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What is TorchMetrics?

TorchMetrics offers a collection of over 90 performance metrics tailored for PyTorch, complemented by an intuitive API that enables users to craft custom metrics effortlessly. By providing a standardized interface, it significantly boosts reproducibility and reduces instances of code duplication. Furthermore, this library is well-suited for distributed training scenarios and has been rigorously tested to confirm its dependability. It includes features like automatic batch accumulation and smooth synchronization across various devices, ensuring seamless functionality. You can easily incorporate TorchMetrics into any PyTorch model or leverage it within PyTorch Lightning to gain additional benefits, all while ensuring that your metrics stay aligned with the same device as your data. Moreover, it's possible to log Metric objects directly within Lightning, which helps streamline your code and eliminate unnecessary boilerplate. Similar to torch.nn, most of the metrics are provided in both class and functional formats. The functional versions are simple Python functions that accept torch.tensors as input and return the respective metric as a torch.tensor output. Almost all functional metrics have a corresponding class-based version, allowing users to select the method that best suits their development style and project needs. This flexibility empowers developers to implement metrics in a way that aligns with their unique workflows and preferences. Furthermore, the extensive range of metrics available ensures that users can find the right tools to enhance their model evaluation and performance tracking.

What is NVIDIA Triton Inference Server?

The NVIDIA Triton™ inference server delivers powerful and scalable AI solutions tailored for production settings. As an open-source software tool, it streamlines AI inference, enabling teams to deploy trained models from a variety of frameworks including TensorFlow, NVIDIA TensorRT®, PyTorch, ONNX, XGBoost, and Python across diverse infrastructures utilizing GPUs or CPUs, whether in cloud environments, data centers, or edge locations. Triton boosts throughput and optimizes resource usage by allowing concurrent model execution on GPUs while also supporting inference across both x86 and ARM architectures. It is packed with sophisticated features such as dynamic batching, model analysis, ensemble modeling, and the ability to handle audio streaming. Moreover, Triton is built for seamless integration with Kubernetes, which aids in orchestration and scaling, and it offers Prometheus metrics for efficient monitoring, alongside capabilities for live model updates. This software is compatible with all leading public cloud machine learning platforms and managed Kubernetes services, making it a vital resource for standardizing model deployment in production environments. By adopting Triton, developers can achieve enhanced performance in inference while simplifying the entire deployment workflow, ultimately accelerating the path from model development to practical application.

Media

Media

Integrations Supported

PyTorch
Lightning AI

Integrations Supported

PyTorch
Alibaba CloudAP
Amazon EKS
Amazon Elastic Container Service (Amazon ECS)
Amazon SageMaker
Azure Kubernetes Service (AKS)
Azure Machine Learning
FauxPilot
Gemini Enterprise Agent Platform
Google Kubernetes Engine (GKE)
HPE Ezmeral
Kubernetes
LiteLLM
MXNet
NVIDIA DeepStream SDK
NVIDIA Morpheus
Prometheus
TensorFlow
Thunder Compute

API Availability

Has API

API Availability

Pricing Information

Free
Free Version

Pricing Information

Free
Free Version

Supported Platforms

SaaS

Supported Platforms

Windows
Mac
Linux

Customer Service / Support

Web-Based Support

Customer Service / Support

Standard Support
Web-Based Support

Training Options

Documentation Hub

Training Options

Documentation Hub
On-Site Training

Company Facts

Organization Name

TorchMetrics

Company Location

United States

Company Website

torchmetrics.readthedocs.io/en/stable/

Company Facts

Organization Name

NVIDIA

Company Location

United States

Company Website

developer.nvidia.com/nvidia-triton-inference-server

Categories and Features

Categories and Features

AI Inference

Not specified

AI Infrastructure

Not specified

Machine Learning

Not specified

ML Model Deployment

Not specified

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