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Java example source code file (DuplicateToTimeSeriesVertex.java)
The DuplicateToTimeSeriesVertex.java Java example source code/* * * * 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.nn.conf.graph.rnn; import com.fasterxml.jackson.annotation.JsonProperty; import lombok.Data; import lombok.EqualsAndHashCode; import org.deeplearning4j.nn.conf.graph.GraphVertex; import org.deeplearning4j.nn.conf.inputs.InputType; import org.deeplearning4j.nn.conf.inputs.InvalidInputTypeException; import org.deeplearning4j.nn.graph.ComputationGraph; import org.nd4j.linalg.api.ndarray.INDArray; /**DuplicateToTimeSeriesVertex is a vertex that goes from 2d activations to a 3d time series activations, by means of * duplication. That is, given a 2d input with shape [numExamples,nIn] duplicate each row to give output of * [numExamples,nIn,timeSeriesLength], where the activations are the same for all time steps.<br> * This method is used for example in sequence to sequence models.<br> * <b>Note: The length of the output time series (number of time steps) is determined by means of referencing one of the * inputs in the ComputationGraph. That is: Because the length of the time series may differ at runtime, we generally want the number * of time steps to match some other input; here, we are specifying the length of the output time series to be the same as * one of the input time series<br> * @author Alex Black */ @Data @EqualsAndHashCode(callSuper=false) public class DuplicateToTimeSeriesVertex extends GraphVertex { private String inputName; /** * @param inputName Name of the input in the ComputationGraph network to use, to determine how long the output time * series should be. This input should (a) exist, and (b) be a time series input */ public DuplicateToTimeSeriesVertex(@JsonProperty("inputName") String inputName){ this.inputName = inputName; } @Override public GraphVertex clone() { return new DuplicateToTimeSeriesVertex(inputName); } @Override public boolean equals(Object o) { if(!(o instanceof DuplicateToTimeSeriesVertex)) return false; DuplicateToTimeSeriesVertex d = (DuplicateToTimeSeriesVertex)o; if(inputName == null && d.inputName != null || inputName != null && d.inputName == null) return false; return inputName == null || inputName.equals(d.inputName); } @Override public int hashCode() { return 534806565 ^ (inputName != null ? inputName.hashCode() : 0); } @Override public int numParams(boolean backprop){ return 0; } @Override public org.deeplearning4j.nn.graph.vertex.GraphVertex instantiate(ComputationGraph graph, String name, int idx, INDArray paramsView, boolean initializeParams) { return new org.deeplearning4j.nn.graph.vertex.impl.rnn.DuplicateToTimeSeriesVertex(graph,name,idx,inputName); } @Override public InputType getOutputType(InputType... vertexInputs) throws InvalidInputTypeException { if(vertexInputs.length != 1) throw new InvalidInputTypeException("Invalid input type: cannot duplicate more than 1 input"); if(vertexInputs[0].getType() != InputType.Type.FF){ throw new InvalidInputTypeException("Invalid input type: cannot duplicate to time series non feed forward input (got: " + vertexInputs[0] + ")"); } return InputType.recurrent(((InputType.InputTypeFeedForward)vertexInputs[0]).getSize()); } } Other Java examples (source code examples)Here is a short list of links related to this Java DuplicateToTimeSeriesVertex.java source code file: |
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