按batch_size读取数据

def data_iter(batch_size, features, labels):
    num_examples = len(features)
    indices = list(range(num_examples))
    random.shuffle(indices)  # 样本的读取顺序是随机的。
    for i in range(0, num_examples, batch_size):
        j = nd.array(indices[i: min(i + batch_size, num_examples)])
        yield features.take(j), labels.take(j)  # take 函数根据索引返回对应元素。

使用：

batch_size = 10

for X, y in data_iter(batch_size, features, labels):
    print(X, y)
    break