liuruiyang98/Jittor-MLP
Unofficial Implementation of MLP-Mixer, gMLP, resMLP, Vision Permutator, S2MLP, S2MLPv2, RaftMLP, HireMLP, ConvMLP, AS-MLP, SparseMLP, ConvMixer, SwinMLP, RepMLPNet, WaveMLP, MorphMLP, DynaMixer, MS-MLP, Sequencer2D in Jittor and PyTorch! Now, Rearrange and Reduce in einops.layers.jittor are support!! trunc_normal_ is supported for Jittor!! MLP Paper is uploaded!
This project offers ready-to-use implementations of various advanced neural network architectures, specifically different types of Multi-Layer Perceptrons (MLPs), for image recognition tasks. It helps researchers and practitioners in computer vision experiment with cutting-edge models. You provide an image dataset, and the project outputs trained models capable of classifying or processing those images.
170 stars. No commits in the last 6 months.
Use this if you are a computer vision researcher or practitioner looking to implement or compare various MLP-based image recognition models using either Jittor or PyTorch.
Not ideal if you are looking for a high-level, no-code solution for image classification or if you need models that rely heavily on Fourier Transform or Deformable Convolution operations, as these are not fully supported in the Jittor implementations.
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170
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20
Language
Python
License
MIT
Category
Last pushed
Jul 14, 2022
Commits (30d)
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