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Posted to issues@mxnet.apache.org by "ASF GitHub Bot (JIRA)" <ji...@apache.org> on 2018/03/08 04:22:00 UTC

[jira] [Commented] (MXNET-58) Add LayerNorm in MXNet

    [ https://issues.apache.org/jira/browse/MXNET-58?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16390723#comment-16390723 ] 

ASF GitHub Bot commented on MXNET-58:
-------------------------------------

sxjscience commented on issue #10029: [MXNET-58]Layer Normalization in C++
URL: https://github.com/apache/incubator-mxnet/pull/10029#issuecomment-371374211
 
 
   Here's the new doc of InstanceNorm http://mxnet-ci-doc.s3-accelerate.dualstack.amazonaws.com/PR-10029/4/api/python/gluon/nn.html#mxnet.gluon.nn.LayerNorm @zhanghang1989 

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> Add LayerNorm in MXNet
> ----------------------
>
>                 Key: MXNET-58
>                 URL: https://issues.apache.org/jira/browse/MXNET-58
>             Project: Apache MXNet
>          Issue Type: New Feature
>            Reporter: Xingjian Shi
>            Priority: Major
>
> # Directly implement layer normalization in C++. The speed and memory cost are both better than the way of stacking the broadcast/reduce OPs. Solves [#9950|https://github.com/apache/incubator-mxnet/issues/9950]
>  # Add LayerNorm in Gluon
>  # Fix the doc of InstanceNorm. In InstanceNorm, the real axis to normalize the input tensor is all axes excluding the 0th axis and the given axis.
>  # Fix the doc of BatchNorm, the inverse std instead of the var is set as the output. Should fix [#9216|https://github.com/apache/incubator-mxnet/issues/9216]



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