• Learn
    Get Started

    Run PyTorch locally or get started quickly with one of the supported cloud platforms

     Tutorials

    Whats new in PyTorch tutorials

     Learn the Basics

    Familiarize yourself with PyTorch concepts and modules

     PyTorch Recipes

    Bite-size, ready-to-deploy PyTorch code examples

     Intro to PyTorch - YouTube Series

    Master PyTorch basics with our engaging YouTube tutorial series
  • Ecosystem
    Tools

    Learn about the tools and frameworks in the PyTorch Ecosystem

     Community

    Join the PyTorch developer community to contribute, learn, and get your questions answered

     Forums

    A place to discuss PyTorch code, issues, install, research

     Developer Resources

    Find resources and get questions answered

     Contributor Awards - 2024

    Award winners announced at this year's PyTorch Conference
  • Edge
    About PyTorch Edge

    Build innovative and privacy-aware AI experiences for edge devices

     ExecuTorch

    End-to-end solution for enabling on-device inference capabilities across mobile and edge devices

     ExecuTorch Docs
  • Docs
    PyTorch

    Explore the documentation for comprehensive guidance on how to use PyTorch

     PyTorch Domains

    Read the PyTorch Domains documentation to learn more about domain-specific libraries
  • Blogs & News
    PyTorch Blog

    Catch up on the latest technical news and happenings

     Community Blog

    Stories from the PyTorch ecosystem

     Videos

    Learn about the latest PyTorch tutorials, new, and more

    Community Stories

    Learn how our community solves real, everyday machine learning problems with PyTorch

     Events

    Find events, webinars, and podcasts

     Newsletter

    Stay up-to-date with the latest updates
  • About
    PyTorch Foundation

    Learn more about the PyTorch Foundation

     Governing Board Cloud Credit Program Technical Advisory Council Staff Contact Us
  • Become a Member
Table of Contents
2.7.0+cu126

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
  • 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

  • Deep Learning with PyTorch: A 60 Minute Blitz
  • Learning PyTorch with Examples
  • What is torch.nn really?
  • NLP from Scratch
  • Visualizing Models, Data, and Training with TensorBoard
  • A guide on good usage of non_blocking and pin_memory() in PyTorch

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 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

Backends

  • Introduction to ONNX

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

  • 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 your PyTorch Module
  • Introduction to Holistic Trace Analysis
  • Trace Diff using Holistic Trace Analysis

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

  • PyTorch Custom Operators
  • Custom Python Operators
  • Custom C++ and CUDA Operators
  • 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

  • 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
  • Compiled Autograd: Capturing a larger backward graph for torch.compile
  • Inductor CPU backend debugging and profiling
  • (Beta) Implementing High-Performance Transformers with Scaled Dot Product Attention (SDPA)
  • Knowledge Distillation Tutorial

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 (FSDP2)
  • Advanced Model Training with Fully Sharded Data Parallel (FSDP)
  • Introduction to Libuv TCPStore Backend
  • Large Scale Transformer model training with Tensor Parallel (TP)
  • Introduction to Distributed Pipeline Parallelism
  • Customize Process Group Backends Using Cpp Extensions
  • Getting Started with Distributed RPC Framework
  • Implementing a Parameter Server Using Distributed RPC Framework
  • Implementing Batch RPC Processing Using Asynchronous Executions
  • Combining Distributed DataParallel with Distributed RPC Framework
  • Distributed Training with Uneven Inputs Using the Join Context Manager

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

  • Introduction to TorchRec
  • Exploring TorchRec sharding

Multimodality

  • TorchMultimodal Tutorial: Finetuning FLAVA
  • Tutorials >
  • Audio Datasets
Shortcuts
beginner/audio_datasets_tutorial
Run in Google Colab
Colab
Download Notebook
Notebook
View on GitHub
GitHub

Audio Datasets¶

Created On: Feb 24, 2023 | Last Updated: Mar 23, 2023 | Last Verified: Nov 05, 2024

This tutorial has been moved to https://pytorch.org/audio/stable/tutorials/audio_datasets_tutorial.html

It will redirect in 3 seconds.

Next Previous
Rate this Tutorial

© Copyright 2024, PyTorch.

Built with Sphinx using a theme provided by Read the Docs.
  • Audio Datasets

Docs

Access comprehensive developer documentation for PyTorch

View Docs

Tutorials

Get in-depth tutorials for beginners and advanced developers

View Tutorials

Resources

Find development resources and get your questions answered

View Resources
  • PyTorch
  • Get Started
  • Features
  • Ecosystem
  • Blog
  • Contributing
  • Resources
  • Tutorials
  • Docs
  • Discuss
  • Github Issues
  • Brand Guidelines
  • Stay up to date
  • Facebook
  • Twitter
  • YouTube
  • LinkedIn
  • PyTorch Podcasts
  • Spotify
  • Apple
  • Google
  • Amazon
  • Terms
  • |
  • Privacy

© Copyright The Linux Foundation. The PyTorch Foundation is a project of The Linux Foundation. For web site terms of use, trademark policy and other policies applicable to The PyTorch Foundation please see www.linuxfoundation.org/policies/. The PyTorch Foundation supports the PyTorch open source project, which has been established as PyTorch Project a Series of LF Projects, LLC. For policies applicable to the PyTorch Project a Series of LF Projects, LLC, please see www.lfprojects.org/policies/.

To analyze traffic and optimize your experience, we serve cookies on this site. By clicking or navigating, you agree to allow our usage of cookies. As the current maintainers of this site, Facebook’s Cookies Policy applies. Learn more, including about available controls: Cookies Policy.

  • Learn
    • Get Started
    • Tutorials
    • Learn the Basics
    • PyTorch Recipes
    • Introduction to PyTorch - YouTube Series
  • Ecosystem
    • Tools
    • Community
    • Forums
    • Developer Resources
    • Contributor Awards - 2024
  • Edge
    • About PyTorch Edge
    • ExecuTorch
    • ExecuTorch Documentation
  • Docs
    • PyTorch
    • PyTorch Domains
  • Blog & News
    • PyTorch Blog
    • Community Blog
    • Videos
    • Community Stories
    • Events
    • Newsletter
  • About
    • PyTorch Foundation
    • Governing Board
    • Cloud Credit Program
    • Technical Advisory Council
    • Staff
    • Contact Us
Morty Proxy This is a proxified and sanitized view of the page, visit original site.