| /* |
| * Licensed to the Apache Software Foundation (ASF) under one or more |
| * contributor license agreements. See the NOTICE file distributed with |
| * this work for additional information regarding copyright ownership. |
| * The ASF licenses this file to You 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.apache.commons.math4.neuralnet; |
| |
| import java.util.function.DoubleUnaryOperator; |
| |
| import org.apache.commons.rng.UniformRandomProvider; |
| import org.apache.commons.rng.sampling.distribution.ContinuousUniformSampler; |
| |
| /** |
| * Creates functions that will select the initial values of a neuron's |
| * features. |
| * |
| * @since 3.3 |
| */ |
| public final class FeatureInitializerFactory { |
| /** Class contains only static methods. */ |
| private FeatureInitializerFactory() {} |
| |
| /** |
| * Uniform sampling of the given range. |
| * |
| * @param min Lower bound of the range. |
| * @param max Upper bound of the range. |
| * @param rng Random number generator used to draw samples from a |
| * uniform distribution. |
| * @return an initializer such that the features will be initialized with |
| * values within the given range. |
| * @throws IllegalArgumentException if {@code min >= max}. |
| */ |
| public static FeatureInitializer uniform(final UniformRandomProvider rng, |
| final double min, |
| final double max) { |
| return randomize(new ContinuousUniformSampler(rng, min, max), |
| function(x -> 0, 0, 0)); |
| } |
| |
| /** |
| * Creates an initializer from a univariate function {@code f(x)}. |
| * The argument {@code x} is set to {@code init} at the first call |
| * and will be incremented at each call. |
| * |
| * @param f Function. |
| * @param init Initial value. |
| * @param inc Increment |
| * @return the initializer. |
| */ |
| public static FeatureInitializer function(final DoubleUnaryOperator f, |
| final double init, |
| final double inc) { |
| return new FeatureInitializer() { |
| /** Argument. */ |
| private double arg = init; |
| |
| /** {@inheritDoc} */ |
| @Override |
| public double value() { |
| final double result = f.applyAsDouble(arg); |
| arg += inc; |
| return result; |
| } |
| }; |
| } |
| |
| /** |
| * Adds some amount of random data to the given initializer. |
| * |
| * @param random Random variable distribution sampler. |
| * @param orig Original initializer. |
| * @return an initializer whose {@link FeatureInitializer#value() value} |
| * method will return {@code orig.value() + random.sample()}. |
| */ |
| public static FeatureInitializer randomize(final ContinuousUniformSampler random, |
| final FeatureInitializer orig) { |
| return new FeatureInitializer() { |
| /** {@inheritDoc} */ |
| @Override |
| public double value() { |
| return orig.value() + random.sample(); |
| } |
| }; |
| } |
| } |