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Chainer is an open source deep learning framework written purely in Python on top of NumPy and CuPy Python libraries. The development is led by Japanese venture company Preferred Networks in partnership with IBM, Intel, Microsoft, and Nvidia.
The code is hosted on GitHub, and community support forums include the GitHub issues page, and a Slack channel. [citation needed] In addition to standard neural networks, Keras has support for convolutional and recurrent neural networks. It supports other common utility layers like dropout, batch normalization, and pooling. [12]
Python: Python: Only on Linux No Yes No Yes Yes Keras: François Chollet 2015 MIT license: Yes Linux, macOS, Windows: Python: Python, R: Only if using Theano as backend Can use Theano, Tensorflow or PlaidML as backends Yes No Yes Yes [20] Yes Yes No [21] Yes [22] Yes MATLAB + Deep Learning Toolbox (formally Neural Network Toolbox) MathWorks ...
Torch is an open-source machine learning library, a scientific computing framework, and a scripting language based on Lua. [3] It provides LuaJIT interfaces to deep learning algorithms implemented in C. It was created by the Idiap Research Institute at EPFL. Torch development moved in 2017 to PyTorch, a port of the library to Python. [4] [5] [6]
PyTorch Lightning is an open-source Python library that provides a high-level interface for PyTorch, a popular deep learning framework. [1] It is a lightweight and high-performance framework that organizes PyTorch code to decouple research from engineering, thus making deep learning experiments easier to read and reproduce.
Features include mixed precision training, single-GPU, multi-GPU, and multi-node training as well as custom model parallelism. The DeepSpeed source code is licensed under MIT License and available on GitHub. [5] The team claimed to achieve up to a 6.2x throughput improvement, 2.8x faster convergence, and 4.6x less communication. [6]
Deeplearning4j can be used via multiple API languages including Java, Scala, Python, Clojure and Kotlin. Its Scala API is called ScalNet. [31] Keras serves as its Python API. [32] And its Clojure wrapper is known as DL4CLJ. [33] The core languages performing the large-scale mathematical operations necessary for deep learning are C, C++ and CUDA C.
Automated Deep Learning Using Neural Network Intelligence: Develop and Design PyTorch and TensorFlow Models Using Python. Apress. Apress. ISBN 978-1484281482 .