Torch.Rb

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torch.rb is an open-source deep learning library for Ruby, powered by LibTorch. It enables Ruby developers to build and deploy machine learning models, including computer vision and NLP tasks.

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At a glance

Pricing

Open Source

Free tier

Yes

API

Yes

Skill level

Technical

About

What is torch.rb?

torch.rb provides deep learning capabilities for Ruby developers, leveraging the power of LibTorch. It allows users to create and manipulate tensors, perform various operations, and build neural networks directly within the Ruby environment. The library closely follows the PyTorch API, with minor adjustments to be more Ruby-like, making it easier for developers familiar with PyTorch to transition. It supports tasks such as image classification, collaborative filtering, and generative adversarial networks, and integrates with TorchVision, TorchText, and TorchAudio for specialized computer vision, NLP, and audio tasks. Performance can be significantly enhanced on GPUs, with support for CUDA on Linux and Metal Performance Shaders (MPS) on Mac.

Best used for

Ideal for developers and researchers who need to implement deep learning models directly within Ruby applications. Especially valuable for those looking to leverage existing PyTorch knowledge in a Ruby environment for tasks like image classification, natural language processing, or building recommendation systems.

Common actions

build deep learning models

implement machine learning

integrate AI into Ruby

process computer vision

develop NLP applications

workflowsautomated workflowopen-sourcedeepfake"AI Agents"github copilotlow-code/no-codecollaborationface swapping

Capabilities

Key features

Deep learning for Ruby
LibTorch powered
PyTorch API compatible
Tensor operations
Neural network building
Autograd for gradients
GPU acceleration

Target Audience

ruby developersmachine learning engineersdata scientists

Integrations

Not yet documented

Pricing & Plans

Open Source

Free

FAQs

What are the system requirements for using torch.rb?

To use torch.rb, you first need to download and install LibTorch. For Mac arm64, a specific curl command is provided. For Linux x86-64, you'll need the build matching your CUDA version. Windows is not currently supported, and compiling the extension can take 5-10 minutes.

How does torch.rb's API differ from PyTorch?

torch.rb largely follows the PyTorch API but includes Ruby-specific conventions. Methods for in-place modifications end with '!' (e.g., `add!`), boolean-returning methods use '?' (e.g., `tensor?`), and Numo is used instead of NumPy for array conversions.

Can torch.rb utilize GPUs for faster processing?

Yes, torch.rb supports GPU acceleration. On Linux, you can use CUDA by installing CUDA and cuDNN. On Mac with Apple silicon, it can leverage Metal Performance Shaders (MPS). The documentation provides instructions for checking availability and moving neural networks to the GPU.

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Content & Design › Audio & Music Research & Education › Scientific Computing

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