Caffe2 Quick Start Guide

Modular and scalable deep learning made easy

By: Ashwin Nanjappa

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eText | 31 May 2019 | Edition Number 1

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Build and train scalable neural network models on various platforms by leveraging the power of Caffe2

Key Features

Migrate models trained with other deep learning frameworks to Caffe2
Integrate Caffe2 with Android or iOS, and implement deep learning models for mobile devices
Leverage the distributed capabilities of Caffe2 to build models that scale easily

Book Description

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.

What you will learn

Build and install Caffe2
Compose neural networks
Import deep learning models from other frameworks
Train neural networks on a CPU or GPU
Deploy models at the edge and in the cloud
Import a neural network from Caffe
Deploy models on CPU or GPU accelerators using inference engines

Who this book is for

Data scientists and machine learning engineers who wish to create fast and scalable deep learning models in Caffe2 will find this book to be very useful. Some understanding of the basic machine learning concepts and prior exposure to programming languages like C++ and Python will be useful.