diff --git a/SUMMARY.md b/SUMMARY.md index a26d406d43547681eeedb683469b4122b4482277..e7ab7b481f24f161e86f638ea8460dbb26b32b0e 100644 --- a/SUMMARY.md +++ b/SUMMARY.md @@ -1,10 +1,431 @@ # Summary -* [Introduction](README.md) -* [PyTorch 1.7 中文文档 & 教程](https://pytorch.apachecn.org/docs/1.7/) -* [PyTorch 1.4 中文文档 & 教程](https://pytorch.apachecn.org/docs/1.4/) -* [PyTorch 1.0 中文文档 & 教程](https://pytorch.apachecn.org/docs/1.0/) -* [PyTorch 0.3 中文文档 & 教程](https://pytorch.apachecn.org/docs/0.3/) -* [PyTorch 0.2 中文文档](https://pytorch.apachecn.org/docs/0.2/) -* [PyTorch 英文文档](https://pytorch.org/docs/) -* [PyTorch 英文教程](https://pytorch.org/tutorials/) ++ [PyTorch 中文教程 & 文档](README.md) ++ [PyTorch 中文官方教程 1.7](docs/1.7/README.md) + + [学习 PyTorch](docs/1.7/01.md) + + [PyTorch 深度学习：60 分钟的突击](docs/1.7/02.md) + + [张量](docs/1.7/03.md) + + [`torch.autograd`的简要介绍](docs/1.7/04.md) + + [神经网络](docs/1.7/05.md) + + [训练分类器](docs/1.7/06.md) + + [通过示例学习 PyTorch](docs/1.7/07.md) + + [热身：NumPy](docs/1.7/08.md) + + [PyTorch：张量](docs/1.7/09.md) + + [PyTorch：张量和 Autograd](docs/1.7/10.md) + + [PyTorch：定义新的 Autograd 函数](docs/1.7/11.md) + + [PyTorch：`nn`](docs/1.7/12.md) + + [PyTorch：`optim`](docs/1.7/13.md) + + [PyTorch：自定义`nn`模块](docs/1.7/14.md) + + [PyTorch：控制流 + 权重共享](docs/1.7/15.md) + + [`torch.nn`到底是什么？](docs/1.7/16.md) + + [使用 TensorBoard 可视化模型，数据和训练](docs/1.7/17.md) + + [图片/视频](docs/1.7/18.md) + + [`torchvision`对象检测微调教程](docs/1.7/19.md) + + [计算机视觉的迁移学习教程](docs/1.7/20.md) + + [对抗示例生成](docs/1.7/21.md) + + [DCGAN 教程](docs/1.7/22.md) + + [音频](docs/1.7/23.md) + + [音频 I/O 和`torchaudio`的预处理](docs/1.7/24.md) + + [使用`torchaudio`的语音命令识别](docs/1.7/25.md) + + [文本](docs/1.7/26.md) + + [使用`nn.Transformer`和`torchtext`的序列到序列建模](docs/1.7/27.md) + + [从零开始的 NLP：使用字符级 RNN 分类名称](docs/1.7/28.md) + + [从零开始的 NLP：使用字符级 RNN 生成名称](docs/1.7/29.md) + + [从零开始的 NLP：使用序列到序列网络和注意力的翻译](docs/1.7/30.md) + + [使用`torchtext`的文本分类](docs/1.7/31.md) + + [`torchtext`语言翻译](docs/1.7/32.md) + + [强化学习](docs/1.7/33.md) + + [强化学习（DQN）教程](docs/1.7/34.md) + + [训练玩马里奥的 RL 智能体](docs/1.7/35.md) + + [在生产中部署 PyTorch 模型](docs/1.7/36.md) + + [通过使用 Flask 的 REST API 在 Python 中部署 PyTorch](docs/1.7/37.md) + + [TorchScript 简介](docs/1.7/38.md) + + [在 C++ 中加载 TorchScript 模型](docs/1.7/39.md) + + [将模型从 PyTorch 导出到 ONNX 并使用 ONNX 运行时运行它（可选）](docs/1.7/40.md) + + [前端 API](docs/1.7/41.md) + + [PyTorch 中的命名张量简介（原型）](docs/1.7/42.md) + + [PyTorch 中通道在最后的内存格式（beta）](docs/1.7/43.md) + + [使用 PyTorch C++ 前端](docs/1.7/44.md) + + [自定义 C++ 和 CUDA 扩展](docs/1.7/45.md) + + [使用自定义 C++ 运算符扩展 