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docs/1.0/SUMMARY.md
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docs/1.0/seq2seq_translation_tutorial.md
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未找到文件。
docs/1.0/SUMMARY.md
浏览文件 @
ea6595ff
+
中文教程
+
[
Getting Started
](
tut_getting_started.md
)
+
[
起步
](
tut_getting_started.md
)
+
[
PyTorch 深度学习: 60 分钟极速入门
](
deep_learning_60min_blitz.md
)
+
[
什么是 PyTorch?
](
blitz_tensor_tutorial.md
)
+
[
Autograd:自动求导
](
blitz_autograd_tutorial.md
)
...
...
@@ -8,46 +8,46 @@
+
[
可选:数据并行处理
](
blitz_data_parallel_tutorial.md
)
+
[
数据加载和处理教程
](
data_loading_tutorial.md
)
+
[
用例子学习 PyTorch
](
pytorch_with_examples.md
)
+
[
Transfer Learning Tutorial
](
transfer_learning_tutorial.md
)
+
[
Deploying a Seq2Seq Model with the Hybrid Frontend
](
deploy_seq2seq_hybrid_frontend_tutorial.md
)
+
[
迁移学习教程
](
transfer_learning_tutorial.md
)
+
[
混合前端的 seq2seq 模型部署
](
deploy_seq2seq_hybrid_frontend_tutorial.md
)
+
[
Saving and Loading Models
](
saving_loading_models.md
)
+
[
What is `torch.nn` _really_?
](
nn_tutorial.md
)
+
[
Image
](
tut_image.md
)
+
[
图像
](
tut_image.md
)
+
[
Torchvision 模型微调
](
finetuning_torchvision_models_tutorial.md
)
+
[
Spatial Transformer Networks Tutorial
](
spatial_transformer_tutorial.md
)
+
[
Neural Transfer Using PyTorch
](
neural_style_tutorial.md
)
+
[
Adversarial Example Generation
](
fgsm_tutorial.md
)
+
[
Transfering a Model from PyTorch to Caffe2 and Mobile using ONNX
](
super_resolution_with_caffe2.md
)
+
[
Text
](
tut_text.md
)
+
[
Chatbot Tutorial
](
chatbot_tutorial.md
)
+
[
Generating Names with a Character-Level RNN
](
char_rnn_generation_tutorial.md
)
+
[
空间变换器网络教程
](
spatial_transformer_tutorial.md
)
+
[
使用 PyTorch 进行图像风格转换
](
neural_style_tutorial.md
)
+
[
对抗性示例生成
](
fgsm_tutorial.md
)
+
[
使用 ONNX 将模型从 PyTorch 传输到 Caffe2 和移动端
](
super_resolution_with_caffe2.md
)
+
[
文本
](
tut_text.md
)
+
[
聊天机器人教程
](
chatbot_tutorial.md
)
+
[
使用字符级别特征的 RNN 网络生成姓氏
](
char_rnn_generation_tutorial.md
)
+
[
使用字符级别特征的 RNN 网络进行姓氏分类
](
char_rnn_classification_tutorial.md
)
+
[
Deep Learning for NLP with Pytorch
](
deep_learning_nlp_tutorial.md
)
+
[
Introduction to PyTorch
](
nlp_pytorch_tutorial.md
)
+
[
PyTorch 介绍
](
nlp_pytorch_tutorial.md
)
+
[
使用 PyTorch 进行深度学习
](
nlp_deep_learning_tutorial.md
)
+
[
Word Embeddings: Encoding Lexical Semantics
](
nlp_word_embeddings_tutorial.md
)
+
[
Sequence Models and Long-Short Term Memory Networks
](
nlp_sequence_models_tutorial.md
)
+
[
Advanced: Making Dynamic Decisions and the Bi-LSTM CRF
](
nlp_advanced_tutorial.md
)
+
[
Translation with a Sequence to Sequence Network and Attention
](
seq2seq_translation_tutorial.md
)
+
[
Generative
](
tut_generative.md
)
+
[
基于注意力机制的 seq2seq 神经网络翻译
](
seq2seq_translation_tutorial.md
)
+
[
生成
](
tut_generative.md
)
+
[
DCGAN Tutorial
](
dcgan_faces_tutorial.md
)
+
[
Reinforcement Learning
](
tut_reinforcement_learning.md
)
+
[
强化学习
](
tut_reinforcement_learning.md
)
+
[
Reinforcement Learning (DQN) Tutorial
](
reinforcement_q_learning.md
)
+
[
Extending
PyTorch
](
tut_extending_pytorch.md
)
+
[
Creating Extensions Using numpy and scipy
](
numpy_extensions_tutorial.md
)
+
[
扩展
PyTorch
](
tut_extending_pytorch.md
)
+
[
用 numpy 和 scipy 创建扩展
](
numpy_extensions_tutorial.md
)
+
[
Custom C++ and CUDA Extensions
](
cpp_extension.md
)
+
[
Extending TorchScript with Custom C++ Operators
](
torch_script_custom_ops.md
)
+
[
Production Usage
](
tut_production_usage.md
)
+
[
生产性使用
](
