org.deeplearning4j.nn.conf.graph.ShiftVertex Maven / Gradle / Ivy
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* * terms of the Apache License, Version 2.0 which is available at
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package org.deeplearning4j.nn.conf.graph;
import lombok.Data;
import lombok.EqualsAndHashCode;
import lombok.NoArgsConstructor;
import lombok.ToString;
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;
import org.nd4j.shade.jackson.annotation.JsonProperty;
@Data
@NoArgsConstructor
@ToString(callSuper = true)
@EqualsAndHashCode(callSuper = false)
public class ShiftVertex extends GraphVertex {
public ShiftVertex(@JsonProperty("shiftFactor") double shiftFactor) {
this.shiftFactor = shiftFactor;
}
protected double shiftFactor = 0.0; // Shift by zero if it's not specified.
@Override
public ShiftVertex clone() {
return new ShiftVertex(shiftFactor);
}
@Override
public long numParams(boolean backprop) {
return 0;
}
@Override
public int minVertexInputs() {
return 1;
}
@Override
public int maxVertexInputs() {
return 1;
}
@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.ShiftVertex(graph, name, idx, shiftFactor, networkDatatype);
}
@Override
public InputType getOutputType(int layerIndex, InputType... vertexInputs) throws InvalidInputTypeException {
if (vertexInputs.length == 1)
return vertexInputs[0];
InputType first = vertexInputs[0];
return first; //Same output shape/size as
}
@Override
public MemoryReport getMemoryReport(InputType... inputTypes) {
//Do one dup on the forward pass (output activations). Accounted for in output activations.
InputType outputType = getOutputType(-1, inputTypes);
return new LayerMemoryReport.Builder(null, ShiftVertex.class, inputTypes[0], outputType).standardMemory(0, 0) //No params
.workingMemory(0, 0, 0, 0).cacheMemory(0, 0) //No caching
.build();
}
}