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DAG-oriented machine learning framework for bug-resistant, readable, efficient, maintainable and trivially deployable models in Java and other JVM languages

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// AUTOGENERATED CODE.  DO NOT MODIFY DIRECTLY!  Instead, please modify the transformer/TupledX.ftl file.
// See the README in the module's src/template directory for details.
package com.linkedin.dagli.transformer;

import com.linkedin.dagli.annotation.equality.ValueEquality;
import com.linkedin.dagli.producer.Producer;
import com.linkedin.dagli.tuple.Tuple5;


/**
 * A transformer that produces a tuple of the values it receives as inputs.
 */
@ValueEquality
public class Tupled5 extends
    AbstractPreparedTransformer5, Tupled5> {
  private static final long serialVersionUID = 1;

  /**
   * Creates a new instance with the specified inputs.
   */
  public Tupled5(Producer input1, Producer input2, Producer input3,
      Producer input4, Producer input5) {
    super(input1, input2, input3, input4, input5);
  }

  @Override
  public Tuple5 apply(A value1, B value2, C value3, D value4, E value5) {
    return Tuple5.of(value1, value2, value3, value4, value5);
  }
}