[JA] Translations

[ilyaspiridonov]

Translated by Alconost

[github-actions]

Localization

Translators and reviewers are encouraged to submit pull requests from our GitLocalize project.

Preview

Preview and run these notebook edits with Google Colab:

• site/ja/addons/tutorials/average_optimizers_callback.ipynb
• site/ja/addons/tutorials/image_ops.ipynb
• site/ja/addons/tutorials/layers_normalizations.ipynb
• site/ja/addons/tutorials/networks_seq2seq_nmt.ipynb
• site/ja/addons/tutorials/optimizers_lazyadam.ipynb
• site/ja/agents/tutorials/0_intro_rl.ipynb
• site/ja/agents/tutorials/10_checkpointer_policysaver_tutorial.ipynb
• site/ja/agents/tutorials/1_dqn_tutorial.ipynb
• site/ja/agents/tutorials/2_environments_tutorial.ipynb
• site/ja/agents/tutorials/3_policies_tutorial.ipynb
• site/ja/agents/tutorials/4_drivers_tutorial.ipynb
• site/ja/agents/tutorials/5_replay_buffers_tutorial.ipynb
• site/ja/agents/tutorials/6_reinforce_tutorial.ipynb
• site/ja/agents/tutorials/7_SAC_minitaur_tutorial.ipynb
• site/ja/agents/tutorials/8_networks_tutorial.ipynb
• site/ja/agents/tutorials/9_c51_tutorial.ipynb
• site/ja/agents/tutorials/bandits_tutorial.ipynb
• site/ja/agents/tutorials/intro_bandit.ipynb
• site/ja/agents/tutorials/per_arm_bandits_tutorial.ipynb
• site/ja/agents/tutorials/ranking_tutorial.ipynb
• site/ja/datasets/dataset_collections.ipynb
• site/ja/datasets/overview.ipynb
• site/ja/datasets/tfless_tfds.ipynb
• site/ja/federated/tutorials/building_your_own_federated_learning_algorithm.ipynb
• site/ja/federated/tutorials/composing_learning_algorithms.ipynb
• site/ja/federated/tutorials/custom_aggregators.ipynb
• site/ja/federated/tutorials/custom_federated_algorithm_with_tff_optimizers.ipynb
• site/ja/federated/tutorials/custom_federated_algorithms_1.ipynb
• site/ja/federated/tutorials/custom_federated_algorithms_2.ipynb
• site/ja/federated/tutorials/federated_learning_for_image_classification.ipynb
• site/ja/federated/tutorials/federated_learning_for_text_generation.ipynb
• site/ja/federated/tutorials/federated_learning_with_differential_privacy.ipynb
• site/ja/federated/tutorials/federated_reconstruction_for_matrix_factorization.ipynb
• site/ja/federated/tutorials/federated_select.ipynb
• site/ja/federated/tutorials/private_heavy_hitters.ipynb
• site/ja/federated/tutorials/random_noise_generation.ipynb
• site/ja/federated/tutorials/simulations.ipynb
• site/ja/federated/tutorials/simulations_with_accelerators.ipynb
• site/ja/federated/tutorials/sparse_federated_learning.ipynb
• site/ja/federated/tutorials/tff_for_federated_learning_research_compression.ipynb
• site/ja/federated/tutorials/tuning_recommended_aggregators.ipynb
• site/ja/federated/tutorials/working_with_client_data.ipynb
• site/ja/guide/autodiff.ipynb
• site/ja/guide/basic_training_loops.ipynb
• site/ja/guide/basics.ipynb
• site/ja/guide/checkpoint.ipynb
• site/ja/guide/core/distribution.ipynb
• site/ja/guide/core/logistic_regression_core.ipynb
• site/ja/guide/core/matrix_core.ipynb
• site/ja/guide/core/optimizers_core.ipynb
• site/ja/guide/core/quickstart_core.ipynb
• site/ja/guide/data.ipynb
• site/ja/guide/data_performance.ipynb
• site/ja/guide/distributed_training.ipynb
• site/ja/guide/dtensor_overview.ipynb
• site/ja/guide/estimator.ipynb
• site/ja/guide/extension_type.ipynb
• site/ja/guide/function.ipynb
• site/ja/guide/intro_to_graphs.ipynb
• site/ja/guide/intro_to_modules.ipynb
• site/ja/guide/jax2tf.ipynb
• site/ja/guide/keras/custom_layers_and_models.ipynb
• site/ja/guide/keras/customizing_what_happens_in_fit.ipynb
• site/ja/guide/keras/functional.ipynb
• site/ja/guide/keras/masking_and_padding.ipynb
• site/ja/guide/keras/preprocessing_layers.ipynb
