Torchmetrics

Visit Tool

TorchMetrics is an open-source library providing machine learning metrics for distributed, scalable PyTorch applications. It offers over 100 PyTorch metric implementations and an easy-to-use API for custom metrics.

Claim this tool

No Views Yet

At a glance

Pricing

Open Source

Free tier

Yes

API

Yes

Skill level

Technical

About

What is torchmetrics?

TorchMetrics is a comprehensive open-source library designed for machine learning metrics within distributed and scalable PyTorch applications. It provides a standardized interface for over 100 built-in metric implementations, covering domains like audio, image, text, and classification. The library reduces boilerplate code by offering automatic accumulation over batches and synchronization across multiple devices, making it ideal for distributed training. Developers can also easily create custom metrics using its API. TorchMetrics integrates seamlessly with PyTorch Lightning, providing additional features like automatic metric placement on the correct device and native logging support. It also includes built-in plotting support for metric visualization.

Best used for

Ideal for data scientists and developers who need to accurately evaluate machine learning models, implement custom performance metrics, and ensure consistent evaluation across distributed PyTorch environments. Especially valuable for those working with PyTorch Lightning to streamline metric logging and device management.

Common actions

evaluate model performance

implement custom metrics

monitor distributed training

visualize metric data

"AI Agents"github copilotface swappinglow-code/no-codeworkflowscollaborationopen-sourcedeepfakeautomated workflow

Capabilities

Key features

100+ PyTorch metric implementations
Easy custom metric API
Automatic batch accumulation
Distributed training synchronization
Built-in plotting support
Module-based metrics
Functional metrics

Target Audience

data scientistdeveloper

Integrations

pytorchpytorch-lightning

Pricing & Plans

Open Source

Free

FAQs

What types of machine learning metrics does TorchMetrics support?

TorchMetrics offers over 100 metrics covering various domains including audio, classification, detection, information retrieval, image, multimodal, nominal, regression, segmentation, and text. It provides both module-based and functional versions for most metrics, allowing flexibility in implementation.

Can TorchMetrics be used with distributed training setups?

Yes, TorchMetrics is specifically designed for distributed and scalable PyTorch applications. It features automatic synchronization between multiple devices and accumulation over batches, making it highly suitable for multi-GPU or multi-node training environments like DDP.

Does TorchMetrics provide visualization capabilities for metrics?

Yes, TorchMetrics includes built-in plotting support for nearly all modular metrics. Users can easily visualize metric trends by calling the `.plot()` method, which helps in understanding model performance and debugging machine learning algorithms.

Trending

Subcategories trending in Coding & Development

Open Source & Models Code Assistants DevOps & Infrastructure No-Code / Low-Code Backend & APIs Prompt Engineering

Trending

Also listed in

This tool also appears in

Data & Analytics › Business Intelligence

Explore

Browse AI tools by category

Content & Design Productivity & Business Coding & Development AI Agents & Automation Research & Education Wellness & Lifestyle Career Development Marketing & Growth Data & Analytics Customer Support & CX Finance E-commerce