0

Explore Products

Best Sellers

New Releases

Books

Videos

Audiobooks

Free Learning

Caffe2 Quick Start Guide

You're reading from Caffe2 Quick Start Guide Modular and scalable deep learning made easy

Product type Paperback

Published in May 2019

Publisher Packt

ISBN-13 9781789137750

Length 136 pages

Edition 1st Edition

Languages

C++

Tools

Caffe

Concepts

Deep Learning

Author (1):

Ashwin Nanjappa

View More author details

Table of Contents (9) Chapters

Preface

1. Introduction and Installation

2. Composing Networks FREE CHAPTER

3. Training Networks

4. Working with Caffe

5. Working with Other Frameworks

6. Deploying Models to Accelerators for Inference

7. Caffe2 at the Edge and in the cloud

8. Other Books You May Enjoy

Leave a review - let other readers know what you think

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

The rest of the chapter is locked

Register for a free Packt account to unlock a world of extra content!

A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.

Unlock this book and the full library FREE for 7 days

Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of

Start free trial

Renews at AU $24.99/month. Cancel anytime

Authors (1)

Ashwin Nanjappa

Ashwin Nanjappa

Ashwin Nanjappa is a senior architect at NVIDIA, working in the TensorRT team on improving deep learning inference on GPU accelerators. He has a PhD from the National University of Singapore in developing GPU algorithms for the fundamental computational geometry problem of 3D Delaunay triangulation. As a post-doctoral research fellow at the BioInformatics Institute (Singapore), he developed GPU-accelerated machine learning algorithms for pose estimation using depth cameras. As an algorithms research engineer at Visenze (Singapore), he implemented computer vision algorithm pipelines in C++, developed a training framework built upon Caffe in Python, and trained deep learning models for some of the world's most popular online shopping portals.

See other products by Ashwin Nanjappa

Other recommended products

Related to this chapter

Generative Adversarial Networks Cookbook

Generative Adversarial Networks Cookbook

Generative Adversarial Networks have opened up many new possibilities in the machine learning domain. This book is all you need to implement different types of GANs using TensorFlow and Keras, in order to provide optimized and efficient deep learning solutions.

Dec 2018 8h 56m

Generative Adversarial Networks Cookbook

Generative Adversarial Networks Cookbook

Generative Adversarial Networks have opened up many new possibilities in the machine learning domain. This book is all you need to implement different types of GANs using TensorFlow and Keras, in order to provide optimized and efficient deep learning solutions.

Dec 2018 8h 56m

Generative Adversarial Networks Cookbook

Generative Adversarial Networks Cookbook

Generative Adversarial Networks have opened up many new possibilities in the machine learning domain. This book is all you need to implement different types of GANs using TensorFlow and Keras, in order to provide optimized and efficient deep learning solutions.

Dec 2018 8h 56m

Generative Adversarial Networks Cookbook

Generative Adversarial Networks Cookbook

Generative Adversarial Networks have opened up many new possibilities in the machine learning domain. This book is all you need to implement different types of GANs using TensorFlow and Keras, in order to provide optimized and efficient deep learning solutions.

Dec 2018 8h 56m

This book is for programmers who want to delve into parallel computing, become part of the high-performance computing community and apply those techniques to build modern applications. Experience with C++ programming is assumed. There are some sample examples on equivalent Fortran code. For Deep Learning enthusiasts python based sample code is also provided.

Sep 2019 16h 56m

This book is for programmers who want to delve into parallel computing, become part of the high-performance computing community and apply those techniques to build modern applications. Experience with C++ programming is assumed. There are some sample examples on equivalent Fortran code. For Deep Learning enthusiasts python based sample code is also provided.

Sep 2019 16h 56m

This book is for programmers who want to delve into parallel computing, become part of the high-performance computing community and apply those techniques to build modern applications. Experience with C++ programming is assumed. There are some sample examples on equivalent Fortran code. For Deep Learning enthusiasts python based sample code is also provided.

Sep 2019 16h 56m

This book is for programmers who want to delve into parallel computing, become part of the high-performance computing community and apply those techniques to build modern applications. Experience with C++ programming is assumed. There are some sample examples on equivalent Fortran code. For Deep Learning enthusiasts python based sample code is also provided.