TorchScript](docs/1.7/46.md) + + [使用自定义 C++ 类扩展 TorchScript](docs/1.7/47.md) + + [TorchScript 中的动态并行性](docs/1.7/48.md) + + [C++ 前端中的 Autograd](docs/1.7/49.md) + + [在 C++ 中注册调度运算符](docs/1.7/50.md) + + [模型优化](docs/1.7/51.md) + + [分析您的 PyTorch 模块](docs/1.7/52.md) + + [使用 Ray Tune 的超参数调整](docs/1.7/53.md) + + [模型剪裁教程](docs/1.7/54.md) + + [LSTM 单词语言模型上的动态量化（beta）](docs/1.7/55.md) + + [BERT 上的动态量化（Beta）](docs/1.7/56.md) + + [PyTorch 中使用 Eager 模式的静态量化（beta）](docs/1.7/57.md) + + [计算机视觉的量化迁移学习教程（beta）](docs/1.7/58.md) + + [并行和分布式训练](docs/1.7/59.md) + + [PyTorch 分布式概述](docs/1.7/60.md) + + [单机模型并行最佳实践](docs/1.7/61.md) + + [分布式数据并行入门](docs/1.7/62.md) + + [用 PyTorch 编写分布式应用](docs/1.7/63.md) + + [分布式 RPC 框架入门](docs/1.7/64.md) + + [使用分布式 RPC 框架实现参数服务器](docs/1.7/65.md) + + [使用 RPC 的分布式管道并行化](docs/1.7/66.md) + + [使用异步执行实现批量 RPC 处理](docs/1.7/67.md) + + [将分布式`DataParallel`与分布式 RPC 框架相结合](docs/1.7/68.md) ++ [PyTorch 1.4 教程&文档](docs/1.4/README.md) + + 入门 + + [使用 PyTorch 进行深度学习：60 分钟的闪电战](docs/1.4/4.md) + + [什么是PyTorch？](docs/1.4/blitz/tensor_tutorial.md) + + [Autograd：自动求导](docs/1.4/blitz/autograd_tutorial.md) + + [神经网络](docs/1.4/blitz/neural_networks_tutorial.md) + + [训练分类器](docs/1.4/blitz/cifar10_tutorial.md) + + [可选：数据并行](docs/1.4/blitz/data_parallel_tutorial.md) + + [编写自定义数据集，数据加载器和转换](docs/1.4/5.md) + + [使用 TensorBoard 可视化模型，数据和训练](docs/1.4/6.md) + + 图片 + + [TorchVision 对象检测微调教程](docs/1.4/8.md) + + [转移学习的计算机视觉教程](docs/1.4/9.md) + + [空间变压器网络教程](docs/1.4/10.md) + + [使用 PyTorch 进行神经传递](docs/1.4/11.md) + + [对抗示例生成](docs/1.4/12.md) + + [DCGAN 教程](docs/1.4/13.md) + + 音频 + + [torchaudio 教程](docs/1.4/15.md) + + 文本 + + [NLP From Scratch: 使用char-RNN对姓氏进行分类](docs/1.4/17.md) + + [NLP From Scratch: 生成名称与字符级RNN](docs/1.4/18.md) + + [NLP From Scratch: 基于注意力机制的 seq2seq 神经网络翻译](docs/1.4/19.md) + + [使用 TorchText 进行文本分类](docs/1.4/20.md) + + [使用 TorchText 进行语言翻译](docs/1.4/21.md) + + [使用 nn.Transformer 和 TorchText 进行序列到序列建模](docs/1.4/22.md) + + 命名为 Tensor(实验性） + + [(实验性）PyTorch 中的命名张量简介](docs/1.4/24.md) + + 强化学习 + + [强化学习(DQN）教程](docs/1.4/26.md) + + 在生产中部署 PyTorch 模型 + + [通过带有 Flask 的 REST API 在 Python 中部署 PyTorch](docs/1.4/28.md) + + [TorchScript 简介](docs/1.4/29.md) + + [在 C ++中加载 TorchScript 模型](docs/1.4/30.md) + + [(可选）将模型从 PyTorch 导出到 ONNX 并使用 ONNX Runtime 运行](docs/1.4/31.md) + + 并行和分布式训练 + + [单机模型并行最佳实践](docs/1.4/33.md) + + [分布式数据并行入门](docs/1.4/34.md) + + [用 PyTorch 编写分布式应用程序](docs/1.4/35.md) + + [分布式 RPC 框架入门](docs/1.4/36.md) + + [(高级）带有 Amazon AWS 的 PyTorch 1.0 分布式训练师](docs/1.4/37.md) + + 扩展 PyTorch + + [使用自定义 C ++运算符扩展 TorchScript](docs/1.4/39.md) + + [使用自定义 