src/core/network/NeuralNetwork.java
private void validateInput(boolean stateCompleted) throws MatrixException, NeuralNetworkException, DynamicParamException {
        validationMetric.reset();
        validationSampler.reset();
        int numberOfIterations = validationSampler.getNumberOfIterations();
        for (int sampleIndex = 0; sampleIndex < numberOfIterations; sampleIndex++) {
            Sequence inputSequence = new Sequence(validationSampler.getDepth());
            Sequence outputSequence = new Sequence(validationSampler.getDepth());
            validationSampler.getSamples(inputSequence, outputSequence);
            validationMetric.report(getInputLayer().predict(inputSequence), outputSequence);
        }
        if (verboseValidation && (totalIterations % verboseCycle == 0)) verboseValidationStatus();
        if (stateCompleted) stateCompleted();
    }
/**
     * Validates with given test set inputs and outputs.
     *
     * @param stateCompleted if flag is sets calls stateCompleted function.
     * @throws MatrixException throws exception if matrix operation fails.
     * @throws NeuralNetworkException throws exception if validation fails.
     * @throws DynamicParamException throws exception if parameter (params) setting fails.
     */
Validates with given test set inputs and outputs.
@param stateCompleted if flag is sets calls stateCompleted function.
@throws MatrixException throws exception if matrix operation fails.
@throws NeuralNetworkException throws exception if validation fails.
@throws DynamicParamException throws exception if parameter (params) setting fails.
Validates with given test set inputs and outputs . @param stateCompleted if flag is sets calls stateCompleted function . @throws MatrixException throws exception if matrix operation fails . @throws NeuralNetworkException throws exception if validation fails . @throws DynamicParamException throws exception if parameter ( params ) setting fails .
private void validateInput(boolean stateCompleted) throws MatrixException, NeuralNetworkException, DynamicParamException {
        validationMetric.reset();
        validationSampler.reset();
        int numberOfIterations = validationSampler.getNumberOfIterations();
        for (int sampleIndex = 0; sampleIndex < numberOfIterations; sampleIndex++) {
            Sequence inputSequence = new Sequence(validationSampler.getDepth());
            Sequence outputSequence = new Sequence(validationSampler.getDepth());
            validationSampler.getSamples(inputSequence, outputSequence);
            validationMetric.report(getInputLayer().predict(inputSequence), outputSequence);
        }
        if (verboseValidation && (totalIterations % verboseCycle == 0)) verboseValidationStatus();
        if (stateCompleted) stateCompleted();
    }
private void validateInput ( boolean stateCompleted ) throws MatrixException , NeuralNetworkException , DynamicParamException { validationMetric . reset ( ) ; validationSampler . reset ( ) ; int numberOfIterations = validationSampler . getNumberOfIterations ( ) ; for ( int sampleIndex = 0 ; sampleIndex < numberOfIterations ; sampleIndex ++ ) { Sequence inputSequence = new Sequence ( validationSampler . getDepth ( ) ) ; Sequence outputSequence = new Sequence ( validationSampler . getDepth ( ) ) ; validationSampler . getSamples ( inputSequence , outputSequence ) ; validationMetric . report ( getInputLayer ( ) . predict ( inputSequence ) , outputSequence ) ; } if ( verboseValidation && ( totalIterations % verboseCycle == 0 ) ) verboseValidationStatus ( ) ; if ( stateCompleted ) stateCompleted ( ) ; }
Validates with given test set inputs and outputs.
Validates with given test set inputs and outputs .