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Oct 31, 2019
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更新文档 #463

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98eff9e
删除没重复的文件
jiangzhonglian Oct 31, 2019
41f9a5b
Merge branch 'master' of https://github.com/apachecn/pytorch-doc-zh
jiangzhonglian Oct 31, 2019
ccb8db0
翻译完：使用 TensorBoard 可视化模型，数据和训练
jiangzhonglian Oct 31, 2019
0ab7a4e
修改格式
jiangzhonglian Oct 31, 2019
4cafb9a
更新：在C++ 中加载 TorchScript 模型
jiangzhonglian Oct 31, 2019
f03e272
更新：用 numpy 和 scipy 创建扩展
jiangzhonglian Oct 31, 2019
a13eef2
修改文件名：NLP From Scratch: 基于注意力机制的 seq2seq 神经网络翻译
jiangzhonglian Oct 31, 2019
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9 changes: 8 additions & 1 deletion .gitignore
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Expand Up @@ -106,6 +106,7 @@ _book

# node.js
node_modules
node_modules.zip

# windows
Thumbs.db
Expand All @@ -118,4 +119,10 @@ Thumbs.db
.idea/

# custom
docs/README.md
# docs/README.md
docs/0.2/book.json
docs/0.3/book.json
docs/0.4/book.json
docs/1.0/book.json
docs/1.2/book.json
docs/LatestChanges/book.json
32 changes: 16 additions & 16 deletions docs/1.2/README.md
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Expand Up @@ -41,12 +41,12 @@
* [数据加载和处理教程](beginner/data_loading_tutorial.html)
* [用例子学习 PyTorch](beginner/pytorch_with_examples.html)
* [迁移学习教程](beginner/transfer_learning_tutorial.html)
* [部署与TorchScript一个Seq2Seq模型](beginner/deploy_seq2seq_hybrid_frontend_tutorial.html)
* [可视化模型，数据，和与训练TensorBoard](intermediate/tensorboard_tutorial.html)
* [利用 TorchScript 部署 Seq2Seq 模型](beginner/deploy_seq2seq_hybrid_frontend_tutorial.html)
* [使用 TensorBoard 可视化模型，数据和训练](intermediate/tensorboard_tutorial.html)
* [保存和加载模型](beginner/saving_loading_models.html)
* [torch.nn 到底是什么？](beginner/nn_tutorial.html)
* 图片
* [TorchVision对象检测教程细化和微调](intermediate/torchvision_tutorial.html)
* [TorchVision 对象检测微调教程](intermediate/torchvision_tutorial.html)
* [微调Torchvision模型](beginner/finetuning_torchvision_models_tutorial.html)
* [空间变压器网络教程](intermediate/spatial_transformer_tutorial.html)
* [使用PyTorch进行神经网络传递](advanced/neural_style_tutorial.html)
Expand All @@ -55,27 +55,27 @@
* 音频
* [torchaudio教程](beginner/audio_preprocessing_tutorial.html)
* 文本
* [NLP从头：判断名称与字符级RNN](intermediate/char_rnn_classification_tutorial.html)
* [NLP从头：生成名称与字符级RNN](intermediate/char_rnn_generation_tutorial.html)
* [NLP从无到有：用序列到序列网络和翻译注意](intermediate/seq2seq_translation_tutorial.html)
* [NLP From Scratch: 使用char-RNN对姓氏进行分类](intermediate/char_rnn_classification_tutorial.html)
* [NLP From Scratch: 生成名称与字符级RNN](intermediate/char_rnn_generation_tutorial.html)
* [NLP From Scratch: 基于注意力机制的 seq2seq 神经网络翻译](intermediate/seq2seq_translation_tutorial.html)
* [文本分类与TorchText ](beginner/text_sentiment_ngrams_tutorial.html)
