FluxML / model-zoo

Please do not feed the models
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Add literature background to the models #340

Open lilianabs opened 2 years ago

lilianabs commented 2 years ago

I'll start working on adding literature background to all of the existing models (ref https://github.com/FluxML/model-zoo/issues/312). Then, we can move on to working on creating a standalone site to host all of the models as notebooks.

I plan to cover the following models:

@DhairyaLGandhi @logankilpatrick just tagging you to keep you in the loop :)

darsnack commented 2 years ago

This is great!

Looking ahead to the website step, I think it would be better and simpler to just host a "model zoo" or "tutorials" section in the Flux docs themselves:

lilianabs commented 2 years ago

Thank you @darsnack! Totally agree with your comments.

CarloLucibello commented 2 years ago

I think it is good to add some comments to some of the basics examples, but I wouldn't want them to be too loaded either. Model-zoo examples are supposedly used for bootstrapping user projects, they aren't meant as tutorials (which we lack and should live in Flux.jl).

lilianabs commented 2 years ago

We can use Literate to create a "clean" version of the examples.

cossio commented 2 years ago

Regarding the Simple ConvNet (LeNet5) example, I noticed it is using relu activations and max-pooling. I think the original LeCun paper doesn't do this. It is also different from https://d2l.ai/chapter_convolutional-neural-networks/lenet.html, which is cited in the readme of this example.

Any reason for these discrepancies?

lilianabs commented 2 years ago

@cossio I just wrote the text and took the code as it was on the repo. Perhaps somebody else can comment on these discrepancies?

CarloLucibello commented 2 years ago

I think that's a modernized version of Lenet5 (relu had not been "invented" at the time) which I've found somewhere (don't remember where though). Maybe we can add a comment on that saying that the original model uses sigmoids?

lilianabs commented 2 years ago

Added a note to the model to specify this.