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Caffe2 Quick Start Guide

You're reading from Caffe2 Quick Start Guide

Product type Book

Published in May 2019

Publisher Packt

ISBN-13 9781789137750

Pages 136 pages

Edition 1st Edition

Languages

Concepts

Author (1):

Ashwin Nanjappa

Table of Contents (9) Chapters

Preface

1. Introduction and Installation

2. Composing Networks

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

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Converting a Caffe2 model to Caffe

In the previous sections in this chapter, we focused on how to convert a Caffe model to a Caffe2 model. Since Caffe is not being actively developed now, and Caffe2 was, in part, created to supersede Caffe2, this path of migrating a Caffe model to Caffe2 is what the majority of users are interested in.

However, if you need to use a Caffe2 model in Caffe, then that process is bound to be more arduous. There does not seem to be any direct way to convert a Caffe2 model to Caffe. If you are sure that the Caffe2 operators and their arguments are fully supported in Caffe, then you could try going through an intermediary format such as ONNX (see Chapter 5, Working with Other Frameworks).

If the ONNX route is not feasible, then you might have to resort to executing the following tasks manually:

Export Caffe2 operators, arguments, and weights of the model...

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Authors (1)

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.

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