Fix compiler warnings

Signed-off-by: brian <brian@brutex.de>
master
Brian Rosenberger 2022-10-05 13:46:28 +02:00
parent ac7df3831e
commit 4ad1987a07
4 changed files with 7 additions and 9 deletions

View File

@ -38,7 +38,7 @@ import com.fasterxml.jackson.databind.module.SimpleModule;
import com.fasterxml.jackson.dataformat.yaml.YAMLFactory; import com.fasterxml.jackson.dataformat.yaml.YAMLFactory;
@Deprecated @Deprecated
@EqualsAndHashCode @EqualsAndHashCode(callSuper = false)
public abstract class BaseEvaluation<T extends BaseEvaluation> extends org.nd4j.evaluation.BaseEvaluation<T> { public abstract class BaseEvaluation<T extends BaseEvaluation> extends org.nd4j.evaluation.BaseEvaluation<T> {
@Getter @Getter

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@ -21,6 +21,7 @@
package org.deeplearning4j.nn.conf.layers.objdetect; package org.deeplearning4j.nn.conf.layers.objdetect;
import lombok.Data; import lombok.Data;
import lombok.EqualsAndHashCode;
import lombok.Getter; import lombok.Getter;
import lombok.Setter; import lombok.Setter;
import org.deeplearning4j.nn.api.Layer; import org.deeplearning4j.nn.api.Layer;
@ -49,6 +50,7 @@ import java.util.List;
import java.util.Map; import java.util.Map;
@Data @Data
@EqualsAndHashCode(callSuper = false)
public class Yolo2OutputLayer extends org.deeplearning4j.nn.conf.layers.Layer { public class Yolo2OutputLayer extends org.deeplearning4j.nn.conf.layers.Layer {
private double lambdaCoord; private double lambdaCoord;

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@ -20,10 +20,7 @@
package org.deeplearning4j.nn.conf.layers.recurrent; package org.deeplearning4j.nn.conf.layers.recurrent;
import lombok.Data; import lombok.*;
import lombok.Getter;
import lombok.NoArgsConstructor;
import lombok.Setter;
import org.deeplearning4j.nn.api.Layer; import org.deeplearning4j.nn.api.Layer;
import org.deeplearning4j.nn.api.ParamInitializer; import org.deeplearning4j.nn.api.ParamInitializer;
import org.deeplearning4j.nn.conf.NeuralNetConfiguration; import org.deeplearning4j.nn.conf.NeuralNetConfiguration;
@ -40,6 +37,7 @@ import java.util.Collection;
import java.util.Map; import java.util.Map;
@Data @Data
@EqualsAndHashCode(callSuper = false)
public class SimpleRnn extends BaseRecurrentLayer { public class SimpleRnn extends BaseRecurrentLayer {
private boolean hasLayerNorm = false; private boolean hasLayerNorm = false;

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@ -20,10 +20,7 @@
package org.deeplearning4j.nn.conf.memory; package org.deeplearning4j.nn.conf.memory;
import lombok.AllArgsConstructor; import lombok.*;
import lombok.Data;
import lombok.NoArgsConstructor;
import lombok.NonNull;
import org.deeplearning4j.nn.conf.CacheMode; import org.deeplearning4j.nn.conf.CacheMode;
import org.deeplearning4j.nn.conf.inputs.InputType; import org.deeplearning4j.nn.conf.inputs.InputType;
import org.nd4j.linalg.api.buffer.DataBuffer; import org.nd4j.linalg.api.buffer.DataBuffer;
@ -35,6 +32,7 @@ import java.util.Map;
@Data @Data
@AllArgsConstructor @AllArgsConstructor
@NoArgsConstructor @NoArgsConstructor
@EqualsAndHashCode(callSuper = false)
public class LayerMemoryReport extends MemoryReport { public class LayerMemoryReport extends MemoryReport {
private String layerName; private String layerName;