Package org.encog.util

Source Code of org.encog.util.EncogValidate

/*
* Encog(tm) Core v3.3 - Java Version
* http://www.heatonresearch.com/encog/
* https://github.com/encog/encog-java-core
* Copyright 2008-2014 Heaton Research, 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.
*  
* For more information on Heaton Research copyrights, licenses
* and trademarks visit:
* http://www.heatonresearch.com/copyright
*/
package org.encog.util;

import org.encog.ml.data.MLDataSet;
import org.encog.neural.NeuralNetworkError;
import org.encog.neural.networks.ContainsFlat;

/**
* Used to validate if training is valid.
*/
public final class EncogValidate {

  /**
   * Validate a network for training.
   *
   * @param network
   *            The network to validate.
   * @param training
   *            The training set to validate.
   */
  public static void validateNetworkForTraining(final ContainsFlat network,
      final MLDataSet training) {

    int inputCount = network.getFlat().getInputCount();
    int outputCount = network.getFlat().getOutputCount();   

    if (inputCount != training.getInputSize()) {
      throw new NeuralNetworkError("The input layer size of "
          + inputCount
          + " must match the training input size of "
          + training.getInputSize() + ".");
    }

    if ((training.getIdealSize() > 0)
        && (outputCount != training.getIdealSize())) {
      throw new NeuralNetworkError("The output layer size of "
          + outputCount
          + " must match the training input size of "
          + training.getIdealSize() + ".");
    }
  }

  /**
   * Private constructor.
   */
  private EncogValidate() {

  }
}
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