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We did a bunch of popular research paper implementations in PyTorch with notes (annotations); might be helpful. https://nn.labml.ai https://nn.labml.ai
by vpj 5y ago
We did a bunch of popular research paper implementations in PyTorch with notes (annotations); might be helpful.
https://nn.labml.ai https://nn.labml.ai
- srvmshr 5y ago@vpj The only drawback I see is that much of the implementation is abstracted by your helper libraries. Not everyone wants to add an extra dependency layer. Otherwise the walkthroughs are super helpful.
- deleted 5y ago[deleted]
- vpj 5y agoAgreed. But it makes implementing and testing a lot easier for us. We try to minimize the dependencies as much as possible. Do you think it also comes in the way of understanding the paper and learning how to implement it?
- srvmshr 5y agoSince the backbone of the implementation is packed away in the library import, I felt it didn't quite show the code & variable interaction well enough. Don't get me wrong. It is useful & concise like you mentioned. But your target audience is beginners & adopters, and it makes it no different from another framework such as Fastai (I have major gripes with them. It has a much bottled-in experience) To be true to walkthroughs, please consider designing helper functions rather than using your framework. Admittedly it may not be as beautiful, but eventually your users will be more appreciative of the extra mile you go into making things transparent & similar to PyTorch docs.
- xkgt 5y agoFor people planning to learn PyTorch or even NN as a whole, it would also help to order or group the implementations in terms of complexity.
- ulnarkressty 5y agoYour notebooks are very useful, thank you! May I suggest making their background white, or the color text less saturated? The keywords, function names etc. are very difficult to read, I have to paste the code in another editor.