# for 11/18(Mon) work ## Prologue * 初心者向けの **"Stock"** を作る?(ここ?) * Slack は "Flow" なので latest は分かっても全体像の把握は難しい。 --- ## Contribute Flow :::info :smiley: **getting started:** 翻訳作業のフロー ::: 1. fork tensorflow/docs. * [リポジトリをフォークする](https://help.github.com/ja/github/getting-started-with-github/fork-a-repo) 1. decide translate file. 1. translate. * Colab上で翻訳すると後々便利です 3. apply [tfug/proofreading](https://github.com/tfug/proofreading) to my work. 4. order to review my work. * Jupyter Notebookの場合、Colabで一度保存したものをPRとして出しましょう * [REVIEWERS](https://github.com/tensorflow/docs/blob/master/site/ja/REVIEWERS) 5. reviewed by reviewers. * then, approve. 6. post "pull request" to official repos. * [フォークからのプルリクエストの作成](https://help.github.com/ja/github/collaborating-with-issues-and-pull-requests/creating-a-pull-request-from-a-fork) ### 追記 * まず official に pull req. してから、 そのチケット上で official REVIEWERS が review / approve し、 merge されるという手順らしい。 --- ## Our battle fields * [github/tensorflow](https://github.com/tensorflow/) * [翻訳対象](https://github.com/tensorflow/docs/tree/master/site/en) * [プルリクが merge された結果](https://github.com/tensorflow/docs/tree/master/site/ja) * is [github/tfug/docs](https://github.com/tensorflow/docs/) obsolete ? * original からの fork だが、 4 months ago なのでもう使用していない? ### Refs: Translators の working repos. * [Mr. Ohtaman](https://github.com/ohtaman/docs) ### Refs: Pull Request * [for beginners](https://blog.qnyp.com/2013/05/28/pull-request-for-github-beginners/) --- ## Slack から抽出した Rules ### 翻訳対象外 * index .md * site/en/r1/ 以下 * .. --- ## Slack で出てきた Keywords * [RedPen](http://redpen.cc/docs/latest/index_ja.html) * =赤ペン。OSS の文章校正ツール。Java * [LGTM! チャットや GitHub でよく見る英略語ってこんな意味](https://blog.sixapart.jp/2016-10/lgtm-github.html) * LGTM! : Looks Good To Me ! * "for me" ではないの? --- ## candidate ipynb files * [誰がどのドキュメントを翻訳中か確認できますか](https://github.com/tensorflow/docs/blob/master/site/ja/CONTRIBUTING.md#誰がどのドキュメントを翻訳中か確認できますか) * ~~現在の pull req. を追いかけるのは大変そうなので~~   希望するファイルをいくつか pickup しておく。 * Slack より引用 * [このへんで今出てる PR が見られるので、<br>かぶらないようにしていきましょう](https://github.com/tensorflow/docs/pulls?utf8=%E2%9C%93&q=is%3Apr+is%3Aopen+JA) 1. tutorials/images/transfer_learning_with_hub.ipynb 1. tutorials/images/transfer_learning.ipynb 1. tutorials/images/segmentation.ipynb 1. tutorials/keras/text_classification_with_hub.ipynb 1. tutorials/load_data/pandas_dataframe.ipynb 1. ~~tutorials/text/text_generation.ipynb~~ * PR is already exist. * ipynb の修正は Google Colab. でいいかな.. * ipynb は json format なので、 一応普通の editor でも edit できるもよう。 --- ## 先々の心配 * pull req. チケットの update notification どうしてるのかな * メール通知あるけどなぁ... * [公式アプリが出たらしい](https://wired.jp/2019/11/15/github-mobile-apps-ios-android/) --- ## Refs: diff *.ipynb btwn site/en/ and site/ja/ * on master branch at 2019/11/16. ~~~diff --- en.txt 2019-11-16 21:29:07.000000000 +0900 +++ ja.txt 2019-11-16 21:29:17.000000000 +0900 @@ -1,42 +1,8 @@ -guide/checkpoint.ipynb -guide/data.ipynb -guide/distributed_training.ipynb guide/eager.ipynb -guide/estimator.ipynb guide/function.ipynb -guide/gpu.ipynb -guide/keras/custom_callback.ipynb -guide/keras/custom_layers_and_models.ipynb -guide/keras/functional.ipynb -guide/keras/masking_and_padding.ipynb -guide/keras/overview.ipynb -guide/keras/rnn.ipynb -guide/keras/save_and_serialize.ipynb -guide/keras/train_and_evaluate.ipynb -guide/migrate.ipynb -guide/ragged_tensor.ipynb -guide/saved_model.ipynb -guide/upgrade.ipynb -r1/guide/autograph.ipynb -r1/guide/distribute_strategy.ipynb r1/guide/eager.ipynb r1/guide/keras.ipynb -r1/guide/ragged_tensors.ipynb -r1/tutorials/_index.ipynb -r1/tutorials/distribute/keras.ipynb -r1/tutorials/distribute/tpu_custom_training.ipynb -r1/tutorials/distribute/training_loops.ipynb -r1/tutorials/eager/automatic_differentiation.ipynb -r1/tutorials/eager/custom_layers.ipynb -r1/tutorials/eager/custom_training.ipynb -r1/tutorials/eager/custom_training_walkthrough.ipynb -r1/tutorials/eager/eager_basics.ipynb -r1/tutorials/estimators/boosted_trees.ipynb -r1/tutorials/estimators/boosted_trees_model_understanding.ipynb -r1/tutorials/estimators/cnn.ipynb -r1/tutorials/estimators/linear.ipynb r1/tutorials/images/hub_with_keras.ipynb -r1/tutorials/images/transfer_learning.ipynb r1/tutorials/keras/basic_classification.ipynb r1/tutorials/keras/basic_regression.ipynb r1/tutorials/keras/basic_text_classification.ipynb @@ -44,59 +10,27 @@ r1/tutorials/keras/save_and_restore_models.ipynb r1/tutorials/load_data/images.ipynb r1/tutorials/load_data/tf_records.ipynb -r1/tutorials/non-ml/mandelbrot.ipynb -r1/tutorials/non-ml/pdes.ipynb -r1/tutorials/representation/unicode.ipynb -r1/tutorials/sequences/text_generation.ipynb tutorials/customization/autodiff.ipynb tutorials/customization/basics.ipynb tutorials/customization/custom_layers.ipynb tutorials/customization/custom_training.ipynb tutorials/customization/custom_training_walkthrough.ipynb tutorials/customization/performance.ipynb -tutorials/distribute/custom_training.ipynb -tutorials/distribute/keras.ipynb -tutorials/distribute/multi_worker_with_estimator.ipynb -tutorials/distribute/multi_worker_with_keras.ipynb -tutorials/distribute/save_and_load.ipynb -tutorials/estimator/boosted_trees.ipynb -tutorials/estimator/boosted_trees_model_understanding.ipynb -tutorials/estimator/keras_model_to_estimator.ipynb -tutorials/estimator/linear.ipynb -tutorials/estimator/premade.ipynb -tutorials/generative/adversarial_fgsm.ipynb -tutorials/generative/cvae.ipynb -tutorials/generative/cyclegan.ipynb -tutorials/generative/dcgan.ipynb -tutorials/generative/deepdream.ipynb -tutorials/generative/pix2pix.ipynb -tutorials/generative/style_transfer.ipynb tutorials/images/classification.ipynb tutorials/images/cnn.ipynb -tutorials/images/segmentation.ipynb -tutorials/images/transfer_learning.ipynb -tutorials/images/transfer_learning_with_hub.ipynb tutorials/keras/classification.ipynb tutorials/keras/overfit_and_underfit.ipynb tutorials/keras/regression.ipynb tutorials/keras/save_and_load.ipynb tutorials/keras/text_classification.ipynb -tutorials/keras/text_classification_with_hub.ipynb tutorials/load_data/csv.ipynb tutorials/load_data/images.ipynb tutorials/load_data/numpy.ipynb -tutorials/load_data/pandas_dataframe.ipynb tutorials/load_data/text.ipynb tutorials/load_data/tfrecord.ipynb -tutorials/load_data/unicode.ipynb tutorials/quickstart/advanced.ipynb tutorials/quickstart/beginner.ipynb tutorials/structured_data/feature_columns.ipynb -tutorials/structured_data/imbalanced_data.ipynb -tutorials/structured_data/time_series.ipynb -tutorials/text/image_captioning.ipynb -tutorials/text/nmt_with_attention.ipynb tutorials/text/text_classification_rnn.ipynb -tutorials/text/text_generation.ipynb -tutorials/text/transformer.ipynb tutorials/text/word_embeddings.ipynb +xla/tutorials/xla_compile.ipynb ~~~ --- ## EOF