Convolutional Neural Network from Scratch

About

A Python implementation of a CNN with only numpy. All theory and formulas behind the code you can read from articles - in Russian on habr and in English on medium.

Also, to check whether the numpy model gets plausible results, it is compared with a similar CNN architecture based on pytorch. Both models have the same initial weights and are trained on the MNIST dataset (all training images are given in the same order) - so you can compare the losses of the models after each cycle and make sure that the numpy-implementation is correct.

Quick setup and start

• Docker

The provided Dockerfile is supplied to build an image with all the necessary dependencies.

Preparations

• Clone the repo.

  git clone git@github.com:skalinin/CNN-from-Scratch.git
  cd CNN-from-Scratch

• sudo make all to build a docker image and create a container.

Run

To create identical initial weights for numpy and torch models:

python src/scripts/make_init_weights.py --torch_seed 1234

To start a numpy model training:

python src/scripts/train_numpy_model.py \
	--load_path /workdir/data/numpy_init_weights.npy

To start a torch model training:

python src/scripts/train_torch_model.py \
	--load_path /workdir/data/torch_init_weights.ckpt