cPickle.so:: PyUnicodeUCS2_DecodeUTF8

本文详细介绍了如何通过调整Python编译参数`--enable-unicode=ucs4`来解决Python和Pythonmodule编译参数不一致导致的unicode支持问题,确保应用程序的正常运行。

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cPickle.so:: PyUnicodeUCS2_DecodeUTF8错误

Python编译的参数,和Python module(mod_wsgi, pymodwsgi)编译参数不一,导致一些unicode的支持出现问题。

重新编译python

 

./configure --enable-unicode=ucs4

转载于:https://www.cnblogs.com/bokun-wang/p/3899681.html

我有这样一个数据集在本地:Dataset layout Python / Matlab versions I will describe the layout of the Python version of the dataset. The layout of the Matlab version is identical. The archive contains the files data_batch_1, data_batch_2, ..., data_batch_5, as well as test_batch. Each of these files is a Python "pickled" object produced with cPickle. Here is a python2 routine which will open such a file and return a dictionary: def unpickle(file): import cPickle with open(file, 'rb') as fo: dict = cPickle.load(fo) return dict And a python3 version: def unpickle(file): import pickle with open(file, 'rb') as fo: dict = pickle.load(fo, encoding='bytes') return dict Loaded in this way, each of the batch files contains a dictionary with the following elements: data -- a 10000x3072 numpy array of uint8s. Each row of the array stores a 32x32 colour image. The first 1024 entries contain the red channel values, the next 1024 the green, and the final 1024 the blue. The image is stored in row-major order, so that the first 32 entries of the array are the red channel values of the first row of the image. labels -- a list of 10000 numbers in the range 0-9. The number at index i indicates the label of the ith image in the array data. The dataset contains another file, called batches.meta. It too contains a Python dictionary object. It has the following entries: label_names -- a 10-element list which gives meaningful names to the numeric labels in the labels array described above. For example, label_names[0] == "airplane", label_names[1] == "automobile", etc. 采用Resnet34对cifar-10数据集进行分类(Pytorch等) 分类范式:输入-模型-分类
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06-10
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