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You're reading from  Caffe2 Quick Start Guide

Product typeBook
Published inMay 2019
Reading LevelBeginner
PublisherPackt
ISBN-139781789137750
Edition1st Edition
Languages
C++
Tools
Caffe
Concepts
Deep Learning
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Author (1)
Ashwin Nanjappa
Ashwin Nanjappa
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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.
Read more about Ashwin Nanjappa

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ONNX in Caffe2

Caffe2 has built-in support for ONNX. This includes support for exporting Caffe2 models to ONNX format and importing ONNX models directly for inference in Caffe2. C++ source files related to Caffe2's support of ONNX can be found in the onnx directory in the Caffe2 source code. Python source files that provide the frontend and backend support for ONNX can be found in the python/onnx directory in the Caffe2 source code.

The onnx/onnx_exporter.h and onnx/onnx_exporter.cc contain the definitions necessary to export a Caffe2 model to ONNX format. Support for exporting from Caffe2 to ONNX includes details such as the mapping from Caffe2 to ONNX for operators, data types, and transformations of data.

For example, in onnx/onnx_exporter.cc we find the following mapping of some Caffe2 operators to ONNX operators:

const std::unordered_map<std::string, std::string>...
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Caffe2 Quick Start Guide
Published in: May 2019Publisher: PacktISBN-13: 9781789137750
© 2019 Packt Publishing Limited All Rights Reserved

Author (1)

author image
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.
Read more about Ashwin Nanjappa

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