liweigu

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], 

liweigu

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

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

	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

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

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;

liweigu

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

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)

liweigu

		// 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());