Ruben Fiszel rubenfiszel
rubenfiszel
/ permutations.scala
Last active
August 29, 2015 14:08
Find all permutations of a Number in Scala with memoization (optimal)
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| def remove(num: Int, list: List[Int]) = list diff List(num) | |
| var mem: Map[List[Int], List[List[Int]]] = Map() | |
| def permutations(l:List[Int]):List[List[Int]] = | |
| if (l.length == 1) List(l) | |
| else { | |
| if (mem.contains(l)) mem(l) | |
| else { | |
| val r = l.flatMap(x=> permutations(remove(x, l)).map(y=> x::y)) |
rubenfiszel
/ poc.scala
Last active
February 13, 2016 23:30
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| val conf: MultiLayerConfiguration = new NeuralNetConfiguration.Builder() | |
| .seed(seed) | |
| .iterations(iterations) | |
| .learningRate(1e-1f) | |
| .optimizationAlgo(OptimizationAlgorithm.CONJUGATE_GRADIENT) | |
| // .l1(1e-1).l2(2e-4) | |
| // .useDropConnect(true) | |
| .list(3) | |
| .layer(0, new DenseLayer.Builder() | |
| .nIn(50) |
rubenfiszel
/ nn
Created
February 14, 2016 11:48
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| val iterations = 500 | |
| val seed = 456 | |
| val listenerFreq = 1 | |
| val batchSize = 100 | |
| val numEx = 5000 | |
| val server = UiServer.getInstance(); | |
| log.info("Started on port " + server.getPort()); | |
| log.info("Load data....") |
rubenfiszel
/ nn.scala
Created
February 14, 2016 11:48
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| val iterations = 500 | |
| val seed = 456 | |
| val listenerFreq = 1 | |
| val batchSize = 100 | |
| val numEx = 5000 | |
| val server = UiServer.getInstance(); | |
| log.info("Started on port " + server.getPort()); | |
| log.info("Load data....") |
rubenfiszel
/ nn2.scala
Created
February 14, 2016 12:17
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| val iterations = 1 | |
| val seed = 456 | |
| val listenerFreq = 1 | |
| val batchSize = 100 | |
| val numEx = 5000 | |
| val server = UiServer.getInstance(); | |
| log.info("Started on port " + server.getPort()); |
rubenfiszel
/ dep.sbt
Created
February 15, 2016 16:07
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| resolvers += "Sonatype OSS Snapshots" at "https://oss.sonatype.org/content/repositories/snapshots" | |
| libraryDependencies ++= Seq( | |
| "org.deeplearning4j" % "deeplearning4j-core" % "0.4-rc3.9-SNAPSHOT", | |
| "org.deeplearning4j" % "deeplearning4j-ui" % "0.4-rc3.9-SNAPSHOT", | |
| "org.nd4j" % "nd4j-x86" % "0.4-rc3.9-SNAPSHOT" | |
| ) |
rubenfiszel
/ trace
Created
March 2, 2016 22:52
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| [error] (run-main-0) java.lang.ArrayIndexOutOfBoundsException: 960 | |
| java.lang.ArrayIndexOutOfBoundsException: 960 | |
| at org.nd4j.linalg.api.buffer.BaseDataBuffer.put(BaseDataBuffer.java:869) | |
| at org.nd4j.linalg.api.buffer.BaseDataBuffer.put(BaseDataBuffer.java:860) | |
| at org.nd4j.linalg.api.buffer.BaseDataBuffer.copyAtStride(BaseDataBuffer.java:441) | |
| at org.nd4j.linalg.api.ndarray.BaseNDArray.assign(BaseNDArray.java:1025) | |
| at org.nd4j.linalg.api.ndarray.BaseNDArray.reshape(BaseNDArray.java:3198) | |
| at org.nd4j.linalg.api.ndarray.BaseNDArray.reshape(BaseNDArray.java:3238) | |
| at ccup.GameFetcher$.normalizeInput(GameFetcher.scala:60) | |
| at ccup.GameFetcher2.fetch(GameFetcher.scala:103) |
rubenfiszel
/ trace
Created
March 2, 2016 22:54
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| java.lang.IllegalStateException: Invalid data transform; features and labels do not have equal rows. First was 1 labels was 100 | |
| at org.nd4j.linalg.dataset.DataSet.<init>(DataSet.java:85) | |
| at org.nd4j.linalg.dataset.DataSet.<init>(DataSet.java:73) | |
| at ccup.GameFetcher2.fetch(GameFetcher.scala:110) | |
| at org.deeplearning4j.datasets.iterator.BaseDatasetIterator.next(BaseDatasetIterator.java:56) | |
| at org.deeplearning4j.datasets.iterator.BaseDatasetIterator.next(BaseDatasetIterator.java:33) | |
| at org.deeplearning4j.nn.graph.ComputationGraph.fit(ComputationGraph.java:467) | |
| at ccup.SelfPlay$.train2(SelfPlay.scala:320) | |
| at ccup.SoloGame$.delayedEndpoint$ccup$SoloGame$1(SoloGame.scala:14) | |
| at ccup.SoloGame$delayedInit$body.apply(SoloGame.scala:6) |
rubenfiszel
/ trace
Created
March 2, 2016 23:12
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| java.lang.IllegalStateException: Unable to get number of of rows for a non 2d matrix | |
| at org.nd4j.linalg.api.ndarray.BaseNDArray.rows(BaseNDArray.java:3411) | |
| at org.nd4j.linalg.api.ndarray.BaseNDArray.mmul(BaseNDArray.java:2321) | |
| at org.deeplearning4j.nn.layers.BaseLayer.preOutput(BaseLayer.java:327) | |
| at org.deeplearning4j.nn.layers.BaseLayer.activate(BaseLayer.java:338) | |
| at org.deeplearning4j.nn.layers.BaseLayer.activate(BaseLayer.java:358) | |
| at org.deeplearning4j.nn.graph.vertex.impl.LayerVertex.doForward(LayerVertex.java:87) | |
| at org.deeplearning4j.nn.graph.ComputationGraph.feedForward(ComputationGraph.java:738) | |
| at org.deeplearning4j.nn.graph.ComputationGraph.computeGradientAndScore(ComputationGraph.java:663) | |
| at org.deeplearning4j.optimize.solvers.BaseOptimizer.gradientAndScore(BaseOptimizer.java:150) |
rubenfiszel
/ build.sbt
Created
March 2, 2016 23:14
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| name := "codecup" | |
| version := "0.3" | |
| scalaVersion := "2.11.7" | |
| scalacOptions += "-deprecation" | |
| scalacOptions += "-unchecked" |
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