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 /*
  * Copyright [2013-2014] eBay Software Foundation
  *  
  * 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 ml.shifu.guagua.mapreduce.example.nn;
Helper class for NN distributed training.
public final class NNUtils {
    private NNUtils() {
    }

    
Generate basic NN network object
    public static BasicNetwork generateNetwork(int inint hiddenint out) {
        final BasicNetwork network = new BasicNetwork();
        network.addLayer(new BasicLayer(new ActivationLinear(), truein));
        network.addLayer(new BasicLayer(new ActivationSigmoid(), truehidden));
        network.addLayer(new BasicLayer(new ActivationSigmoid(), falseout));
        network.getStructure().finalizeStructure();
        network.reset();
        return network;
    }

    
Determine the sign of the value.

Parameters:
value The value to check.
Returns:
-1 if less than zero, 1 if greater, or 0 if zero.
    public static int sign(final double value) {
        if(Math.abs(value) < .) {
            return 0;
        } else if(value > 0) {
            return 1;
        } else {
            return -1;
        }
    }
    public static void randomize(int seeddouble[] weights) {
        NguyenWidrowRandomizer randomizer = new NguyenWidrowRandomizer(-1, 1);
        randomizer.randomize(weights);
    }
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