LiFe-net: Data-driven Modelling of Time-dependent Temperatures and Charging Statistics Of Tesla’s LiFePo4 EV Battery
cuda 11.1
python/3.7.4
torch>=1.8.1
numpy>=1.19.5
matplotlib>=3.1.1
python LiFe-net_baseline.py
python LiFe-net_regularised.py
python LiFe-net_t_stability.py
model.load_state_dict(torch.load(PATH))
See evaluation_plots.ipynb
Jupyter Notebook
See documentations of Weights and Biases library: https://docs.wandb.ai/guides/sweeps
Example:
python -m wandb sweep sweep-alpha.yaml
python -m wandb agent 'name/of/the/agent'