Merge pull request #75 from MartinuzziFrancesco/fm/docs

Docs landing page cleanup

README.md

@@ -37,7 +37,9 @@
     <h2>RecurrentLayers.jl</h2>
 </div>
 
-RecurrentLayers.jl extends [Flux.jl](https://github.com/FluxML/Flux.jl) recurrent layers offering by providing implementations of bleeding edge recurrent layers not commonly available in base deep learning libraries. It is designed for a seamless integration with the larger Flux ecosystem, enabling researchers and practitioners to leverage the latest developments in recurrent neural networks.
+RecurrentLayers.jl extends [Flux.jl](https://github.com/FluxML/Flux.jl)
+recurrent layers offering by providing implementations of additional
+recurrent layers not available in base deep learning libraries.
 
 ## Features 🚀
 

benchmarks/adding_problem/main.jl

@@ -1,4 +1,4 @@
-using Flux, RecurrentLayers, MLUtils, StatsBase, Comonicon, Printf, CUDA
+using Flux, RecurrentLayers, MLUtils, StatsBase, Comonicon, Printf, CUDA, cuDNN
 
 function generate_adding_data(sequence_length::Int, n_samples::Int;
         kwargs...)
@@ -72,9 +72,9 @@ function test_recurrent(epoch, test_loader, model, criterion)
     #println("Epoch $epoch/$num_epochs, Loss: $(round(avg_loss, digits=4))")
 end
 
-Comonicon.@main function main(; rlayer=MGU, epochs::Int=50, shuffle::Bool=false,
-        batchsize::Int=32, sequence_length::Int=10, n_train::Int=500, n_test::Int=200,
-        hidden_size::Int=32, learning_rate::AbstractFloat=0.01, num_layers::Int=2,
+Comonicon.@main function main(; rlayer=MGU, epochs::Int=1000, shuffle::Bool=false,
+        batchsize::Int=100, sequence_length::Int=50, n_train::Int=10000, n_test::Int=1000,
+        hidden_size::Int=100, learning_rate::AbstractFloat=0.001, num_layers::Int=1,
         dropout::AbstractFloat=0.2)
     println("Getting data...")
     train_loader, test_loader = generate_dataloaders(

docs/src/index.md

@@ -4,12 +4,13 @@ CurrentModule = RecurrentLayers
 
 # RecurrentLayers
 
-RecurrentLayers.jl extends [Flux.jl](https://github.com/FluxML/Flux.jl) recurrent layers offering by providing implementations of bleeding edge recurrent layers not commonly available in base deep learning libraries. It is designed for a seamless integration with the larger Flux ecosystem, enabling researchers and practitioners to leverage the latest developments in recurrent neural networks.
+RecurrentLayers.jl extends [Flux.jl](https://github.com/FluxML/Flux.jl)
+recurrent layers offering by providing implementations of additional
+recurrent layers not available in base deep learning libraries.
 
-## Implemented layers
+## Features
 
-
-The package offers multiple cells and architectures:
+The package offers multiple layers for [Flux.jl](https://github.com/FluxML/Flux.jl):
  - Modifications of vanilla RNNs:
    [Independently recurrent neural networks](https://arxiv.org/abs/1803.04831),
    [Structurally constrained recurrent neural network](https://arxiv.org/pdf/1412.7753), and
@@ -39,10 +40,35 @@ The package offers multiple cells and architectures:
 
  - Additional wrappers: [Stacked RNNs](https://arxiv.org/pdf/1312.6026)
 
+## Installation
+
+You can install `RecurrentLayers` using either of:
+
+```julia
+using Pkg
+Pkg.add("RecurrentLayers")
+```
+
+```julia_repl
+julia> ]
+pkg> add RecurrentLayers
+```
+
 ## Contributing
 
 Contributions are always welcome! We specifically look for :
  - Recurrent cells you would like to see implemented 
  - Benchmarks
  - Fixes for any bugs/errors
- - Documentation, in any form: examples, how tos, docstrings  
+ - Documentation, in any form: examples, how tos, docstrings
+
+Please consider the following guidelines before opening a pull request:
+ - The code should be formatted according to the format file provided
+ - Variable names should be meaningful: please no single letter variables,
+   and try to avoid double letters variables too. I know at the moment there are
+   some in the codebase, but I will need a breaking change in order to fix the majority of them.
+ - The format file does not format markdown. If you are adding docs, or docstrings
+   please take care of not going over 92 cols.
+
+For any clarification feel free to contact me directly (@MartinuzziFrancesco)
+either in the julia slack, by email or X/bluesky.