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【布客】PyTorch 中文翻译

【布客】PyTorch 中文翻译

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apachecn/pytorch-doc-zh

【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
- V2.6
- V2.5
- V2.4
- V2.3
- V2.2
- V2.1
- 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
    
    Whole Slide Image Classification Using PyTorch and TIAToolbox
  - 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
    
    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
    
    Pendulum: Writing your environment and transforms with TorchRL
  - 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!)
  - Profiling PyTorch
    Profiling PyTorch
    
    Profiling your PyTorch Module
    
    Introduction to Holistic Trace Analysis
    
    Trace Diff using Holistic Trace Analysis
  - 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
    
    Introduction to torch.compile
    
    Inductor CPU backend debugging and profiling
    
    (Beta) Implementing High-Performance Transformers with Scaled Dot Product Attention (SDPA)
    
    (Beta) Implementing High-Performance Transformers with Scaled Dot Product Attention (SDPA)
    
    (Beta) Implementing High-Performance Transformers with Scaled Dot Product Attention (SDPA)
    
    (Beta) Implementing High-Performance Transformers with Scaled Dot Product Attention (SDPA)
    
    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)
    
    Large Scale Transformer model training with Tensor Parallel (TP)
    
    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 Distributed Data Parallel and Pipeline Parallelism
    
    Distributed Training with Uneven Inputs Using the Join Context Manager
  - Edge with ExecuTorch
    Edge with ExecuTorch
    
    Exporting to ExecuTorch Tutorial
    
    Running an ExecuTorch Model in C++ Tutorial
    
    Using the ExecuTorch SDK to Profile a Model
    
    Building an ExecuTorch iOS Demo App
    
    Building an ExecuTorch Android Demo App
    
    Lowering a Model as a Delegate
  - 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
  - Pytorch
  - Torchaudio
  - TorchText
  - TorchVision
  - TorchArrow
  - TorchRec
  - TorchServe
  - TorchX
  - 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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