge
conda install -c anaconda pandas openpyxl
conda install -c conda-forge matplotlib scikit-learn

Training

python3 train.py --run_name LSTM_Data5_Batch-28 --dataset ./Data5 --model lstm --lr 0.01 --hidden_dim 16 --num_layers 2 --batch_size 8 # --wandb
or
python3 train.py --run_name RNN_Data5_Batch-28 --dataset ./Data5 --model rnn --lr 0.01 --hidden_dim 16 --num_layers 2 --batch_size 32 # --wandb

Testing

python3 test.py --weights logs/Data5/LSTM_Data5_Batch-28/weights_best.tar --dataset ./Data5 --model lstm --hidden_dim 16 --num_layers 2
or
python3 test.py --weights logs/Data5/RNN_Data5_Batch-28/weights_best.tar --dataset ./Data5 --model rnn --hidden_dim 16 --num_layers 2 

Reference

@article{bonanni2023deep,
  title={A Deep Learning Approach to Optimize Recombinant Protein Production in Escherichia coli Fermentations},
  author={Bonanni, Domenico and Litrico, Mattia and Ahmed, Waqar and Morerio, Pietro and Cazzorla, Tiziano and Spaccapaniccia, Elisa and Cattani, Franca and Allegretti, Marcello and Beccari, Andrea Rosario and Del Bue, Alessio and others},
  journal={Fermentation},
  volume={9},
  number={6},
  pages={503},
  year={2023},
  publisher={MDPI}
}