Measure and accelerate PyTorch Inference on Arm servers

Who is this for?

This is an introductory topic for software developers who want to learn how to measure and accelerate the performance of Natural Language Processing (NLP), vision and recommender PyTorch models on Arm-based servers.

What will you learn?

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

• Download and install the PyTorch Benchmarks suite.
• Evaluate PyTorch model inference performance on an Arm-based server using the PyTorch Benchmark suite.
• Compare the model inference performance using eager mode and `torch.compile` mode in PyTorch.

Prerequisites

Before starting, you will need the following:

• An Arm-based instance from a cloud service provider or an on-premise Arm server.