/** * This method builds new ParallelInference instance * * @return */ public ParallelInference build() { ParallelInference inference = new ParallelInference(); inference.batchLimit = this.batchLimit; inference.queueLimit = this.queueLimit; inference.inferenceMode = this.inferenceMode; inference.model = this.model; inference.workers = this.workers; inference.init(); return inference; } }
public INDArray output(INDArray input) { // basically, depending on model type we either // throw stuff to specific model, or wait for batch return output(new INDArray[] {input})[0]; }
public INDArray output(INDArray input) { // basically, depending on model type we either // throw stuff to specific model, or wait for batch return output(new INDArray[] {input})[0]; }
/** * This method builds new ParallelInference instance * * @return */ public ParallelInference build() { ParallelInference inference = new ParallelInference(); inference.batchLimit = this.batchLimit; inference.queueLimit = this.queueLimit; inference.inferenceMode = this.inferenceMode; inference.model = this.model; inference.workers = this.workers; inference.init(); return inference; } }
/** * * @param input * @return */ public INDArray output(float[] input) { return output(Nd4j.create(input)); }
/** * * @param input * @return */ public INDArray output(double[] input) { return output(Nd4j.create(input)); }
/** * * @param input * @return */ public INDArray output(double[] input) { return output(Nd4j.create(input)); }
/** * * @param dataSet * @return */ public INDArray output(DataSet dataSet) { return output(dataSet.getFeatureMatrix()); }
/** * * @param input * @return */ public INDArray output(float[] input) { return output(Nd4j.create(input)); }
/** * * @param dataSet * @return */ public INDArray output(DataSet dataSet) { return output(dataSet.getFeatureMatrix()); }