{"id":15662578,"url":"https://github.com/dnouri/gnumpy","last_synced_at":"2026-03-01T11:04:10.791Z","repository":{"id":6025440,"uuid":"7249383","full_name":"dnouri/gnumpy","owner":"dnouri","description":"A distutils package for gnumpy and npmat","archived":false,"fork":false,"pushed_at":"2017-11-10T18:46:06.000Z","size":148,"stargazers_count":18,"open_issues_count":4,"forks_count":6,"subscribers_count":4,"default_branch":"master","last_synced_at":"2025-05-06T01:45:48.235Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"Python","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/dnouri.png","metadata":{"files":{"readme":"README.rst","changelog":null,"contributing":null,"funding":null,"license":"LICENSE.txt","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2012-12-19T23:50:20.000Z","updated_at":"2023-06-14T14:26:23.000Z","dependencies_parsed_at":"2022-08-06T19:01:05.134Z","dependency_job_id":null,"html_url":"https://github.com/dnouri/gnumpy","commit_stats":null,"previous_names":[],"tags_count":1,"template":false,"template_full_name":null,"purl":"pkg:github/dnouri/gnumpy","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/dnouri%2Fgnumpy","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/dnouri%2Fgnumpy/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/dnouri%2Fgnumpy/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/dnouri%2Fgnumpy/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/dnouri","download_url":"https://codeload.github.com/dnouri/gnumpy/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/dnouri%2Fgnumpy/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":29967932,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-03-01T10:55:55.490Z","status":"ssl_error","status_checked_at":"2026-03-01T10:55:55.175Z","response_time":124,"last_error":"SSL_read: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"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":"2024-10-03T13:33:22.025Z","updated_at":"2026-03-01T11:04:10.776Z","avatar_url":"https://github.com/dnouri.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"[This document is a copy of the original.  `The latest version is\navailable on Tijmen Tieleman's\nhomepage. \u003chttp://www.cs.toronto.edu/~tijmen/gnumpy.html\u003e`_]\n\nGnumpy is free software, but if you use it in scientific work that\ngets published, you should cite `this tech report\n\u003chttp://www.cs.toronto.edu/~tijmen/gnumpyTr.pdf\u003e`_ in your\npublication.\n\nDocumentation: `here\n\u003chttp://www.cs.toronto.edu/~tijmen/gnumpyDoc.html\u003e`_.\n\nDo you want to have both the compute power of GPU's and the\nprogramming convenience of Python numpy? Gnumpy + Cudamat will bring\nyou that.\n\nGnumpy is a simple Python module that interfaces in a way almost\nidentical to numpy, but does its computations on your computer's\nGPU. See `this example\n\u003chttp://www.cs.toronto.edu/~tijmen/gnumpy_example.py\u003e`_, training an\nRBM using Gnumpy.\n\nGnumpy runs on top of, and therefore requires, the excellent `cudamat\n\u003chttp://code.google.com/p/cudamat/\u003e`_ library, written by `Vlad Mnih\n\u003chttp://www.cs.toronto.edu/~vmnih/\u003e`_.\n\nGnumpy can run in simulation mode: everything happens on the CPU, but\nthe interface is the same. This can be helpful if you like to write\nyour programs on your GPU-less laptop before running them on a\nGPU-equipped machine. It also allows you to easily test what\nperformance gain you get from using a GPU. The simulation mode\nrequires `npmat \u003chttp://www.cs.toronto.edu/~ilya/npmat.py\u003e`_, written\nby `Ilya Sutskever \u003chttp://www.cs.toronto.edu/~ilya\u003e`_.  [npmat is\nincluded in this distribution.]\n\nGnumpy is licensed with a BSD-style license (i.e. it's completely free\nto use for everyone, also as a component in commercial software), with\none added note: if you use it for scientific work that gets published,\nyou must include reference to the Gnumpy tech report in your\npublication. For details of the license, see the top of gnumpy.py.\n\nRecent changes:\n\n- 2012-07-25: Bugfix. gnumpy.dot(x, x), when x is a 1-dimensional array, didn't work but now works.\n- 2011-06-06: gnumpy.dot() now takes arrays of ndim\u003e2.\n- 2011-04-19: Bugfix: several bugs involving zero size arrays were fixed.\n- 2011-04-15: Bugfix. \"x=gnumpy.zeros(10); x[array([])] = garray([])\" didn't work as it should. Now it does.\n- 2011-03-24: Added gnumpy.outer().\n- 2011-03-15: The ability to check for infs and nans automatically has been added to Gnumpy.\n- 2010-07-19: Cudamat now enables fast indexing with arrays of indices. Download the newest Cudamat to have fast indexing with arrays in Gnumpy.\n- 2010-07-08: Renamed the project to Gnumpy. It used to be called Gpunnumpy.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdnouri%2Fgnumpy","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fdnouri%2Fgnumpy","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdnouri%2Fgnumpy/lists"}