Book Image

Caffe2 Quick Start Guide

By : Ashwin Nanjappa
Book Image

Caffe2 Quick Start Guide

By: Ashwin Nanjappa

Overview of this book

Caffe2 is a popular deep learning library used for fast and scalable training, and inference of deep learning models on different platforms. This book introduces you to the Caffe2 framework and demonstrates how you can leverage its power to build, train, and deploy efficient neural network models at scale. The Caffe 2 Quick Start Guide will help you in installing Caffe2, composing networks using its operators, training models, and deploying models to different architectures. The book will also guide you on how to import models from Caffe and other frameworks using the ONNX interchange format. You will then cover deep learning accelerators such as CPU and GPU and learn how to deploy Caffe2 models for inference on accelerators using inference engines. Finally, you'll understand how to deploy Caffe2 to a diverse set of hardware, using containers on the cloud and resource-constrained hardware such as Raspberry Pi. By the end of this book, you will not only be able to compose and train popular neural network models with Caffe2, but also deploy them on accelerators, to the cloud and on resource-constrained platforms such as mobile and embedded hardware.
Table of Contents (9 chapters)

Working with Caffe

In Chapter 2, Composing Networks, and Chapter 3, Training Networks, we learned how to compose networks and train them, respectively. In this chapter, we will examine the relationship between Caffe2 and Caffe and look at how to use Caffe models in Caffe2 and vice versa.

The objectives of this chapter are as follows:

  • The relationship between Caffe and Caffe2
  • Introduction to AlexNet
  • Building and installing Caffe
  • Caffe model file formats
  • Caffe2 model file formats
  • Converting a Caffe model to Caffe2
  • Converting a Caffe2 model to Caffe