org.nd4j.linalg.lossfunctions.serde.RowVectorDeserializer Maven / Gradle / Ivy
/*******************************************************************************
* Copyright (c) 2015-2018 Skymind, Inc.
*
* 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.
*
* 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.nd4j.linalg.lossfunctions.serde;
import org.nd4j.linalg.api.ndarray.INDArray;
import org.nd4j.linalg.factory.Nd4j;
import org.nd4j.shade.jackson.core.JsonParser;
import org.nd4j.shade.jackson.databind.DeserializationContext;
import org.nd4j.shade.jackson.databind.JsonDeserializer;
import org.nd4j.shade.jackson.databind.JsonNode;
import java.io.IOException;
/**
* Simple JSON deserializer for use in {@link org.nd4j.linalg.lossfunctions.ILossFunction} loss function weight serialization.
* Used in conjunction with {@link RowVectorSerializer}
*
* @author Alex Black
*/
public class RowVectorDeserializer extends JsonDeserializer {
@Override
public INDArray deserialize(JsonParser jsonParser, DeserializationContext deserializationContext)
throws IOException {
JsonNode node = jsonParser.getCodec().readTree(jsonParser);
if (node == null)
return null;
int size = node.size();
double[] d = new double[size];
for (int i = 0; i < size; i++) {
d[i] = node.get(i).asDouble();
}
return Nd4j.create(d);
}
}