我正在尝试加载mnist角色数据集(遵循此处概述的教程:http://neuralnetworksanddeeplearning.com/chap1.html)
当我运行load_data_wrapper函数时,我收到错误。
UnicodeDecodeError: 'ascii' codec can't decode byte 0x90 in position 614: ordinal not in range(128)
代码运行是:
import numpy as np
import gzip
def load_data():
f = gzip.open('../data/mnist.pkl.gz', 'rb')
training_data, validation_data, test_data = pickle.load(f)
f.close()
return (training_data, validation_data, test_data)
def load_data_wrapper():
tr_d, va_d, te_d = load_data()
training_inputs = [np.reshape(x, (784,1)) for x in tr_d[0]]
training_results = [vectorized_result(y) for y in tr_d[1]]
training_data = zip(training_inputs, training_results)
validation_inputs = [np.reshape(x,(784, 1))for x in va_d[0]]
validation_data = zip(validation_inputs, va_d[1])
test_inputs = [np.reshape(x, (784, 1)) for x in te_d[0]]
test_data = zip(test_inputs, te_d[1])
return(training_data, validation_data, test_data)
def vectorized_result(j):
e = np.zeros((10,1))
e[j] = 1.0
return e
更新:问题似乎是我试图使用python 2.x进行pickle的python 3.6。
答案 0 :(得分:19)
如上所述,主要问题是python 2.x cPickle和python 3.x pickle之间不兼容。
将编码设置为' latin-1'似乎工作。
training_data, validation_data, test_data = pickle.load(f, encoding='latin1')
这里的答案有很多帮助:Pickle incompatability of numpy arrays between Python 2 and 3
答案 1 :(得分:0)
您可以尝试以下方法:
import chainer
train, test = chainer.datasets.get_mnist(ndim=1)