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From "wangwei (JIRA)" <>
Subject [jira] [Commented] (SINGA-137) To be compatible with Caffe's data format and neural net configuration
Date Tue, 27 Sep 2016 08:30:20 GMT


wangwei commented on SINGA-137:

Yes. We would include popular models like VGG.
1. We have provided the IO component for saving snapshots, which could be used like this
Adding a save/load function into net class (
would be useful. You are also welcomed to help implement it.
2. There are examples of vgg/alexnet/resnet using pysinga. We have trained CPP versions of
resent and alexnet over ImageNet, and would create a webpage to share them.

BTW, we have tested the size of vgg-16 using protobuf for serialization, which is about 600MB (would be merged into master soon).

> To be compatible with Caffe's data format and neural net configuration
> ----------------------------------------------------------------------
>                 Key: SINGA-137
>                 URL:
>             Project: Singa
>          Issue Type: New Feature
>            Reporter: wangwei
>            Assignee: Xiangrui
>              Labels: Caffe
> Caffe has many built-in models and a large user base.
> If we can train over Caffe's data (input data prepared using Caffe's tools) and neural
net configuration, it would help users to switch from Caffe to SINGA for distributed training.

> Here are two options.
> 1. update SINGA's variable name and some data structure to be consistent with Caffe.
> 2. write scripts/tools to convert Caffe's configuration protocol into SINGA protocol.

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