Fine-tuning neural graphics models with Model Gym

About this Learning Path

Who is this for?

This is an advanced topic for developers exploring neural graphics and interested in training and deploying upscaling models like Neural Super Sampling (NSS) using PyTorch and Arm’s hardware-aware backend.

What will you learn?

Upon completion of this Learning Path, you will be able to:

• Understand the principles of neural graphics and how it’s applied to game performance
• Learn how to fine-tune and evaluate a neural network for Neural Super Sampling (NSS)
• Use the Model Gym Python API and CLI to configure and train neural graphics models
• Visualize and inspect .vgf models using the Model Explorer tool

Prerequisites

Before starting, you will need the following:

• Basic understanding of PyTorch and machine learning concepts
• A development machine running Ubuntu 22.04, with a CUDA-capable NVIDIA® GPU
• CUDA Toolkit version 11.8 or later