liweigu liweigu
liweigu
/ the input and label
Created
March 30, 2020 07:33
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| ds = ===========INPUT=================== | |
| [[ 0.9206, 0.0396], | |
| [ 1.1601, 1.1761], | |
| [ 0.9884, 1.7857], | |
| [ 0.3592, 1.5785], | |
| [ 0.5957, 0.7707], | |
| [ 0.9643, 1.8737], | |
| [ 2.8688, 1.3088], | |
| [ 2.5304, 0.0485], | |
| [ 1.2180, 0.7743], |
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| package xxxxx; | |
| import java.util.Collections; | |
| import java.util.List; | |
| import java.util.Random; | |
| import org.deeplearning4j.datasets.iterator.impl.ListDataSetIterator; | |
| import org.deeplearning4j.nn.api.OptimizationAlgorithm; | |
| import org.deeplearning4j.nn.conf.NeuralNetConfiguration; | |
| import org.deeplearning4j.nn.conf.layers.DenseLayer; |
liweigu
/ libmkldnn error
Created
September 6, 2018 03:23
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| Caused by: java.lang.RuntimeException: ND4J is probably missing dependencies. For more information, please refer to: http://nd4j.org/getstarted.html | |
| at org.nd4j.nativeblas.NativeOpsHolder.<init>(NativeOpsHolder.java:68) | |
| at org.nd4j.nativeblas.NativeOpsHolder.<clinit>(NativeOpsHolder.java:36) | |
| ... 35 more | |
| Caused by: java.lang.UnsatisfiedLinkError: no jnind4jcpu in java.library.path | |
| at java.lang.ClassLoader.loadLibrary(ClassLoader.java:1867) | |
| at java.lang.Runtime.loadLibrary0(Runtime.java:870) | |
| at java.lang.System.loadLibrary(System.java:1122) | |
| at org.bytedeco.javacpp.Loader.loadLibrary(Loader.java:1224) | |
| at org.bytedeco.javacpp.Loader.load(Loader.java:982) |
liweigu
/ getComputationGraph
Created
September 3, 2018 07:16
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| public ComputationGraph getComputationGraph(){ | |
| ComputationGraph multiLayerNetwork; | |
| NeuralNetConfiguration.Builder builder = new NeuralNetConfiguration.Builder(); | |
| builder.seed(140); | |
| builder.optimizationAlgo(OptimizationAlgorithm.STOCHASTIC_GRADIENT_DESCENT); | |
| builder.weightInit(WeightInit.XAVIER); | |
| Map<Integer, Double> lrSchedule = new HashMap<>(); | |
| lrSchedule.put(0, 1e-2); |
liweigu
/ mask error
Last active
September 3, 2018 06:36
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| error info: | |
| java.lang.IllegalStateException: Expected rank 4 mask array for 2D CNN layers. Mask arrays for 2D CNN layers must have shape [batchSize,channels,X,Y] where X = (1 or activationsHeight) and Y = (1 or activationsWidth): Got rank 2 array with shape [60, 1] | |
| at org.deeplearning4j.util.ConvolutionUtils.cnn2dMaskReduction(ConvolutionUtils.java:602) | |
| at org.deeplearning4j.nn.layers.convolution.ConvolutionLayer.feedForwardMaskArray(ConvolutionLayer.java:473) | |
| at org.deeplearning4j.nn.graph.vertex.impl.LayerVertex.feedForwardMaskArrays(LayerVertex.java:196) | |
| at org.deeplearning4j.nn.graph.ComputationGraph.setLayerMaskArrays(ComputationGraph.java:3689) | |
| at org.deeplearning4j.nn.graph.ComputationGraph.fitHelper(ComputationGraph.java:1115) | |
| at org.deeplearning4j.nn.graph.ComputationGraph.fit(ComputationGraph.java:1097) | |
| at org.deeplearning4j.nn.graph.ComputationGraph.fit(ComputationGraph.java:962) | |
liweigu
/ SimpleConvLSTM
Created
August 30, 2018 08:59
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| package com.liweigu.dls.competition.srad; | |
| import java.io.IOException; | |
| import java.util.HashMap; | |
| import java.util.Map; | |
| import org.deeplearning4j.nn.api.OptimizationAlgorithm; | |
| import org.deeplearning4j.nn.conf.BackpropType; | |
| import org.deeplearning4j.nn.conf.GradientNormalization; | |
| import org.deeplearning4j.nn.conf.InputPreProcessor; |
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| network: | |
| GraphBuilder graphBuilder = builder.graphBuilder().backpropType(BackpropType.Standard).addInputs("inputs") | |
| .addLayer("cnn1", | |
| new ConvolutionLayer.Builder(new int[] { kernelSize1, kernelSize1 }, | |
| new int[] { cnnStride1, cnnStride1 }, | |
| new int[] { padding, padding }) | |
| .nIn(channels) | |
| .nOut(64) | |
| inputPreProcessors.put("cnn1", new RnnToCnnPreProcessor(501, 501, channels)); |
liweigu
/ gist:9e1b9e2917b5d06d1faf9493701c8d54
Created
July 11, 2018 03:25
ND4JWorkspaceException-dl4j
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| Error Log: | |
| java.lang.IllegalStateException: Backprop: array (ACTIVATION_GRAD) workspace validation failed (vertex lstm1 - class: GravesLSTM) - array is defined in incorrect workspace | |
| at org.deeplearning4j.nn.graph.ComputationGraph.validateArrayWorkspaces(ComputationGraph.java:1708) | |
| at org.deeplearning4j.nn.graph.ComputationGraph.calcBackpropGradients(ComputationGraph.java:2435) | |
| at org.deeplearning4j.nn.graph.ComputationGraph.computeGradientAndScore(ComputationGraph.java:1319) | |
| at org.deeplearning4j.nn.graph.ComputationGraph.computeGradientAndScore(ComputationGraph.java:1280) | |
| at org.deeplearning4j.optimize.solvers.BaseOptimizer.gradientAndScore(BaseOptimizer.java:178) | |
| at org.deeplearning4j.optimize.solvers.StochasticGradientDescent.optimize(StochasticGradientDescent.java:60) | |
| at org.deeplearning4j.optimize.Solver.optimize(Solver.java:54) | |
| at org.deeplearning4j.nn.graph.ComputationGraph.fit(ComputationGraph.java:1104) |
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| // MultiLayerConfiguration | |
| int OutDemension = 2; | |
| ListBuilder listBuilder = builder.list(); | |
| int layerIndex = 0; | |
| listBuilder.layer(layerIndex++, new GravesLSTM.Builder().activation(Activation.SOFTSIGN) // SOFTSIGN, TANH, RELU, SIGMOID | |
| .nIn(inNum).nOut(hiddenCount).build()); | |
| listBuilder.layer(layerIndex++, new GravesLSTM.Builder().activation(Activation.SOFTSIGN) | |
| .nIn(hiddenCount).nOut(hiddenCount).build()); | |
| listBuilder.layer(layerIndex++, new DenseLayer.Builder().activation(Activation.TANH) | |
| .nIn(hiddenCount).nOut(denseLayerHiddenCount).build()); |