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Posted to dev@singa.apache.org by "ASF subversion and git services (JIRA)" <ji...@apache.org> on 2016/12/23 03:44:58 UTC
[jira] [Commented] (SINGA-278) Convert trained caffe parameters to
singa
[ https://issues.apache.org/jira/browse/SINGA-278?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15771783#comment-15771783 ]
ASF subversion and git services commented on SINGA-278:
-------------------------------------------------------
Commit eca642bc6f542dcdd3220f148b50521b5619c2ae in incubator-singa's branch refs/heads/master from wangwei
[ https://git-wip-us.apache.org/repos/asf?p=incubator-singa.git;h=eca642b ]
SINGA-278 Convert trained caffe parameters to singa
Update the running instructions in the readme file
> Convert trained caffe parameters to singa
> -----------------------------------------
>
> Key: SINGA-278
> URL: https://issues.apache.org/jira/browse/SINGA-278
> Project: Singa
> Issue Type: New Feature
> Reporter: Xiangrui
>
> Convert trained parameters of caffe model to singa.
> Run vgg as an example. Some tricks should be noticed:
> 1. The order of image axes in caffe is height, width and channels due to opencv implementation, while it is width, height, channels in singa if you use python PIL.
> 2. Another problem caused by these two libraries is the order of channels, BGR(caffe, opencv) v.s. RGB(singa, PIL).
> 3. It needs to transpose the weight tensor in InnerProduct(Dense) layer.
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