• site/ja/guide/keras/rnn.ipynb
• site/ja/guide/keras/sequential_model.ipynb
• site/ja/guide/keras/transfer_learning.ipynb
• site/ja/guide/keras/writing_a_training_loop_from_scratch.ipynb
• site/ja/guide/migrate/canned_estimators.ipynb
• site/ja/guide/migrate/early_stopping.ipynb
• site/ja/guide/migrate/migrating_feature_columns.ipynb
• site/ja/guide/migrate/migration_debugging.ipynb
• site/ja/guide/migrate/saved_model.ipynb
• site/ja/guide/migrate/tensorboard.ipynb
• site/ja/guide/migrate/tf1_vs_tf2.ipynb
• site/ja/guide/migrate/tflite.ipynb
• site/ja/guide/migrate/validate_correctness.ipynb
• site/ja/guide/mixed_precision.ipynb
• site/ja/guide/saved_model.ipynb
• site/ja/guide/tensor.ipynb
• site/ja/guide/tf_numpy.ipynb
• site/ja/guide/tf_numpy_type_promotion.ipynb
• site/ja/guide/tpu.ipynb
• site/ja/hub/tutorials/action_recognition_with_tf_hub.ipynb
• site/ja/hub/tutorials/bangla_article_classifier.ipynb
• site/ja/hub/tutorials/bert_experts.ipynb
• site/ja/hub/tutorials/bigbigan_with_tf_hub.ipynb
• site/ja/hub/tutorials/biggan_generation_with_tf_hub.ipynb
• site/ja/hub/tutorials/boundless.ipynb
• site/ja/hub/tutorials/cord_19_embeddings.ipynb
• site/ja/hub/tutorials/cord_19_embeddings_keras.ipynb
• site/ja/hub/tutorials/cropnet_cassava.ipynb
• site/ja/hub/tutorials/cropnet_on_device.ipynb
• site/ja/hub/tutorials/cross_lingual_similarity_with_tf_hub_multilingual_universal_encoder.ipynb
• site/ja/hub/tutorials/hrnet_semantic_segmentation.ipynb
• site/ja/hub/tutorials/image_classification.ipynb
• site/ja/hub/tutorials/image_enhancing.ipynb
• site/ja/hub/tutorials/image_feature_vector.ipynb
• site/ja/hub/tutorials/movenet.ipynb
• site/ja/hub/tutorials/movinet.ipynb
• site/ja/hub/tutorials/object_detection.ipynb
• site/ja/hub/tutorials/retrieval_with_tf_hub_universal_encoder_qa.ipynb
• site/ja/hub/tutorials/s3gan_generation_with_tf_hub.ipynb
• site/ja/hub/tutorials/semantic_approximate_nearest_neighbors.ipynb
• site/ja/hub/tutorials/semantic_similarity_with_tf_hub_universal_encoder.ipynb
• site/ja/hub/tutorials/semantic_similarity_with_tf_hub_universal_encoder_lite.ipynb
• site/ja/hub/tutorials/senteval_for_universal_sentence_encoder_cmlm.ipynb
• site/ja/hub/tutorials/spice.ipynb
• site/ja/hub/tutorials/text_classification_with_tf_hub_on_kaggle.ipynb
• site/ja/hub/tutorials/text_to_video_retrieval_with_s3d_milnce.ipynb
• site/ja/hub/tutorials/tf2_arbitrary_image_stylization.ipynb
• site/ja/hub/tutorials/tf2_image_retraining.ipynb
• site/ja/hub/tutorials/tf2_object_detection.ipynb
• site/ja/hub/tutorials/tf2_semantic_approximate_nearest_neighbors.ipynb
• site/ja/hub/tutorials/tf2_text_classification.ipynb
• site/ja/hub/tutorials/tf_hub_delf_module.ipynb
• site/ja/hub/tutorials/tf_hub_film_example.ipynb
• site/ja/hub/tutorials/tf_hub_generative_image_module.ipynb
• site/ja/hub/tutorials/tweening_conv3d.ipynb
• site/ja/hub/tutorials/wav2vec2_saved_model_finetuning.ipynb
• site/ja/hub/tutorials/wiki40b_lm.ipynb
• site/ja/hub/tutorials/yamnet.ipynb
• site/ja/io/tutorials/audio.ipynb
• site/ja/io/tutorials/avro.ipynb
• site/ja/io/tutorials/bigquery.ipynb
• site/ja/io/tutorials/colorspace.ipynb
• site/ja/io/tutorials/dicom.ipynb
• site/ja/io/tutorials/genome.ipynb
• site/ja/io/tutorials/postgresql.ipynb
• site/ja/io/tutorials/prometheus.ipynb
• site/ja/lattice/tutorials/canned_estimators.ipynb
• site/ja/lattice/tutorials/premade_models.ipynb
• site/ja/lattice/tutorials/shape_constraints.ipynb
• site/ja/lattice/tutorials/shape_constraints_for_ethics.ipynb
• site/ja/lite/examples/on_device_training/overview.ipynb
• site/ja/lite/examples/style_transfer/overview.ipynb
• site/ja/lite/guide/model_analyzer.ipynb