C ++类扩展 TorchScript](docs/1.4/40.md) + + [使用 numpy 和 scipy 创建扩展](docs/1.4/41.md) + + [自定义 C ++和 CUDA 扩展](docs/1.4/42.md) + + 模型优化 + + [LSTM Word 语言模型上的(实验）动态量化](docs/1.4/44.md) + + [(实验性）在 PyTorch 中使用 Eager 模式进行静态量化](docs/1.4/45.md) + + [(实验性）计算机视觉教程的量化转移学习](docs/1.4/46.md) + + [(实验）BERT 上的动态量化](docs/1.4/47.md) + + [修剪教程](docs/1.4/48.md) + + PyTorch 用其他语言 + + [使用 PyTorch C ++前端](docs/1.4/50.md) + + PyTorch 基础知识 + + [通过示例学习 PyTorch](docs/1.4/52.md) + + [torch.nn 到底是什么？](docs/1.4/53.md) + + 文件 + + 笔记 + + [自动求导机制](docs/1.4/56.md) + + [广播语义](docs/1.4/57.md) + + [CPU 线程和 TorchScript 推断](docs/1.4/58.md) + + [CUDA 语义](docs/1.4/59.md) + + [分布式 Autograd 设计](docs/1.4/60.md) + + [扩展 PyTorch](docs/1.4/61.md) + + [经常问的问题](docs/1.4/62.md) + + [大规模部署的功能](docs/1.4/63.md) + + [并行处理最佳实践](docs/1.4/64.md) + + [重现性](docs/1.4/65.md) + + [远程参考协议](docs/1.4/66.md) + + [序列化语义](docs/1.4/67.md) + + [Windows 常见问题](docs/1.4/68.md) + + [XLA 设备上的 PyTorch](docs/1.4/69.md) + + 语言绑定 + + [PyTorch C ++ API](docs/1.4/71.md) + + [PyTorch Java API](docs/1.4/72.md) + + Python API + + [torch](docs/1.4/74.md) + + [torch.nn](docs/1.4/75.md) + + [torch功能](docs/1.4/76.md) + + [torch张量](docs/1.4/77.md) + + [张量属性](docs/1.4/78.md) + + [自动差分包-Torch.Autograd](docs/1.4/79.md) + + [torch.cuda](docs/1.4/80.md) + + [分布式通讯包-Torch.Distributed](docs/1.4/81.md) + + [概率分布-torch分布](docs/1.4/82.md) + + [torch.hub](docs/1.4/83.md) + + [torch脚本](docs/1.4/84.md) + + [torch.nn.init](docs/1.4/85.md) + + [torch.onnx](docs/1.4/86.md) + + [torch.optim](docs/1.4/87.md) + + [量化](docs/1.4/88.md) + + [分布式 RPC 框架](docs/1.4/89.md) + + [torch随机](docs/1.4/90.md) + + [torch稀疏](docs/1.4/91.md) + + [torch存储](docs/1.4/92.md) + + [torch.utils.bottleneck](docs/1.4/93.md) + + [torch.utils.checkpoint](docs/1.4/94.md) + + [torch.utils.cpp_extension](docs/1.4/95.md) + + [torch.utils.data](docs/1.4/96.md) + + [torch.utils.dlpack](docs/1.4/97.md) + + [torch.utils.model_zoo](docs/1.4/98.md) + + [torch.utils.tensorboard](docs/1.4/99.md) + + [类型信息](docs/1.4/100.md) + + [命名张量](docs/1.4/101.md) + + [命名为 Tensors 操作员范围](docs/1.4/102.md) + + [糟糕！](docs/1.4/103.md) + + torchvision参考 + + [torchvision](docs/1.4/105.md) + + 音频参考 + + [torchaudio](docs/1.4/107.md) + + torchtext参考 + + [torchtext](docs/1.4/109.md) + + 社区 + + [PyTorch 贡献指南](docs/1.4/111.md) + + [PyTorch 治理](docs/1.4/112.md) + + [PyTorch 治理| 感兴趣的人](docs/1.4/113.md) ++ [PyTorch 1.0 中文文档](docs/1.0/README.md) + + 中文教程 + + [起步](docs/1.0/tut_getting_started.md) + + [PyTorch 深度学习: 60 分钟极速入门](docs/1.0/deep_learning_60min_blitz.md) + + [什么是 