Ubuntu
torch3 package

torch3 3.1-2.2build1 source package in Ubuntu

Changelog

torch3 (3.1-2.2build1) focal; urgency=medium

  * No-change rebuild for libgcc-s1 package name change.

 -- Matthias Klose <email address hidden>  Sun, 22 Mar 2020 16:59:58 +0100

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Uploaded by:
Matthias Klose
Uploaded to:
Focal
Original maintainer:
Cosimo Alfarano
Architectures:
any
Section:
libs
Urgency:
Medium Urgency

See full publishing history Publishing

Series Pocket Published Component Section
Focal release universe libs

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File Size SHA-256 Checksum
torch3_3.1.orig.tar.gz 771.1 KiB 503d7f02b7d717d8eee2f6e56ce4a4badc9571e5197a2ce9c3db056e34d92e29
torch3_3.1-2.2build1.diff.gz 11.4 KiB 14b76926f9fcd9dff73ba80a415b15fe07d8eb551be6233e3ea8129c5573fb3f
torch3_3.1-2.2build1.dsc 1.7 KiB 89d14b730e5e64d1e8c18a981fe0672d93b5133ba9eebcfdd216e9f0aa0239fc

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Binary packages built by this source

libtorch3-dev: State of the art machine learning library - development files

 Torch is a machine-learning library, written in C++. Its aim is to
 provide the state-of-the-art of the best algorithms.
 .
  * Many gradient-based methods, including multi-layered perceptrons,
    radial basis functions, and mixtures of experts. Many small "modules"
    (Linear module, Tanh module, SoftMax module, ...) can be plugged
    together.
  * Support Vector Machine, for classification and regression.
  * Distribution package, includes Kmeans, Gaussian Mixture Models,
    Hidden Markov Models, and Bayes Classifier, and classes for speech
    recognition with embedded training.
  * Ensemble models such as Bagging and Adaboost.
  * Non-parametric models such as K-nearest-neighbors, Parzen Regression
    and Parzen Density Estimator.
 .
 This package is the Torch development package (header files and
 static library.)

libtorch3c2: State of the art machine learning library - runtime library

 Torch is a machine-learning library, written in C++. Its aim is to
 provide the state-of-the-art of the best algorithms for
 machine-learning.
 .
  * Many gradient-based methods, including multi-layered perceptrons,
    radial basis functions, and mixtures of experts. Many small "modules"
    (Linear module, Tanh module, SoftMax module, ...) can be plugged
    together.
  * Support Vector Machine, for classification and regression.
  * Distribution package, includes Kmeans, Gaussian Mixture Models,
    Hidden Markov Models, and Bayes Classifier, and classes for speech
    recognition with embedded training.
  * Ensemble models such as Bagging and Adaboost.
  * Non-parametric models such as K-nearest-neighbors, Parzen Regression
    and Parzen Density Estimator.
 .
 This package is the Torch runtime library.

libtorch3c2-dbgsym: No summary available for libtorch3c2-dbgsym in ubuntu groovy.

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