Notice: nnabla is under maintenance phase and we will not be actively developing.

Neural Network Libraries - Examples

This repository contains working examples of Neural Network Libraries.
Before running any of the examples in this repository, you must install the Python package for Neural Network Libraries. The Python install guide can be found here.

Before running an example, also run the following command inside the example directory, to install additional dependencies:

cd example_directory
pip install -r requirements.txt

Docker workflow

• Our Docker workflow offers an easy installation and setup of running environments of our examples.
• See this page.

nnabla-examples-utils (neu)

neu can now be installed as a python package. It provides a wide range of utility functions. For installation and usage, check utils

Interactive Demos

We have prepared interactive demos, where you can play around without having to worry about the codes and the internal mechanism. You can run it directly on Colab from the links in the table below.

Vision: Generation, Enhancement, Animation

Name	Notebook	Task	Example
SLE-GAN		Image Generation	<a href="url">

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| First Order Motion Model | | Facial Motion Transfer |<a href="url">

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| Zooming Slow-Mo | | Video Super-Resolution |<a href="url">

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| StyleGAN2 | | Image Generation |<a href="url">

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| Deep-Exemplar-based-Video-Colorization | | Video Colorization | <a href="url">

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| TecoGAN | | Video Super-Resolution |<a href="url">

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| ESR-GAN | | Super-Resolution|<a href="url">

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| Self-Attention GAN | | Image Generation|<a href="url">

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| StarGAN | | Image Translation |<a href="url">

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| DCGAN | | Image Generation ||

Vision & Language

Name	Notebook	Task	Example
CLIP		Zero-shot image classification	<a href="url">

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Vision: Recognition

Name	Notebook	Task	Example
CenterNet		Object Detection	<a href="url">

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| PSMNet | | Stereo Depth Estimation |<a href="url">

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| Face Alignment Network | | Facial Keypoint Detection |<a href="url">

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| YOLO v2 | | Object Detection ||
| ResNet/ResNeXt/SENet | | Image Classification |<a href="url">

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Audio

Name	Notebook	Task	Example
D3Net		Music Source Separation
X-UMX		Music Source Separation	<a href="url">

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Machine Learning

Name	Notebook	Task	Example
Out-of-Core training		Out-of-Core training	<a href="url">

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| MixUp / CutMix / VH-Mixup | | Data Augmentation |<a href="url">

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| Virtual Adversarial Training | | Semi-Supervised Learning ||
| SiameseNet | | Feature Embedding ||
| Variational Auto-encoder | | Unsupervised Learning ||

eXplainable AI

Name	Notebook	Task	Example
Grad-CAM		Visualization	<a href="url">

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SHAP | | Visualization |<a href="url">

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Attention Branch Network | | Visualization | <a href="url">

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Fairness of Machine Learning

Name	Notebook	Task	Example
Demographic parity <br> Disparate Impact <br> Equal opportunity <br> Equalised odds		[Metrics tutorial] <br> Dataset/Model Bias Check	<a href="url">

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Reweighing | | [Pre-processing tutorial] <br> Dataset/Model Bias Check and Mitigation by Reweighing |<a href="url">

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Massage Data | | [Pre-processing tutorial] <br> Dataset/Model Bias Check and Mitigation by Massage Data |<a href="url">

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Preferential Sampling | | [Pre-processing tutorial] <br> Dataset/Model Bias Check and Mitigation by Preferential Sampling|<a href="url">

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GAN Data Debiasing | | [Pre-processing tutorial] <br> Dataset/Model Bias Check and Mitigation by GAN |<a href="url">

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Prejudice Remover Regularizer | | [In-processing tutorial] <br> Model Bias Check and Mitigation by Prejudice Removal Technique |<a href="url">

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Prejudice Remover Regularizer for Images| | [In-processing tutorial] <br> Model Bias Check and Mitigation by Prejudice Removal Technique for Images |<a href="url">

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Adversarial Debiasing Tutorial | | [In-processing tutorial] <br> Model Bias Check and Mitigation by Adversarial Debiasing |<a href="url">

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Adversarial Debiasing for Images| | [In-processing tutorial] <br> Model Bias Check and Mitigation by Adversarial Debiasing for Images|<a href="url">

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Rejection Option based Classification | | [Post-processing tutorial] <br> Prediction Bias Check and Mitigation by ROC |<a href="url">

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Rejection Option based Classification for Images| | [Post-processing tutorial] <br> Prediction Bias Check and Mitigation by ROC for Images |<a href="url">

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Skin color (Masked Images) | | Facial evaluation for skin color |<a href="url">

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Model Quantization

Name	Notebook	Task	Example
Post-training quantization		Post-training quantization