[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"project-6293":3},{"id":4,"name":5,"fullName":6,"owner":7,"repo":5,"description":8,"homepage":9,"htmlUrl":10,"language":11,"languages":10,"totalLinesOfCode":10,"stars":12,"forks":13,"watchers":14,"openIssues":15,"contributorsCount":16,"subscribersCount":16,"size":16,"stars1d":17,"stars7d":18,"stars30d":19,"stars90d":16,"forks30d":16,"starsTrendScore":20,"compositeScore":21,"rankGlobal":10,"rankLanguage":10,"license":22,"archived":23,"fork":23,"defaultBranch":24,"hasWiki":25,"hasPages":23,"topics":26,"createdAt":10,"pushedAt":10,"updatedAt":27,"readmeContent":28,"aiSummary":29,"trendingCount":16,"starSnapshotCount":16,"syncStatus":18,"lastSyncTime":30,"discoverSource":31},6293,"torch7","torch\u002Ftorch7","torch","http:\u002F\u002Ftorch.ch","",null,"C",9127,2346,608,283,0,1,2,8,3,41,"Other",false,"master",true,[],"2026-06-12 02:01:17","[![Join the chat at https:\u002F\u002Fgitter.im\u002Ftorch\u002Ftorch7](https:\u002F\u002Fbadges.gitter.im\u002FJoin%20Chat.svg)](https:\u002F\u002Fgitter.im\u002Ftorch\u002Ftorch7?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge)\n[![Build Status](https:\u002F\u002Ftravis-ci.org\u002Ftorch\u002Ftorch7.svg)](https:\u002F\u002Ftravis-ci.org\u002Ftorch\u002Ftorch7)\n\n## Development Status\n\nTorch is not in active development. 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:\u002F\u002Fgithub.com\u002Fpytorch\u002Fpytorch\u002Ftree\u002Fmaster\u002Faten), [mirror](https:\u002F\u002Fgithub.com\u002Fzdevito\u002FATen\u002F)).\nATen 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\u002Faten\u002Fsrc\u002FREADME.md](https:\u002F\u002Fgithub.com\u002Fpytorch\u002Fpytorch\u002Ftree\u002Fmaster\u002Faten\u002Fsrc#the-c-interface).\n\n\n## Need help? ##\n\nTorch7 community support can be found at the following locations. As of 2019, the Torch-7 community is close to non-existent.\n\n* Questions, Support, Install issues: [Google groups](https:\u002F\u002Fgroups.google.com\u002Fforum\u002F#!forum\u002Ftorch7)\n* Reporting bugs: [torch7](https:\u002F\u002Fgithub.com\u002Ftorch\u002Ftorch7\u002Fissues) [nn](https:\u002F\u002Fgithub.com\u002Ftorch\u002Fnn\u002Fissues) [cutorch](https:\u002F\u002Fgithub.com\u002Ftorch\u002Fcutorch\u002Fissues) [cunn](https:\u002F\u002Fgithub.com\u002Ftorch\u002Fcutorch\u002Fissues) [optim](https:\u002F\u002Fgithub.com\u002Ftorch\u002Foptim\u002Fissues) [threads](https:\u002F\u002Fgithub.com\u002Ftorch\u002Fthreads\u002Fissues)\n* Hanging out with other developers and users (strictly no install issues, no large blobs of text): [Gitter Chat](https:\u002F\u002Fgitter.im\u002Ftorch\u002Ftorch7)\n\n\u003Ca name=\"torch.reference.dok\">\u003C\u002Fa>\n# Torch Package Reference Manual #\n\n__Torch__ is the main package in [Torch7](http:\u002F\u002Ftorch.ch) where data\nstructures for multi-dimensional tensors and mathematical operations\nover these are defined. Additionally, it provides many utilities for\naccessing files, serializing objects of arbitrary types and other\nuseful utilities.\n\n\u003Ca name=\"torch.overview.dok\">\u003C\u002Fa>\n## Torch Packages ##\n\n  * Tensor Library\n    * [Tensor](doc\u002Ftensor.md) defines the _all powerful_ tensor object that provides multi-dimensional numerical arrays with type templating.\n    * [Mathematical operations](doc\u002Fmaths.md) that are defined for the tensor object types.\n    * [Storage](doc\u002Fstorage.md) defines a simple storage interface that controls the underlying storage for any tensor object.\n  * File I\u002FO Interface Library\n    * [File](doc\u002Ffile.md) is an abstract interface for common file operations.\n    * [Disk File](doc\u002Fdiskfile.md) defines operations on files stored on disk.\n    * [Memory File](doc\u002Fmemoryfile.md) defines operations on stored in RAM.\n    * [Pipe File](doc\u002Fpipefile.md) defines operations for using piped commands.\n    * [High-Level File operations](doc\u002Fserialization.md) defines higher-level serialization functions.\n  * Useful Utilities\n    * [Timer](doc\u002Ftimer.md) provides functionality for _measuring time_.\n    * [Tester](doc\u002Ftester.md) is a generic tester framework.\n    * [CmdLine](doc\u002Fcmdline.md) is a command line argument parsing utility.\n    * [Random](doc\u002Frandom.md) defines a random number generator package with various distributions.\n    * Finally useful [utility](doc\u002Futility.md) functions are provided for easy handling of torch tensor types and class inheritance.\n\n\u003Ca name=\"torch.links.dok\">\u003C\u002Fa>\n## Useful Links ##\n\n  * [Community packages](https:\u002F\u002Fgithub.com\u002Ftorch\u002Ftorch7\u002Fwiki\u002FCheatsheet)\n  * [Torch Blog](http:\u002F\u002Ftorch.ch\u002Fblog\u002F)\n  * [Torch Slides](https:\u002F\u002Fgithub.com\u002Fsoumith\u002Fcvpr2015\u002Fblob\u002Fmaster\u002Fcvpr-torch.pdf)\n\n","Torch7 是一个基于C语言的科学计算框架，主要用于多维张量的数据结构定义及数学运算。其核心功能包括强大的张量对象、丰富的数学操作以及灵活的存储接口，支持文件I\u002FO接口库，涵盖磁盘文件、内存文件和管道文件等多种操作。尽管Torch7不再活跃开发，但其提供的TH、THNN等库仍被ATen C++11库扩展和重写。Torch7适合需要高效处理多维数组数据的应用场景，如机器学习、深度学习等领域中的算法实现与研究工作。","2026-06-11 03:06:19","top_language"]