from framework.utils import serial
from framework.datasets import cifar10
from framework.datasets import preprocessing
train = cifar10.CIFAR10(which_set="train")
pipeline = preprocessing.Pipeline()
pipeline.items.append(
preprocessing.ExtractPatches(patch_shape=(8, 8), num_patches=150000))
pipeline.items.append(preprocessing.GlobalContrastNormalization())
pipeline.items.append(preprocessing.ZCA())
test = cifar10.CIFAR10(which_set="test")
train.apply_preprocessor(preprocessor=pipeline, can_fit=True)
test.apply_preprocessor(preprocessor=pipeline, can_fit=False)
train.use_design_loc('cifar10_preprocessed_train_design.npy')
test.use_design_loc('cifar10_preprocessed_test_design.npy')
serial.save('cifar10_preprocessed_train.pkl', train)
serial.save('cifar10_preprocessed_test.pkl', test)
from framework.utils import serial
from framework.datasets import cifar10
from framework.datasets import preprocessing
train = cifar10.CIFAR10(which_set="train")
pipeline = preprocessing.Pipeline()
pipeline.items.append(preprocessing.ExtractPatches(patch_shape=(8,8),num_patches=200000))
pipeline.items.append(preprocessing.GlobalContrastNormalization())
pipeline.items.append(preprocessing.ZCA())
train.apply_preprocessor(preprocessor = pipeline, can_fit = True)
serial.save('preprocessor.pkl',pipeline)
def __init__(self, which_set):
self.underlying = cifar10.CIFAR10(which_set = which_set)
self.preprocessor = serial.load('/u/goodfeli/framework/recons_srbm/cifar10_preprocessor_2M.pkl')