{"id":15356398,"url":"https://github.com/saravanabalagi/keras_tensorboard_starter","last_synced_at":"2026-04-09T21:58:05.537Z","repository":{"id":84130053,"uuid":"256334726","full_name":"saravanabalagi/keras_tensorboard_starter","owner":"saravanabalagi","description":"Starter project for Keras with Tensorboard logging","archived":false,"fork":false,"pushed_at":"2020-04-17T22:34:54.000Z","size":83,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"master","last_synced_at":"2025-03-27T14:53:21.747Z","etag":null,"topics":["keras","tensorboard","tensorflow","tensorflow2"],"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/saravanabalagi.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"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}},"created_at":"2020-04-16T21:32:54.000Z","updated_at":"2020-04-17T22:35:21.000Z","dependencies_parsed_at":null,"dependency_job_id":"2f15e0a9-1dd0-43f9-ad5c-d1ee8645f97e","html_url":"https://github.com/saravanabalagi/keras_tensorboard_starter","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/saravanabalagi/keras_tensorboard_starter","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/saravanabalagi%2Fkeras_tensorboard_starter","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/saravanabalagi%2Fkeras_tensorboard_starter/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/saravanabalagi%2Fkeras_tensorboard_starter/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/saravanabalagi%2Fkeras_tensorboard_starter/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/saravanabalagi","download_url":"https://codeload.github.com/saravanabalagi/keras_tensorboard_starter/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/saravanabalagi%2Fkeras_tensorboard_starter/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":270422580,"owners_count":24580828,"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":"2025-08-14T02:00:10.309Z","response_time":75,"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":["keras","tensorboard","tensorflow","tensorflow2"],"created_at":"2024-10-01T12:28:36.172Z","updated_at":"2026-04-09T21:58:05.493Z","avatar_url":"https://github.com/saravanabalagi.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Keras Tensorboard Starter\n\nThis is a keras starter project that provides tf.summary logging out of the box \ninside your model inference code for both train and eval runs.\n\nYou should be able to see something like\n\n![Screenshot](images/screenshot.png)\n\nwhere \n- eval has exactly 3 records (at 0, 10 and 20 corresponding to 3 `evaluate`s)\n- train has 20 records (0-9 and 10-19 corresponding to 2 `fit`s with 10 epochs each)\n \n## Instructions\n \nFrom Tensorflow 2.2, we can override Keras `model.fit` using `Model.train_step`. \nThis allows us to write a custom train step and use the same old `model.fit` in an elegant way, \nbut to call our custom train step logic. See example at [train_and_evaluate.py](train_and_evaluate.py)\n\n## For Older Versions\n\nFor older versions of tensorflow, the hack implemented in [train_and_evaluate_old.py](train_and_evaluate_old.py) \nwhere we can pass the summary writer into an argument\nand use it in `call` method to log can be a workaround.\n\nAlthough it's not as elegant as the above method, it works!\n\n![Screenshot Old](images/screenshot_old.png)\n\n## Licence\n\nPlease see attached [Licence](LICENCE)","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsaravanabalagi%2Fkeras_tensorboard_starter","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fsaravanabalagi%2Fkeras_tensorboard_starter","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsaravanabalagi%2Fkeras_tensorboard_starter/lists"}