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From "ASF GitHub Bot (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (HORN-32) Support RNN
Date Sat, 03 Dec 2016 23:31:59 GMT

    [ https://issues.apache.org/jira/browse/HORN-32?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15718928#comment-15718928
] 

ASF GitHub Bot commented on HORN-32:
------------------------------------

GitHub user ssallys opened a pull request:

    https://github.com/apache/incubator-horn/pull/31

    HORN-32: Support RNN

    This implements basic RNN model which supports  not only the  Elman net but also the recurrent
model with the multi-layered neurons.
    Example can be run by the following command.
    
    >> MNIST RNN example
    bin/horn jar target/horn-0.1.0-SNAPSHOT.jar MnistRecurrentMultiLayerPerceptron ./model_rnn
mnist.seq 0.01 0.9 0.0005 196 200 10 4 1 10 12000
    
    >> Exclusive OR example
     * preparing dataset
    bin/horn jar target/horn-0.1.0-SNAPSHOT.jar ExclusiveOrConverter
    
     * training
    bin/horn jar target/horn-0.1.0-SNAPSHOT.jar ExclusiveOrRecurrentMultiLayerPerceptron ./model_semi_rnn
semi.seq 0.01 0.9 0.0005 1 2 2 2 1 10 10000


You can merge this pull request into a Git repository by running:

    $ git pull https://github.com/ssallys/incubator-horn HORN-32

Alternatively you can review and apply these changes as the patch at:

    https://github.com/apache/incubator-horn/pull/31.patch

To close this pull request, make a commit to your master/trunk branch
with (at least) the following in the commit message:

    This closes #31
    
----
commit 7335639eb42c2914de8ee12386082e6906e21168
Author: Yeounhee Lee <leeyh@etri.re.kr>
Date:   2016-11-25T05:15:03Z

    HORN-32: Support RNN

----


> Support RNN
> -----------
>
>                 Key: HORN-32
>                 URL: https://issues.apache.org/jira/browse/HORN-32
>             Project: Apache Horn
>          Issue Type: New Feature
>            Reporter: Yeounhee Lee
>            Assignee: Yeounhee Lee
>
> This implements basic RNN neuron to support RNN models like a Elman net.
> Basic unit might be a simple RNN neuron, which will be extended to LSTM later on.



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