Sep 2019 16h 56m

This book is for programmers who want to delve into parallel computing, become part of the high-performance computing community and apply those techniques to build modern applications. Experience with C++ programming is assumed. There are some sample examples on equivalent Fortran code. For Deep Learning enthusiasts python based sample code is also provided.

Sep 2019 16h 56m

This book is for programmers who want to delve into parallel computing, become part of the high-performance computing community and apply those techniques to build modern applications. Experience with C++ programming is assumed. There are some sample examples on equivalent Fortran code. For Deep Learning enthusiasts python based sample code is also provided.

Sep 2019 16h 56m

This book is for programmers who want to delve into parallel computing, become part of the high-performance computing community and apply those techniques to build modern applications. Experience with C++ programming is assumed. There are some sample examples on equivalent Fortran code. For Deep Learning enthusiasts python based sample code is also provided.

Sep 2019 16h 56m

Mastering Computer Vision with TensorFlow 2.x

Mastering Computer Vision with TensorFlow 2.x

You will learn the principles of computer vision and deep learning, and understand various models and architectures with their pros and cons. You will learn how to use TensorFlow 2.x to build your own neural network model and apply it to various computer vision tasks such as image acquiring, processing, and analyzing.

May 2020 14h 20m

Personalised recommendations for you

Based on your interests and search pattern

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Data Governance Handbook

Data Governance Handbook

This book provides a highly focused view of real business outcomes powered by data governance, that resonate with non-data executives such as CFOs and CEOs. You'll also find useful insights into how to implement data governance initiatives.

May 2024 13h 8m

Data Engineering with Databricks Cookbook

Data Engineering with Databricks Cookbook

This book shows you how to use Apache Spark, Delta Lake, and Databricks to build data pipelines, manage and transform data, optimize performance, and more. Additionally, you'll implement DataOps and DevOps practices, and orchestrate data workflows.

May 2024 14h 36m

Azure Data Engineer Associate Certification Guide

Azure Data Engineer Associate Certification Guide

Unlock the power of Azure data engineering with this certification guide, elevating your skills in data processing, storage, and security with the help of practical insights, hands-on exercises, and the latest advancements.

May 2024 18h 16m

Microsoft Power BI Cookbook

Microsoft Power BI Cookbook

Microsoft Power BI is the most sought-after platform for BI professionals' visualization needs. Explore the latest Power BI features, future AI enhancements, and integration with other Power Platform tools via new recipes in this updated edition.

Jul 2024 19h 56m

Python Data Cleaning Cookbook

Python Data Cleaning Cookbook

The book shows you how to clean, wrangle, and view data from multiple perspectives, including dataset and column attributes. You will cover common and not-so-common challenges that are faced while cleaning messy data for complex situations and learn to manipulate data to get it down to a form that can be useful for making the right decisions.

May 2024 16h 12m

Microsoft Azure AI Fundamentals AI-900 Exam Guide

Microsoft Azure AI Fundamentals AI-900 Exam Guide

This AI-900 study guide will help you prepare and practice for the certification exam. You'll delve into AI workloads, ML principles, computer vision, NLP, knowledge mining, and generative AI using Azure cloud services.

May 2024 9h 36m

Using Stable Diffusion with Python

Using Stable Diffusion with Python

This book shows you how to use Python to control Stable Diffusion and generate high-quality images. In addition to covering the basic usage of the diffusers package, the book provides solutions for extending the package for more advanced purposes.

Jun 2024 11h 44m

Getting Started with DuckDB

Getting Started with DuckDB

This hands-on book teaches you to analyze large datasets with blazing speed and ease. You will learn how to use DuckDB to quickly load, query, transform, analyze, and visualize data effectively through a series of practical examples.

Jun 2024 12h 44m

Databricks Certified Associate Developer for Apache Spark Using Python

Databricks Certified Associate Developer for Apache Spark Using Python

This guide gets you ready for certification with expert-backed content, key exam concepts, and topic reviews. Additionally, you'll be able to make the most of Apache Spark 3.0 to modernize workloads and more using specific tools and techniques.