• site/ja/lite/guide/signatures.ipynb
• site/ja/lite/models/modify/model_maker/image_classification.ipynb
• site/ja/lite/models/modify/model_maker/object_detection.ipynb
• site/ja/lite/models/modify/model_maker/question_answer.ipynb
• site/ja/lite/models/modify/model_maker/text_classification.ipynb
• site/ja/lite/models/modify/model_maker/text_searcher.ipynb
• site/ja/lite/performance/post_training_float16_quant.ipynb
• site/ja/lite/tutorials/pose_classification.ipynb
• site/ja/model_optimization/guide/clustering/clustering_comprehensive_guide.ipynb
• site/ja/model_optimization/guide/quantization/training_comprehensive_guide.ipynb
• site/ja/neural_structured_learning/tutorials/adversarial_keras_cnn_mnist.ipynb
• site/ja/probability/examples/A_Tour_of_TensorFlow_Probability.ipynb
• site/ja/probability/examples/Bayesian_Gaussian_Mixture_Model.ipynb
• site/ja/probability/examples/Fitting_DPMM_Using_pSGLD.ipynb
• site/ja/probability/examples/Gaussian_Process_Regression_In_TFP.ipynb
• site/ja/probability/examples/Generalized_Linear_Models.ipynb
• site/ja/probability/examples/HLM_TFP_R_Stan.ipynb
• site/ja/probability/examples/JointDistributionAutoBatched_A_Gentle_Tutorial.ipynb
• site/ja/probability/examples/Linear_Mixed_Effects_Model_Variational_Inference.ipynb
• site/ja/probability/examples/Linear_Mixed_Effects_Models.ipynb
• site/ja/probability/examples/Modeling_with_JointDistribution.ipynb
• site/ja/probability/examples/Multilevel_Modeling_Primer.ipynb
• site/ja/probability/examples/Multiple_changepoint_detection_and_Bayesian_model_selection.ipynb
• site/ja/probability/examples/Probabilistic_Layers_VAE.ipynb
• site/ja/probability/examples/TFP_Release_Notebook_0_11_0.ipynb
• site/ja/probability/examples/TFP_Release_Notebook_0_12_1.ipynb
• site/ja/probability/examples/TFP_Release_Notebook_0_13_0.ipynb
• site/ja/probability/examples/TensorFlow_Distributions_Tutorial.ipynb
• site/ja/probability/examples/TensorFlow_Probability_Case_Study_Covariance_Estimation.ipynb
• site/ja/probability/examples/TensorFlow_Probability_on_JAX.ipynb
• site/ja/probability/examples/Understanding_TensorFlow_Distributions_Shapes.ipynb
• site/ja/probability/examples/Variational_Inference_with_Multipart_Bijectors.ipynb
• site/ja/quantum/tutorials/hello_many_worlds.ipynb
• site/ja/quantum/tutorials/mnist.ipynb
• site/ja/quantum/tutorials/quantum_reinforcement_learning.ipynb
• site/ja/tensorboard/get_started.ipynb
• site/ja/tensorboard/graphs.ipynb
• site/ja/tensorboard/hyperparameter_tuning_with_hparams.ipynb
• site/ja/tensorboard/image_summaries.ipynb
• site/ja/tensorboard/migrate.ipynb
• site/ja/tensorboard/scalars_and_keras.ipynb
• site/ja/tensorboard/tbdev_getting_started.ipynb
• site/ja/tensorboard/tensorboard_in_notebooks.ipynb
• site/ja/tensorboard/tensorboard_profiling_keras.ipynb
• site/ja/tensorboard/tensorboard_projector_plugin.ipynb
• site/ja/tfx/tutorials/model_analysis/tfma_basic.ipynb
• site/ja/tfx/tutorials/serving/rest_simple.ipynb
• site/ja/tfx/tutorials/tfx/CSV_Downloader_Component.ipynb
• site/ja/tfx/tutorials/tfx/components.ipynb
• site/ja/tfx/tutorials/tfx/components_keras.ipynb
• site/ja/tfx/tutorials/tfx/gcp/vertex_pipelines_bq.ipynb
• site/ja/tfx/tutorials/tfx/gcp/vertex_pipelines_simple.ipynb
• site/ja/tfx/tutorials/tfx/gcp/vertex_pipelines_vertex_training.ipynb
• site/ja/tfx/tutorials/tfx/neural_structured_learning.ipynb
• site/ja/tfx/tutorials/tfx/penguin_simple.ipynb
• site/ja/tfx/tutorials/tfx/penguin_template.ipynb
• site/ja/tfx/tutorials/tfx/penguin_tfdv.ipynb
• site/ja/tfx/tutorials/tfx/penguin_tfma.ipynb
• site/ja/tfx/tutorials/tfx/penguin_transform.ipynb
• site/ja/tfx/tutorials/tfx/python_function_component.ipynb
