org.deeplearning4j.arbiter.layers.RBMLayerSpace Maven / Gradle / Ivy
/*
*
* * Copyright 2016 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.
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*/
package org.deeplearning4j.arbiter.layers;
import org.deeplearning4j.arbiter.optimize.parameter.FixedValue;
import org.deeplearning4j.arbiter.optimize.api.ParameterSpace;
import org.deeplearning4j.nn.conf.layers.RBM;
import java.util.List;
public class RBMLayerSpace extends BasePretrainNetworkLayerSpace {
private ParameterSpace hiddenUnit;
private ParameterSpace visibleUnit;
private ParameterSpace k;
private ParameterSpace sparsity;
private RBMLayerSpace(Builder builder){
super(builder);
this.hiddenUnit = builder.hiddenUnit;
this.visibleUnit = builder.visibleUnit;
this.k = builder.k;
this.sparsity = builder.sparsity;
}
@Override
public List collectLeaves(){
List list = super.collectLeaves();
if(hiddenUnit != null) list.addAll(hiddenUnit.collectLeaves());
if(visibleUnit != null) list.addAll(visibleUnit.collectLeaves());
if(k != null) list.addAll(k.collectLeaves());
if(sparsity != null) list.addAll(sparsity.collectLeaves());
return list;
}
@Override
public RBM getValue(double[] values) {
RBM.Builder b = new RBM.Builder();
setLayerOptionsBuilder(b,values);
return b.build();
}
protected void setLayerOptionsBuilder(RBM.Builder builder,double[] values){
super.setLayerOptionsBuilder(builder,values);
if(hiddenUnit != null) builder.hiddenUnit(hiddenUnit.getValue(values));
if(visibleUnit != null) builder.visibleUnit(visibleUnit.getValue(values));
if(k != null) builder.k(k.getValue(values));
if(sparsity != null) builder.sparsity(sparsity.getValue(values));
}
@Override
public String toString(){
return toString(", ");
}
@Override
public String toString(String delim){
StringBuilder sb = new StringBuilder("RBMLayerSpace(");
if(hiddenUnit != null) sb.append("hiddenUnit: ").append(hiddenUnit).append(delim);
if(visibleUnit != null) sb.append("visibleUnit: ").append(visibleUnit).append(delim);
if(k != null) sb.append("k: ").append(k).append(delim);
if(sparsity != null) sb.append("sparsity: ").append(sparsity).append(delim);
sb.append(super.toString(delim)).append(")");
return sb.toString();
}
public class Builder extends BasePretrainNetworkLayerSpace.Builder{
private ParameterSpace hiddenUnit;
private ParameterSpace visibleUnit;
private ParameterSpace k;
private ParameterSpace sparsity;
public Builder hiddenUnit(RBM.HiddenUnit hiddenUnit){
return hiddenUnit(new FixedValue<>(hiddenUnit));
}
public Builder hiddenUnit(ParameterSpace hiddenUnit){
this.hiddenUnit = hiddenUnit;
return this;
}
public Builder visibleUnit(RBM.VisibleUnit visibleUnit){
return visibleUnit(new FixedValue<>(visibleUnit));
}
public Builder visibleUnit(ParameterSpace visibleUnit){
this.visibleUnit = visibleUnit;
return this;
}
public Builder k( int k ){
return k(new FixedValue<>(k));
}
public Builder k(ParameterSpace k){
this.k = k;
return this;
}
public Builder sparsity(double sparsity){
return sparsity(new FixedValue<>(sparsity));
}
public Builder sparsity(ParameterSpace sparsity){
this.sparsity = sparsity;
return this;
}
public RBMLayerSpace build(){
return new RBMLayerSpace(this);
}
}
}
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