Getting Started

This section covers the usage of Renate from the installation to the training of a model. The content is intended to explain the basic steps to be taken when creating a new training pipeline based on Renate.

If your goal is to test multiple Renate algorithms on your dataset or to test a specific algorithm on multiple datasets and scenarios, you will be better served by the benchmarking functionalities provided in Renate Benchmarks.

• Installation
• How to Write a Config File
  • Model Definition
  • Loss Definition
  • Data Preparation
  • Optimizer
  • Learning Rate Schedulers
  • Transforms
  • Custom Metrics
  • Custom Function Arguments
• How to Run a Training Job
  • Setup
  • Run a local training job
  • Run a training job on SageMaker
  • Run a training job with HPO
  • Custom Function Arguments
• Renate’s output
  • Loading the Updated Model
• Supported Algorithms
• Avalanche - Usage and Limitations
  • Usage
  • Limitations
• Distribution Shift Detection
  • Shift Types
  • Shift Detector Interface
  • Available Methods
  • Example