pytest-archon
PyTorch-VAE
| pytest-archon | PyTorch-VAE | |
|---|---|---|
| 1 | 5 | |
| 52 | 6,013 | |
| - | - | |
| 5.2 | 0.0 | |
| 2 months ago | 7 months ago | |
| Python | Python | |
| Apache License 2.0 | Apache License 2.0 |
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pytest-archon
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Why Domain Driven Design?
Funny coincidence: just one week ago I and a colleague of mine started with "pytest-arch" [1], a pytest plugin to test for architectural constraints. On purpose we kept it very simple. It is already usable and works well, at least for our use cases.
You can use it to check e.g. if your domain model is importing stuff that it should not import.
We are planning to publish it soon on pypi.
[1]: https://github.com/jwbargsten/pytest-arch
PyTorch-VAE
- Help with VAE
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Confusions on VAE implementation
I am a beginner in VAE implementation and I am currently going through codes here.
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Confusion regarding Variational AutoEncoder Implementation
I am referring to the code in the link here for VAE code. I have the following questions and confusions:
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How to extract feature from 2 tensors into one? what layer should be used?
Here's a repo that has a large number of VAE variants for Pytorch: https://github.com/AntixK/PyTorch-VAE
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VAEs
Face embedding with VAEs https://github.com/AntixK/PyTorch-VAE
What are some alternatives?
Awesome-VAEs - A curated list of awesome work on VAEs, disentanglement, representation learning, and generative models.
Robo-Semantic-Segmentation - Just a simple semantic segmentation library that I developed to speed up the image segmentation pipeline
6DRepNet - Official Pytorch implementation of 6DRepNet: 6D Rotation representation for unconstrained head pose estimation.
qubo-nn - Classifying, auto-encoding and reverse-engineering QUBO matrices
disentangling-vae - Experiments for understanding disentanglement in VAE latent representations
torch-metrics - Metrics for model evaluation in pytorch
benchmark_VAE - Unifying Variational Autoencoder (VAE) implementations in Pytorch (NeurIPS 2022)
Amortized-SVGD-GAN - Learning to draw samples: with application to amortized maximum likelihood estimator for generative adversarial learning
Advanced-Deep-Learning-with-Keras - Advanced Deep Learning with Keras, published by Packt
minimal_VAE_on_Mario - A minimal VAE trained on Super Mario Bros levels.
vae-anomaly-detector - Experiments on unsupervised anomaly detection using variational autoencoder. The variational autoencoder is implemented in Pytorch.
text-to-motion - Official implementation for "Generating Diverse and Natural 3D Human Motions from Texts (CVPR2022)."