Since PyTorch launched in January 2017, its popularity has continued to grow. PyTorch was quickly adopted by many researchers and engineers because of its many advantages, such as Python, dynamic graph mechanism, flexible network construction, and strong community.

A recent visit to GitHub found a great list of Pytorch resources, including NLP/CV projects, sample code, libraries, paper implementations, and more. Here I have done a sort, recommend to you.

Coincidentally, I am familiar with this list of resources. Compared with the previous article, I found that there was an original English version on GitHub before, and this one was translated into Chinese

GitHub project address: \

Github.com/bharathgs/A…

GitHub address: \

Github.com/xavier-zy/A…

Directory \

This large list of resources mainly includes the following:

**1. PyTorch and related libraries **

  • Natural language processing and speech processing
  • Computer vision
  • Probability library and generative library
  • Other libraries

**2. Tutorials and examples **

**3. The thesis realizes **

4. Reports and meetings

5. Other \

The following are introduced respectively! \

1. Natural language processing and speech processing

This section contains 41 popular PyTorch NLP related projects, such as a cross-speaker speech generation method, speech to text end-to-end model implementation, fast WaveNet generation implementation; PyTorch NLP is a popular library related to PyTorch NLP, such as The PyTorch NLP library based on FastAI, LASER, which is used to calculate and use multi-language statement embedding. PyTorch NLP related popular frameworks and tools, such as PyTorch – SeQ2SeQ, PyTorch’s sequence-to-sequence framework nMTPyTorch, etc.

It is worth noting that many of these projects are official implementations, usually with instructions for the use of the system, including detailed explanations of installation, loading, training, testing, and demonstration. And the official has been updated, very good.

2. Computer vision \

This section contains 25 popular PyTorch CV related projects and libraries. Examples include TorchVision, which includes popular data sets, model architectures, and image transformations commonly used in computer vision, Augmentor, an image enhancement library for machine learning, maskrCNN-Benchmark, a fast modular reference implementation for instance segmentation and object detection, PyTorch based 2D and 3D face alignment library ACE -alignment and more.

This part of the project mainly involves neural style transfer, image classification, face alignment, semantic segmentation, RoI calculation, image enhancement and other tasks, as well as some special CNN architectures.

3. Probability library and generation library

This part mainly includes probabilistic programming and statistical inference, generating probability libraries, and Bayesian optimization in PyTorch. \

4. Tutorials and examples \

This section features 66 PyTorch classic tutorials, including reinforcement learning, NLP, and CV. Logistic, CNN, RNN, LSTM and other neural network models are implemented by several lines of code, and some advanced examples are implemented by complex models.

This list of sample tutorials basically covers PyTorch’s various tutorials, ranging from beginners to advanced learners. \

For example, the fifth is PyTorch’s various tutorials, which in their official tutorials are full of content: \

pytorch.org/tutorials/

Deep Learning with PyTorch: A 60 Minute Blitz is the best introduction to PyTorch. \

5. Thesis realization \

This section includes 338 PyTorch related paper implementations. For example, PyTorch implements a recursive variational autoencoder for generating sequence data, PyTorch implements v-Net: Full convolutional neural network for the application of body medical image segmentation, and PyTorch implements a simple implementation for generating adversarial network, focusing on cartoon face painting, etc.

6. Other \

This section covers 37 PyTorch resources, including a list of tutorials, papers, projects, communities, forums, and Deep Learning templates. There are also some interesting projects, such as drawing with neural networks, a chatbot with PyTorch, and playing backgammon with AlphaZero.

Overall, this is a great and comprehensive list of PyTorch resources. And the original project was translated. Worth recommending!

Finally, attach the GitHub address of the project:

Github.com/xavier-zy/A…

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