This repository borrows most of the code from the paper

Hao Li, Zheng Xu, Gavin Taylor, Christoph Studer and Tom Goldstein. Visualizing the Loss Landscape of Neural Nets. NIPS, 2018.

Given a network architecture and its pre-trained parameters, this tool memorize and visualizes the optimization trajectory. The calculation is set to be done on single GPU, with multiple process.

Setup

Ensure the following software/libraries installed:

• Python 3.10
• PyTorch 2.0

You can install other dependencies using the following command:

pip install -r requirements.txt

Then, launch the backend simply run:

python api.py

Reference

EfficientNetV2 implementation

Other CNNs