我有自己的数据集,我想训练我的模型。我已经成功创建了.pk.gz文件,但我不知道如何将它们导入到我的模型中。
我正在使用windows 10,python 3.5.2 with tensor-flow和tflearn以及sublime text 3来编写代码。
我用来创建pickle文件的代码:
from numpy import genfromtxt
import gzip
import _pickle as cPickle
#data = sio.loadmat('C:/DeepLearning_lib/Theano/Data/test_x.mat')
train_set_x = genfromtxt('C:/Users/Jay/Desktop/MachineLearning/dataset/NSL-KDD Processed/Kdd_Train_41.csv', delimiter=',')
train_set_y = genfromtxt('C:/Users/Jay/Desktop/MachineLearning/dataset/NSL-KDD Processed/NSL_TrainLabels_mat4.csv', delimiter=',')
valid_set_x = genfromtxt('C:/Users/Jay/Desktop/MachineLearning/dataset/NSL-KDD Processed/Kdd_Valid_41.csv', delimiter=',')
valid_set_y = genfromtxt('C:/Users/Jay/Desktop/MachineLearning/dataset/NSL-KDD Processed/NSL_ValidLabels_int2.csv', delimiter=',')
test_set_x = genfromtxt('C:/Users/Jay/Desktop/MachineLearning/dataset/NSL-KDD Processed/Kdd_Test_41.csv', delimiter=',')
test_set_y = genfromtxt('C:/Users/Jay/Desktop/MachineLearning/dataset/NSL-KDD Processed/NSL_TestLabels_mat5.csv', delimiter=',')
train_set = test_set_x
train_set_labels= test_set_y
valid_set = valid_set_x
valid_set_labels= valid_set_y
test_set = train_set_x
test_set_labels= train_set_y
f = gzip.open('C:/Users/Jay/Desktop/Data/train_set.pkl.gz','wb')
cPickle.dump(train_set, f, protocol=2)
f.close()
f = gzip.open('C:/Users/Jay/Desktop/Data/train_set_labels.pkl.gz','wb')
cPickle.dump(train_set_labels, f, protocol=2)
f.close()
f = gzip.open('C:/Users/Jay/Desktop/Data/valid_set_labels.pkl.gz','wb')
cPickle.dump(valid_set_labels, f, protocol=2)
f.close()
f = gzip.open('C:/Users/Jay/Desktop/Data/test_set_labels.pkl.gz','wb')
cPickle.dump(test_set_labels, f, protocol=2)
f.close()
f = gzip.open('C:/Users/Jay/Desktop/Data/valid_set.pkl.gz','wb')
cPickle.dump(valid_set, f, protocol=2)
f.close()
f = gzip.open('C:/Users/Jay/Desktop/Data/test_set.pkl.gz','wb')
cPickle.dump(test_set, f, protocol=2)
f.close()
错误:使用时' rb'
'OSError: [Errno 9] peek() on write-only GzipFile object'
答案 0 :(得分:0)
以下代码应重建您的train_set
:
with gzip.open('C:/Users/Jay/Desktop/Data/train_set.pkl.gz', 'rb') as f:
train_set = cPickle.load(f)