Skip to content

SR-Forge

Overview

Initializing search

Home
Getting Started
Anatomy of a Training
Architecture
Core Concepts
FAQ — “How do I…?”
Cheatsheet
Guide
API

SR-Forge

Home
Getting Started
Anatomy of a Training
Architecture
Core Concepts
FAQ — “How do I…?”
Cheatsheet
Guide
Guide
- Entry
- Collation
- Datasets
- Transforms
  Transforms
- IO Binding
- Models
  Models
- Losses
- Writing Scripts
- Trainers & Runners
- Distributed & Multi-GPU
- Configuration
- Experiment Tracking
- Hooks
- Observers & Events (legacy)
- Extending SR-Forge
API
API
- Config
- Registry
- Deprecation
- Models
  Models
  - Basic
  - SISR
    SISR
    
    DSen2
    
    FSRCNN
  - MISR
    MISR
    
    MagNAt
    
    RAMS
    
    TRMISR
- Transforms
- Data
  Data
  - Core Structures
  - Collation
  - Loader
  - Multispectral
    Multispectral
    
    Overview
    
    Descriptors
    
    Utilities
- Datasets
  Datasets
- Loss
  Loss
- Training
  Training
- Observers
  Observers
- Neural Networks
  Neural Networks
  - Graph
    Graph
    
    Overview Overview
    Table of contents
    
    graph
    
    Convolution
    
    Interpolation
- Events
- Utilities
  Utilities
  - IO

Table of contents

graph

Home
API
Neural Networks
Graph

SR-Forge

Graph Neural Networks¶

Was this page helpful?

Thanks for your feedback!

Thanks! Help us improve by opening an issue.

Made with Material for MkDocs