import tensorflow as tf

    sigma2 = 1.0 / 0.26
    f1 = 'CE'


def models(hps, images, RCE_train, logits=False, tsne_logits=False):
    model = model_name.ResNet(hps, images, FLAGS.mode, Reuse=True)
    model.build_graph()
    op = model.predictions.op
    logit, = op.inputs
    if RCE_train==True:
        logit = -logit
    if tsne_logits==True:
        return tf.nn.softmax(logit), model.t_SNE_logits
    if logits==True:
        return tf.nn.softmax(logit), logit
    return tf.nn.softmax(logit)

class models_carlini:
    def __init__(self,hps):
        self.image_size = image_size
        self.num_channels = num_channel############MNIST and CIFAR10 are different ar here
        self.num_labels = num_classes
        self.hps = hps