PyTorch？](docs/1.0/blitz_tensor_tutorial.md) + + [Autograd：自动求导](docs/1.0/blitz_autograd_tutorial.md) + + [神经网络](docs/1.0/blitz_neural_networks_tutorial.md) + + [训练分类器](docs/1.0/blitz_cifar10_tutorial.md) + + [可选：数据并行处理](docs/1.0/blitz_data_parallel_tutorial.md) + + [数据加载和处理教程](docs/1.0/data_loading_tutorial.md) + + [用例子学习 PyTorch](docs/1.0/pytorch_with_examples.md) + + [迁移学习教程](docs/1.0/transfer_learning_tutorial.md) + + [混合前端的 seq2seq 模型部署](docs/1.0/deploy_seq2seq_hybrid_frontend_tutorial.md) + + [Saving and Loading Models](docs/1.0/saving_loading_models.md) + + [What is torch.nn really?](docs/1.0/nn_tutorial.md) + + [图像](docs/1.0/tut_image.md) + + [Torchvision 模型微调](docs/1.0/finetuning_torchvision_models_tutorial.md) + + [空间变换器网络教程](docs/1.0/spatial_transformer_tutorial.md) + + [使用 PyTorch 进行图像风格转换](docs/1.0/neural_style_tutorial.md) + + [对抗性示例生成](docs/1.0/fgsm_tutorial.md) + + [使用 ONNX 将模型从 PyTorch 传输到 Caffe2 和移动端](docs/1.0/super_resolution_with_caffe2.md) + + [文本](docs/1.0/tut_text.md) + + [聊天机器人教程](docs/1.0/chatbot_tutorial.md) + + [使用字符级别特征的 RNN 网络生成姓氏](docs/1.0/char_rnn_generation_tutorial.md) + + [使用字符级别特征的 RNN 网络进行姓氏分类](docs/1.0/char_rnn_classification_tutorial.md) + + [Deep Learning for NLP with Pytorch](docs/1.0/deep_learning_nlp_tutorial.md) + + [PyTorch 介绍](docs/1.0/nlp_pytorch_tutorial.md) + + [使用 PyTorch 进行深度学习](docs/1.0/nlp_deep_learning_tutorial.md) + + [Word Embeddings: Encoding Lexical Semantics](docs/1.0/nlp_word_embeddings_tutorial.md) + + [序列模型和 LSTM 网络](docs/1.0/nlp_sequence_models_tutorial.md) + + [Advanced: Making Dynamic Decisions and the Bi-LSTM CRF](docs/1.0/nlp_advanced_tutorial.md) + + [基于注意力机制的 seq2seq 神经网络翻译](docs/1.0/seq2seq_translation_tutorial.md) + + [生成](docs/1.0/tut_generative.md) + + [DCGAN Tutorial](docs/1.0/dcgan_faces_tutorial.md) + + [强化学习](docs/1.0/tut_reinforcement_learning.md) + + [Reinforcement Learning (DQN) Tutorial](docs/1.0/reinforcement_q_learning.md) + + [扩展 PyTorch](docs/1.0/tut_extending_pytorch.md) + + [用 numpy 和 scipy 创建扩展](docs/1.0/numpy_extensions_tutorial.md) + + [Custom C++ and CUDA Extensions](docs/1.0/cpp_extension.md) + + [Extending TorchScript with Custom C++ Operators](docs/1.0/torch_script_custom_ops.md) + + [生产性使用](docs/1.0/tut_production_usage.md) + + [Writing Distributed Applications with PyTorch](docs/1.0/dist_tuto.md) + + [使用 Amazon AWS 进行分布式训练](docs/1.0/aws_distributed_training_tutorial.md) + + [ONNX 现场演示教程](docs/1.0/ONNXLive.md) + + [在 C++ 中加载 PYTORCH 模型](docs/1.0/cpp_export.md) + + [其它语言中的 PyTorch](docs/1.0/tut_other_language.md) + + [使用 