@Test public void testGetNetInputSize(){ assertEquals("The size of the network input is not as expected.", NET_TOPOLOGY[0], neuralNet.getNetInputSize()); }
public int getNetInputSize() { return netInputDim; }
BasicNeuralNet implements NeuralNet, Serializable { public int getNetInputSize() { return netInputDim; } }
BasicNeuralNet implements NeuralNet, Serializable { public int getNetInputSize() { return netInputDim; } BasicNeuralNet(int[] netTopology, double biasInput,
            Class<? extends ActivationFunction> activationFunction, Random random); }
BasicNeuralNet implements NeuralNet, Serializable { public int getNetInputSize() { return netInputDim; } BasicNeuralNet(int[] netTopology, double biasInput,
            Class<? extends ActivationFunction> activationFunction, Random random); List<Neuron> getLayerUnits(int layerIndex); int getLayersCount(); double[] feedForward(final double[] inputPattern); double[] getOutput(); void reset(); int getNetInputSize(); int getNetOutputSize(); }
BasicNeuralNet implements NeuralNet, Serializable { public int getNetInputSize() { return netInputDim; } BasicNeuralNet(int[] netTopology, double biasInput,
            Class<? extends ActivationFunction> activationFunction, Random random); List<Neuron> getLayerUnits(int layerIndex); int getLayersCount(); double[] feedForward(final double[] inputPattern); double[] getOutput(); void reset(); int getNetInputSize(); int getNetOutputSize();  }