{"id":21124867,"url":"https://github.com/harveyslash/sympyle","last_synced_at":"2025-10-07T15:43:47.644Z","repository":{"id":52705001,"uuid":"137254960","full_name":"harveyslash/sympyle","owner":"harveyslash","description":"Automatic differentiation in python","archived":false,"fork":false,"pushed_at":"2022-06-21T21:21:58.000Z","size":14982,"stargazers_count":9,"open_issues_count":2,"forks_count":3,"subscribers_count":6,"default_branch":"master","last_synced_at":"2024-11-08T07:12:39.233Z","etag":null,"topics":["backpropagation","computational-graphs","deep-learning","learning","machine-learning","neural-network","tutorial"],"latest_commit_sha":null,"homepage":"http://harveyslash.github.io/sympyle/","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"gpl-3.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/harveyslash.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2018-06-13T18:25:30.000Z","updated_at":"2022-03-02T22:54:26.000Z","dependencies_parsed_at":"2022-08-22T10:21:37.619Z","dependency_job_id":null,"html_url":"https://github.com/harveyslash/sympyle","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/harveyslash%2Fsympyle","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/harveyslash%2Fsympyle/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/harveyslash%2Fsympyle/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/harveyslash%2Fsympyle/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/harveyslash","download_url":"https://codeload.github.com/harveyslash/sympyle/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":225231320,"owners_count":17441569,"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":["backpropagation","computational-graphs","deep-learning","learning","machine-learning","neural-network","tutorial"],"created_at":"2024-11-20T04:18:18.753Z","updated_at":"2025-10-07T15:43:47.514Z","avatar_url":"https://github.com/harveyslash.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Sympyle \nSimple Symbolic Graphs in Python\n\n\n[![Build Status](https://travis-ci.com/harveyslash/sympyle.svg?branch=master)](https://travis-ci.com/harveyslash/sympyle)\n[![codecov](https://codecov.io/gh/harveyslash/Sympyle/branch/master/graph/badge.svg)](https://codecov.io/gh/harveyslash/Sympyle)\n[![CodeFactor](https://www.codefactor.io/repository/github/harveyslash/sympyle/badge/master)](https://www.codefactor.io/repository/github/harveyslash/sympyle/overview/master)\n\n\n## About\n\n##### Project documentation: http://harveyslash.github.io/sympyle/\n\n\nSympyle is a Python library to demonstrate the inner workings of Computational\nGraphs. Computational Graphs are used by highly optimised computational\nframeworks like [tensorflow](https://tensorflow.org) and\n[pytorch](https://pytorch.org).\n\nHowever, these frameworks make several assumptions and optimisations in order\nto optimise for speed and memory. This often makes it harder to understand\nthe inner workings of how these libraries work.\n\nSympyle is a simplified model library to demonstrate the working of\ncomputational graphs, and how\n[backpropagation](https://en.wikipedia.org/wiki/Backpropagation)\nworks on arbitrary 'networks'.\n\n### Examples and tutorials\n\nAll tutorials are under docs/source/tutorials and interactible at https://harveyslash.github.io/sympyle/ (under the tutorials section)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fharveyslash%2Fsympyle","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fharveyslash%2Fsympyle","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fharveyslash%2Fsympyle/lists"}