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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 Selector Analytics?

Selector's software-as-a-service utilizes advanced machine learning and natural language processing to provide self-service analytics that enable quick access to actionable insights, leading to a remarkable reduction in mean time to resolution (MTTR) by up to 90%. The groundbreaking Selector Analytics platform harnesses artificial intelligence alongside machine learning to execute three vital functions, providing network, cloud, and application operators with essential insights. It consolidates data from a vast array of sources, such as configurations, alerts, metrics, events, and logs, which can include information from router logs, device performance statistics, or the settings of devices across the network. After collecting this data, the system normalizes, filters, clusters, and correlates it through established workflows to produce actionable insights. Following this, Selector Analytics employs machine learning-based data analysis to scrutinize metrics and events, facilitating the automated identification of anomalies. This process allows operators to quickly pinpoint and resolve issues, thereby improving overall operational efficiency. By adopting this thorough methodology, organizations not only enhance their data processing capabilities but also gain the ability to make informed decisions driven by real-time analytics. Ultimately, this empowers teams to respond to challenges proactively and adapt swiftly to the dynamic landscape of their operations.

Media

Media

Integrations Supported

Amazon CloudWatch
Elastic Cloud
GitHub
Google Cloud Platform
Grafana
Humio
Lightning AI
Microsoft Azure
Microsoft Teams
MongoDB
New Relic
PagerDuty
PostgreSQL
Prometheus
PyTorch
ServiceNow
SolarWinds Access Rights Manager
Splunk Cloud Platform
Syslog-ng
Zabbix

Integrations Supported

Amazon CloudWatch
Elastic Cloud
GitHub
Google Cloud Platform
Grafana
Humio
Lightning AI
Microsoft Azure
Microsoft Teams
MongoDB
New Relic
PagerDuty
PostgreSQL
Prometheus
PyTorch
ServiceNow
SolarWinds Access Rights Manager
Splunk Cloud Platform
Syslog-ng
Zabbix

API Availability

Has API

API Availability

Has API

Pricing Information

Free
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

TorchMetrics

Company Location

United States

Company Website

torchmetrics.readthedocs.io/en/stable/

Company Facts

Organization Name

Selector

Company Location

United States

Company Website

www.selector.ai/product/

Categories and Features

Application Development

Access Controls/Permissions
Code Assistance
Code Refactoring
Collaboration Tools
Compatibility Testing
Data Modeling
Debugging
Deployment Management
Graphical User Interface
Mobile Development
No-Code
Reporting/Analytics
Software Development
Source Control
Testing Management
Version Control
Web App Development

Categories and Features

Network Monitoring

Bandwidth Monitoring
Baseline Manager
Diagnostic Tools
IP Address Monitoring
Internet Usage Monitoring
Real Time Analytics
Resource Management
SLA Monitoring
Server Monitoring
Uptime Monitoring
Web Traffic Reporting

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