singa-dev mailing list archives

Site index · List index
Message view « Date » · « Thread »
Top « Date » · « Thread »
From "wangwei (JIRA)" <j...@apache.org>
Subject [jira] [Created] (SINGA-383) Add Separable Convolution for autograd
Date Fri, 13 Jul 2018 06:54:00 GMT
wangwei created SINGA-383:
-----------------------------

             Summary: Add Separable Convolution for autograd
                 Key: SINGA-383
                 URL: https://issues.apache.org/jira/browse/SINGA-383
             Project: Singa
          Issue Type: New Feature
            Reporter: wangwei


This type of convolution is used in [Xception model|https://arxiv.org/pdf/1610.02357.pdf]
and is supported by [other libraries|[https://github.com/pytorch/pytorch/issues/1708].]

 

To implement it in Singa, we create a new operation (separable_conv_2d) by calling a depthwise_conv_2d
(normal convolution with number of output channels=1, and number of groups = number of input
channels); and then calling normal convolution with number of groups=1, and kernel size=1,
i.e. pointwise convolution.



--
This message was sent by Atlassian JIRA
(v7.6.3#76005)

Mime
View raw message