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Java example source code file (GRUParamInitializer.java)
The GRUParamInitializer.java Java example source code/* * * * Copyright 2015 Skymind,Inc. * * * * Licensed under the Apache License, Version 2.0 (the "License"); * * you may not use this file except in compliance with the License. * * You may obtain a copy of the License at * * * * http://www.apache.org/licenses/LICENSE-2.0 * * * * Unless required by applicable law or agreed to in writing, software * * distributed under the License is distributed on an "AS IS" BASIS, * * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * * See the License for the specific language governing permissions and * * limitations under the License. * */ package org.deeplearning4j.nn.params; import org.canova.api.conf.Configuration; import org.deeplearning4j.nn.api.ParamInitializer; import org.deeplearning4j.nn.conf.NeuralNetConfiguration; import org.deeplearning4j.nn.conf.distribution.Distributions; import org.deeplearning4j.nn.weights.WeightInitUtil; import org.nd4j.linalg.api.ndarray.INDArray; import org.nd4j.linalg.api.rng.distribution.Distribution; import org.nd4j.linalg.factory.Nd4j; import java.util.Map; public class GRUParamInitializer implements ParamInitializer { /** Weights for previous time step -> current time step connections */ public final static String RECURRENT_WEIGHT_KEY = "RW"; public final static String BIAS_KEY = DefaultParamInitializer.BIAS_KEY; public final static String INPUT_WEIGHT_KEY = DefaultParamInitializer.WEIGHT_KEY; @Override public int numParams(NeuralNetConfiguration conf, boolean backprop) { throw new UnsupportedOperationException("Not yet implemented"); //TODO } @Override public void init(Map<String, INDArray> params, NeuralNetConfiguration conf, INDArray paramsView, boolean initializeParams) { org.deeplearning4j.nn.conf.layers.GRU layerConf = (org.deeplearning4j.nn.conf.layers.GRU) conf.getLayer(); // Distribution dist = Distributions.createDistribution(layerConf.getDist()); // // int nL = layerConf.getNOut(); //i.e., n neurons in this layer // int nLast = layerConf.getNIn(); //i.e., n neurons in previous layer // // conf.addVariable(INPUT_WEIGHT_KEY); // conf.addVariable(RECURRENT_WEIGHT_KEY); // conf.addVariable(BIAS_KEY); // // //Order: RUC - i.e., reset, update, candidate // params.put(INPUT_WEIGHT_KEY,WeightInitUtil.initWeights(nLast, 3 * nL, layerConf.getWeightInit(), dist)); // params.put(RECURRENT_WEIGHT_KEY,WeightInitUtil.initWeights(nL, 3 * nL, layerConf.getWeightInit(), dist)); // params.put(BIAS_KEY, Nd4j.zeros(1,3*nL)); // // params.get(INPUT_WEIGHT_KEY).data().persist(); // params.get(RECURRENT_WEIGHT_KEY).data().persist(); // params.get(BIAS_KEY).data().persist(); throw new UnsupportedOperationException("Not yet implemented"); //TODO } @Override public Map<String, INDArray> getGradientsFromFlattened(NeuralNetConfiguration conf, INDArray gradientView) { throw new UnsupportedOperationException("Not yet implemented"); } } Other Java examples (source code examples)Here is a short list of links related to this Java GRUParamInitializer.java source code file: |
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