[jira] [Commented] (SINGA-275) Add Cross Entropy Loss for multiple labels

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    [ https://issues.apache.org/jira/browse/SINGA-275?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15704267#comment-15704267 ] 

ASF subversion and git services commented on SINGA-275:
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Commit d1110c0b7101fff6999db1dd5cccb14bf8370578 in incubator-singa's branch refs/heads/master from [~wangwei.cs]
[ https://git-wip-us.apache.org/repos/asf?p=incubator-singa.git;h=d1110c0 ]

SINGA-275 - Add Cross Entropy Loss for multiple labels

Updated the softmax cross entorpy loss layer and the tensor functions to enable
the ground truth be an binary array for each instance;

Added unittests for cross entropy with multiple labels per instance;

For input of a batch of instances, the ground truth tensor could be either an integer array, one value per
instance, or a binary matrix one row per instance.

For a single instance input, the feature tensor is 1-d array, and the
ground truth tensor is a 1-d array (with a single integer value or a
binary array)


> Add Cross Entropy Loss for multiple labels
> ------------------------------------------
>
>                 Key: SINGA-275
>                 URL: https://issues.apache.org/jira/browse/SINGA-275
>             Project: Singa
>          Issue Type: New Feature
>            Reporter: RUAN PINGCHENG
>            Priority: Critical
>
> A cross entropy loss function can consider for multiple labels. Normalize the label vector during training and testing, e.g, <1, 0, 0, 1> -> <0.5, 0, 0, 0.5>. 



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