PyTorch C++ 前端](docs/1.0/cpp_frontend.md) + + 中文文档 + + [注解](docs/1.0/docs_notes.md) + + [自动求导机制](docs/1.0/notes_autograd.md) + + [广播语义](docs/1.0/notes_broadcasting.md) + + [CUDA 语义](docs/1.0/notes_cuda.md) + + [Extending PyTorch](docs/1.0/notes_extending.md) + + [Frequently Asked Questions](docs/1.0/notes_faq.md) + + [Multiprocessing best practices](docs/1.0/notes_multiprocessing.md) + + [Reproducibility](docs/1.0/notes_randomness.md) + + [Serialization semantics](docs/1.0/notes_serialization.md) + + [Windows FAQ](docs/1.0/notes_windows.md) + + [包参考](docs/1.0/docs_package_ref.md) + + [torch](docs/1.0/torch.md) + + [Tensors](docs/1.0/torch_tensors.md) + + [Random sampling](docs/1.0/torch_random_sampling.md) + + [Serialization, Parallelism, Utilities](docs/1.0/torch_serialization_parallelism_utilities.md) + + [Math operations](docs/1.0/torch_math_operations.md) + + [Pointwise Ops](docs/1.0/torch_math_operations_pointwise_ops.md) + + [Reduction Ops](docs/1.0/torch_math_operations_reduction_ops.md) + + [Comparison Ops](docs/1.0/torch_math_operations_comparison_ops.md) + + [Spectral Ops](docs/1.0/torch_math_operations_spectral_ops.md) + + [Other Operations](docs/1.0/torch_math_operations_other_ops.md) + + [BLAS and LAPACK Operations](docs/1.0/torch_math_operations_blas_lapack_ops.md) + + [torch.Tensor](docs/1.0/tensors.md) + + [Tensor Attributes](docs/1.0/tensor_attributes.md) + + [数据类型信息](docs/1.0/type_info.md) + + [torch.sparse](docs/1.0/sparse.md) + + [torch.cuda](docs/1.0/cuda.md) + + [torch.Storage](docs/1.0/storage.md) + + [torch.nn](docs/1.0/nn.md) + + [torch.nn.functional](docs/1.0/nn_functional.md) + + [torch.nn.init](docs/1.0/nn_init.md) + + [torch.optim](docs/1.0/optim.md) + + [Automatic differentiation package - torch.autograd](docs/1.0/autograd.md) + + [Distributed communication package - torch.distributed](docs/1.0/distributed.md) + + [Probability distributions - torch.distributions](docs/1.0/distributions.md) + + [Torch Script](docs/1.0/jit.md) + + [多进程包 - torch.multiprocessing](docs/1.0/multiprocessing.md) + + [torch.utils.bottleneck](docs/1.0/bottleneck.md) + + [torch.utils.checkpoint](docs/1.0/checkpoint.md) + + [torch.utils.cpp_extension](docs/1.0/docs_cpp_extension.md) + + [torch.utils.data](docs/1.0/data.md) + + [torch.utils.dlpack](docs/1.0/dlpack.md) + + [torch.hub](docs/1.0/hub.md) + + [torch.utils.model_zoo](docs/1.0/model_zoo.md) + + [torch.onnx](docs/1.0/onnx.md) + + [Distributed communication package (deprecated) - torch.distributed.deprecated](docs/1.0/distributed_deprecated.md) + + [torchvision 