Based on the paper "Semantic Cognition: A Parallel Distributed Processing Approach" from 2003 by Rogers and McClelland, whose model is itself an adaptation of an earlier one by Rumelhart (1990).
Inspired by the PyTorch implementation from https://github.com/jeffreyallenbrooks/rogers-and-mcclelland.
The necessary packages change over time, but be sure to
pip/conda install torch torchvision tensorboard pandas scipy numpy seaborn scikit-learn matplotlib
To train the model and generate log data, run
python feedforward.py
To view the logs in TensorBoard (it's nice to keep this running in a seperate process), run
tensorboard --logdir logs/fit
and go to localhost:6006
in your browser. One run will show up in TensorBoard as two sets of data; one containing the scalar metrics (in ${run_name}/train
) and another containing the images (in ${run_name}/
).
To clear the logs (the folder tends to fill up fast), run
python clear_logs.py