如何使用PHP进行神经网络和深度神经网络模型实现？

class NeuralNetwork {
    public $inputLayer = array();
    public $hiddenLayer = array();
    public $outputLayer = array();
    
    function __construct($input, $hidden, $output) {
        // 初始化神经网络参数
    }
    
    function train($inputData, $outputData, $learningRate, $epochs) {
        // 训练神经网络模型
    }
    
    function predict($inputData) {
        // 预测结果
    }
}

class DeepNeuralNetwork {
    public $inputLayer = array();
    public $hiddenLayers = array();
    public $outputLayer = array();

    function __construct($input, $hiddenLayers, $output) {
        // 初始化神经网络参数
    }

    function train($inputData, $outputData, $learningRate, $epochs) {
        // 训练神经网络模型
    }

    function predict($inputData) {
        // 预测结果
    }
}

use PhpmlNeuralNetworkActivationFunctionPReLU;
use PhpmlNeuralNetworkActivationFunctionSigmoid;
use PhpmlNeuralNetworkLayer;
use PhpmlNeuralNetworkNetworkMultilayerPerceptron;

// 初始化神经网络参数
$inputLayer = new Layer(2, new Sigmoid());
$hiddenLayer = new Layer(5, new PReLU());
$outputLayer = new Layer(1, new Sigmoid());

// 创建神经网络模型
$mlp = new MultilayerPerceptron([$inputLayer, $hiddenLayer, $outputLayer]);

// 训练神经网络模型
$mlp->train(
    [[0, 0], [0, 1], [1, 0], [1, 1]],
    [0, 1, 1, 0],
    100000,
    0.1
);

// 预测结果
echo '0 xor 0 => ', $mlp->predict([0, 0]), "
";
echo '0 xor 1 => ', $mlp->predict([0, 1]), "
";
echo '1 xor 0 => ', $mlp->predict([1, 0]), "
";
echo '1 xor 1 => ', $mlp->predict([1, 1]), "
";