{"id":15159447,"url":"https://github.com/ondrejbiza/tfset","last_synced_at":"2026-02-11T06:04:05.402Z","repository":{"id":57474902,"uuid":"101539888","full_name":"ondrejbiza/tfset","owner":"ondrejbiza","description":"Interactive Tensorflow training.","archived":false,"fork":false,"pushed_at":"2018-02-02T12:30:09.000Z","size":11470,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"master","last_synced_at":"2025-09-15T03:48:28.079Z","etag":null,"topics":["deep-learning","deep-neural-networks","machine-learning","tensorflow","tensorflow-experiments"],"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/ondrejbiza.png","metadata":{"files":{"readme":"README.rst","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":"2017-08-27T08:35:03.000Z","updated_at":"2019-02-10T09:54:05.000Z","dependencies_parsed_at":"2022-09-10T02:23:17.977Z","dependency_job_id":null,"html_url":"https://github.com/ondrejbiza/tfset","commit_stats":null,"previous_names":["ondrejba/tfset"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/ondrejbiza/tfset","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ondrejbiza%2Ftfset","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ondrejbiza%2Ftfset/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ondrejbiza%2Ftfset/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ondrejbiza%2Ftfset/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/ondrejbiza","download_url":"https://codeload.github.com/ondrejbiza/tfset/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ondrejbiza%2Ftfset/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":29327915,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-02-11T03:52:29.695Z","status":"ssl_error","status_checked_at":"2026-02-11T03:52:23.094Z","response_time":97,"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":["deep-learning","deep-neural-networks","machine-learning","tensorflow","tensorflow-experiments"],"created_at":"2024-09-26T21:22:07.404Z","updated_at":"2026-02-11T06:04:05.389Z","avatar_url":"https://github.com/ondrejbiza.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"tfset\n=====\n\n.. figure:: tfset/images/validation_curve.png\n   :alt: Validation Curve\n\n**Change the hyper-parameters** of your Tensorflow training session on\nthe fly. The package allows you to schedule events that change the\nvalues of arbitrary Tensors with a simple command.\n\nRequirements\n~~~~~~~~~~~~\n\n-  Python \u003e= 3\n-  tensorflow \u003e= 1.0\n\nSet Up\n~~~~~~\n\nInstall the package with pip:\n\n``pip install tfset``\n\nOr clone and install from github:\n\n.. code-block:: bash\n\n   git clone https://github.com/ondrejba/tfset.git\n   cd tfset\n   python setup.py install\n\nUsage\n~~~~~\n\ntfset DEMO\n^^^^^^^^^^^^^^^^^^^^^^^^^^^\n\nCheck\n`MNIST\\_demo.ipynb \u003chttps://github.com/ondrejba/tfset/blob/master/tfset/MNIST_demo.ipynb\u003e`__\nfor a demostration of the usage of tfset in a simple\ntraining script.\n\nServer\n^^^^^^\n\nImport tfset server.\n\n::\n\n    import tfset.server as server\n\nCreate Tensors for your hyper-parameters.\n\n::\n\n    learning_rate = tf.get_variable(\"learning_rate\", initializer=tf.constant(0.1, dtype=tf.float32))\n    dropout_prob = tf.get_variable(\"dropout_prob\", initializer=tf.constant(0.9, dtype=tf.float32))\n\nCreate and start a Session Server.\n\n::\n\n    # \"session\" is a Tensorflow session\n    s, thread = server.run_server([learning_rate, dropout_prob], session)\n\nPeriodically check for events.\n\n::\n\n    # \"step\" is the global step of your training procedure\n    s.check_events(step)\n\nStop the server.\n\n::\n\n    s.shutdown()\n    thread.join(timeout=10)\n\nClient\n^^^^^^\n\nGet status.\n\n``tfset -s``\n\nAdd an event (this event sets the learning rate to 0.01 at iteration\n10000).\n\n``tfset -a -n learning_rate:0 -i 10000 --value 0.01``\n\nRemove an event (with index 0 in this case).\n\n``tfset -r -e 0``\n\nEvents\n^^^^^^\n\ntfset schedules hyper-parameter changes based on\n**events**. An event contains the following information:\n\n-  **iteration**: when to execute the event\n-  **Tensor name**: which Tensor to change\n-  **value**: value to set the Tensor to\n\nThe reason for the use of events is that you might want to schedule\nhyper-parameter changes in the future (e.g. lower learning rate to 10e-3\nat 800k iteration). If two events targeting the same Tensor are\nscheduled at the same iteration, the one that was scheduled later is\ngoing to be executed.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fondrejbiza%2Ftfset","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fondrejbiza%2Ftfset","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fondrejbiza%2Ftfset/lists"}