{"id":20885650,"url":"https://github.com/xinshuoweng/cnnramwatcher","last_synced_at":"2025-09-05T02:33:29.292Z","repository":{"id":112028842,"uuid":"87006597","full_name":"xinshuoweng/CNNRamWatcher","owner":"xinshuoweng","description":"Memory Monitor and Net Visualizer for Deep Neural Network ","archived":false,"fork":false,"pushed_at":"2017-04-06T17:44:42.000Z","size":1671,"stargazers_count":6,"open_issues_count":0,"forks_count":3,"subscribers_count":1,"default_branch":"master","last_synced_at":"2025-08-16T17:44:20.310Z","etag":null,"topics":["caffe","memory","monitor","tensorflow","torch","visualizer"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/xinshuoweng.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,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null}},"created_at":"2017-04-02T18:27:17.000Z","updated_at":"2023-03-09T03:48:20.000Z","dependencies_parsed_at":"2023-03-13T13:29:55.024Z","dependency_job_id":null,"html_url":"https://github.com/xinshuoweng/CNNRamWatcher","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/xinshuoweng/CNNRamWatcher","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/xinshuoweng%2FCNNRamWatcher","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/xinshuoweng%2FCNNRamWatcher/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/xinshuoweng%2FCNNRamWatcher/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/xinshuoweng%2FCNNRamWatcher/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/xinshuoweng","download_url":"https://codeload.github.com/xinshuoweng/CNNRamWatcher/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/xinshuoweng%2FCNNRamWatcher/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":273702383,"owners_count":25152882,"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","status":"online","status_checked_at":"2025-09-05T02:00:09.113Z","response_time":402,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"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":["caffe","memory","monitor","tensorflow","torch","visualizer"],"created_at":"2024-11-18T08:14:07.376Z","updated_at":"2025-09-05T02:33:29.268Z","avatar_url":"https://github.com/xinshuoweng.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Ramwatcher\nA very lightweight deep learning tool for monitoring **data flow**, **parameter size** and their corresponding **memory usage** throughout deep neural network. This tool **doesn't** need any powerful computational resource (eg. GPU). And it's very easy to use since it follows many similar rules in popular deep learning frameworks (**Caffe**, **Tensorflow**, **Torch**)\n\n#### Usage:\n\n*1. clone the github repository recursively including xinshuo_toolbox.*\n~~~shell\ngit clone --recursive https://github.com/xinshuoweng/ramwatcher\n~~~\n\n*2. install dependency for the toolbox.*\n~~~shell\ncd ramwatcher/xinshuo_toolbox\npip install -r requirements.txt\n~~~\n\n*3. define the network and print the memory info (one might want to look at example.py first for a quick and simple instruction).*\n~~~shell\ncd ..\npython example.py\n~~~\n\n#### Example Result:\n\n*Network Info Table:*\n\u003cp align=\"center\"\u003e\n\u003cimg alt=\"Network Info Table\", src=\"network_info.png\")\n\u003c/p\u003e\n\n*Memory Usage Pie Chart:*\n\u003cp align=\"center\"\u003e\n\u003cimg alt=\"Memory Usage Pie Chart\", src=\"memory_chart.png\")\n\u003c/p\u003e\n\n*Model Graph:*\n\u003cp align=\"center\"\u003e\n\u003cimg alt=\"Model Graph\", src=\"model_graph.png\")\n\u003c/p\u003e\n\n\n#### Limitation:\n\n*1. Only basic layers (Convolution, Pooling, Activation, Dense, Concat) are supported right now. More layers will be added in the future.*\u003cbr\u003e\n*2. Add prototxt parse function in the future.*\u003cbr\u003e\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fxinshuoweng%2Fcnnramwatcher","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fxinshuoweng%2Fcnnramwatcher","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fxinshuoweng%2Fcnnramwatcher/lists"}