From dev-return-310047-archive-asf-public=cust-asf.ponee.io@lucene.apache.org Mon Jan 29 18:21:06 2018 Return-Path: X-Original-To: archive-asf-public@eu.ponee.io Delivered-To: archive-asf-public@eu.ponee.io Received: from cust-asf.ponee.io (cust-asf.ponee.io [163.172.22.183]) by mx-eu-01.ponee.io (Postfix) with ESMTP id 9B78C180658 for ; Mon, 29 Jan 2018 18:21:06 +0100 (CET) Received: by cust-asf.ponee.io (Postfix) id 8B28C160C2C; Mon, 29 Jan 2018 17:21:06 +0000 (UTC) Delivered-To: archive-asf-public@cust-asf.ponee.io Received: from mail.apache.org (hermes.apache.org [140.211.11.3]) by cust-asf.ponee.io (Postfix) with SMTP id D23E2160C31 for ; Mon, 29 Jan 2018 18:21:05 +0100 (CET) Received: (qmail 51230 invoked by uid 500); 29 Jan 2018 17:21:04 -0000 Mailing-List: contact dev-help@lucene.apache.org; run by ezmlm Precedence: bulk List-Help: List-Unsubscribe: List-Post: List-Id: Reply-To: dev@lucene.apache.org Delivered-To: mailing list dev@lucene.apache.org Received: (qmail 51152 invoked by uid 99); 29 Jan 2018 17:21:04 -0000 Received: from pnap-us-west-generic-nat.apache.org (HELO spamd2-us-west.apache.org) (209.188.14.142) by apache.org (qpsmtpd/0.29) with ESMTP; Mon, 29 Jan 2018 17:21:04 +0000 Received: from localhost (localhost [127.0.0.1]) by spamd2-us-west.apache.org (ASF Mail Server at spamd2-us-west.apache.org) with ESMTP id F3FAC1A3059 for ; Mon, 29 Jan 2018 17:21:03 +0000 (UTC) X-Virus-Scanned: Debian amavisd-new at spamd2-us-west.apache.org X-Spam-Flag: NO X-Spam-Score: -101.511 X-Spam-Level: X-Spam-Status: No, score=-101.511 tagged_above=-999 required=6.31 tests=[KAM_ASCII_DIVIDERS=0.8, RCVD_IN_DNSWL_MED=-2.3, SPF_PASS=-0.001, T_RP_MATCHES_RCVD=-0.01, USER_IN_WHITELIST=-100] autolearn=disabled Received: from mx1-lw-eu.apache.org ([10.40.0.8]) by localhost (spamd2-us-west.apache.org [10.40.0.9]) (amavisd-new, port 10024) with ESMTP id x5B9D2ptnNqg for ; Mon, 29 Jan 2018 17:21:02 +0000 (UTC) Received: from mailrelay1-us-west.apache.org (mailrelay1-us-west.apache.org [209.188.14.139]) by mx1-lw-eu.apache.org (ASF Mail Server at mx1-lw-eu.apache.org) with ESMTP id 102D85F47E for ; Mon, 29 Jan 2018 17:21:02 +0000 (UTC) Received: from jira-lw-us.apache.org (unknown [207.244.88.139]) by mailrelay1-us-west.apache.org (ASF Mail Server at mailrelay1-us-west.apache.org) with ESMTP id 1E0E0E01D9 for ; Mon, 29 Jan 2018 17:21:01 +0000 (UTC) Received: from jira-lw-us.apache.org (localhost [127.0.0.1]) by jira-lw-us.apache.org (ASF Mail Server at jira-lw-us.apache.org) with ESMTP id 7AA6A240FE for ; Mon, 29 Jan 2018 17:21:00 +0000 (UTC) Date: Mon, 29 Jan 2018 17:21:00 +0000 (UTC) From: "Jeroen Steggink (JIRA)" To: dev@lucene.apache.org Message-ID: In-Reply-To: References: Subject: [jira] [Commented] (SOLR-11838) explore supporting Deeplearning4j NeuralNetwork models MIME-Version: 1.0 Content-Type: text/plain; charset=utf-8 Content-Transfer-Encoding: quoted-printable X-JIRA-FingerPrint: 30527f35849b9dde25b450d4833f0394 [ https://issues.apache.org/jira/browse/SOLR-11838?page=3Dcom.atlassian= .jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=3D1634= 3656#comment-16343656 ]=20 Jeroen Steggink commented on SOLR-11838: ---------------------------------------- As a start, I think applying models for LTR or classifying documents/fields= when indexing would be most useful. One thing we shouldn't underestimate is data structures for Neural Networks= . Depending on the network structure a model may depend on a specific data = structure. For example, timeseries-vectors are very different from other ve= ctors. Are we doing just bag-of-words or do we keep the order of words? How= many fields would your like as input? How many inputs can models have (pre= ferably ComputationGraphs, as they are more flexible). Furthermore, we should think about what is actually going to work. Having o= ne-hot encoding for all terms in an index could be problematic. There is al= ready a=C2=A0logistic regression implementation which works great for simpl= e classification. If we're going to use DL4J it should add something more t= han Solr already offers. Maybe we can think of a few specific use cases to make a prototype for? =C2=A0 I think=C2=A0we can make a DataVec record reader for Solr=C2=A0(@[~kwatters= ]). But I guess this is something we can add to DataVec itself, instead of = adding this to Solr. An alternative could be to use Solr's Streaming API to= return data in a=C2=A0format which is efficient and could be directly used= by DataVec. Another thing I'd like to mention is dependencies. Instead of relying on DL= 4J specifically, we could think about abstracting data input and output for= machine learning and applying models in general. As a DL4J user I'm not ve= ry interested in running it on a Solr server. I have dedicated servers runn= ing DL4J models which I serve using REST APIs. The reason is that I have se= rvers with GPUs and lot's of RAM dedicated for this type of process. Solr o= n the other hand can be very demanding in a different way. =C2=A0 > explore supporting Deeplearning4j NeuralNetwork models > ------------------------------------------------------ > > Key: SOLR-11838 > URL: https://issues.apache.org/jira/browse/SOLR-11838 > Project: Solr > Issue Type: New Feature > Reporter: Christine Poerschke > Priority: Major > Attachments: SOLR-11838.patch > > > [~yuyano] wrote in SOLR-11597: > bq. ... If we think to apply this to more complex neural networks in the = future, we will need to support layers ... > [~malcorn_redhat] wrote in SOLR-11597: > bq. ... In my opinion, if this is a route Solr eventually wants to go, I = think a better strategy would be to just add a dependency on [Deeplearning4= j|https://deeplearning4j.org/] ... > Creating this ticket for the idea to be explored further (if anyone is in= terested in exploring it), complimentary to and independent of the SOLR-115= 97 RankNet related effort. -- This message was sent by Atlassian JIRA (v7.6.3#76005) --------------------------------------------------------------------- To unsubscribe, e-mail: dev-unsubscribe@lucene.apache.org For additional commands, e-mail: dev-help@lucene.apache.org