【布客】PyTorch 中文翻译
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【布客】PyTorch 中文翻译
apachecn/pytorch-doc-zh
PyTorch 中文文档 & 教程
PyTorch 新特性
PyTorch 新特性
V2.0
V1.13
V1.12
V1.11
V1.10
V1.9
V1.8
V1.7
V1.6
V1.5
V1.4
V1.3
V1.2
PyTorch 2.x 中文文档 & 教程
PyTorch 2.x 中文文档 & 教程
中文教程
中文教程
PyTorch Recipes
PyTorch Recipes
See All Recipes
See All Prototype Recipes
Introduction to PyTorch
Introduction to PyTorch
Learn the Basics
Quickstart
Tensors
Datasets & DataLoaders
Transforms
Build the Neural Network
Automatic Differentiation with torch.autograd
Optimizing Model Parameters
Save and Load the Model
Introduction to PyTorch on YouTube
Introduction to PyTorch on YouTube
Introduction to PyTorch - YouTube Series
Introduction to PyTorch
Introduction to PyTorch Tensors
The Fundamentals of Autograd
Building Models with PyTorch
PyTorch TensorBoard Support
Training with PyTorch
Model Understanding with Captum
Learning PyTorch
Learning PyTorch
Deep Learning with PyTorch: A 60 Minute Blitz
Learning PyTorch with Examples
What is torch.nn really?
Visualizing Models, Data, and Training with TensorBoard
Image and Video
Image and Video
TorchVision Object Detection Finetuning Tutorial
Transfer Learning for Computer Vision Tutorial
Adversarial Example Generation
DCGAN Tutorial
Spatial Transformer Networks Tutorial
Optimizing Vision Transformer Model for Deployment
Audio
Audio
Audio I/O
Audio Resampling
Audio Data Augmentation
Audio Feature Extractions
Audio Feature Augmentation
Audio Datasets
Speech Recognition with Wav2Vec2
Text-to-speech with Tacotron2
Forced Alignment with Wav2Vec2
Text
Text
Language Modeling with nn.Transformer and torchtext
Fast Transformer Inference with Better Transformer
NLP From Scratch: Classifying Names with a Character-Level RNN
NLP From Scratch: Generating Names with a Character-Level RNN
NLP From Scratch: Translation with a Sequence to Sequence Network and Attention
Text classification with the torchtext library
Language Translation with nn.Transformer and torchtext
Preprocess custom text dataset using Torchtext
Backends
Backends
Introduction to ONNX
Reinforcement Learning
Reinforcement Learning
Reinforcement Learning (DQN) Tutorial
Reinforcement Learning (PPO) with TorchRL Tutorial
Train a Mario-playing RL Agent
Deploying PyTorch Models in Production
Deploying PyTorch Models in Production
Introduction to ONNX
Deploying PyTorch in Python via a REST API with Flask
Introduction to TorchScript
Loading a TorchScript Model in C++
(optional) Exporting a Model from PyTorch to ONNX and Running it using ONNX Runtime
Real Time Inference on Raspberry Pi 4 (30 fps!)
Code Transforms with FX
Code Transforms with FX
(beta) Building a Convolution/Batch Norm fuser in FX
(beta) Building a Simple CPU Performance Profiler with FX
Frontend APIs
Frontend APIs
(beta) Channels Last Memory Format in PyTorch
Forward-mode Automatic Differentiation (Beta)
Jacobians, Hessians, hvp, vhp, and more: composing function transforms
Model ensembling
Per-sample-gradients
Using the PyTorch C++ Frontend
Dynamic Parallelism in TorchScript
Autograd in C++ Frontend
Extending PyTorch
Extending PyTorch
Double Backward with Custom Functions
Fusing Convolution and Batch Norm using Custom Function
Custom C++ and CUDA Extensions
Extending TorchScript with Custom C++ Operators
Extending TorchScript with Custom C++ Classes
Registering a Dispatched Operator in C++
Extending dispatcher for a new backend in C++
Facilitating New Backend Integration by PrivateUse1
Model Optimization
Model Optimization
Profiling your PyTorch Module
PyTorch Profiler With TensorBoard
Hyperparameter tuning with Ray Tune
Optimizing Vision Transformer Model for Deployment
Parametrizations Tutorial
Pruning Tutorial
(beta) Dynamic Quantization on an LSTM Word Language Model
(beta) Dynamic Quantization on BERT
(beta) Quantized Transfer Learning for Computer Vision Tutorial
(beta) Static Quantization with Eager Mode in PyTorch
