问题:老板让测试运行Keras官网里的Mnist-cnn.py,结果从下载数据就是一路坑……
当前环境:Ubuntu12.04、python2.7、Keras 1.1.1(不知道这个版本号对不对,在启动文件里查到的)
按遇到问题的先后逐个出解决方案:
1、load_data数据,下载老是报Errno 104 Connection reset by peer
解决:
①因为无论是否FQ下载都很慢,下载数据到本地并解压出pkl文件,绝对路径中不能有中文,
②重写数据加载函数,后面上代码,
2、运行代码时报错:
OverflowError: Range exceeds valid bounds
从异常跑出的栈里看是numpy的random函数有越界,
解决:有两种方法,就试了种简单的,另一种没试,
文件前面初始化设置:
from keras import backend
backend.set_image_dim_ordering('th')
查看具体解释。
下面是修改后的代码:如有问题还望能评论指出,谢谢,至少现在是能跑的,
import gzip from six.moves import cPickle from keras import backend backend.set_image_dim_ordering('th') batch_size = 128 nb_classes = 10 nb_epoch = 12 # input image dimensions img_rows, img_cols = 28, 28 # number of convolutional filters to use nb_filters = 32 # size of pooling area for max pooling nb_pool = 2 # convolution kernel size nb_conv = 3 def load_data(path='mnist.pkl.gz'): # path = get_file(path, origin='https://s3.amazonaws.com/img-datasets/mnist.pkl.gz') path = r'/home/wh/mnist.pkl' if path.endswith('.gz'): f = gzip.open(path, 'rb') else: f = open(path, 'rb') f = open(path, 'rb') data = cPickle.load(f)
f.close() return data # (X_train, y_train), (X_test, y_test) # the data, shuffled and split between train and test sets #(X_train, y_train), (X_test, y_test) = mnist.load_data() (X_train, y_train), (X_test, y_test) = load_data()
时间戳:2016-12-5 20:50:13
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