AttributeError: ‘builtin_function_or_method‘ object has no attribute ‘shuffle‘

今天在复现深度学习的代码的时候，遇到了一个问题，百思不得其解：

Traceback (most recent call last):
  File "d:\Code Project\15.动手学深度学习代码手撸\线性回归.py", line 34, in <module>
    for X, y in data_iter(batch_size, features, labels):
  File "d:\Code Project\15.动手学深度学习代码手撸\线性回归.py", line 21, in data_iter
    random.shuffle(indices)
AttributeError: 'builtin_function_or_method' object has no attribute 'shuffle'

没有找到shuffle模块！

我们回头看一下源代码：

import math
from random import random
import time
import numpy as np
import torch
from d2l import torch as d2l
import matplotlib.pyplot as plt
from matplotlib_inline import backend_inline


def data_iter(batch_size, features, labels):
    num_examples = len(features)
    indices = list(range(num_examples))
    # 这些样本是随机读取的，没有特定的顺序
    random.shuffle(indices)
    for i in range(0, num_examples, batch_size):
        batch_indices = torch.tensor(indices[i : min(i + batch_size, num_examples)])
        yield features[batch_indices], labels[batch_indices]

这里我们可以看出来，错误的原因是调包调错了，应该把from random import random改为import random：

改正后的结果如下：

tensor([[ 0.7425,  0.1878],
        [ 0.0685, -2.4066],
        [-0.6766,  1.4171],
        [ 1.1995, -1.2895],
        [ 0.9222,  2.1167],
        [ 1.4341, -2.5776],
        [ 0.1866,  0.3323],
        [-1.3769,  1.3391],
        [ 0.6745,  0.6171],
        [ 0.9577,  0.7001]]) 
 tensor([[ 5.0335],
        [12.5133],
        [-1.9797],
        [10.9888],
        [-1.1390],
        [15.8354],
        [ 3.4411],
        [-3.1252],
        [ 3.4511],
        [ 3.7230]])

问题得到顺利解决！