Carsten, Thank you for your patience. Following discussions with Numenta engineering, I will try to have this resolved by end of day Wednesday latest...
Cheers! David On Mon, Oct 19, 2015 at 9:42 AM, Carsten Schnober < [email protected]> wrote: > Sure, here's the stacktrace: > > Exception in thread "main" java.lang.IllegalArgumentException: Cannot > initialize this Sensor's MultiEncoder with a null settings > at > org.numenta.nupic.network.sensor.HTMSensor.initEncoders(HTMSensor.java:595) > at > org.numenta.nupic.network.sensor.HTMSensor.initEncoder(HTMSensor.java:566) > at org.numenta.nupic.network.Network.setSensor(Network.java:549) > at org.numenta.nupic.network.Region.setNetwork(Region.java:126) > at org.numenta.nupic.network.Network.add(Network.java:489) > at > > org.numenta.nupic.examples.category_prediction.CategoryPrediction.main(CategoryPrediction.java:43) > > The tokens.txt file is here: > https://gist.github.com/carschno/c0504952c9f7f7f9799a > > Carsten > > > Am 19.10.2015 um 16:11 schrieb cogmission (David Ray): > > Hi Carsten, > > > > This is a two-parter... > > > > I can help with the first, and maybe @rhyolight can help with the second. > > > > RE: The first problem (IllegalArgumentException) can you write back with > > your whole stack trace? > > > > We'll take it from there... > > > > Cheers, > > David > > > > On Mon, Oct 19, 2015 at 8:15 AM, Carsten Schnober > > <[email protected] > > <mailto:[email protected]>> wrote: > > > > Hi, > > To get started with HTM(.java), I am trying to re-implement the > category > > prediction example from the Python version in Java. > > However, I am trying to figure out the exact model parameters as > > specified here: > > > https://github.com/numenta/nupic/blob/master/examples/prediction/category_prediction/run.py > > > > At first, I am trying to decode the Python example in as much detail > as > > I am able to. Please correct me where I am wrong: > > > > The model: > > - CLA > > - One region, one layer with a spatial pooler and a temporal memory. > > > > Sensor: > > - read the token list (produced beforehand, one token per line, no > > stopwords, sequential order). > > > > Hence, what I am aiming for in the Java implementation (pseudo-code): > > - Create a CLA model: `Network.create("CLA", parameters)` > > - Create a region: > > `model.add(Network.createRegion("CLAClassifierRegion"))` > > - Create a layer: `region.add(Network.createLayer("Layer 2/3", > > parameters) > > .add(new SpatialPooler()) > > .add(new TemporalMemory())` > > - Add a sensor to the layer: > > `layer.add(Sensor.create(FileSensor::create, > > SensorParams.create(Keys::path, "", > tokensFile.getAbsolutePath())))));` > > > > > > The first issue I run into is the sensor which causes a > > IllegalArgumentException: > > Exception in thread "main" java.lang.IllegalArgumentException: Cannot > > initialize this Sensor's MultiEncoder with a null settings > > > > I suspect this might have to do with the FileSensor requiring a CSV > > file, doesn't it? The tokens with, however, is one token per line. I > was > > hoping that this somehow corresponds to a CSV with a single column > > though. > > > > Furthermore, I am not sure how to train and run the network in the > > following. I've created a gist with my initial start, perhaps you > could > > comment on that: > https://gist.github.com/carschno/7f3828c2ea0c1a2b3be9 > > > > Thanks! > > Carsten > > > > > > > > -- > > Carsten Schnober > > Doctoral Researcher > > Ubiquitous Knowledge Processing (UKP) Lab > > FB 20 / Computer Science Department > > Technische Universität Darmstadt > > Hochschulstr. 10, D-64289 Darmstadt, Germany > > phone [+49] (0)6151 16-6227 > > <tel:%5B%2B49%5D%20%280%296151%2016-6227>, fax -5455, room S2/02/B111 > > [email protected] > > <mailto:[email protected]> > > www.ukp.tu-darmstadt.de <http://www.ukp.tu-darmstadt.de> > > > > Web Research at TU Darmstadt (WeRC): www.werc.tu-darmstadt.de > > <http://www.werc.tu-darmstadt.de> > > GRK 1994: Adaptive Preparation of Information from Heterogeneous > Sources > > (AIPHES): www.aiphes.tu-darmstadt.de < > http://www.aiphes.tu-darmstadt.de> > > PhD program: Knowledge Discovery in Scientific Literature (KDSL) > > www.kdsl.tu-darmstadt.de <http://www.kdsl.tu-darmstadt.de> > > > > > > > > > > -- > > /With kind regards,/ > > > > David Ray > > Java Solutions Architect > > > > *Cortical.io <http://cortical.io/>* > > Sponsor of: HTM.java <https://github.com/numenta/htm.java> > > > > [email protected] <mailto:[email protected]> > > http://cortical.io <http://cortical.io/> > > -- > Carsten Schnober > Doctoral Researcher > Ubiquitous Knowledge Processing (UKP) Lab > FB 20 / Computer Science Department > Technische Universität Darmstadt > Hochschulstr. 10, D-64289 Darmstadt, Germany > phone [+49] (0)6151 16-6227, fax -5455, room S2/02/B111 > [email protected] > www.ukp.tu-darmstadt.de > > Web Research at TU Darmstadt (WeRC): www.werc.tu-darmstadt.de > GRK 1994: Adaptive Preparation of Information from Heterogeneous Sources > (AIPHES): www.aiphes.tu-darmstadt.de > PhD program: Knowledge Discovery in Scientific Literature (KDSL) > www.kdsl.tu-darmstadt.de > > -- *With kind regards,* David Ray Java Solutions Architect *Cortical.io <http://cortical.io/>* Sponsor of: HTM.java <https://github.com/numenta/htm.java> [email protected] http://cortical.io
