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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 Tensor?

Tensor aspires to be the leading trading platform tailored for professional NFT traders. The platform was born from our personal experiences of frequently flipping NFTs, during which we identified significant gaps in the existing tools. Our quest for improved speed, expanded coverage, more detailed data, and advanced order types inspired the development of Tensor. When users access Tensor, they will find a user-friendly decentralized application (dApp) that operates seamlessly with various elements working together in the background. With our innovative bonding-curve-based orders, available in both linear and exponential formats, traders can easily execute dollar-cost averaging strategies for their NFT investments. We also recognize the importance of promptly listing new collections, catering to traders eager to explore the latest assets. Users can earn trading fees and liquidity provider rewards by supplying liquidity and aiding in the creation of markets for their preferred NFT collections on TensorSwap. Furthermore, market makers are essential in boosting market liquidity, allowing other traders to enter and exit positions at more favorable prices, which ultimately contributes to a lively trading atmosphere. These features combine to make Tensor an essential resource for NFT aficionados aiming to refine their trading approaches, ensuring they have the tools necessary to thrive in a competitive landscape.

Media

Media

Integrations Supported

Base App
Brave Browser
Brave Wallet
Dataoorts GPU Cloud
Glow Wallet
Ledger
Lightning AI
Phantom
PyTorch
Rally
Slope
Solana
Solflare
Torus

Integrations Supported

Base App
Brave Browser
Brave Wallet
Dataoorts GPU Cloud
Glow Wallet
Ledger
Lightning AI
Phantom
PyTorch
Rally
Slope
Solana
Solflare
Torus

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

Tensor

Company Website

www.tensor.trade/

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

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