* [语言翻译与TorchText ](beginner/torchtext_translation_tutorial.html)
* [序列到序列与nn.Transformer和TorchText建模](beginner/transformer_tutorial.html)
* 强化学习
* [强化学习（DQN）教程](intermediate/reinforcement_q_learning.html)
* 在生产部署PyTorch模型
* [1.部署PyTorch在Python经由REST API从Flask](intermediate/flask_rest_api_tutorial.html)
* [2.介绍TorchScript](beginner/Intro_to_TorchScript_tutorial.html)
* [3.装载++一个TorchScript模型在C ](advanced/cpp_export.html)
* [4.（可选）从导出到PyTorch一个ONNX模型并使用ONNX运行时运行它](advanced/super_resolution_with_onnxruntime.html)
* [部署PyTorch在Python经由REST API从Flask](intermediate/flask_rest_api_tutorial.html)
* [介绍TorchScript](beginner/Intro_to_TorchScript_tutorial.html)
* [在C ++中加载TorchScript模型 ](advanced/cpp_export.html)
* [（可选）将模型从PyTorch导出到ONNX并使用ONNX Runtime运行 ](advanced/super_resolution_with_onnxruntime.html)
* 并行和分布式训练
* [1.型号并行最佳实践](intermediate/model_parallel_tutorial.html)
* [2.入门分布式数据并行](intermediate/ddp_tutorial.html)
* [3. PyTorch编写分布式应用](intermediate/dist_tuto.html)
* [4.（高级）PyTorch 1.0分布式训练与Amazon AWS](beginner/aws_distributed_training_tutorial.html)
* [模型并行化最佳实践](intermediate/model_parallel_tutorial.html)
* [入门分布式数据并行](intermediate/ddp_tutorial.html)
* [PyTorch编写分布式应用](intermediate/dist_tuto.html)
* [（高级）PyTorch 1.0分布式训练与Amazon AWS](beginner/aws_distributed_training_tutorial.html)
* 扩展PyTorch
* [使用自定义 C++ 扩展算TorchScript ](advanced/torch_script_custom_ops.html)
* [创建扩展使用numpy的和SciPy的](advanced/numpy_extensions_tutorial.html)
* [用 numpy 和 scipy 创建扩展](advanced/numpy_extensions_tutorial.html)
* [自定义 C++ 和CUDA扩展](advanced/cpp_extension.html)
* PyTorch在其他语言
* [使用PyTorch C++ 前端](advanced/cpp_frontend.html)
Expand All @@ -95,7 +95,7 @@
* 社区
* [PyTorch贡献说明书](community/contribution_guide.html)
* [PyTorch治理](community/governance.html)
* [PyTorch治理 | 感兴趣的人](community/persons_of_interest.html)
* [PyTorch治理感兴趣的人](community/persons_of_interest.html)
* 封装参考文献
* [torch](torch.html)
* [torch.Tensor](tensors.html)
Expand Down
38 changes: 19 additions & 19 deletions docs/1.2/SUMMARY.md
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Expand Up @@ -12,12 +12,12 @@
* [数据加载和处理教程](beginner/data_loading_tutorial.md)
* [用例子学习 PyTorch](beginner/pytorch_with_examples.md)
* [迁移学习教程](beginner/transfer_learning_tutorial.md)
* [部署与TorchScript一个Seq2Seq模型](beginner/deploy_seq2seq_hybrid_frontend_tutorial.md)
* [可视化模型，数据，和与训练TensorBoard](intermediate/tensorboard_tutorial.md)
* [利用 TorchScript 部署 Seq2Seq 模型](beginner/deploy_seq2seq_hybrid_frontend_tutorial.md)
* [使用 TensorBoard 可视化模型，数据和训练](intermediate/tensorboard_tutorial.md)
* [保存和加载模型](beginner/saving_loading_models.md)
* [torch.nn 到底是什么？](beginner/nn_tutorial.md)
* 图片
* [TorchVision对象检测教程细化和微调](intermediate/torchvision_tutorial.md)
* [TorchVision 对象检测微调教程](intermediate/torchvision_tutorial.md)
* [微调Torchvision模型](beginner/finetuning_torchvision_models_tutorial.md)
* [空间变压器网络教程](intermediate/spatial_transformer_tutorial.md)
* [使用PyTorch进行神经网络传递](advanced/neural_style_tutorial.md)
Expand All @@ -26,27 +26,27 @@
* 音频
* [torchaudio教程](beginner/audio_preprocessing_tutorial.md)
* 文本
* [NLP从头：判断名称与字符级RNN](intermediate/char_rnn_classification_tutorial.md)
* [NLP从头：生成名称与字符级RNN](intermediate/char_rnn_generation_tutorial.md)
* [NLP从无到有：用序列到序列网络和翻译注意](intermediate/seq2seq_translation_tutorial.md)
* [文本分类与TorchText ](beginner/text_sentiment_ngrams_tutorial.md)
* [语言翻译与TorchText ](beginner/torchtext_translation_tutorial.md)
* [NLP From Scratch: 使用char-RNN对姓氏进行分类](intermediate/char_rnn_classification_tutorial.md)
* [NLP From Scratch: 生成名称与字符级RNN](intermediate/char_rnn_generation_tutorial.md)
* [NLP From Scratch: 基于注意力机制的 seq2seq 神经网络翻译](intermediate/seq2seq_translation_tutorial.md)
* [文本分类与TorchText](beginner/text_sentiment_ngrams_tutorial.md)
* [语言翻译与TorchText](beginner/torchtext_translation_tutorial.md)
* [序列到序列与nn.Transformer和TorchText建模](beginner/transformer_tutorial.md)
*
* 强化学习
* [强化学习（DQN）教程](intermediate/reinforcement_q_learning.md)
* 在生产部署PyTorch模型
* [1.部署PyTorch在Python经由REST API从Flask](intermediate/flask_rest_api_tutorial.md)
* [2.介绍TorchScript](beginner/Intro_to_TorchScript_tutorial.md)
* [3.装载++一个TorchScript模型在C ](advanced/cpp_export.md)
* [4.（可选）从导出到PyTorch一个ONNX模型并使用ONNX运行时运行它](advanced/super_resolution_with_onnxruntime.md)
* [部署PyTorch在Python经由REST API从Flask](intermediate/flask_rest_api_tutorial.md)
* [介绍TorchScript](beginner/Intro_to_TorchScript_tutorial.md)
* [在C ++中加载TorchScript模型 ](advanced/cpp_export.md)
* [（可选）将模型从PyTorch导出到ONNX并使用ONNX Runtime运行 ](advanced/super_resolution_with_onnxruntime.md)
* 并行和分布式训练
* [1.型号并行最佳实践](intermediate/model_parallel_tutorial.md)
* [2.入门分布式数据并行](intermediate/ddp_tutorial.md)
* [3. PyTorch编写分布式应用](intermediate/dist_tuto.md)
* [4.（高级）PyTorch 1.0分布式训练与Amazon AWS](beginner/aws_distributed_training_tutorial.md)
* [模型并行化最佳实践](intermediate/model_parallel_tutorial.md)
* [入门分布式数据并行](intermediate/ddp_tutorial.md)
* [PyTorch编写分布式应用](intermediate/dist_tuto.md)
* [（高级）PyTorch 1.0分布式训练与Amazon AWS](beginner/aws_distributed_training_tutorial.md)
* 扩展PyTorch
* [使用自定义 C++ 扩展算TorchScript ](advanced/torch_script_custom_ops.md)
* [创建扩展使用numpy的和SciPy的](advanced/numpy_extensions_tutorial.md)
* [用 numpy 和 scipy 创建扩展](advanced/numpy_extensions_tutorial.md)
* [自定义 C++ 和CUDA扩展](advanced/cpp_extension.md)
* PyTorch在其他语言
* [使用PyTorch C++ 前端](advanced/cpp_frontend.md)
Expand All @@ -66,7 +66,7 @@
* 社区
* [PyTorch贡献说明书](community/contribution_guide.md)
* [PyTorch治理](community/governance.md)
* [PyTorch治理 | 感兴趣的人](community/persons_of_interest.md)
* [PyTorch治理感兴趣的人](community/persons_of_interest.md)
* 封装参考文献
* [torch](torch.md)
* [torch.Tensor](tensors.md)
Expand Down
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