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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