mlpack-testing

This repository contains verifications, tests and visualizations for different mlpack features I have worked on. Each feature is structured into a separate folder, each of which has a README describing its contents and how to execute the sample code included within., along with links to PRs and blogs I have created. The dependencies for running each file are also listed there itself. To view the READMEs as web-pages, you can visit the pages of the following format.

https://iamshnoo.github.io/mlpack-testing/{feature-name}

For the current {feature-name} options, these can thus be one of the following :

• instance_norm
• loss_functions
• multilabel_soft_margin_loss,
• pixel_shuffle
• soft_margin_loss
• spatial_dropout
• unpool

I have also worked on a couple of PRs which can't really be presented in the format I follow in this repository. I am listing all my PRs below for reference so that all the features can be accessed from one place.

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Blogs

My blogs for GSoC can be found at this link. I write one every week ;)

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mlpack/mlpack

Here is a list of all the branches I have worked on so far.

All PRs

1. ANN Accessor Methods - PR #2321
2. MultiLabel Soft Margin Loss - PR #2345
3. UnPool Layer - PR #2493
4. Soft Margin Loss - PR #2494
5. Re-design ANN loss functions along with some bug fixes - PR #2495
6. Instance Norm Layer - PR #2562
7. Pixel Shuffle Layer - PR #2563
8. Spatial Dropout layer - PR #2564

All Issues

1. Accessor method implementations for layers in ANN module - Issue #2258
2. Modifying maxpooling.hpp to access poolingIndices - Issue #2439
3. Some of the loss functions probably don't work correctly - Issue #2444

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mlpack-TensorFlow-Translator

I have also contributed to mlpack-TensorFlow-Translator in the last couple of weeks. The work done so far can be tracked down to the following single large PR that incorporates many changes across the entire source code. Currently, there are only a couple more issues left to resolve to bring the translator to a complete working state.

• PR #2

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• If any of the links are broken, and you can't access them, let me know by creating a issue here and I will update them right away!

• If you find any issues/bugs in any of the implementations, mention them here or in the official mlpack repository depending on whether the features have been merged yet or not, and I will fix them ASAP.

Suggestions and feedback always welcome! Thanks.