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🚨 test(examples): compare training with PyTorch #94

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May 22, 2023
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🚨 test(examples): compare training with PyTorch #94

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0849faf
Compare training with PyTorch.
jean-francoisreboud May 21, 2023
e9fbcbe
Refactor AutoEncoderExample.
jean-francoisreboud May 21, 2023
15796e3
Iterate.
jean-francoisreboud May 22, 2023
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1 change: 1 addition & 0 deletions CHANGELOG.md
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Expand Up @@ -4,6 +4,7 @@ All notable changes to this project will be documented in this file.

## [unreleased]

🚨 **examples**: compare training with PyTorch ([#94](https://github.com/owkin/GrAIdient/pull/94))\
🪜 **layer_2d:** ColorJitterHSV, Image & ImageTests ([#93](https://github.com/owkin/GrAIdient/pull/93))\
🪜 **layer_2d:** Flip2D & config_kernels ([#92](https://github.com/owkin/GrAIdient/pull/92))\
🔨 **layer_2d:** remove computeVQ ([#91](https://github.com/owkin/GrAIdient/pull/91))\
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5 changes: 3 additions & 2 deletions Docs/Examples/AutoEncoder.md
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Expand Up @@ -65,5 +65,6 @@ conda env remove --name graiexamples
## Steps

1. Dump the training dataset.
1. Train a simple UNet like auto encoder model on the training dataset.
1. Train a simple StyleGAN like auto encoder model on the training dataset.
1. Train a simple auto encoder model.
1. Train a UNet like auto encoder model.
1. Train a StyleGAN like auto encoder model.
2 changes: 1 addition & 1 deletion Docs/Examples/VisionTransformer.md
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Expand Up @@ -85,4 +85,4 @@ conda env remove --name graiexamples
## Steps

1. Dump the training dataset.
1. Train a simple Vision Transformer model on the training dataset.
1. Train a simple Vision Transformer model.
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