给出python读取cifar-10-python.tar.gz的代码，要求要分出训练集，验证集，测试集

以下是Python读取CIFAR-10数据集并分割成训练集、验证集和测试集的示例代码：

import os
import numpy as np
import pickle

def unpickle(file):
    '''使用pickle模块读取数据'''
    with open(file, 'rb') as fo:
        dict = pickle.load(fo, encoding='bytes')
    return dict

def load_cifar10_data(data_dir):
    '''读取CIFAR-10数据集'''
    train_x = []
    train_y = []
    test_x = []
    test_y = []

    # 读取训练集数据和标签
    for i in range(1, 6):
        filename = os.path.join(data_dir, 'data_batch_{}'.format(i))
        data_dict = unpickle(filename)
        train_x.append(data_dict[b'data'])
        train_y += data_dict[b'labels']

    # 读取测试集数据和标签
    test_dict = unpickle(os.path.join(data_dir, 'test_batch'))
    test_x.append(test_dict[b'data'])
    test_y += test_dict[b'labels']

    # 将训练集和测试集的数据和标签合并
    train_x = np.concatenate(train_x, axis=0)
    test_x = np.concatenate(test_x, axis=0)
    train_y = np.array(train_y)
    test_y = np.array(test_y)

    # 划分训练集和验证集
    num_train = len(train_x)
    indices = np.arange(num_train)
    np.random.shuffle(indices)
    val_size = int(num_train * 0.1)  # 验证集大小，根据需要自己调整
    train_indices, val_indices = indices[val_size:], indices[:val_size]

    # 返回训练集、验证集和测试集的数据和标签
    return train_x[train_indices], train_y[train_indices], train_x[val_indices], train_y[val_indices], test_x, test_y

data_dir = 'path/to/cifar-10-batches-py'
train_x, train_y, val_x, val_y, test_x, test_y = load_cifar10_data(data_dir)

其中，`train_x`、`train_y`分别为训练集的数据和标签，`val_x`、`val_y`分别为验证集的数据和标签，`test_x`、`test_y`分别为测试集的数据和标签。在`load_cifar10_data`函数中，先读取训练集和测试集的数据和标签，然后根据需要分割出一部分用于验证集，最后返回训练集、验证集和测试集的数据和标签。