• site/ja/tfx/tutorials/tfx/recommenders.ipynb
• site/ja/tfx/tutorials/tfx/template.ipynb
• site/ja/tfx/tutorials/tfx/template_beam.ipynb
• site/ja/tfx/tutorials/transform/census.ipynb
• site/ja/tfx/tutorials/transform/simple.ipynb
• site/ja/tutorials/audio/music_generation.ipynb
• site/ja/tutorials/audio/simple_audio.ipynb
• site/ja/tutorials/audio/transfer_learning_audio.ipynb
• site/ja/tutorials/distribute/custom_training.ipynb
• site/ja/tutorials/distribute/dtensor_keras_tutorial.ipynb
• site/ja/tutorials/distribute/dtensor_ml_tutorial.ipynb
• site/ja/tutorials/distribute/input.ipynb
• site/ja/tutorials/distribute/keras.ipynb
• site/ja/tutorials/distribute/multi_worker_with_ctl.ipynb
• site/ja/tutorials/distribute/multi_worker_with_estimator.ipynb
• site/ja/tutorials/distribute/multi_worker_with_keras.ipynb
• site/ja/tutorials/distribute/parameter_server_training.ipynb
• site/ja/tutorials/distribute/save_and_load.ipynb
• site/ja/tutorials/estimator/linear.ipynb
• site/ja/tutorials/generative/adversarial_fgsm.ipynb
• site/ja/tutorials/generative/autoencoder.ipynb
• site/ja/tutorials/generative/cvae.ipynb
• site/ja/tutorials/generative/cyclegan.ipynb
• site/ja/tutorials/generative/dcgan.ipynb
• site/ja/tutorials/generative/deepdream.ipynb
• site/ja/tutorials/generative/pix2pix.ipynb
• site/ja/tutorials/generative/style_transfer.ipynb
• site/ja/tutorials/images/classification.ipynb
• site/ja/tutorials/images/cnn.ipynb
• site/ja/tutorials/images/data_augmentation.ipynb
• site/ja/tutorials/images/segmentation.ipynb
• site/ja/tutorials/images/transfer_learning.ipynb
• site/ja/tutorials/images/transfer_learning_with_hub.ipynb
• site/ja/tutorials/interpretability/integrated_gradients.ipynb
• site/ja/tutorials/keras/keras_tuner.ipynb
• site/ja/tutorials/keras/overfit_and_underfit.ipynb
• site/ja/tutorials/keras/regression.ipynb
• site/ja/tutorials/keras/save_and_load.ipynb
• site/ja/tutorials/keras/text_classification.ipynb
• site/ja/tutorials/keras/text_classification_with_hub.ipynb
• site/ja/tutorials/load_data/csv.ipynb
• site/ja/tutorials/load_data/images.ipynb
• site/ja/tutorials/load_data/numpy.ipynb
• site/ja/tutorials/load_data/text.ipynb
• site/ja/tutorials/load_data/tfrecord.ipynb
• site/ja/tutorials/load_data/video.ipynb
• site/ja/tutorials/quickstart/advanced.ipynb
• site/ja/tutorials/quickstart/beginner.ipynb
• site/ja/tutorials/reinforcement_learning/actor_critic.ipynb
• site/ja/tutorials/structured_data/preprocessing_layers.ipynb
• site/ja/tutorials/structured_data/time_series.ipynb
• site/ja/tutorials/understanding/sngp.ipynb
• site/ja/tutorials/video/transfer_learning_with_movinet.ipynb
• site/ja/tutorials/video/video_classification.ipynb
• site/ja/xla/tutorials/autoclustering_xla.ipynb

Rendered notebook diffs available on ReviewNB.com.

Format and style

Use the TensorFlow docs notebook tools to format for consistent source diffs and lint for style:

$ python3 -m pip install -U --user git+https://github.com/tensorflow/docs

$ python3 -m tensorflow_docs.tools.nbfmt notebook.ipynb

$ python3 -m tensorflow_docs.tools.nblint --arg=repo:tensorflow/docs-l10n \ 
    --styles=tensorflow,tensorflow_docs_l10n notebook.ipynb

If commits are added to the pull request, synchronize your local branch: git pull origin 3afad2270cfa3fdb01193178f334721e4b2b4c3b

[ilyaspiridonov]

Lint warning are License/Copyright (inherited from English counterparts)

[ilyaspiridonov]

@pcoet Can this be merged? There doesn't seem to be anything out of the ordinary here?

[pcoet]

Nothing concerning in the lint errors. They should be on the English side. Nothing concerning in a sanity check of an .md and .ipynb file. LGTM.