Question

当我尝试导入两个用于Python培训的文本文件时，我收到以下错误：

Traceback (most recent call last):
File "C:\Users\user\Desktop\test.py", line 31, in <module>
X_train, y_train = load_mnist('mnist', kind='train')
File "C:\Users\user\Desktop\test.py", line 27, in load_mnist
dtype=np.uint8).reshape(len(labels), 784)
ValueError: total size of new array must be unchanged

正在运行的代码部分是：

import os
import struct
import numpy as np
from scipy.special import expit
import sys
import matplotlib.pyplot as plt

def load_mnist(path, kind='train'):
    """Load MNIST data from `path`"""
    labels_path = os.path.join(path,'%s-labels-idx1-ubyte' % kind)
    images_path = os.path.join(path, '%s-images-idx3-ubyte' % kind)

    with open('C:/Users/user/~MNISTnumLabels5000.txt', 'rb') as lbpath:
        magic, n = struct.unpack('>II', lbpath.read(8))
        labels = np.fromfile(lbpath, dtype=np.uint8)

    with open('C:/Users/user/~MNISTnumImages5000.txt', 'rb') as imgpath:
        magic, num, rows, cols = struct.unpack(">IIII", imgpath.read(16))
        images = np.fromfile(imgpath, dtype=np.uint8).reshape(len(labels), 784)

    return images, labels

X_train, y_train = load_mnist('mnist', kind='train')
print('Rows: %d, columns: %d' % (X_train.shape[0], X_train.shape[1]))

MNISTnumImages5000.txt文件具有5,000个数字的数据，每个数字是尺寸为28×28像素的灰度图像（即，每个784像素）。数据文件的每一行都有784个值，表示0到9之间一位数的图像强度。

MNISTnumLabels5000.txt文件每行有一个整数，表示在图像数据文件的相应行中更正图像的标签。因此，第一个条目＆＃39; 7＆＃39;表示图像数据文件的第一行具有手写数字7的数据。

ValueError：新数组的总大小必须保持不变 - 机器学习

0 个答案: