/*
* Encog(tm) Core v2.5 - Java Version
* http://www.heatonresearch.com/encog/
* http://code.google.com/p/encog-java/
* Copyright 2008-2010 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.engine.network.flat;
import org.encog.engine.EncogEngineError;
import org.encog.engine.EngineMachineLearning;
import org.encog.engine.network.activation.ActivationFunction;
import org.encog.engine.validate.BasicMachineLearningValidate;
/**
* Validate the network to be sure it can run on OpenCL.
*
*/
public class ValidateForOpenCL extends BasicMachineLearningValidate {
/**
* Determine if the network is valid for OpenCL.
*
* @param network
* The network to check.
* @return The string indicating the error that prevents OpenCL from using
* the network, or null if the network is fine for OpenCL.
*/
@Override
public String isValid(final EngineMachineLearning network) {
if (!(network instanceof FlatNetwork)) {
return "Only flat networks are valid to be used for OpenCL";
}
final FlatNetwork flat = (FlatNetwork) network;
for (ActivationFunction activation : flat.getActivationFunctions()) {
if (activation.getOpenCLExpression(true) == null) {
return "Can't use OpenCL if activation function does not have an OpenCL expression.";
}
}
if (flat.hasSameActivationFunction() == null) {
return "Can't use OpenCL training on a neural network that uses multiple activation functions.";
}
boolean hasContext = false;
for (int i = 0; i < flat.getLayerCounts().length; i++) {
if (flat.getContextTargetOffset()[i] != 0) {
hasContext = true;
}
if (flat.getContextTargetSize()[i] != 0) {
hasContext = true;
}
}
if (hasContext) {
return "Can't use OpenCL if context neurons are present.";
}
return null;
}
}