tut_production_usage.md
)
+
[
Writing Distributed Applications with PyTorch
](
dist_tuto.md
)
+
[
PyTorch 1.0 Distributed Trainer with Amazon AWS
](
aws_distributed_training_tutorial.md
)
+
[
ONNX
Live Tutorial
](
ONNXLive.md
)
+
[
ONNX
现场演示教程
](
ONNXLive.md
)
+
[
在 C++ 中加载 PYTORCH 模型
](
cpp_export.md
)
+
[
PyTorch in Other Languages
](
tut_other_language.md
)
+
[
Using the PyTorch C++ Frontend
](
cpp_frontend.md
)
+
[
其它语言中的 PyTorch
](
tut_other_language.md
)
+
[
使用 PyTorch C++ 前端
](
cpp_frontend.md
)
+
中文文档
+
[
Notes
](
docs_notes.md
)
+
[
Autograd mechanics
](
notes_autograd.md
)
+
[
Broadcasting semantics
](
notes_broadcasting.md
)
+
[
注解
](
docs_notes.md
)
+
[
自动求导机制
](
notes_autograd.md
)
+
[
广播语义
](
notes_broadcasting.md
)
+
[
CUDA semantics
](
notes_cuda.md
)
+
[
Extending PyTorch
](
notes_extending.md
)
+
[
Frequently Asked Questions
](
notes_faq.md
)
...
...
@@ -55,11 +55,11 @@
+
[
Reproducibility
](
notes_randomness.md
)
+
[
Serialization semantics
](
notes_serialization.md
)
+
[
Windows FAQ
](
notes_windows.md
)
+
[
Package Reference
](
docs_package_ref.md
)
+
[
包参考
](
docs_package_ref.md
)
+
[
torch
](
torch.md
)
+
[
torch.Tensor
](
tensors.md
)
+
[
Tensor Attributes
](
tensor_attributes.md
)
+
[
Type Info
](
type_info.md
)
+
[
数据类型信息
](
type_info.md
)
+
[
torch.sparse
](
sparse.md
)
+
[
torch.cuda
](
cuda.md
)
+
[
torch.Storage
](
storage.md
)
...
...
@@ -81,7 +81,7 @@
+
[
torch.utils.model_zoo
](
model_zoo.md
)
+
[
torch.onnx
](
onnx.md
)
+
[
Distributed communication package (deprecated) - torch.distributed.deprecated
](
distributed_deprecated.md
)
+
[
torchvision
Reference
](
docs_torchvision_ref.md
)
+
[
torchvision
参考
](
docs_torchvision_ref.md
)
+
[
torchvision.datasets
](
torchvision_datasets.md
)
+
[
torchvision.models
](
torchvision_models.md
)
+
[
torchvision.transforms
](
torchvision_transforms.md
)
...
...
docs/1.0/docs_notes.md
浏览文件 @
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#
Notes
#
注解
docs/1.0/docs_package_ref.md
浏览文件 @
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#
Package Reference
#
包参考
docs/1.0/docs_torchvision_ref.md
浏览文件 @
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# torchvision
Reference
# torchvision
参考
The
[
`torchvision`
](
#module-torchvision
"torchvision"
)
package consists of popular datasets, model architectures, and common image transformations for computer vision.
...
...
docs/1.0/seq2seq_translation_tutorial.md
浏览文件 @
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# 基于注意力机制的
seq2seq神经网络进行
翻译
# 基于注意力机制的
seq2seq 神经网络
翻译
> 译者:[mengfu188](https://github.com/mengfu188)
...
...
docs/1.0/tut_extending_pytorch.md
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ea6595ff
#
Extending
PyTorch
#
扩展
PyTorch
docs/1.0/tut_generative.md
浏览文件 @
ea6595ff
#
Generative
#
生成
docs/1.0/tut_getting_started.md
浏览文件 @
ea6595ff
#
Getting Started
#
起步
docs/1.0/tut_image.md
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#
Image
#
图像
docs/1.0/tut_other_language.md
浏览文件 @
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#
PyTorch in Other Languages
#
其它语言中的 PyTorch
docs/1.0/tut_production_usage.md
浏览文件 @
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#
Production Usage
#
生产性使用
docs/1.0/tut_reinforcement_learning.md
浏览文件 @
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#
Reinforcement Learning
#
强化学习
docs/1.0/tut_text.md
浏览文件 @
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#
Text
#
文本
编辑
预览
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