参考](docs/1.0/docs_torchvision_ref.md) + + [torchvision.datasets](docs/1.0/torchvision_datasets.md) + + [torchvision.models](docs/1.0/torchvision_models.md) + + [torchvision.transforms](docs/1.0/torchvision_transforms.md) + + [torchvision.utils](docs/1.0/torchvision_utils.md) ++ [PyTorch 0.4 中文文档](docs/0.4/README.md) + + [笔记](docs/0.4/0.md) + + [自动求导机制](docs/0.4/1.md) + + [Torch](docs/0.4/10.md) + + [torch.Tensor](docs/0.4/11.md) + + [Tensor Attributes](docs/0.4/12.md) + + [torch.sparse](docs/0.4/13.md) + + [torch.cuda](docs/0.4/14.md) + + [torch.Storage](docs/0.4/15.md) + + [torch.nn](docs/0.4/16.md) + + [torch.nn.functional](docs/0.4/17.md) + + [自动差异化包 - torch.autograd](docs/0.4/18.md) + + [torch.optim](docs/0.4/19.md) + + [广播语义](docs/0.4/2.md) + + [torch.nn.init](docs/0.4/20.md) + + [torch.distributions](docs/0.4/21.md) + + [Multiprocessing 包 - torch.multiprocessing](docs/0.4/22.md) + + [分布式通讯包 - torch.distributed](docs/0.4/23.md) + + [torch.utils.bottleneck](docs/0.4/24.md) + + [torch.utils.checkpoint](docs/0.4/25.md) + + [torch.utils.cpp_extension](docs/0.4/26.md) + + [torch.utils.data](docs/0.4/27.md) + + [torch.utils.ffi](docs/0.4/28.md) + + [torch.utils.model_zoo](docs/0.4/29.md) + + [CUDA 语义](docs/0.4/3.md) + + [torch.onnx](docs/0.4/30.md) + + [遗留包 - torch.legacy](docs/0.4/31.md) + + [torchvision 参考](docs/0.4/32.md) + + [torchvision](docs/0.4/33.md) + + [torchvision.datasets](docs/0.4/34.md) + + [torchvision.models](docs/0.4/35.md) + + [torchvision.transform](docs/0.4/36.md) + + [torchvision.utils](docs/0.4/37.md) + + [扩展 PyTorch](docs/0.4/4.md) + + [常见问题](docs/0.4/5.md) + + [多进程最佳实践](docs/0.4/6.md) + + [序列化语义](docs/0.4/7.md) + + [Windows 常见问题](docs/0.4/8.md) + + [包参考](docs/0.4/9.md) ++ [PyTorch 0.3 中文文档 & 教程](docs/0.3/README.md) + + [中文教程](docs/0.3/tut.md) + + [初学者教程](docs/0.3/beginner_tutorials.md) + + [PyTorch 深度学习: 60 分钟极速入门教程](docs/0.3/deep_learning_60min_blitz.md) + + [PyTorch 是什么？](docs/0.3/blitz_tensor_tutorial.md) + + [自动求导: 自动微分](docs/0.3/blitz_autograd_tutorial.md) + + [神经网络](docs/0.3/blitz_neural_networks_tutorial.md) + + [训练一个分类器](docs/0.3/blitz_cifar10_tutorial.md) + + [可选: 数据并行](docs/0.3/blitz_data_parallel_tutorial.md) + + [PyTorch for former Torch users](docs/0.3/former_torchies_tutorial.md) + + [Tensors](docs/0.3/former_torchies_tensor_tutorial.md) + + [Autograd (自动求导)](docs/0.3/former_torchies_autograd_tutorial.md) + + [nn package](docs/0.3/former_torchies_nn_tutorial.md) + + [Multi-GPU examples](docs/0.3/former_torchies_parallelism_tutorial.md) + + [跟着例子学习 PyTorch](docs/0.3/pytorch_with_examples.md) + + [Warm-up: numpy](docs/0.3/pytorch_with_examples_warm-up-numpy.md) + + [PyTorch: Tensors](docs/0.3/pytorch_with_examples_pytorch-tensors.md) + + [PyTorch: 变量和autograd](docs/0.3/pytorch_with_examples_pytorch-variables-and-autograd.md) + + [PyTorch: 定义新的autograd函数](docs/0.3/pytorch_with_examples_pytorch-defining-new-autograd-functions.md) + + [TensorFlow: 静态图](docs/0.3/pytorch_with_examples_tensorflow-static-graphs.md) + + [PyTorch: nn包](docs/0.3/pytorch_with_examples_pytorch-nn.md) + + [PyTorch: optim包](docs/0.3/pytorch_with_examples_pytorch-optim.md) + + [PyTorch: 定制化nn模块](docs/0.3/pytorch_with_examples_pytorch-custom-nn-modules.md) + + [PyTorch: 动态控制流程 + 权重共享](docs/0.3/pytorch_with_examples_pytorch-control-flow-weight-sharing.md) + + [迁移学习教程](docs/0.3/transfer_learning_tutorial.md) + + [数据加载和处理教程](docs/0.3/data_loading_tutorial.md) + + [针对NLP的Pytorch深度学习](docs/0.3/deep_learning_nlp_tutorial.md) + + [PyTorch介绍](docs/0.3/nlp_pytorch_tutorial.md) + + [PyTorch深度学习](docs/0.3/nlp_deep_learning_tutorial.md) + + [词汇嵌入:编码词汇语义](docs/0.3/nlp_word_embeddings_tutorial.md) + + [序列模型和 LSTM 网络(长短记忆网络）](docs/0.3/nlp_sequence_models_tutorial.md) + + [高级教程: 作出动态决策和 Bi-LSTM CRF](docs/0.3/nlp_advanced_tutorial.md) + + [中级教程](docs/0.3/intermediate_tutorials.md) + + [用字符级RNN分类名称](docs/0.3/char_rnn_classification_tutorial.md) + + [基与字符级RNN(Char-RNN）的人名生成](docs/0.3/char_rnn_generation_tutorial.md) + + [用基于注意力机制的seq2seq神经网络进行翻译](docs/0.3/seq2seq_translation_tutorial.md) + + [强化学习(DQN）教程](docs/0.3/reinforcement_q_learning.md) + + [Writing Distributed Applications with PyTorch](docs/0.3/dist_tuto.md) + + [空间转换网络 (Spatial Transformer Networks) 教程](docs/0.3/spatial_transformer_tutorial.md) + + [高级教程](docs/0.3/advanced_tutorials.md) + + [用 PyTorch 做 神经转换 (Neural Transfer)](docs/0.3/neural_style_tutorial.md) + + [使用 numpy 和 scipy 创建扩展](docs/0.3/numpy_extensions_tutorial.md) + + [使用 ONNX 将模型从 PyTorch 迁移到 Caffe2 和 Mobile](docs/0.3/super_resolution_with_caffe2.md) + + [为 pytorch 自定义 C 扩展](docs/0.3/c_extension.md) + + [中文文档](docs/0.3/doc.md) + + [介绍](docs/0.3/notes.md) + + [自动求导机制](docs/0.3/notes_autograd.md) + + [广播语义](docs/0.3/notes_broadcasting.md) + + [CUDA 语义](docs/0.3/notes_cuda.md) + + [扩展 PyTorch](docs/0.3/notes_extending.md) + + [多进程的最佳实践](docs/0.3/notes_multiprocessing.md) + + [序列化语义](docs/0.3/notes_serialization.md) + + [Package 