| 教程部分 |
- |
- |
| Deep Learning with PyTorch: A 60 Minute Blitz |
@bat67 |
100% |
| What is PyTorch? |
@bat67 |
100% |
| Autograd: Automatic Differentiation |
@bat67 |
100% |
| Neural Networks |
@bat67 |
100% |
| Training a Classifier |
@bat67 |
100% |
| Optional: Data Parallelism |
@bat67 |
100% |
| Data Loading and Processing Tutorial |
@yportne13 |
100% |
| Learning PyTorch with Examples |
@bat67 |
100% |
| Transfer Learning Tutorial |
@jiangzhonglian |
100% |
| Deploying a Seq2Seq Model with the Hybrid Frontend |
@cangyunye |
100% |
| Saving and Loading Models |
@sfyumi |
|
| What is <cite>torch.nn</cite> really? |
@lhc741 |
|
| Finetuning Torchvision Models |
@ZHHAYO |
100% |
| Spatial Transformer Networks Tutorial |
@PEGASUS1993 |
100% |
| Neural Transfer Using PyTorch |
@bdqfork |
100% |
| Adversarial Example Generation |
@cangyunye |
100% |
| 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 |
@BreezeHavana |
|
| Introduction to PyTorch |
@guobaoyo |
100% |
| Deep Learning with PyTorch |
@bdqfork |
100% |
| Word Embeddings: Encoding Lexical Semantics |
@sight007 |
|
| 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 |
|
| Reinforcement Learning (DQN) Tutorial |
@BreezeHavana |
|
| Creating Extensions Using numpy and scipy |
|
|
| Custom C++ and CUDA Extensions |
@Lotayou |
|
| Extending TorchScript with Custom C++ Operators |
|
|
| Writing Distributed Applications with PyTorch |
@firdameng |
|
| 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 |
|
| Frequently Asked Questions |
@PEGASUS1993 |
|
| Multiprocessing best practices |
@cvley |
|
| Reproducibility |
@WyattHuang1 |
|
| Serialization semantics |
|
|
| Windows FAQ |
@PEGASUS1993 |
|
| torch |
|
|
| torch.Tensor |
@hijkzzz |
100% |
| Tensor Attributes |
|
|
| Type Info |
@PEGASUS1993 |
100% |
| torch.sparse |
|
|
| torch.cuda |
@bdqfork |
100% |
| torch.Storage |
|
|
| torch.nn |
|
|
| torch.nn.functional |
@hijkzzz |
|
| torch.nn.init |
@GeneZC |
|
| torch.optim |
@qiaokuoyuan |
|
| Automatic differentiation package - torch.autograd |
|
|
| Distributed communication package - torch.distributed |
|
|
| Probability distributions - torch.distributions |
|
|
| Torch Script |
|
|
| Multiprocessing package - torch.multiprocessing |
@hijkzzz |
100% |
| torch.utils.bottleneck |
|
|
| torch.utils.checkpoint |
|
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| torch.utils.cpp_extension |
|
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| torch.utils.data |
|
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| torch.utils.dlpack |
|
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| torch.hub |
|
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| torch.utils.model_zoo |
|
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| torch.onnx |
@guobaoyo |
100% |
| Distributed communication package (deprecated) - torch.distributed.deprecated |
|
|
| torchvision Reference |
|
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| torchvision.datasets |
|
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| torchvision.models |
|
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| torchvision.transforms |
|
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| torchvision.utils |
|
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