写一段用于多分类的感知机算法程序，python语言

以下是一个简单的多分类感知机算法程序，使用Python语言实现：

import numpy as np

class Perceptron:
    def __init__(self, num_classes, input_size, lr=0.1, epochs=1000):
        self.num_classes = num_classes
        self.input_size = input_size
        self.lr = lr
        self.epochs = epochs
        self.weights = np.zeros((num_classes, input_size))
        self.biases = np.zeros(num_classes)

    def train(self, X, y):
        for epoch in range(self.epochs):
            for i in range(X.shape[0]):
                x = X[i]
                target = y[i]
                output = self.predict(x)
                if output != target:
                    self.weights[target] += self.lr * x
                    self.biases[target] += self.lr
                    self.weights[output] -= self.lr * x
                    self.biases[output] -= self.lr

    def predict(self, x):
        scores = np.dot(self.weights, x) + self.biases
        return np.argmax(scores)

if __name__ == '__main__':
    X = np.array([[1, 1], [2, 1], [2, 3], [3, 2]])
    y = np.array([0, 0, 1, 1])
    num_classes = 2
    input_size = 2
    perceptron = Perceptron(num_classes, input_size)
    perceptron.train(X, y)
    print(perceptron.predict(np.array([1, 2])))

此程序使用了一个简单的数据集，其中包含四个样本，每个样本有两个特征。在训练过程中，该程序会使用感知机算法来更新权重和偏置，直到达到指定的训练次数。最后，该程序会输出一个新样本的预测类别。