Pytorch 教程翻译【持续迭代 - 2.x 最新版本】

[jiangzhonglian]

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✅ "PyTorch Recipes"

• See All Recipes
• See All Prototype Recipes

✅ "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

2.0版本翻译者： Daydaylight

✅ "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

2.0版本翻译者：Fadegentle

‼️ "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"

• 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 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"

• 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

‼️ "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 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!)

2.0版本翻译者： masteryi-0018

✅ "Code Transforms with FX"

• (beta) Building a Convolution/Batch Norm fuser in FX
• (beta) Building a Simple CPU Performance Profiler with FX

❌ "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"

• 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++

❌ "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

❌ "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"

• Image Segmentation DeepLabV3 on iOS
• Image Segmentation DeepLabV3 on Android

✅ "Recommendation Systems"

• Introduction to TorchRec
• Exploring TorchRec sharding

✅ "Multimodality"

• TorchMultimodal Tutorial: Finetuning FLAVA

[jiangzhonglian]

好兄弟，记得在这里登记哈： #583