cavis/cavis-dnn/cavis-dnn-nn/src/main/java/org/deeplearning4j/nn/params/WrapperLayerParamInitializer.java
2023-08-07 10:39:16 +02:00

105 lines
3.5 KiB
Java

/*
* ******************************************************************************
* *
* *
* * 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.
* *
* * See the NOTICE file distributed with this work for additional
* * information regarding copyright ownership.
* * 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.
* *
* * SPDX-License-Identifier: Apache-2.0
* *****************************************************************************
*/
package org.deeplearning4j.nn.params;
import java.util.List;
import java.util.Map;
import org.deeplearning4j.nn.api.AbstractParamInitializer;
import org.deeplearning4j.nn.conf.layers.LayerConfiguration;
import org.deeplearning4j.nn.conf.layers.wrapper.BaseWrapperLayerConfiguration;
import org.nd4j.linalg.api.ndarray.INDArray;
public class WrapperLayerParamInitializer extends AbstractParamInitializer {
private static final WrapperLayerParamInitializer INSTANCE = new WrapperLayerParamInitializer();
public static WrapperLayerParamInitializer getInstance(){
return INSTANCE;
}
private WrapperLayerParamInitializer(){
}
@Override
public long numParams(LayerConfiguration layer) {
LayerConfiguration l = underlying(layer);
return l.initializer().numParams(l);
}
@Override
public List<String> paramKeys(LayerConfiguration layer) {
LayerConfiguration l = underlying(layer);
return l.initializer().paramKeys(l);
}
@Override
public List<String> weightKeys(LayerConfiguration layer) {
LayerConfiguration l = underlying(layer);
return l.initializer().weightKeys(l);
}
@Override
public List<String> biasKeys(LayerConfiguration layer) {
LayerConfiguration l = underlying(layer);
return l.initializer().biasKeys(l);
}
@Override
public boolean isWeightParam(LayerConfiguration layer, String key) {
LayerConfiguration l = underlying(layer);
return l.initializer().isWeightParam(layer, key);
}
@Override
public boolean isBiasParam(LayerConfiguration layer, String key) {
LayerConfiguration l = underlying(layer);
return l.initializer().isBiasParam(layer, key);
}
@Override
public Map<String, INDArray> init(LayerConfiguration conf, INDArray paramsView, boolean initializeParams) {
LayerConfiguration orig = conf;
LayerConfiguration l = underlying(conf);
Map<String,INDArray> m = l.initializer().init(conf, paramsView, initializeParams);
return m;
}
@Override
public Map<String, INDArray> getGradientsFromFlattened(LayerConfiguration conf, INDArray gradientView) {
LayerConfiguration orig = conf;
LayerConfiguration l = underlying(conf);
Map<String,INDArray> m = l.initializer().getGradientsFromFlattened(conf, gradientView);
return m;
}
private LayerConfiguration underlying(LayerConfiguration layer){
while (layer instanceof BaseWrapperLayerConfiguration) {
layer = ((BaseWrapperLayerConfiguration)layer).getUnderlying();
}
return layer;
}
}