ValueError: setting an array element with a sequence in Python

Question

首先，这是我的代码：

"""Softmax."""

scores = [3.0, 1.0, 0.2]

import numpy as np

def softmax(x):
    """Compute softmax values for each sets of scores in x."""
    num = np.exp(x)
    score_len = len(x)
    y = np.array([0]*score_len)
    sum_n = np.sum(num)
    #print sum_n
    for index in range(1,score_len):
        y[index] = (num[index])/sum_n
    return y

print(softmax(scores))

错误出现在行：

y[index] = (num[index])/sum_n

我运行代码为：

# Plot softmax curves
import matplotlib.pyplot as plt
x = np.arange(-2.0, 6.0, 0.1)
scores = np.vstack([x, np.ones_like(x), 0.2 * np.ones_like(x)])

plt.plot(x, softmax(scores).T, linewidth=2)
plt.show()

这里到底出了什么问题？

Answer 1

只需将 print 语句编辑为 "debugger" 即可揭示正在发生的事情：

import numpy as np

def softmax(x):
    """Compute softmax values for each sets of scores in x."""
    num = np.exp(x)
    score_len = len(x)
    y = np.array([0]*score_len)
    sum_n = np.sum(num)
    #print sum_n
    for index in range(1,score_len):
        print((num[index])/sum_n)
        y[index] = (num[index])/sum_n
    return y

x = np.arange(-2.0, 6.0, 0.1)
scores = np.vstack([x, np.ones_like(x), 0.2 * np.ones_like(x)])
softmax(scores).T

这会打印

[ 0.00065504  0.00065504  0.00065504  0.00065504  0.00065504  0.00065504
  0.00065504  0.00065504  0.00065504  0.00065504  0.00065504  0.00065504
  0.00065504  0.00065504  0.00065504  0.00065504  0.00065504  0.00065504
  0.00065504  0.00065504  0.00065504  0.00065504  0.00065504  0.00065504
  0.00065504  0.00065504  0.00065504  0.00065504  0.00065504  0.00065504
  0.00065504  0.00065504  0.00065504  0.00065504  0.00065504  0.00065504
  0.00065504  0.00065504  0.00065504  0.00065504  0.00065504  0.00065504
  0.00065504  0.00065504  0.00065504  0.00065504  0.00065504  0.00065504
  0.00065504  0.00065504  0.00065504  0.00065504  0.00065504  0.00065504
  0.00065504  0.00065504  0.00065504  0.00065504  0.00065504  0.00065504
  0.00065504  0.00065504  0.00065504  0.00065504  0.00065504  0.00065504
  0.00065504  0.00065504  0.00065504  0.00065504  0.00065504  0.00065504
  0.00065504  0.00065504  0.00065504  0.00065504  0.00065504  0.00065504
  0.00065504  0.00065504]

所以你试图将这个数组分配给另一个数组的一个元素。这是不允许的！

有几种方法可以使它正常工作。刚换

y = np.array([0]*score_len)

多维数组可以工作：

y = np.zeros(score.shape)

这应该可以解决问题，但我不确定这是否是您想要的。

编辑：

看来你不想多维输入所以你只需要改变：

scores = np.vstack([x, np.ones_like(x), 0.2 * np.ones_like(x)])

到

scores = np.hstack([x, np.ones_like(x), 0.2 * np.ones_like(x)])

通过打印 scores.shape 来验证这些数组的形状确实可以帮助您自己发现此类错误。第一个沿第一个轴 (vstack) 堆叠，hstack 沿第零轴堆叠 (这就是你想要的)

Answer 2

这是一种糟糕的数组初始化方式：

y = np.array([0]*score_len)

最好做一些类似的事情

y = np.zeros((n,m))

其中 n 和 m 是最终产品的 2 个维度。我从你的另一个问题假设你希望 y 是二维的（毕竟你在它上面做了一个 .T）。

注意传递给函数的 scores 的形状。并在迭代时包含 :。它可以是可选的，但你需要它来保持你自己头脑中的尺寸：

y[index,:] = (num[index,:])/sum_n

总而言之 - 重点了解如何使用多维数组 - 如何创建它们，如何索引它们，如何在没有迭代的情况下使用它们，以及如何在需要时正确迭代。

Answer 3

这应该可以完美快速地工作

scores = [3.0, 1.0, 0.2]

import numpy as np


def softmax(x):

    num = np.exp(x)
    score_len = len(x)

    y = np.zeros(score_len, object) # or => np.asarray([None]*score_len)
    sum_n = np.sum(num)

    for i in range(score_len):
        y[i] = num[i] / sum_n

    return y


print(softmax(scores))

x = np.arange(-2.0, 6.0, 0.1)
scores = np.vstack([x, np.ones_like(x), 0.2 * np.ones_like(x)])

printout = softmax(scores).T

print(printout)

输出：

[0.8360188027814407 0.11314284146556011 0.050838355752999158]