参考](docs/0.3/package_reference.md) + + [torch](docs/0.3/torch.md) + + [torch.Tensor](docs/0.3/tensors.md) + + [torch.sparse](docs/0.3/sparse.md) + + [torch.Storage](docs/0.3/storage.md) + + [torch.nn](docs/0.3/nn.md) + + [torch.optim](docs/0.3/optim.md) + + [Automatic differentiation package - torch.autograd](docs/0.3/autograd.md) + + [Probability distributions - torch.distributions](docs/0.3/distributions.md) + + [Multiprocessing package - torch.multiprocessing](docs/0.3/multiprocessing.md) + + [Distributed communication package - torch.distributed](docs/0.3/distributed.md) + + [Legacy package - torch.legacy](docs/0.3/legacy.md) + + [torch.cuda](docs/0.3/cuda.md) + + [torch.utils.ffi](docs/0.3/ffi.md) + + [torch.utils.data](docs/0.3/data.md) + + [torch.utils.model_zoo](docs/0.3/model_zoo.md) + + [torch.onnx](docs/0.3/onnx.md) + + [torchvision 参考](docs/0.3/torchvision_reference.md) + + [torchvision](docs/0.3/torchvision.md) + + [torchvision.datasets](docs/0.3/datasets.md) + + [torchvision.models](docs/0.3/models.md) + + [torchvision.transforms](docs/0.3/transforms.md) + + [torchvision.utils](docs/0.3/utils.md) ++ [PyTorch 0.2 中文文档](docs/0.2/README.md) + + 说明 + + [自动求导机制](docs/0.2/notes/autograd.md) + + [CUDA语义](docs/0.2/notes/cuda.md) + + [扩展PyTorch](docs/0.2/notes/extending.md) + + [多进程最佳实践](docs/0.2/notes/multiprocessing.md) + + [序列化语义](docs/0.2/notes/serialization.md) + + PACKAGE参考 + + [torch](docs/0.2/package_references/torch.md) + + [torch.Tensor](docs/0.2/package_references/Tensor.md) + + [torch.Storage](docs/0.2/package_references/Storage.md) + + [torch.nn](docs/0.2/package_references/torch-nn.md) + + [torch.nn.functional](docs/0.2/package_references/functional.md) + + [torch.autograd](docs/0.2/package_references/torch-autograd.md) + + [torch.optim](docs/0.2/package_references/torch-optim.md) + + [torch.nn.init](docs/0.2/package_references/nn_init.md) + + [torch.multiprocessing](docs/0.2/package_references/torch-multiprocessing.md) + + [torch.legacy](docs/0.2/package_references/legacy.md) + + [torch.cuda](docs/0.2/package_references/torch-cuda.md) + + [torch.utils.ffi](docs/0.2/package_references/ffi.md) + + [torch.utils.data](docs/0.2/package_references/data.md) + + [torch.utils.model_zoo](docs/0.2/package_references/model_zoo.md) + + TORCHVISION参考 + + [torchvision](docs/0.2/torchvision/torchvision.md) + + [torchvision.datasets](docs/0.2/torchvision/torchvision-datasets.md) + + [torchvision.models](docs/0.2/torchvision/torchvision-models.md) + + [torchvision.transforms](docs/0.2/torchvision/torchvision-transform.md) + + [torchvision.utils](docs/0.2/torchvision/torchvision-utils.md) + + [致谢](docs/0.2/acknowledgement.md)