torch-core-free - 20171127 main

Torch is a scientific computing framework with wide support for machine
learning algorithms that puts GPUs first. It is easy to use and efficient,
thanks to an easy and fast scripting language, LuaJIT, and an underlying
C/CUDA implementation.
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A summary of core features:
* a powerful N-dimensional array
* lots of routines for indexing, slicing, transposing, ...
* amazing interface to C, via LuaJIT
* linear algebra routines
* neural network, and energy-based models
* numeric optimization routines
* Fast and efficient GPU support
* Embeddable, with ports to iOS, Android and FPGA backends
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The goal of Torch is to have maximum flexibility and speed in building
your scientific algorithms while making the process extremely simple.
Torch comes with a large ecosystem of community-driven packages in
machine learning, computer vision, signal processing, parallel
processing, image, video, audio and networking among others, and
builds on top of the Lua community.
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At the heart of Torch are the popular neural network and optimization
libraries which are simple to use, while having maximum flexibility
in implementing complex neural network topologies. You can build
arbitrary graphs of neural networks, and parallelize them over CPUs
and GPUs in an efficient manner.
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This package is a metapackage, which pulls the following core and *free*
modules for you: cwrap, paths, sys, xlua, torch7, nn, graph, nngraph,
optim, sundown, dok, trepl, image.
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Note that cutorch (CUDA backend for torch) and cunn (CUDA backend for
neural network) are not present in this metapacakge - they will be
shipped in the torch-core-contrib metapackage in the future.