org.deeplearning4j.nn.conf.graph.L2Vertex Maven / Gradle / Ivy
/*
* ******************************************************************************
* *
* *
* * 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.conf.graph;
import lombok.val;
import org.deeplearning4j.nn.conf.inputs.InputType;
import org.deeplearning4j.nn.conf.inputs.InvalidInputTypeException;
import org.deeplearning4j.nn.conf.memory.LayerMemoryReport;
import org.deeplearning4j.nn.conf.memory.MemoryReport;
import org.deeplearning4j.nn.graph.ComputationGraph;
import org.nd4j.linalg.api.buffer.DataType;
import org.nd4j.linalg.api.ndarray.INDArray;
public class L2Vertex extends GraphVertex {
protected double eps;
/**
* Constructor with default epsilon value of 1e-8
*/
public L2Vertex() {
this.eps = 1e-8;
}
/**
* @param eps Epsilon value to add to inputs (to avoid all zeros input and hence undefined gradients)
*/
public L2Vertex(double eps) {
this.eps = eps;
}
@Override
public L2Vertex clone() {
return new L2Vertex();
}
@Override
public boolean equals(Object o) {
return o instanceof L2Vertex;
}
@Override
public long numParams(boolean backprop) {
return 0;
}
@Override
public int minVertexInputs() {
return 2;
}
@Override
public int maxVertexInputs() {
return 2;
}
@Override
public int hashCode() {
return 433682566;
}
@Override
public org.deeplearning4j.nn.graph.vertex.GraphVertex instantiate(ComputationGraph graph, String name, int idx,
INDArray paramsView, boolean initializeParams, DataType networkDatatype) {
return new org.deeplearning4j.nn.graph.vertex.impl.L2Vertex(graph, name, idx, null, null, eps, networkDatatype);
}
@Override
public InputType getOutputType(int layerIndex, InputType... vertexInputs) throws InvalidInputTypeException {
return InputType.feedForward(1);
}
@Override
public MemoryReport getMemoryReport(InputType... inputTypes) {
InputType outputType = getOutputType(-1, inputTypes);
//Inference: only calculation is for output activations; no working memory
//Working memory for training:
//1 for each example (fwd pass) + output size (1 per ex) + input size + output size... in addition to the returned eps arrays
//output size == input size here
val trainWorkingSizePerEx = 3 + 2 * inputTypes[0].arrayElementsPerExample();
return new LayerMemoryReport.Builder(null, L2Vertex.class, inputTypes[0], outputType).standardMemory(0, 0) //No params
.workingMemory(0, 0, 0, trainWorkingSizePerEx).cacheMemory(0, 0) //No caching
.build();
}
}