{"id":13473854,"url":"https://github.com/torch/torch7","last_synced_at":"2025-09-25T18:05:19.419Z","repository":{"id":38290531,"uuid":"13677187","full_name":"torch/torch7","owner":"torch","description":"http://torch.ch","archived":false,"fork":false,"pushed_at":"2022-10-26T03:55:13.000Z","size":2624,"stargazers_count":8993,"open_issues_count":299,"forks_count":2377,"subscribers_count":624,"default_branch":"master","last_synced_at":"2024-10-30T06:33:36.071Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":"","language":"C","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"other","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/torch.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":"CONTRIBUTING.md","funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2013-10-18T12:13:58.000Z","updated_at":"2024-10-29T05:07:10.000Z","dependencies_parsed_at":"2022-07-12T02:02:13.176Z","dependency_job_id":null,"html_url":"https://github.com/torch/torch7","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/torch%2Ftorch7","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/torch%2Ftorch7/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/torch%2Ftorch7/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/torch%2Ftorch7/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/torch","download_url":"https://codeload.github.com/torch/torch7/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":245722964,"owners_count":20661856,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2024-07-31T16:01:07.516Z","updated_at":"2025-09-25T18:05:19.411Z","avatar_url":"https://github.com/torch.png","language":"C","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\u0026utm_medium=badge\u0026utm_campaign=pr-badge\u0026utm_content=badge)\n[![Build Status](https://travis-ci.org/torch/torch7.svg)](https://travis-ci.org/torch/torch7)\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://github.com/pytorch/pytorch/tree/master/aten), [mirror](https://github.com/zdevito/ATen/)).\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/aten/src/README.md](https://github.com/pytorch/pytorch/tree/master/aten/src#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://groups.google.com/forum/#!forum/torch7)\n* 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)\n* Hanging out with other developers and users (strictly no install issues, no large blobs of text): [Gitter Chat](https://gitter.im/torch/torch7)\n\n\u003ca name=\"torch.reference.dok\"\u003e\u003c/a\u003e\n# Torch Package Reference Manual #\n\n__Torch__ is the main package in [Torch7](http://torch.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\"\u003e\u003c/a\u003e\n## Torch Packages ##\n\n  * Tensor Library\n    * [Tensor](doc/tensor.md) defines the _all powerful_ tensor object that provides multi-dimensional numerical arrays with type templating.\n    * [Mathematical operations](doc/maths.md) that are defined for the tensor object types.\n    * [Storage](doc/storage.md) defines a simple storage interface that controls the underlying storage for any tensor object.\n  * File I/O Interface Library\n    * [File](doc/file.md) is an abstract interface for common file operations.\n    * [Disk File](doc/diskfile.md) defines operations on files stored on disk.\n    * [Memory File](doc/memoryfile.md) defines operations on stored in RAM.\n    * [Pipe File](doc/pipefile.md) defines operations for using piped commands.\n    * [High-Level File operations](doc/serialization.md) defines higher-level serialization functions.\n  * Useful Utilities\n    * [Timer](doc/timer.md) provides functionality for _measuring time_.\n    * [Tester](doc/tester.md) is a generic tester framework.\n    * [CmdLine](doc/cmdline.md) is a command line argument parsing utility.\n    * [Random](doc/random.md) defines a random number generator package with various distributions.\n    * Finally useful [utility](doc/utility.md) functions are provided for easy handling of torch tensor types and class inheritance.\n\n\u003ca name=\"torch.links.dok\"\u003e\u003c/a\u003e\n## Useful Links ##\n\n  * [Community packages](https://github.com/torch/torch7/wiki/Cheatsheet)\n  * [Torch Blog](http://torch.ch/blog/)\n  * [Torch Slides](https://github.com/soumith/cvpr2015/blob/master/cvpr-torch.pdf)\n\n","funding_links":[],"categories":["Scientific Computing","C","正则表达式","Machine Learning","其他_机器学习与深度学习"],"sub_categories":["科学计算","Frameworks"],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftorch%2Ftorch7","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Ftorch%2Ftorch7","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftorch%2Ftorch7/lists"}