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Posted to dev@singa.apache.org by "wangwei (JIRA)" <ji...@apache.org> on 2018/07/13 06:54:00 UTC

[jira] [Created] (SINGA-383) Add Separable Convolution for autograd

wangwei created SINGA-383:
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             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.



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