Examples of java.io.DataOutput.writeBoolean()

java.io.DataOutput.writeBoolean()
Writes a boolean value to this output stream. If the argument v is true, the value (byte)1 is written; if v is false, the value (byte)0 is written. The byte written by this method may be read by the readBoolean method of interface DataInput, which will then return a boolean equal to v. @param v the boolean to be written. @throws IOException if an I/O error occurs.

    
    d.writeBoolean( this.datasetPassComplete );
    d.writeBoolean( this.preTrainPhaseComplete );
    
    d.writeBoolean( this.masterSignalToStartFineTunePhase );
    d.writeBoolean( this.masterSignalToStartNextDatasetPass );
    
    d.writeInt( this.dbn_payload.length );
    out.write( this.dbn_payload );

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      d.writeDouble( this.sparsity ); 
      d.writeDouble( this.momentum );
      d.writeDouble( this.l2 );
      d.writeInt( this.renderWeightsEveryNumEpochs );
      d.writeDouble( this.fanIn );
      d.writeBoolean( this.useRegularization );


        


    } catch (IOException e) {
      throw new RuntimeException(e);

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      d.writeInt( rows );
      d.writeInt( cols );
      d.writeInt( numIterations );
      
      d.writeDouble( lrDecay );
      d.writeBoolean(  decayLr );
      d.writeDouble( minLearningRate );
        
        
        
    } catch (IOException e) {

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//        MatrixWritable.writeMatrix(d, this.labels );      


        MatrixWritable.writeMatrix(d, this.connectionWeights );
        MatrixWritable.writeMatrix(d, this.biasTerms );
        
        d.writeBoolean( this.useRegularization );
        


        d.writeBoolean( this.useAdaGrad );
        this.adaLearningRates.write( os );
        this.biasAdaGrad.write( os );

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        MatrixWritable.writeMatrix(d, this.biasTerms );
        
        d.writeBoolean( this.useRegularization );
        


        d.writeBoolean( this.useAdaGrad );
        this.adaLearningRates.write( os );
        this.biasAdaGrad.write( os );
        d.writeBoolean( this.firstTimeThrough );
        d.writeBoolean( this.normalizeByInputRows );

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        d.writeBoolean( this.useAdaGrad );
        this.adaLearningRates.write( os );
        this.biasAdaGrad.write( os );
        d.writeBoolean( this.firstTimeThrough );
        d.writeBoolean( this.normalizeByInputRows );
        
        // TODO: dont remember how to serde an Enum. fix. (only two options today)
        if (OptimizationAlgorithm.CONJUGATE_GRADIENT == this.optimizationAlgorithm) {

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        d.writeBoolean( this.useAdaGrad );
        this.adaLearningRates.write( os );
        this.biasAdaGrad.write( os );
        d.writeBoolean( this.firstTimeThrough );
        d.writeBoolean( this.normalizeByInputRows );
        
        // TODO: dont remember how to serde an Enum. fix. (only two options today)
        if (OptimizationAlgorithm.CONJUGATE_GRADIENT == this.optimizationAlgorithm) {
          
          d.writeInt(0);

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