mlpack features I am working on.
Contains all the work done on the Pixel Shuffle layer.
Probably the most intuitive illustration of Pixel Shuffle on the internet.
I had a lot of fun understanding and making this.
Pixel_Shuffle_Demo_1.ipynb
- understanding the PyTorch implementation
of the layer.Pixel_Shuffle_Demo_2.ipynb
- comparison between PyTorch/numpy
and mlpack/armadillo implementations of the layer.Pixel_Shuffle_Visual_Experiments.ipynb
- to recreate the visuals in blog
post 2.test.cpp
- Armadillo implementation of the layer’s functionality.To run the .cpp
file, you need to have armadillo installed in your system.
g++ test.cpp -o test -larmadillo && ./test
To run Pixel_Shuffle_Demo_1.ipynb
, you would need pytorch and numpy
python libraries.
To run Pixel_Shuffle_Demo_2.ipynb
, you would need pytorch,
numpy and armadillo. To avoid issues with linking the libraries correctly, it is
better to run the notebook in Google Colab.
To run Pixel_Shuffle_Visual_Experiments.ipynb
, you would need pytorch,
matplotlib, seaborn, numpy python libraries.