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PyTorch 1.2 中文文档校对活动 | ApacheCN

2019-09-26 20:55 作者:绝不原创的飞龙  | 我要投稿

整体进度:https://github.com/apachecn/pytorch-doc-zh/issues/422

贡献指南:https://github.com/apachecn/pytorch-doc-zh/blob/master/CONTRIBUTING.md

项目仓库:https://github.com/apachecn/pytorch-doc-zh

贡献指南

请您勇敢地去翻译和改进翻译。虽然我们追求卓越,但我们并不要求您做到十全十美,因此请不要担心因为翻译上犯错——在大部分情况下,我们的服务器已经记录所有的翻译,因此您不必担心会因为您的失误遭到无法挽回的破坏。(改编自维基百科)

可能有用的链接:

  • 英文文档(https://pytorch.org/docs/)

  • 英文教程(https://pytorch.org/tutorials/)

负责人:

  • 片刻(https://github.com/jiangzhonglian):529815144

  • Alex(https://github.com/AlexJakin): 1272296763

  • Holly(https://github.com/kunwuz): 514397511

章节列表

  • 中文教程

  • 入门

  • PyTorch 深度学习: 60 分钟极速入门(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/beginner/deep_learning_60min_blitz.md)

  • 数据加载和处理教程(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/beginner/data_loading_tutorial.md)

  • 用例子学习 PyTorch(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/beginner/pytorch_with_examples.md)

  • 部署与Torch一个Seq2Seq模型(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/beginner/deploy_seq2seq_hybrid_frontend_tutorial.md)

  • 可视化模型,数据,和与训练TensorBoard(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/intermediate/tensorboard_tutorial.md)

  • 保存和加载模型(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/beginner/saving_loading_models.md)

  • torch.nn 到底是什么?(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/beginner/nn_tutorial.md)

  • TorchVision对象检测教程细化和微调(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/intermediate/torchvision_tutorial.md)

  • 微调Torchvision模型(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/beginner/finetuning_torchvision_models_tutorial.md)

  • 空间变压器网络教程(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/intermediate/spatial_transformer_tutorial.md)

  • 使用PyTorch进行神经网络传递(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/advanced/neural_style_tutorial.md)

  • 对抗性示例生成(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/beginner/fgsm_tutorial.md)

  • DCGAN教程(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/beginner/dcgan_faces_tutorial.md)

  • 音频

  • torchaudio教程(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/beginner/audio_preprocessing_tutorial.md)

  • NLP从头:判断名称与字符级RNN(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/intermediate/char_rnn_classification_tutorial.md)

  • 文本分类与TorchText (https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/beginner/text_sentiment_ngrams_tutorial.md)

  • 语言翻译与TorchText (https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/beginner/torchtext_translation_tutorial.md)

  • 序列到序列与nn.Transformer和TorchText建模(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/beginner/transformer_tutorial.md)

  • 1.部署PyTorch在Python经由REST API从Flask(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/intermediate/flask_rest_api_tutorial.md)

  • 2.介绍Torch(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/beginner/Intro_to_Torch_tutorial.md)

  • 3.装载++一个Torch模型在C (https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/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(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/advanced/super_resolution_with_onnxruntime.md)

  • 并行和分布式训练

  • 1.型号并行最佳实践(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/intermediate/model_parallel_tutorial.md)

  • 2.入门分布式数据并行(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/intermediate/ddp_tutorial.md)

  1. PyTorch编写分布式应用(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/intermediate/dist_tuto.md)

  • 4.(高级)PyTorch 1.0分布式训练与Amazon AWS(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/beginner/aws_distributed_training_tutorial.md)

  • 扩展PyTorch

  • 使用自定义 C++ 扩展算Torch (https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/advanced/torch__custom_ops.md)

  • 创建扩展使用numpy的和SciPy的(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/advanced/numpy_extensions_tutorial.md)

  • 自定义 C++ 和CUDA扩展(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/advanced/cpp_extension.md)

  • PyTorch在其他语言

  • 使用PyTorch C++ 前端(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/advanced/cpp_frontend.md)

  • 中文文档

  • 注解

  • 自动求导机制(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/notes/autograd.md)

  • 广播语义(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/notes/broadcasting.md)

  • CPU线程和Torch推理(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/notes/cpu_threading_torch_inference.md)

  • CUDA语义(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/notes/cuda.md)

  • 扩展PyTorch(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/notes/extending.md)

  • 常见问题(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/notes/faq.md)

  • 对于大规模部署的特点(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/notes/large_scale_deployments.md)

  • 多处理最佳实践(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/notes/multiprocessing.md)

  • 重复性(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/notes/randomness.md)

  • 序列化语义(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/notes/serialization.md)

  • Windows 常见问题(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/notes/windows.md)

  • 社区

  • PyTorch贡献说明书(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/community/contribution_guide.md)

  • PyTorch治理(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/community/governance.md)

  • PyTorch治理兴趣人(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/community/persons_of_interest.md)

  • 封装参考文献

  • torch(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/torch.md)

  • torch.Tensor(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/tensors.md)

  • Tensor Attributes(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/tensor_attributes.md)

  • Type Info(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/type_info.md)

  • torch.sparse(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/sparse.md)

  • torch.cuda(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/cuda.md)

  • torch.Storage(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/storage.md)

  • torch.nn(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/nn.md)

  • torch.nn.functional(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/nn.functional.md)

  • torch.nn.init(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/nn.init.md)

  • torch.optim(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/optim.md)

  • torch.autograd(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/autograd.md)

  • torch.distributed(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/distributed.md)

  • torch.distributions(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/distributions.md)

  • torch.hub(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/hub.md)

  • torch.jit(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/jit.md)

  • torch.multiprocessing(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/multiprocessing.md)

  • torch.random(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/random.md)

  • torch.utils.bottleneck(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/bottleneck.md)

  • torch.utils.checkpoint(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/checkpoint.md)

  • torch.utils.cpp_extension(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/cpp_extension.md)

  • torch.utils.data(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/data.md)

  • torch.utils.dlpack(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/dlpack.md)

  • torch.utils.model_zoo(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/model_zoo.md)

  • torch.utils.tensorboard(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/tensorboard.md)

  • torch.onnx(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/onnx.md)

  • torch.__ config__(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/config.md)

  • torchvision 参考文献

  • torchvision(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/torchvision/index.md)

  • torchaudio Reference

  • torchaudio(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/https://pytorch.org/audio)

  • torchtext Reference

  • torchtext(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/https://pytorch.org/text)

流程

一、认领

首先查看整体进度(https://github.com/apachecn/pytorch-doc-zh/issues/274),确认没有人认领了你想认领的章节。

然后回复 ISSUE,注明“章节 + QQ 号”(一定要留 QQ)。

二、校对

需要校对:

  1. 语法

  2. 术语使用

  3. 文档格式

Note: 可以合理利用翻译引擎(例如谷歌(https://translate.google.cn/)),但一定要把它变得可读!

如果觉得现有翻译不好,重新翻译也是可以的。

三、提交

提交的时候不要改动文件名称,即使它跟章节标题不一样也不要改,因为文件名和原文的链接是对应的!!!

  • fork Github 项目

  • 将译文放在docs/1.2文件夹下

  • push

  • pull request

请见 Github 入门指南(https://github.com/apachecn/kaggle/blob/master/docs/GitHub)。

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