Torch Machine Learning Platform
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A Torch Machine Learning Platform is an open source Lua-based machine learning library.
- Context:
- It can contain a Torch torch Library.
- It can contain a Torch nn Library.
- It can be enhanced with an Extension Library, such as fblualib[1].
- Example(s):
- Torch7 [2].
- Torch5 2008 [3]. “... Torch5 provides a Matlab-like environment for state-of-the-art machine learning algorithms. It is easy to use and provides a very efficient implementation, thanks to an easy and fast scripting language (Lua) and a underlying C implementation. Torch5 is the official successor of Torch3, and is now developed at NEC Laboratories America and Google Labs. ... “
- Torch4 [4].
- Torch3 2004 [5].
- …
- Counter-Example(s):
- TensorFlow Framework.
- Caffe Framework.
- Theano Python Library.
- Scikit-Learn.
- Deeplearning4j, an open source deep learning library written for Java and Scala.
- OpenNN, an open source neural networks library written in C++ for deep learning.
- Spark MLlib.
- See: PyTorch, LuaJIT, CUDA, Matrix-Vector Multiplication, Matrix Multiplication, Matrix-Vector Product.
References
2017
- (Wikipedia, 2017) ⇒ https://en.wikipedia.org/wiki/Torch_(machine_learning) Retrieved:2017-8-24.
- Torch is an open source machine learning library, a scientific computing framework, and a script language based on the Lua programming language. It provides a wide range of algorithms for deep machine learning, and uses the scripting language LuaJIT, and an underlying C implementation.
2017b
Software | Creator | Software licenseTemplate:Efn | Open source | Platform | Written in | Interface | OpenMP support | OpenCL support | CUDA support | Automatic differentiation[1] | Has pretrained models | Recurrent nets | Convolutional nets | RBM/DBNs | Parallel execution (multi node) |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Torch | Ronan Collobert, Koray Kavukcuoglu, Clement Farabet | Template:Free | Yes | Linux, Mac OS X, Windows,[2] Android,[3] iOS | C, Lua | Lua, LuaJIT,[4] C, utility library for C++/OpenCL[5] | Yes | Template:Depends | Yes[6][7] | Through Twitter's Autograd[8] | Yes[9] | Yes | Yes | Yes | Yes[10] |
2016
- http://googleresearch.blogspot.com/2016/04/deepmind-moves-to-tensorflow.html
- QUOTE: For nearly four years, the open source Torch7 machine learning library has served as our primary research platform, combining excellent flexibility with very fast runtime execution, enabling rapid prototyping. ... Torch7 is currently being used by Facebook, Twitter, and many start-ups and academic labs as well as DeepMind, and I’m proud of the significant contribution it has made to a large community in both research and industry.
2015
- (Wikipedia, 2015) ⇒ http://en.wikipedia.org/wiki/Torch_(machine_learning) Retrieved:2015-1-17.
- Torch is an open source deep learning library for the Lua programming language and a scientific computing framework with wide support for machine learning algorithms. It uses a fast scripting language LuaJIT, and an underlying C implementation.
2015
- (Wikipedia, 2015) ⇒ http://en.wikipedia.org/wiki/Torch_(machine_learning)#torch Retrieved:2015-1-17.
- The core package of Torch is torch. It provides a flexible N-dimensional array or Tensor, which supports basic routines for indexing, slicing, transposing, type-casting, resizing, sharing storage and cloning. This object is used by most other packages and thus forms the core object of the library. The Tensor also supports mathematical operations like
max
,min
,sum
, statistical distributions like uniform, normal and multinomial, and BLAS operations like dot product, matrix-vector multiplication, matrix-matrix multiplication, matrix-vector product and matrix product.The following exemplifies using torch via its REPL interpreter: ...
- The core package of Torch is torch. It provides a flexible N-dimensional array or Tensor, which supports basic routines for indexing, slicing, transposing, type-casting, resizing, sharing storage and cloning. This object is used by most other packages and thus forms the core object of the library. The Tensor also supports mathematical operations like
2015
- https://research.facebook.com/blog/879898285375829/fair-open-sources-deep-learning-modules-for-torch/
- QUOTE: Many research projects on machine learning and AI at FAIR use Torch, an open source development environment for numerics, machine learning, and computer vision, with a particular emphasis on deep learning and convolutional nets.
2014
- http://torch.ch/
- Torch is a scientific computing framework with wide support for machine learning algorithms. It is easy to use and efficient, thanks to an easy and fast scripting language, LuaJIT, and an underlying C/CUDA implementation.
A summary of core features:
- a powerful N-dimensional array.
- lots of routines for indexing, slicing, transposing, ...
- linear algebra routines.
- neural network, and energy-based models.
- numeric optimization routines.
- Fast and efficient GPU support
- Torch is a scientific computing framework with wide support for machine learning algorithms. It is easy to use and efficient, thanks to an easy and fast scripting language, LuaJIT, and an underlying C/CUDA implementation.
2014
- https://github.com/torch/torch7/blob/master/README.md
- Torch is the main package in Torch7 where data structures for multi-dimensional tensors and mathematical operations over these are defined. Additionally, it provides many utilities for accessing files, serializing objects of arbitrary types and other useful utilities.
- Tensor Library.
- Tensor defines the all powerful tensor object that provides multi-dimensional numerical arrays with type templating.
- Mathematical operations that are defined for the tensor object types.
- ↑ Template:Cite arXiv
- ↑ https://github.com/torch/torch7/wiki/Windows
- ↑ "GitHub - soumith/torch-android: Torch-7 for Android". GitHub. https://github.com/soumith/torch-android.
- ↑ "Torch7: A Matlab-like Environment for Machine Learning". http://ronan.collobert.com/pub/matos/2011_torch7_nipsw.pdf.
- ↑ "GitHub - jonathantompson/jtorch: An OpenCL Torch Utility Library". GitHub. https://github.com/jonathantompson/jtorch.
- ↑ "Torch CUDA backend". GitHub. https://github.com/torch/cutorch.
- ↑ "Torch CUDA backend for nn". GitHub. https://github.com/torch/cunn.
- ↑ https://github.com/twitter/torch-autograd
- ↑ "ModelZoo". GitHub. https://github.com/torch/torch7/wiki/ModelZoo.
- ↑ https://github.com/torch/torch7/wiki/Cheatsheet#distributed-computing--parallel-processing