From aff27db65e8517fa05e155df32b49f0d92da6cd4 Mon Sep 17 00:00:00 2001 From: nicBarbara Date: Thu, 26 Oct 2023 15:39:59 +1100 Subject: [PATCH 1/3] Fixed a bug in the docs and removed LiveServer as a dependency --- docs/Project.toml | 1 - src/Wrappers/LBDN/sandwich_fc.jl | 2 +- 2 files changed, 1 insertion(+), 2 deletions(-) diff --git a/docs/Project.toml b/docs/Project.toml index 643363c7..e4466f43 100644 --- a/docs/Project.toml +++ b/docs/Project.toml @@ -2,7 +2,6 @@ CairoMakie = "13f3f980-e62b-5c42-98c6-ff1f3baf88f0" Documenter = "e30172f5-a6a5-5a46-863b-614d45cd2de4" Flux = "587475ba-b771-5e3f-ad9e-33799f191a9c" -LiveServer = "16fef848-5104-11e9-1b77-fb7a48bbb589" Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c" RobustNeuralNetworks = "a1f18e6b-8af1-433f-a85d-2e1ee636a2b8" diff --git a/src/Wrappers/LBDN/sandwich_fc.jl b/src/Wrappers/LBDN/sandwich_fc.jl index 7adccc5d..70342c24 100644 --- a/src/Wrappers/LBDN/sandwich_fc.jl +++ b/src/Wrappers/LBDN/sandwich_fc.jl @@ -63,7 +63,7 @@ println(round.(y;digits=2)) # output -[3.62 4.74 3.58 8.75 3.64 3.0 0.73 1.16 1.0 1.73] +[4.13 4.37 3.22 8.38 4.15 3.71 0.7 2.04 1.78 2.64] ``` See also [`DenseLBDNParams`](@ref), [`DiffLBDN`](@ref). From ae650749117f47cdbe75a2662bccbb44f6bb4c8a Mon Sep 17 00:00:00 2001 From: nicBarbara Date: Thu, 26 Oct 2023 15:49:43 +1100 Subject: [PATCH 2/3] Fixed typo --- docs/src/examples/lbdn_mnist.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/src/examples/lbdn_mnist.md b/docs/src/examples/lbdn_mnist.md index ecc66fea..8ac0ea9b 100644 --- a/docs/src/examples/lbdn_mnist.md +++ b/docs/src/examples/lbdn_mnist.md @@ -17,7 +17,7 @@ For details on how Lipschitz bounds increase classification robustness and relia Let's start by loading the training and test data. [`MLDatasets.jl`](https://juliaml.github.io/MLDatasets.jl/stable/) contains a number of common machine-learning datasets, including the [MNIST dataset](https://juliaml.github.io/MLDatasets.jl/stable/datasets/vision/#MLDatasets.MNIST). The following code loads the full dataset of 60,000 training images and 10,000 test images. !!! info "Working on the GPU" - Since we're dealing with images, we will load are data and models onto the GPU to speed up training. We'll be using [`CUDA.jl`](https://github.com/JuliaGPU/CUDA.jl). + Since we're dealing with images, we will load our data and models onto the GPU to speed up training. We'll be using [`CUDA.jl`](https://github.com/JuliaGPU/CUDA.jl). If you don't have a GPU on your machine, just switch to `dev = cpu`. If you have a GPU but not an NVIDIA GPU, switch out `CUDA.jl` with whichever GPU backend supports your device. For more information on training models on a GPU, see [here](https://fluxml.ai/Flux.jl/stable/gpu/). From 823f7b927233e644f40655b777dade1a4779068a Mon Sep 17 00:00:00 2001 From: nicBarbara Date: Thu, 26 Oct 2023 15:50:57 +1100 Subject: [PATCH 3/3] Version bump --- Project.toml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/Project.toml b/Project.toml index ef46c96d..d445085f 100644 --- a/Project.toml +++ b/Project.toml @@ -1,7 +1,7 @@ name = "RobustNeuralNetworks" uuid = "a1f18e6b-8af1-433f-a85d-2e1ee636a2b8" authors = ["Nicholas H. Barbara", "Max Revay", "Ruigang Wang", "Jing Cheng", "Jerome Justin", "Ian R. Manchester"] -version = "0.3.0" +version = "0.3.1" [deps] ChainRulesCore = "d360d2e6-b24c-11e9-a2a3-2a2ae2dbcce4"