{"id":17594552,"url":"https://github.com/tgjeon/tf-eager-execution-guide-kr","last_synced_at":"2025-04-30T04:34:12.898Z","repository":{"id":90561526,"uuid":"121479807","full_name":"tgjeon/TF-Eager-Execution-Guide-KR","owner":"tgjeon","description":"Programmer Guide (for Korean): TensorFlow Eager Execution","archived":false,"fork":false,"pushed_at":"2018-04-13T18:51:25.000Z","size":87,"stargazers_count":30,"open_issues_count":1,"forks_count":3,"subscribers_count":6,"default_branch":"master","last_synced_at":"2025-03-30T12:33:53.927Z","etag":null,"topics":["eager","guide","korean","tensorflow"],"latest_commit_sha":null,"homepage":"","language":null,"has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"apache-2.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/tgjeon.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}},"created_at":"2018-02-14T06:45:12.000Z","updated_at":"2023-09-08T17:36:39.000Z","dependencies_parsed_at":null,"dependency_job_id":"3f32f3a2-9cff-48e0-9c49-da2550f29b19","html_url":"https://github.com/tgjeon/TF-Eager-Execution-Guide-KR","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/tgjeon%2FTF-Eager-Execution-Guide-KR","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/tgjeon%2FTF-Eager-Execution-Guide-KR/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/tgjeon%2FTF-Eager-Execution-Guide-KR/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/tgjeon%2FTF-Eager-Execution-Guide-KR/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/tgjeon","download_url":"https://codeload.github.com/tgjeon/TF-Eager-Execution-Guide-KR/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":251643314,"owners_count":21620471,"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":["eager","guide","korean","tensorflow"],"created_at":"2024-10-22T07:08:14.481Z","updated_at":"2025-04-30T04:34:12.877Z","avatar_url":"https://github.com/tgjeon.png","language":null,"funding_links":[],"categories":[],"sub_categories":[],"readme":"# 즉시 실행 (Eager Execution)\n\n즉시 실행 (Eager execution)은 ([NumPy](http://www.numpy.org)와 유사한) 명령형 프로그래밍 스타일을 텐서플로우에서 제공합니다.\n사용자가 즉시 실행을 활성화 시킨다면, 텐서플로우 연산이 즉시 실행됩니다.\n사용자는 미리 만들어진 그래프를 [`Session.run()`](https://www.tensorflow.org/api_docs/python/tf/Session)\n으로 실행할 필요가 없습니다.\n\n예를 들면, 텐서플로우에서 간단한 계산을 수행한다고 생각해봅시다:\n\n```python\nx = tf.placeholder(tf.float32, shape=[1, 1])\nm = tf.matmul(x, x)\n\nwith tf.Session() as sess:\n  print(sess.run(m, feed_dict={x: [[2.]]}))\n\n# Will print [[4.]]\n```\n\n즉시 실행 (Eager execution)은 이 작업을 단순하게 할 수 있습니다:\n\n```python\nx = [[2.]]\nm = tf.matmul(x, x)\n\nprint(m)\n```\n\n## 주의사항\n\n본 기능은 초기 단계에 있으며, 분산 및 다수 GPU 학습과 성능에 대한 원활한 지원을 위해 개선사항이 남아 있습니다.\n\n- [알려진 이슈 사항](https://github.com/tensorflow/tensorflow/issues?q=is%3Aissue%20is%3Aopen%20label%3Acomp%3Aeager)\n- 피드백을 기다립니다, [문제 제기](https://github.com/tensorflow/tensorflow/issues/new)를 통해 피드백 주세요.\n\n## 설치\n\n즉시 실행 (Eager execution)은 텐서플로우 1.7 버전 이상에 포함되어 있습니다.\n설치 방법은 [공식 홈페이지 설치문서](https://www.tensorflow.org/install/)를 참고하세요.\n\n## 문서화\n\n텐서플로우의 즉시 실행 (eager execution)을 설명하기 위해 작성된 문서가 있습니다. 다음을 참고하세요:\n\n- [한글 사용자 가이드 (User Guides for Korean)](./guide.md) ([source](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/docs_src/programmers_guide/eager.md))\n- 노트북: [기본 사용법 (Basic Usages)](./examples/notebooks/1_basics.ipynb)\n- 노트북: [경사도 (Gradients)](./examples/notebooks/2_gradients.ipynb)\n- 노트북: [데이터 불러오기 (Importing Data)](./examples/notebooks/3_datasets.ipynb)\n\n## 변화사항\n\n- 2017/10/31: 초기 preview 버전 출시. (in TensorFlow 1.5)\n- 2017/12/01: 동적 신경망의 예제:\n  [SPINN: Stack-augmented Parser-Interpreter Neural Network](https://arxiv.org/abs/1603.06021).\n  자세한 내용은 다음 문서를 참고하세요: [README.md](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/contrib/eager/python/examples/spinn/README.md)\n- 2017/03: TensorFlow 1.7 버전에서 핵심 기능들이 실험적인 tf.contrib 네임스페이스에서 벗어났습니다.\n\n## TODO\n- 다양한 Example 수록\n  - gan\n  - linear_regression\n  - mnist\n  - resnet50\n  - rnn_colorbot\n  - rnn_ptb\n  - spinn","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftgjeon%2Ftf-eager-execution-guide-kr","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Ftgjeon%2Ftf-eager-execution-guide-kr","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftgjeon%2Ftf-eager-execution-guide-kr/lists"}