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项目仓库:https://github.com/apachecn/p…
整体进度
章节 | 贡献者 | 进度 | 校验者 | 进度 |
---|---|---|---|---|
教程部分 | – | – | – | – |
Deep Learning with PyTorch: A 60 Minute Blitz | @bat67 | 100% | @AllenZYJ | |
What is PyTorch? | @bat67 | 100% | @AllenZYJ | |
Autograd: Automatic Differentiation | @bat67 | 100% | @AllenZYJ | |
Neural Networks | @bat67 | 100% | @AllenZYJ | |
Training a Classifier | @bat67 | 100% | @AllenZYJ | |
Optional: Data Parallelism | @bat67 | 100% | ||
Data Loading and Processing Tutorial | @yportne13 | 100% | ||
Learning PyTorch with Examples | @bat67 | 100% | @Smilexuhc | |
Transfer Learning Tutorial | @jiangzhonglian | 100% | @infdahai | |
Deploying a Seq2Seq Model with the Hybrid Frontend | @cangyunye | 100% | ||
Saving and Loading Models | @bruce1408 | 100% | ||
What is torch.nn really? | @lhc741 | 100% | ||
Finetuning Torchvision Models | @ZHHAYO | 100% | ||
Spatial Transformer Networks Tutorial | @PEGASUS1993 | 100% | @Smilexuhc | |
Neural Transfer Using PyTorch | @bdqfork | 100% | ||
Adversarial Example Generation | @cangyunye | 100% | @infdahai | |
Transfering a Model from PyTorch to Caffe2 and Mobile using ONNX | @PEGASUS1993 | 100% | ||
Chatbot Tutorial | @a625687551 | 100% | ||
Generating Names with a Character-Level RNN | @hhxx2015 | 100% | ||
Classifying Names with a Character-Level RNN | @hhxx2015 | 100% | ||
Deep Learning for NLP with Pytorch | @bruce1408 | 100% | ||
Introduction to PyTorch | @guobaoyo | 100% | ||
Deep Learning with PyTorch | @bdqfork | 100% | ||
Word Embeddings: Encoding Lexical Semantics | @sight007 | 100% | @Smilexuhc | |
Sequence Models and Long-Short Term Memory Networks | @ETCartman | 100% | ||
Advanced: Making Dynamic Decisions and the Bi-LSTM CRF | @JohnJiangLA | |||
Translation with a Sequence to Sequence Network and Attention | @mengfu188 | 100% | ||
DCGAN Tutorial | @wangshuai9517 | 100% | ||
Reinforcement Learning (DQN) Tutorial | @friedhelm739 | 100% | ||
Creating Extensions Using numpy and scipy | @cangyunye | 100% | ||
Custom C++ and CUDA Extensions | @P3n9W31 | |||
Extending TorchScript with Custom C++ Operators | @sunxia233 | |||
Writing Distributed Applications with PyTorch | @firdameng | 100% | ||
PyTorch 1.0 Distributed Trainer with Amazon AWS | @yportne13 | 100% | ||
ONNX Live Tutorial | @PEGASUS1993 | 100% | ||
Loading a PyTorch Model in C++ | @talengu | 100% | ||
Using the PyTorch C++ Frontend | @solerji | 100% | ||
文档部分 | – | – | – | – |
Autograd mechanics | @PEGASUS1993 | 100% | ||
Broadcasting semantics | @PEGASUS1993 | 100% | ||
CUDA semantics | @jiangzhonglian | 100% | ||
Extending PyTorch | @PEGASUS1993 | 100% | ||
Frequently Asked Questions | @PEGASUS1993 | 100% | ||
Multiprocessing best practices | @cvley | 100% | ||
Reproducibility | @WyattHuang1 | |||
Serialization semantics | @yuange250 | 100% | ||
Windows FAQ | @PEGASUS1993 | 100% | ||
torch | @yiran7324 | |||
torch.Tensor | @hijkzzz | 100% | ||
Tensor Attributes | @yuange250 | 100% | ||
Type Info | @PEGASUS1993 | 100% | ||
torch.sparse | @hijkzzz | 100% | ||
torch.cuda | @bdqfork | 100% | ||
torch.Storage | @yuange250 | 100% | ||
torch.nn | @yuange250 | 100% | ||
torch.nn.functional | @hijkzzz | 100% | ||
torch.nn.init | @GeneZC | 100% | ||
torch.optim | @qiaokuoyuan | |||
Automatic differentiation package – torch.autograd | @gfjiangly | 100% | ||
Distributed communication package – torch.distributed | @univeryinli | 100% | ||
Probability distributions – torch.distributions | @hijkzzz | 100% | ||
Torch Script | @keyianpai | 100% | ||
Multiprocessing package – torch.multiprocessing | @hijkzzz | 100% | ||
torch.utils.bottleneck | @belonHan | 100% | ||
torch.utils.checkpoint | @belonHan | 100% | ||
torch.utils.cpp_extension | @belonHan | 100% | ||
torch.utils.data | @BXuan694 | 100% | ||
torch.utils.dlpack | @kunwuz | 100% | ||
torch.hub | @kunwuz | 100% | ||
torch.utils.model_zoo | @BXuan694 | 100% | ||
torch.onnx | @guobaoyo | 100% | ||
Distributed communication package (deprecated) – torch.distributed.deprecated | @luxinfeng | |||
torchvision Reference | @BXuan694 | 100% | ||
torchvision.datasets | @BXuan694 | 100% | ||
torchvision.models | @BXuan694 | 100% | ||
torchvision.transforms | @BXuan694 | 100% | ||
torchvision.utils | @BXuan694 | 100% |
奖励
贡献者可以领取官方的纪念礼物。邮件部分内容如下:
As a start, let us know where we can ship you some PyTorch swag!
We have stickers, t-shirts, hoodies, and backpacks – let us know what sizes you need.
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