1. MLP-Mixer is a variation on a depthwise separable convnet 2. FNet is similar to Transformer encoder but replaces attention with a Fourier transform 3. gMLP uses a spatial gating unit
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Today on http://keras.io : three MLP models for image classification, demonstrated in less than 300 lines of code in total. MLP-Mixer, FNet, and gMLP.https://keras.io/examples/vision/mlp_image_classification/ …
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Is there any way to reach you about an example I'd like to add to Keras, if relevant? (Proteins & attention/pretraining + mixed local/global tasks example).https://www.biorxiv.org/content/10.1101/2021.05.24.445464v1 …
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You can open a PR. The only requirement is that the example should fit in less than 300 lines.
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