org.deeplearning4j.nn.updater.graph.ComputationGraphUpdater Maven / Gradle / Ivy
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* * This program and the accompanying materials are made available under the
* * terms of the Apache License, Version 2.0 which is available at
* * https://www.apache.org/licenses/LICENSE-2.0.
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* * information regarding copyright ownership.
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* * SPDX-License-Identifier: Apache-2.0
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package org.deeplearning4j.nn.updater.graph;
import org.deeplearning4j.nn.api.Layer;
import org.deeplearning4j.nn.api.Trainable;
import org.deeplearning4j.nn.graph.ComputationGraph;
import org.deeplearning4j.nn.graph.vertex.GraphVertex;
import org.deeplearning4j.nn.updater.BaseMultiLayerUpdater;
import org.nd4j.linalg.api.ndarray.INDArray;
import java.util.Arrays;
import java.util.HashMap;
public class ComputationGraphUpdater extends BaseMultiLayerUpdater {
protected Trainable[] orderedLayers;
public ComputationGraphUpdater(ComputationGraph graph) {
this(graph, null);
}
public ComputationGraphUpdater(ComputationGraph graph, INDArray updaterState) {
super(graph, updaterState);
layersByName = new HashMap<>();
Trainable[] layers = getOrderedLayers();
for (Trainable l : layers) {
layersByName.put(l.getConfig().getLayerName(), l);
}
}
@Override
protected Trainable[] getOrderedLayers() {
if (orderedLayers != null) {
return orderedLayers;
}
GraphVertex[] vertices = network.getVertices();
//In CompGraph: we need to know topological ordering, so we know how parameters are laid out in the 1d view arrays
int[] topologicalOrdering = network.topologicalSortOrder();
Trainable[] out = new Trainable[network.getVertices().length];
int j = 0;
for (int i = 0; i < topologicalOrdering.length; i++) {
GraphVertex currentVertex = vertices[topologicalOrdering[i]];
if (currentVertex.numParams() == 0) {
continue;
}
out[j++] = currentVertex;
}
if(j != out.length){
out = Arrays.copyOfRange(out, 0, j);
}
orderedLayers = out;
return orderedLayers;
}
@Override
public INDArray getFlattenedGradientsView() {
if (network.getFlattenedGradients() == null) {
network.initGradientsView();
}
return network.getFlattenedGradients();
}
@Override
protected INDArray getParams() {
return network.params();
}
@Override
protected boolean isMiniBatch() {
return network.conf().isMiniBatch();
}
}