Grokking PyTorch Intel CPU performance from first principles
Grokking PyTorch Intel CPU performance from first principles (Part 2)
Getting Started - Accelerate Your Scripts with nvFuser
Multi-Objective NAS with Ax
torch.compile Tutorial
Inductor CPU backend debugging and profiling
(Beta) Implementing High-Performance Transformers with Scaled Dot Product Attention (SDPA)
Using SDPA with torch.compile
Conclusion
Knowledge Distillation Tutorial
Parallel and Distributed Training
Parallel and Distributed Training
Distributed and Parallel Training Tutorials
PyTorch Distributed Overview
Distributed Data Parallel in PyTorch - Video Tutorials
Single-Machine Model Parallel Best Practices
Getting Started with Distributed Data Parallel
Writing Distributed Applications with PyTorch
Getting Started with Fully Sharded Data Parallel(FSDP)
Advanced Model Training with Fully Sharded Data Parallel (FSDP)
Customize Process Group Backends Using Cpp Extensions
Getting Started with Distributed RPC Framework
Implementing a Parameter Server Using Distributed RPC Framework
Distributed Pipeline Parallelism Using RPC
Implementing Batch RPC Processing Using Asynchronous Executions
Combining Distributed DataParallel with Distributed RPC Framework
Training Transformer models using Pipeline Parallelism
Training Transformer models using Distributed Data Parallel and Pipeline Parallelism
Distributed Training with Uneven Inputs Using the Join Context Manager
Mobile
Mobile
Image Segmentation DeepLabV3 on iOS
Image Segmentation DeepLabV3 on Android
Recommendation Systems
Recommendation Systems
Introduction to TorchRec
Exploring TorchRec sharding
Multimodality
Multimodality
TorchMultimodal Tutorial: Finetuning FLAVA
中文文档
中文文档
介绍
Community
Community
PyTorch Governance | Build + CI
PyTorch Contribution Guide
PyTorch Design Philosophy
PyTorch Governance | Mechanics
PyTorch Governance | Maintainers
Developer Notes
Developer Notes
CUDA Automatic Mixed Precision examples
Autograd mechanics
Broadcasting semantics
CPU threading and TorchScript inference
CUDA semantics
Distributed Data Parallel
Extending PyTorch
Extending torch.func with autograd.Function
Frequently Asked Questions
Gradcheck mechanics
HIP (ROCm) semantics
Features for large-scale deployments
Modules
MPS backend
Multiprocessing best practices
Numerical accuracy
Reproducibility
Serialization semantics
Windows FAQ
Language Bindings
Language Bindings
C++
Javadoc
torch::deploy
Python API
Python API
torch
torch.nn
torch.nn.functional
torch.Tensor
Tensor Attributes
Tensor Views
torch.amp
torch.autograd
torch.library
torch.cpu
torch.cuda
Understanding CUDA Memory Usage
Generating a Snapshot
Using the visualizer
Snapshot API Reference
torch.mps
torch.backends
torch.export
torch.distributed
torch.distributed.algorithms.join
torch.distributed.elastic
torch.distributed.fsdp
torch.distributed.optim
torch.distributed.tensor.parallel
torch.distributed.checkpoint
torch.distributions
torch.compiler
torch.fft
torch.func
torch.futures
torch.fx
torch.hub
torch.jit
torch.linalg
torch.monitor
torch.signal
torch.special
torch.overrides
torch.package
torch.profiler
torch.nn.init
torch.onnx
torch.optim
Complex Numbers
DDP Communication Hooks
Pipeline Parallelism
Quantization
Distributed RPC Framework
torch.random
torch.masked
torch.nested
torch.sparse
torch.Storage
torch.testing
torch.utils
torch.utils.benchmark
torch.utils.bottleneck
torch.utils.checkpoint
torch.utils.cpp_extension
torch.utils.data
torch.utils.jit
torch.utils.dlpack
torch.utils.mobile_optimizer
torch.utils.model_zoo
torch.utils.tensorboard
Type Info
Named Tensors
Named Tensors operator coverage
torch.__config__
torch._logging
Libraries
Libraries
torchaudio
TorchData
TorchRec
TorchServe
torchtext
torchvision
PyTorch on XLA Devices
PyTorch 1.7 中文文档
PyTorch 1.4 中文文档 & 教程
PyTorch 1.0 中文文档 & 教程
PyTorch 0.4 中文文档
PyTorch 0.3 中文文档 & 教程
PyTorch 0.2 中文文档
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