Here are some of the relevant resources from today’s Lecture:
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Here is a link to the AutoDiff Notebook from Akash: TF_JAX_Tutorials - Part 9 (Autodiff in JAX) | Kaggle
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Here’s the PyTree Notebook from Akash: TF_JAX_tutorials - Part 10 (Pytrees in JAX) | Kaggle
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Here’s the link to “Flax Basics” from the Flax docs: Google Colab
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Here’s the link to “Annotated MNIST” from the Flax docs: Google Colab
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Here’s a link to the UNET lecture from last month: PyTorch Book Reading - 8. U-net, Image Segmentation and Image Augmentations in PyTorch - YouTube
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Here’s the Scenic implementation of U-net: scenic/unet.py at main · google-research/scenic · GitHub