PyTorch 1.2 中文文檔校對(duì)活動(dòng) | ApacheCN

整體進(jìn)度:https://github.com/apachecn/pytorch-doc-zh/issues/422
貢獻(xiàn)指南:https://github.com/apachecn/pytorch-doc-zh/blob/master/CONTRIBUTING.md
項(xiàng)目倉(cāng)庫(kù):https://github.com/apachecn/pytorch-doc-zh
貢獻(xiàn)指南
請(qǐng)您勇敢地去翻譯和改進(jìn)翻譯。雖然我們追求卓越,但我們并不要求您做到十全十美,因此請(qǐng)不要擔(dān)心因?yàn)榉g上犯錯(cuò)——在大部分情況下,我們的服務(wù)器已經(jīng)記錄所有的翻譯,因此您不必?fù)?dān)心會(huì)因?yàn)槟氖д`遭到無(wú)法挽回的破壞。(改編自維基百科)
可能有用的鏈接:
英文文檔(https://pytorch.org/docs/)
英文教程(https://pytorch.org/tutorials/)
負(fù)責(zé)人:
片刻(https://github.com/jiangzhonglian):529815144
Alex(https://github.com/AlexJakin): 1272296763
Holly(https://github.com/kunwuz): 514397511
章節(jié)列表
中文教程
入門(mén)
PyTorch 深度學(xué)習(xí): 60 分鐘極速入門(mén)(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/beginner/deep_learning_60min_blitz.md)
數(shù)據(jù)加載和處理教程(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/beginner/data_loading_tutorial.md)
用例子學(xué)習(xí) PyTorch(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/beginner/pytorch_with_examples.md)
部署與Torch一個(gè)Seq2Seq模型(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/beginner/deploy_seq2seq_hybrid_frontend_tutorial.md)
可視化模型,數(shù)據(jù),和與訓(xùn)練TensorBoard(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/intermediate/tensorboard_tutorial.md)
保存和加載模型(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對(duì)象檢測(cè)教程細(xì)化和微調(diào)(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/intermediate/torchvision_tutorial.md)
微調(diào)Torchvision模型(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/beginner/finetuning_torchvision_models_tutorial.md)
空間變壓器網(wǎng)絡(luò)教程(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/intermediate/spatial_transformer_tutorial.md)
使用PyTorch進(jìn)行神經(jīng)網(wǎng)絡(luò)傳遞(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/advanced/neural_style_tutorial.md)
對(duì)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)
音頻
torchaudio教程(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/beginner/audio_preprocessing_tutorial.md)
NLP從頭:判斷名稱(chēng)與字符級(jí)RNN(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/intermediate/char_rnn_classification_tutorial.md)
文本分類(lèi)與TorchText (https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/beginner/text_sentiment_ngrams_tutorial.md)
語(yǔ)言翻譯與TorchText (https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/beginner/torchtext_translation_tutorial.md)
序列到序列與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經(jīng)由REST API從Flask(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/intermediate/flask_rest_api_tutorial.md)
2.介紹Torch(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/beginner/Intro_to_Torch_tutorial.md)
3.裝載++一個(gè)Torch模型在C (https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/advanced/cpp_export.md)
4.(可選)從導(dǎo)出到PyTorch一個(gè)ONNX模型并使用ONNX運(yùn)行時(shí)運(yùn)行它(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/advanced/super_resolution_with_onnxruntime.md)
并行和分布式訓(xùn)練
1.型號(hào)并行最佳實(shí)踐(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/intermediate/model_parallel_tutorial.md)
2.入門(mén)分布式數(shù)據(jù)并行(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/intermediate/ddp_tutorial.md)
PyTorch編寫(xiě)分布式應(yīng)用(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/intermediate/dist_tuto.md)
4.(高級(jí))PyTorch 1.0分布式訓(xùn)練與Amazon AWS(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/beginner/aws_distributed_training_tutorial.md)
擴(kuò)展PyTorch
使用自定義 C++ 擴(kuò)展算Torch (https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/advanced/torch__custom_ops.md)
創(chuàng)建擴(kuò)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)
自定義 C++ 和CUDA擴(kuò)展(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/advanced/cpp_extension.md)
PyTorch在其他語(yǔ)言
使用PyTorch C++ 前端(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/advanced/cpp_frontend.md)
中文文檔
注解
自動(dòng)求導(dǎo)機(jī)制(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/notes/autograd.md)
廣播語(yǔ)義(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/notes/broadcasting.md)
CPU線程和Torch推理(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/notes/cpu_threading_torch_inference.md)
CUDA語(yǔ)義(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/notes/cuda.md)
擴(kuò)展PyTorch(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/notes/extending.md)
常見(jiàn)問(wèn)題(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/notes/faq.md)
對(duì)于大規(guī)模部署的特點(diǎn)(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/notes/large_scale_deployments.md)
多處理最佳實(shí)踐(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/notes/multiprocessing.md)
重復(fù)性(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/notes/randomness.md)
序列化語(yǔ)義(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/notes/serialization.md)
Windows 常見(jiàn)問(wèn)題(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/notes/windows.md)
社區(qū)
PyTorch貢獻(xiàn)說(shuō)明書(shū)(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治理興趣人(https://github.com/apachecn/pytorch-doc-zh/blob/master/docs/1.2/community/persons_of_interest.md)
封裝參考文獻(xiàn)
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 參考文獻(xiàn)
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、認(rèn)領(lǐng)
首先查看整體進(jìn)度(https://github.com/apachecn/pytorch-doc-zh/issues/274),確認(rèn)沒(méi)有人認(rèn)領(lǐng)了你想認(rèn)領(lǐng)的章節(jié)。
然后回復(fù) ISSUE,注明“章節(jié) + QQ 號(hào)”(一定要留 QQ)。
二、校對(duì)
需要校對(duì):
語(yǔ)法
術(shù)語(yǔ)使用
文檔格式
Note: 可以合理利用翻譯引擎(例如谷歌(https://translate.google.cn/)),但一定要把它變得可讀!
如果覺(jué)得現(xiàn)有翻譯不好,重新翻譯也是可以的。
三、提交
提交的時(shí)候不要改動(dòng)文件名稱(chēng),即使它跟章節(jié)標(biāo)題不一樣也不要改,因?yàn)槲募驮牡逆溄邮菍?duì)應(yīng)的?。?!
fork Github 項(xiàng)目
將譯文放在docs/1.2文件夾下
push
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