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Java example source code file (GraphVertex.java)
The GraphVertex.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; import com.fasterxml.jackson.annotation.JsonSubTypes; import com.fasterxml.jackson.annotation.JsonTypeInfo; import org.deeplearning4j.nn.conf.graph.rnn.DuplicateToTimeSeriesVertex; import org.deeplearning4j.nn.conf.graph.rnn.LastTimeStepVertex; 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; import java.io.Serializable; /** * A GraphVertex is a vertex in the computation graph. It may contain Layer, or define some arbitrary forward/backward pass * behaviour based on the inputs * * @author Alex Black */ @JsonTypeInfo(use = JsonTypeInfo.Id.NAME, include = JsonTypeInfo.As.WRAPPER_OBJECT) @JsonSubTypes(value = { @JsonSubTypes.Type(value = ElementWiseVertex.class, name = "ElementWiseVertex"), @JsonSubTypes.Type(value = MergeVertex.class, name = "MergeVertex"), @JsonSubTypes.Type(value = SubsetVertex.class, name = "SubsetVertex"), @JsonSubTypes.Type(value = LayerVertex.class, name = "LayerVertex"), @JsonSubTypes.Type(value = LastTimeStepVertex.class, name = "LastTimeStepVertex"), @JsonSubTypes.Type(value = DuplicateToTimeSeriesVertex.class, name = "DuplicateToTimeSeriesVertex"), @JsonSubTypes.Type(value = PreprocessorVertex.class, name = "PreprocessorVertex") }) public abstract class GraphVertex implements Cloneable, Serializable { @Override public abstract GraphVertex clone(); @Override public abstract boolean equals(Object o); @Override public abstract int hashCode(); public abstract int numParams(boolean backprop); /** * Create a {@link org.deeplearning4j.nn.graph.vertex.GraphVertex} instance, for the given computation graph, * given the configuration instance. * * @param graph The computation graph that this GraphVertex is to be part of * @param name The name of the GraphVertex object * @param idx The index of the GraphVertex * @param paramsView A view of the full parameters array * @param initializeParams If true: initialize the parameters. If false: make no change to the values in the paramsView array * @return The implementation GraphVertex object (i.e., implementation, no the configuration) */ public abstract org.deeplearning4j.nn.graph.vertex.GraphVertex instantiate(ComputationGraph graph, String name, int idx, INDArray paramsView, boolean initializeParams); /** * Determine the type of output for this GraphVertex, given the specified inputs. Given that a GraphVertex may do arbitrary * processing or modifications of the inputs, the output types can be quite different to the input type(s).<br> * This is generally used to determine when to add preprocessors, as well as the input sizes etc for layers * * @param vertexInputs The inputs to this vertex * @return The type of output for this vertex * @throws InvalidInputTypeException If the input type is invalid for this type of GraphVertex */ public abstract InputType getOutputType(InputType... vertexInputs) throws InvalidInputTypeException; } Other Java examples (source code examples)Here is a short list of links related to this Java GraphVertex.java source code file: |
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