网址:https://s3.amazonaws.com/img-datasets/mnist.npz,由于显而易见的原因,无法访问。
npz实际上是numpy提供的数组存储方式,简单的可看做是一系列npy数据的组合,利用np.load函数读取后得到一个类似字典的对象,可以通过关键字进行值查询,关键字对应的值其实就是一个npy数据。
如果用keras自带的example(from keras.datasets import mnist,在mnist.py下的load_data函数),会使用这种格式。
我自己解决方法是在国外的vps机器上下载,然后传到本地,假设保存为mnist.npz,则加载方法:
import numpy as np def load_data(path=\'mnist.npz\'): """Loads the MNIST dataset. # Arguments path: path where to cache the dataset locally (relative to ~/.keras/datasets). # Returns Tuple of Numpy arrays: `(x_train, y_train), (x_test, y_test)`. path = get_file(path, origin=\'https://s3.amazonaws.com/img-datasets/mnist.npz\', file_hash=\'8a61469f7ea1b51cbae51d4f78837e45\') """ f = np.load(path) x_train, y_train = f[\'x_train\'], f[\'y_train\'] x_test, y_test = f[\'x_test\'], f[\'y_test\'] f.close() return (x_train, y_train), (x_test, y_test) # the data, split between train and test sets (x_train, y_train), (x_test, y_test) = load_data()
原来的是:
(x_train, y_train), (x_test, y_test) = mnist.load_data()
替换下OK!