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https://github.com/torch/torch7

http://torch.ch
https://github.com/torch/torch7

Last synced: 3 months ago
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http://torch.ch

Host: GitHub
URL: https://github.com/torch/torch7
Owner: torch
License: other
Created: 2013-10-18T12:13:58.000Z (about 11 years ago)
Default Branch: master
Last Pushed: 2022-10-26T03:55:13.000Z (about 2 years ago)
Last Synced: 2024-08-01T16:34:08.436Z (6 months ago)
Language: C
Homepage:
Size: 2.5 MB
Stars: 8,966
Watchers: 625
Forks: 2,379
Open Issues: 299
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md

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README

        [![Join the chat at https://gitter.im/torch/torch7](https://badges.gitter.im/Join%20Chat.svg)](https://gitter.im/torch/torch7?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge)

[![Build Status](https://travis-ci.org/torch/torch7.svg)](https://travis-ci.org/torch/torch7)

## Development Status

Torch is not in active developement. The functionality provided by the C backend of Torch, which are the TH, THNN, THC, THCUNN libraries is actively extended and re-written in the ATen C++11 library ([source](https://github.com/pytorch/pytorch/tree/master/aten), [mirror](https://github.com/zdevito/ATen/)).

ATen exposes all operators you would expect from torch7, nn, cutorch, and cunn directly in C++11 and includes additional support for sparse tensors and distributed operations. It is to note however that the API and semantics of the backend libraries in Torch-7 are different from the semantice provided by ATen. For example ATen provides numpy-style broadcasting while TH* dont. For information on building the forked Torch-7 libraries in C, refer to ["The C interface" in pytorch/aten/src/README.md](https://github.com/pytorch/pytorch/tree/master/aten/src#the-c-interface).

## Need help? ##

Torch7 community support can be found at the following locations. As of 2019, the Torch-7 community is close to non-existent.

* Questions, Support, Install issues: [Google groups](https://groups.google.com/forum/#!forum/torch7)

* Reporting bugs: [torch7](https://github.com/torch/torch7/issues) [nn](https://github.com/torch/nn/issues) [cutorch](https://github.com/torch/cutorch/issues) [cunn](https://github.com/torch/cutorch/issues) [optim](https://github.com/torch/optim/issues) [threads](https://github.com/torch/threads/issues)

* Hanging out with other developers and users (strictly no install issues, no large blobs of text): [Gitter Chat](https://gitter.im/torch/torch7)



# Torch Package Reference Manual #

__Torch__ is the main package in [Torch7](http://torch.ch) 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.



## Torch Packages ##

  * Tensor Library

    * [Tensor](doc/tensor.md) defines the _all powerful_ tensor object that provides multi-dimensional numerical arrays with type templating.

    * [Mathematical operations](doc/maths.md) that are defined for the tensor object types.

    * [Storage](doc/storage.md) defines a simple storage interface that controls the underlying storage for any tensor object.

  * File I/O Interface Library

    * [File](doc/file.md) is an abstract interface for common file operations.

    * [Disk File](doc/diskfile.md) defines operations on files stored on disk.

    * [Memory File](doc/memoryfile.md) defines operations on stored in RAM.

    * [Pipe File](doc/pipefile.md) defines operations for using piped commands.

    * [High-Level File operations](doc/serialization.md) defines higher-level serialization functions.

  * Useful Utilities

    * [Timer](doc/timer.md) provides functionality for _measuring time_.

    * [Tester](doc/tester.md) is a generic tester framework.

    * [CmdLine](doc/cmdline.md) is a command line argument parsing utility.

    * [Random](doc/random.md) defines a random number generator package with various distributions.

    * Finally useful [utility](doc/utility.md) functions are provided for easy handling of torch tensor types and class inheritance.



## Useful Links ##

  * [Community packages](https://github.com/torch/torch7/wiki/Cheatsheet)

  * [Torch Blog](http://torch.ch/blog/)

  * [Torch Slides](https://github.com/soumith/cvpr2015/blob/master/cvpr-torch.pdf)