Support for CIFAR10?

[XuyangBai]

Hello, I am trying to train your model on CIFAR10 by loading cifar picture and modify some hyperparameter in trainDataSpaceNetwork and generateFigure

def loadCIFAR():
    with open("cifar-10-batches-py/data_batch_1", 'rb') as f:
        dict = pickle.load(f, encoding='bytes')
        data1 = dict[b'data']
    with open("cifar-10-batches-py/data_batch_2", 'rb') as f:
        dict = pickle.load(f, encoding='bytes')
        data2 = dict[b'data']
    with open("cifar-10-batches-py/data_batch_3", 'rb') as f:
        dict = pickle.load(f, encoding='bytes')
        data3 = dict[b'data']
    with open("cifar-10-batches-py/data_batch_4", "rb") as f:
        dict = pickle.load(f, encoding='bytes')
        data4 = dict[b'data']
    with open("cifar-10-batches-py/data_batch_5", "rb") as f:
        dict = pickle.load(f, encoding='bytes')
        data5 = dict[b'data']
    return np.concatenate((data1, data2, data3, data4, data5), axis=0)

def trainDataSpaceNetwork(dataset):
     #  something...
    elif dataset == 'cifar':
        input_dim = 3072
        image_side = 32
        num_examples = 50000
        train_x = loadCIFAR()

but the generated pictures are of very low quality, just like noise. So have you used your model for CIFAR10? Should I change other hyperparameter like num_iterations or batch_size?

Thank You.