Introduction

CNNumpy is a Convolutional Neural Network written in pure Numpy (educational purpose only).
There are 2 implementation versions:
- Slow: The naive version with nested for loops.
- Fast: The im2col/col2im version.
The slow implementation takes around 4 hours for 1 epoch where the fast implementation takes only 6 min for 1 epoch.
For your information, with the same architecture using Pytorch, it will take around 1 min for 1 epoch.
For more details, here are my blog posts explaining in depth what's going on under the hood for each implementation (slow and fast).
In the demo-cnnumpy-fast.ipynb notebook, the im2col/col2im implementation can achieve an accuracy up to 97.2% in 1 epoch (~6 min). Here are some results:

Installation

Create a virtual environment in the root folder using virtualenv and activate it.

# On Linux terminal, using virtualenv.
virtualenv myenv
# Activate it.
source myenv/bin/activate

pip install -r requirements.txt
# Tidy up the root folder.
python3 setup.py clean

To play with the demo-notebooks/ files, you need to make sure jupyter notebook can select your virtual environnment as a kernel.

Follow "Installation" instructions first and make sure your virtual environment is still activated.
Run the following line in the terminal.

python -m ipykernel install --user--name=myenv

Run the notebook file only from demo_notebooks/ and then select Kernel > Switch Kernel > myenv. You are now ready to go !