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Date: Tue, 3 Nov 2015 14:34:28 +0000 (UTC)
From: "Thomas Jungblut (JIRA)" <jira@apache.org>
To: dev@horn.incubator.apache.org
Message-ID: <JIRA.12906953.1445480233000.137108.1446561268168@Atlassian.JIRA>
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Subject: [jira] [Commented] (HORN-4) Designing Programming APIs
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    [ https://issues.apache.org/jira/browse/HORN-4?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14987365#comment-14987365 ] 

Thomas Jungblut commented on HORN-4:
------------------------------------

I think it is a very powerful idea as well. I see some technical difficulties here. Let's try to get a small multi-layer perceptron running with Rootbeer and a neuron-centric model on a local machine and see the feasibility. I see some issues with convolutions and tensors and in the configuration of these. 

> Designing Programming APIs
> --------------------------
>
>                 Key: HORN-4
>                 URL: https://issues.apache.org/jira/browse/HORN-4
>             Project: Apache Horn
>          Issue Type: Sub-task
>          Components: api
>            Reporter: Edward J. Yoon
>
> As described in original proposal, we will have neuron-centric programming interface (or we can support multiple programming paradigms e.g., layer-centric). Regarding languages, we're going to be supporting a number of languages such as Java, Python, Scala.
> At the moment, I'll focus only on Java-based neuron-centric in this ticket. 
> Below is my rough sketch. I suggest that we provides two methods: upward and downward. The reason of separating into two methods is to provide more intuitive programming model and reduce user-side code complexity. The up or downward can be determined by message type internally, and basically each neuron can be activated only when the messages are delivered. 
> {code}
> public interface NeuronInterface<M extends Writable> {
>   /**
>    * This method is called when the messages are propagated from the lower
>    * layer. It can be used to determine if the neuron would activate, or fire.
>    * 
>    * @param messages
>    * @throws IOException
>    */
>   public void upward(Iterable<M> messages) throws IOException;
>   /**
>    * This method is called when the errors are propagated from the upper layer.
>    * It can be used to calculate the error of each neuron and change the
>    * weights.
>    * 
>    * @param messages
>    * @throws IOException
>    */
>   public void downward(Iterable<M> messages) throws IOException;
> }
> {code}


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