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fix: not conditional but convolutional
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avik-pal committed Jan 15, 2025
1 parent 2903784 commit 5fe0236
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Showing 6 changed files with 8 additions and 8 deletions.
2 changes: 1 addition & 1 deletion docs/make.jl
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Expand Up @@ -29,7 +29,7 @@ pages = [
"tutorials/intermediate/2_BayesianNN.md",
"tutorials/intermediate/3_HyperNet.md",
"tutorials/intermediate/4_PINN2DPDE.md",
"tutorials/intermediate/5_ConditionalVAE.md",
"tutorials/intermediate/5_ConvolutionalVAE.md",
],
"Advanced" => [
"tutorials/advanced/1_GravitationalWaveForm.md"
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4 changes: 2 additions & 2 deletions docs/src/.vitepress/config.mts
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Expand Up @@ -219,8 +219,8 @@ export default defineConfig({
link: "/tutorials/intermediate/4_PINN2DPDE",
},
{
text: "Conditional VAE for MNIST using Reactant",
link: "/tutorials/intermediate/5_ConditionalVAE",
text: "Convolutional VAE for MNIST using Reactant",
link: "/tutorials/intermediate/5_ConvolutionalVAE",
}
],
},
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6 changes: 3 additions & 3 deletions docs/src/tutorials/index.md
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Expand Up @@ -67,10 +67,10 @@ const intermediate = [
desc: "Train a PINN to solve 2D PDEs (using Nested AD)."
},
{
href: "intermediate/5_ConditionalVAE",
href: "intermediate/5_ConvolutionalVAE",
src: "../conditional_vae.png",
caption: "Conditional VAE for MNIST using Reactant",
desc: "Train a Conditional VAE to generate images from a latent space."
caption: "Convolutional VAE for MNIST using Reactant",
desc: "Train a Convolutional VAE to generate images from a latent space."
}
];
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2 changes: 1 addition & 1 deletion docs/tutorials.jl
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Expand Up @@ -12,7 +12,7 @@ const INTERMEDIATE_TUTORIALS = [
"BayesianNN/main.jl" => "CPU",
"HyperNet/main.jl" => "CUDA",
"PINN2DPDE/main.jl" => "CUDA",
"ConditionalVAE/main.jl" => "CUDA",
"ConvolutionalVAE/main.jl" => "CUDA",
]
const ADVANCED_TUTORIALS = [
"GravitationalWaveForm/main.jl" => "CPU",
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File renamed without changes.
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@@ -1,4 +1,4 @@
# # [Conditional VAE for MNIST using Reactant](@id Conditional-VAE-Tutorial)
# # [Convolutional VAE for MNIST using Reactant](@id Convolutional-VAE-Tutorial)

# Convolutional variational autoencoder (CVAE) implementation in MLX using MNIST. This is
# based on the [CVAE implementation in MLX](https://github.com/ml-explore/mlx-examples/blob/main/cvae/).
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