def loadMnist():
f = gzip.open('mnist.pkl.gz', 'rb')
train_set, valid_set, test_set = cPickle.load(f)
f.close()
trainingData = MakeData.shared(train_set)
validationData = MakeData.shared(valid_set)
testData = MakeData.shared(test_set)
return trainingData, validationData, testData
def loadCifar100():
train_set, test_set = cifar100.load_data()
X, Y = train_set
X = X.reshape((X.shape[0], X.shape[1] * X.shape[2] * X.shape[3]))
Y = Y.reshape((Y.shape[0],))
trainingData = MakeData.shared((X[0:40000, :], Y[0:40000]))
validationData = MakeData.shared((X[40000:50000, :], Y[40000:50000]))
X, Y = test_set
X = X.reshape((X.shape[0], X.shape[1] * X.shape[2] * X.shape[3]))
Y = Y.reshape((Y.shape[0],))
testData = MakeData.shared((X, Y))
return trainingData, validationData, testData