[ array([  3.26123038e-05,   3.60421698e-05,   3.98327578e-05,
         4.40220056e-05,   4.86518403e-05,   5.37685990e-05,
         5.94234919e-05,   6.56731151e-05,   7.25800169e-05,
         8.02133239e-05,   8.86494329e-05,   9.79727751e-05,
         1.08276662e-04,   1.19664218e-04,   1.32249413e-04,
         1.46158206e-04,   1.61529798e-04,   1.78518035e-04,
         1.97292941e-04,   2.18042421e-04,   2.40974142e-04,
         2.66317614e-04,   2.94326482e-04,   3.25281069e-04,
         3.59491177e-04,   3.97299194e-04,   4.39083515e-04,
         4.85262332e-04,   5.36297817e-04,   5.92700751e-04,
         6.55035633e-04,   7.23926331e-04,   8.00062328e-04,
         8.84205618e-04,   9.77198335e-04,   1.07997118e-03,
         1.19355274e-03,   1.31907978e-03,   1.45780861e-03,
         1.61112768e-03,   1.78057146e-03,   1.96783579e-03,
         2.17479489e-03,   2.40352006e-03,   2.65630048e-03,
         2.93566604e-03,   3.24441273e-03,   3.58563059e-03,
         3.96273465e-03,   4.37949910e-03,   4.84009504e-03,
         5.34913227e-03,   5.91170543e-03,   6.53344491e-03,
         7.22057331e-03,   7.97996764e-03,   8.81922816e-03,
         9.74675448e-03,   1.07718296e-02,   1.19047128e-02,
         1.31567424e-02,   1.45404491e-02,   1.60696814e-02,
         1.77597446e-02,   1.96275532e-02,   2.16918010e-02,
         2.39731477e-02,   2.64944256e-02,   2.92808687e-02,
         3.23603645e-02,   3.57637337e-02,   3.95250385e-02,
         4.36819230e-02,   4.82759910e-02,   5.33532213e-02,
         5.89644285e-02,   6.51657716e-02,   7.20193157e-02,
         7.95936532e-02,   8.79645908e-02])
 array([ 0.00065504,  0.00065504,  0.00065504,  0.00065504,  0.00065504,
        0.00065504,  0.00065504,  0.00065504,  0.00065504,  0.00065504,
        0.00065504,  0.00065504,  0.00065504,  0.00065504,  0.00065504,
        0.00065504,  0.00065504,  0.00065504,  0.00065504,  0.00065504,
        0.00065504,  0.00065504,  0.00065504,  0.00065504,  0.00065504,
        0.00065504,  0.00065504,  0.00065504,  0.00065504,  0.00065504,
        0.00065504,  0.00065504,  0.00065504,  0.00065504,  0.00065504,
        0.00065504,  0.00065504,  0.00065504,  0.00065504,  0.00065504,
        0.00065504,  0.00065504,  0.00065504,  0.00065504,  0.00065504,
        0.00065504,  0.00065504,  0.00065504,  0.00065504,  0.00065504,
        0.00065504,  0.00065504,  0.00065504,  0.00065504,  0.00065504,
        0.00065504,  0.00065504,  0.00065504,  0.00065504,  0.00065504,
        0.00065504,  0.00065504,  0.00065504,  0.00065504,  0.00065504,
        0.00065504,  0.00065504,  0.00065504,  0.00065504,  0.00065504,
        0.00065504,  0.00065504,  0.00065504,  0.00065504,  0.00065504,
        0.00065504,  0.00065504,  0.00065504,  0.00065504,  0.00065504])
 array([ 0.00029433,  0.00029433,  0.00029433,  0.00029433,  0.00029433,
        0.00029433,  0.00029433,  0.00029433,  0.00029433,  0.00029433,
        0.00029433,  0.00029433,  0.00029433,  0.00029433,  0.00029433,
        0.00029433,  0.00029433,  0.00029433,  0.00029433,  0.00029433,
        0.00029433,  0.00029433,  0.00029433,  0.00029433,  0.00029433,
        0.00029433,  0.00029433,  0.00029433,  0.00029433,  0.00029433,
        0.00029433,  0.00029433,  0.00029433,  0.00029433,  0.00029433,
        0.00029433,  0.00029433,  0.00029433,  0.00029433,  0.00029433,
        0.00029433,  0.00029433,  0.00029433,  0.00029433,  0.00029433,
        0.00029433,  0.00029433,  0.00029433,  0.00029433,  0.00029433,
        0.00029433,  0.00029433,  0.00029433,  0.00029433,  0.00029433,
        0.00029433,  0.00029433,  0.00029433,  0.00029433,  0.00029433,
        0.00029433,  0.00029433,  0.00029433,  0.00029433,  0.00029433,
        0.00029433,  0.00029433,  0.00029433,  0.00029433,  0.00029433,
        0.00029433,  0.00029433,  0.00029433,  0.00029433,  0.00029433,
        0.00029433,  0.00029433,  0.00029433,  0.00029433,  0.00029433])]

Answer 4

数组构造的不一致可能会导致这种问题例如

[[1,2,3,4], [2,3], [1],[1,2,3,4]]

这是一个糟糕的示例数组。

ValueError: setting an array element with a sequence in Python

ValueError: setting an array element with a sequence in Python

python

arrays

numpy

softmax