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Chainer vs Torch: What are the differences?
What is Chainer? A Powerful, Flexible, and Intuitive Framework for Neural Networks. It is an open source deep learning framework written purely in Python on top of Numpy and CuPy Python libraries aiming at flexibility. It supports CUDA computation. It only requires a few lines of code to leverage a GPU. It also runs on multiple GPUs with little effort.
What is Torch? An open-source machine learning library and a script language based on the Lua programming language. It is easy to use and efficient, thanks to an easy and fast scripting language, LuaJIT, and an underlying C/CUDA implementation.
Chainer and Torch can be primarily classified as "Machine Learning" tools.
Some of the features offered by Chainer are:
- Supports CUDA computation
- Runs on multiple GPUs
- Supports various network architectures
On the other hand, Torch provides the following key features:
- A powerful N-dimensional array
- Lots of routines for indexing, slicing, transposing
- Amazing interface to C, via LuaJIT
Chainer is an open source tool with 5.03K GitHub stars and 1.33K GitHub forks. Here's a link to Chainer's open source repository on GitHub.