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http://torch.ch/
A SCIENTIFIC COMPUTING FRAMEWORK FOR LUAJIT

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.

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




  • 00000101000635330810690208207635082076390821539508215398
    Synapse creator 15.09.2016 - 14:08:57 level: 1 UP [1K] New Hardlink
    Torch-7 for Android
    Torch7 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.

    Modified to be compiled and used with Android

    For CUDA-enabled version: NVIDIA CodeWorks for Android: https://developer.nvidia.com/codeworks-android. For CPU-only version : Android NDK and Android SDK
    https://github.com/soumith/torch-android
  • 00000101000635330810690208207635082076390821539508215396
    ulkas 15.09.2016 - 14:07:39 level: 1 UP New
    Re: Torch
    Torch Packages

    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.
    Storage defines a simple storage interface that controls the underlying storage for any tensor object.
    File I/O Interface Library
    File is an abstract interface for common file operations.
    Disk File defines operations on files stored on disk.
    Memory File defines operations on stored in RAM.
    Pipe File defines operations for using piped commands.
    High-Level File operations defines higher-level serialization functions.
    Useful Utilities
    Timer provides functionality for measuring time.
    Tester is a generic tester framework.
    CmdLine is a command line argument parsing utility.
    Random defines a random number generator package with various distributions.
    Finally useful utility functions are provided for easy handling of torch tensor types and class inheritance.