Facebook to Open PyText Source Code

NLP-library (Natural Language Processing - processing of natural speech) is used in neural networks for the processing of written and oral speech
17 December 2018   606

Facebook has opened the source code for PyText, a library for processing spoken and written language. According to the developers, such a move should accelerate the development of the project.

NLP-library (Natural Language Processing - processing of natural speech) is used in neural networks for the processing of written and oral speech. According to the developers, the tool is useful for document classification, speech sequence marking, semantic analysis, and multitasking modeling.

The structure of the library makes it easy to move from the development of an NLP system to practical application. The company's engineers claim that using the PyText implementation of the neural network model that recognizes human speech will take only a few days.

Library features:

  • PyText is based on PyTorch, a framework with a developed ecosystem, so models created using the NLP library are easy to publish.
  • The tool includes several ready-made models. The structure of PyText allows you to modify them with little effort, which simplifies development.
  • Developers have included special models in the library that use the context of speech to better recognize the essence of statements. They are tested on datasets using the M Suggestions tool (one of the helper functions) in Facebook Messenger.
  • PyText can conduct distributed training, as well as work with several models at the same time.
  • Integration with the PyTorch framework allows the library to convert models to ONNX and use the Caffe2 engine to export them.
  • Scaling your own models in PyTorch is limited due to the multithreading limit of the Global Interpreter Lock principle in Python.
  • Exported models allow you to use C ++ features to improve performance.

The company is already using PyText in practice. According to the developers, the models created with its help make more than a billion predictions on Facebook every day. The opening of the source code and a free license should attract independent specialists to the improvement of the tool. At the same time, the company's engineers are not eliminated from further developing the system. They intend to focus on the use of its capabilities in the field of mobile devices.

Get more info at GitHub

Neural Network to Create Landscapes from Sketches

Nvidia created GauGAN model that uses generative-competitive neural networks to process segmented images and create beautiful landscapes from peoples' sketches
20 March 2019   156

At the GTC 2019 conference, NVIDIA presented a demo version of the GauGAN neural network, which can turn sketchy drawings into photorealistic images.

The GauGAN model, named after the famous artist Paul Gauguin, uses generative-competitive neural networks to process segmented images. The generator creates an image and transfers it to the discriminator trained in real photographs. He in turn pixel-by-pixel tells the generator what to fix and where.

Simply put, the principle of the neural network is similar to the coloring of the coloring, but instead of children's drawings, it produces beautiful landscapes. Its creators emphasize that it does not just glue pieces of images, but generates unique ones, like a real artist.

Among other things, the neural network is able to imitate the styles of various artists and change the times of the day and year in the image. It also generates realistic reflections on water surfaces, such as ponds and rivers.

So far, GauGAN is configured to work with landscapes, but the neural network architecture allows us to train it to create urban images as well. The source text of the report in PDF is available here.

GauGAN can be useful to both architects and city planners, and landscape designers with game developers. An AI that understands what the real world looks like will simplify the implementation of their ideas and help you quickly change them. Soon the neural network will be available on the AI ​​Playground.