org.deeplearning4j.arbiter.layers.BasePretrainNetworkLayerSpace 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.
*
*/
package org.deeplearning4j.arbiter.layers;
import lombok.AccessLevel;
import lombok.Data;
import lombok.EqualsAndHashCode;
import lombok.NoArgsConstructor;
import org.deeplearning4j.arbiter.optimize.api.ParameterSpace;
import org.deeplearning4j.arbiter.optimize.parameter.FixedValue;
import org.deeplearning4j.nn.conf.layers.BasePretrainNetwork;
import org.nd4j.linalg.lossfunctions.LossFunctions.LossFunction;
import org.nd4j.shade.jackson.annotation.JsonProperty;
@Data
@EqualsAndHashCode(callSuper = true)
@NoArgsConstructor(access = AccessLevel.PROTECTED) //For Jackson JSON/YAML deserialization
public abstract class BasePretrainNetworkLayerSpace extends FeedForwardLayerSpace {
@JsonProperty
protected ParameterSpace lossFunction;
protected BasePretrainNetworkLayerSpace(Builder builder) {
super(builder);
this.lossFunction = builder.lossFunction;
}
public static abstract class Builder extends FeedForwardLayerSpace.Builder {
protected ParameterSpace lossFunction;
public T lossFunction(LossFunction lossFunction) {
return lossFunction(new FixedValue(lossFunction));
}
public T lossFunction(ParameterSpace lossFunction) {
this.lossFunction = lossFunction;
return (T) this;
}
}
}