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https://issues.apache.org/jira/browse/SYSTEMML-1678?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Glenn Weidner updated SYSTEMML-1678:
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Fix Version/s: (was: SystemML 1.0)
SystemML 0.15
> Add new 1D top_k utility function
> ---------------------------------
>
> Key: SYSTEMML-1678
> URL: https://issues.apache.org/jira/browse/SYSTEMML-1678
> Project: SystemML
> Issue Type: New Feature
> Reporter: Mike Dusenberry
> Assignee: Fei Hu
> Fix For: SystemML 0.15
>
>
> We should add new {{top_k}} and {{top_k2d}} utility functions (in
> {{nn/util.dml}}) that accept a matrix {{X}} and return matrices {{values}}
> and {{indices}} with the top {{k}} values (i.e. probabilities) and associated
> indices (i.e. classes) along a certain dimension. This will be modeled after
> the [{{top_k}} function in TensorFlow |
> https://www.tensorflow.org/api_docs/python/tf/nn/top_k] For the 1D case,
> {{top_k}} will operate on the columns dimension. A typical use case is that
> in which {{X}} is the output of a {{softmax}} layer (so each row contains a
> set of normalized class probabilities), and {{values}} and {{indices}} will
> contain rows with the top {{k}} probabilities and class indices as described
> above. For the 2D case, {{top_k}} will operate on the channels dimension. A
> typical use case here is that in which {{X}} is the output of a {{softmax2d}}
> layer (so each channel contains a set of normalized class probabilities), and
> {{values}} and {{indices}} will contain the top {{k}} probabilities and
> indices along the channel axis. This scenario would be common in an image
> segmentation problem, in which every pixel of the output image will have a
> set of class probabilities along the channel axis.
> Having these {{top-k}} functions will allow us to extract either predict a
> single class for each item, or the top {{k}} classes, and therefore may be
> more useful that a {{predict_class}} function.
> Although we will use {{values}} and {{indices}} as the names of the returned
> matrices within the functions, in practice, one is likely to name the results
> {{probs}} and {{classes}} in the calling environment.
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